The impact of international crises on the statistic and
economic evidence of the Linder hypothesis
ERASMUS UNIVERSITY ROTTERDAM
Erasmus School of Economics
Master International Economics
8 october 2011
Student: Aart Noordegraaf
Student number: 297982
Thesis supervisor: Dr. K.G. Berden
Co-reader: Prof. Dr. J.M.A. Viaene
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1.1 Introduction and Overview ............................................................................................................... 2
1.1 Historical context........................................................................................................................... 3
1.2 Linder hypothesis .......................................................................................................................... 5
1.3 Aim of the research ....................................................................................................................... 7
1.4 Research question and hypotheses............................................................................................... 9
1.5 Structure of the thesis ................................................................................................................. 10
2. Literature review ............................................................................................................................... 11
2.1 Introduction ................................................................................................................................. 11
2.2 Development of international trade theory ................................................................................ 11
2.3 Previous work on the Linder hypothesis ..................................................................................... 19
2.4 Contributions to the existing literature ....................................................................................... 21
2.5 Research question and hypothesis .............................................................................................. 22
2.6 Conceptual model ....................................................................................................................... 23
3. Research Methodology ..................................................................................................................... 24
3.1 Introduction ................................................................................................................................. 24
3.2 Gravity model .............................................................................................................................. 24
3.3 Empirical Approach and variable description.............................................................................. 25
3.3 Data collection ............................................................................................................................. 28
3.4 Summary statistics....................................................................................................................... 28
4. Results and discussion ....................................................................................................................... 28
4.1 Introduction ................................................................................................................................. 28
4.2 Results ......................................................................................................................................... 29
4.3 Hypotheses and research question ............................................................................................. 34
4.4 Recommendations for further research...................................................................................... 36
References ............................................................................................................................................. 36
Appendix................................................................................................................................................ 41
Appendix 1: Summary statistics ........................................................................................................ 41
Appendix 2: Benchmark regressions ................................................................................................. 43
Appendix 3: Yearly regressions ......................................................................................................... 47
Appendix 4: Basic data correlations .................................................................................................. 69
Appendix 5: Pooled regressions ........................................................................................................ 70
Appendix 6: Pooled data correlations ............................................................................................... 94
Appendix 7 Correlation matrixes....................................................................................................... 99
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1.1 Introduction and Overview
1.1 Historical context
International trade is believed to have taken place throughout recorded human history. The
earliest examples of trade took place during the stone age, recently evidence was found that
obsidian and flint were traded. In Ancient history the Phoenicians sailed northern over the
Mediterranean sea to England in order to obtain tin so that they could make bronze. During
the Roman empire international trade flourished in Western Europe. However, in the dark
ages, after the fall of the Roman empire, trade routes disappeared and the trade network in
Europe was on the verge of collapsing. Trade in other parts of the world continued to exist
and flourished. International trade returned to Europe when the Hanseatic league was
established, a alliance of trading cities who secured a monopoly within northern Europe and
the Baltic’s. In the 15th century the age of discovery started, and trade thrived again due to
new trade routes to South America and India. In this era mercantilism was the ruling
economic doctrine, which stated that the control of foreign trade was of vital importance for
economic prosperity and the security of a country. More specific, the doctrine followed by
most western countries assured that most western countries had a positive trade balance and
high tariffs on manufactured goods. (Brue & Grant, 2007) The book written by Adam Smith,
the wealth of nations, criticized mercantilism and stated that all tariffs, possibly beneficial for
some industries, overall hurt the country. (Smith, 1776) Another important new insight in the
field of international trade was developed by David Ricardo, who wrote a book on how both
rich and poor countries could benefit from trade, the so called comparative advantage.
(Marrewijk, 2007)
When an inefficient producer sends the merchandise it produces best to a country able
to produce it more efficiently, both countries benefit.(Ricardo, 1817)
This doctrine is nowadays still one of the most counterintuitive explanations for international
trade. (Costinot, 2009) In the 20th century trade flourished and the volume of trade increased
with enormous speed. Some setbacks encountered, like the Great depression and both World
Wars, were quickly overcome and international trade thrived once again. globalization,
Industrialization, and multinational corporations, all have a major impact on the international
trade volumes. Growing volumes of
international trade is vital to the continuance of
globalization. (Hainmueller & Hiscox, 2006) However, in the past two decades the world has
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encountered three international crisis that had a detrimental effect on the volume of
international trade. Firstly, in 1997 the Asian crisis had a detrimental effect on the world trade
volume and economic growth. Secondly, in 2000 the dot.com bubble bursts, resulting in
dramatically declining volumes of international trade over the entire world. Last, from 2008
the international financial crisis, spreading to the corners of the world and also resulting in a
tremendous reduction in trade volumes all over the world.
Figure 1.1 Worldwide economic growth and international trade in the past 15 years.
Source: International trade, WTO
Source: GDP growth, World Bank
In figure 1.1 the both economic indicators are shown. Interesting to see is that the volatility of
international trade is much higher than the volatility of economic growth measured by world
GDP. The most recent crisis, the international financial crises, is said to be the worst of all
crises, except the Great Depression of 1929-1933. Many concerned politicians and economists
advertise a double dip, proclaiming the climbing volumes of international trade will plummet
again. (Roubini, 2009) (Rahn, 2009) Opinions about these recession differ among economists,
some argue it is needed in order to reorganize the world economic and cut out the bad
performing companies. Some authors argue that crises ensure periods of high inflation needed
to reform the economy. (Drazen & Grilli, 1990) Others suggest that enormous international
crises should and could have been prevented. (Mishkin, 1993) (Pearson & Mitroff, 1993)
However, from a pure scientific point of view these crises are interesting events that might
lead to new insights about the dynamics of certain economic phenomena.
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1.2 Linder hypothesis
Many studies suggest international trade is one of the most important and sigificant
determinants of economic prosperity. (Frankel & Romer, 1999) (Kormendi & Meguire, 1985)
In the last few decades international trade volumes increased dramatically resulting in rapid
economic growth in many parts of the world. This importance of international trade has
attracted economists to write new theories about international trade. Many theories emphasize
on the supply side of the economy in order to explain international trade, of which the
Heckser Ohlin proposition is the most famous example. In contrast to the theories based on
the supply side of the economy, some authors tried explaining international trade focusing on
the demand side of the economy. In chapter two these trade theories will be explained in
more detail, however in this section some of the theories are briefly discussed in order to
understand why the Linder hypothesis is such an important part of international trade theory.
The first important trade theory discussed in this part is that of the classical economist David
Ricardo who was mentioned above. He derived a model that focuses on comparative
advantage, possibly the most recognized concept in international trade theory nowadays.
(Costinot, 2009) Within this Ricardian model countries specialize to produce what they
produce best, resulting in full specialization instead of countries that produce several different
types of goods. The Ricardian model does not take into account the initial amount of both
labor and capital within available within country borders. Instead of focusing on factors
endowments the main determinant of international trade within the Ricardian model is
differences in the state of technology. A response to the classical international trade theory
emerged in the early 1900s. Two economists, Eli Heckser and Bertil Ohlin, contributed to the
field of international trade theory with an approach called the Heckser-Ohlin proposition. This
proposition stresses that countries should produce and export the goods that require the factor,
labor or capital, which it has plenty of. Instead of producing and exporting according to
efficiency standards, as was custom with the classical approach, in the neo-classical theory
countries should produce and export according to their initial and relative factor endowments;
the amount of labor and capital available in the economy. (Marrewijk, 2007) The theory was
developed as a response to the classical Ricardian approach of comparative advantage. While
the Heckser-Ohlin proposition has more depth and complexity it does not provide with
accurate predictions when empirically tested. (Vanek, 1968; Marrewijk, 2007). To reach the
basic conclusions within the framework strong assumptions, no economies of scale and
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costless access to technology must be present. Within this theory one would expect the United
States, which were and still are capital abundant, to export mostly capital intensive goods.
However, in 1954 Wassily Leontief empirically tested this proposition and found that the
United states tended to produce and export labor intensive goods. (Marrewijk, 2007) This is
known as the Leontief’s paradox. Many authors tried to defend the Heckser-Ohlin proposition
by changing the measurements of the model of trying a different interpretation. In various
models the strong assumptions were loosened, concluding that imperfect competition and
economies of scale determined the size of international trade volumes. (Helleiner, 1992).
Furthermore, technology-gap theories tried to explain international trade by the role of
technology. (Dosi et al, 1990). Instead of defending the Heckser-Ohlin proposition, other
economists tried explaining the paradox. (Vanek, 1968) Among them was Staffan Burenstam
Linder, who in 1961 offered a possible explanation for the Leontief paradox named the Linder
hypothesis.
The Linder hypothesis states that all countries produce goods in order to accompany the
domestic needs and preferences of inhabitants of that country. (Linder, 1961) However,
consumers have different tastes and international trade provide a means for those consumers
to have access to slightly differentiated manufacturers and benefit from a wider selection of
goods. Next, Linder argues that countries with a similar standard of living will have the same
preferences for consuming certain types of goods, resulting in more international trade
between countries that have the same consumer preference. The more similar the demand
structures of a country, the more they trade with each other. Linder explains that the process
of product development, advertising and economies of scale create export opportunities for
certain types of goods. This opportunity can only be grasped if the demand structure in the
trading country is similar. (Linder, 1961) In empirical research the gross domestic product per
capita if often used as a proxy for demand structure and consumer preferences. (Choi, 2001)
(Mcpherson et al., 2001) An interesting example in favor of the validity of the Linder
hypothesis is the international trade in the automotive industry between Germany and the
United States of America. Both countries have a high GDP per capita 1, which is, according to
Linder, an indication that their consumer preferences are alike. The trade volume in the
automotive industry between Germany and the USA is immense2, while one might say; a car
1
In 2010 Germany had a GDP per capita of $40,670 and The USA $45,989. Data source: Worldbank
In 2010 the total trade in vehicles between Germany and the USA was $8,756,325,564 Data source: UN
Comtrade
2
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is a car, no international trade is needed to facilitate demand for cars in both countries. This is
due to the fact that consumers in both countries have the same preferences and demand for
slightly differentiated automobiles. This ensures American consumers might want to drive a
BMW and German consumers might want to buy a Hummer, which in turn makes sure
international trade between those two countries exist. While both countries are capital
abundant they still trade intensively with each other. According to the Heckser Ohlin
proposition this would not be possible, Leontief was the first to notice this empirically, and
Linder one of the economists who came up with a feasible solution to Leontief’s paradox.
1.3 Aim of the research
From the previous part it became obvious that the Linder hypothesis has had a major impact
on the development of the international trade theory. The recent empirical support for this
hypothesis is believed to be caused by the increased globalization, and the according increase
in international trade volumes. Choi (2001) concludes his paper with the mention that the
recent increase of empirical evidence in favor of the Linder hypothesis might be the result of
increased volumes of international trade. This thesis aims to investigate what happens to the
empirical validity of the Linder hypothesis during a international crisis, or when the volumes
of international trade decline drastically the empirical evidence for the Linder hypothesis
diminishes. The intuitive idea behind this statement is that during a crises the volume of
international trade declines dramatically. Engel’s Law states that when income of a family
rises, the proportion of income spend on food falls. This does not mean that actual
expenditure on food cannot rise, it does state that relative expenditures on food rise less than
income. One can buy the minimum amount needed to survive, while the other can buy more.
However, it is irrational to buy more food than one can consume, so food spending will
remain somewhat balanced between the rich and the poor. Food has a low income elasticity
and is a primary good, needed to survive. (Regmi, 2002) The rich countries do not have a
agricultural sector big enough to feed the entire population, therefore they import agricultural
products from other , usually poor, parts of the world. As said before, food is a basic necessity
needed to survive, so during an international crisis, the import of agricultural products from
poor parts in the world to rich parts of the world will remain, while the trade flows of luxury
goods between rich countries will decrease. This reasoning can be used for more types of
goods, other than only agricultural products. Low income countries usually exports
agricultural products and raw materials. Raw materials, including oil, are very volatile in
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prices, but when corrected for those price changes during a crisis, the real decline in trade
volume is relatively less when compared to consumer and luxury goods. In figure 1.2 the
difference between agricultural products and manufacturers becomes obvious. From 2008
until 2009 the volume of trade in agricultural products declined by 12,78%, while the decline
in manufacturers was 20,19%.
Figure 1.2 Worldwide trade in agricultural products and manufacturers in the past 15 years.
Source: agricultural products and manufacturers, WTO
Therefore, in this thesis the emphasis will be on investigating whether there is empirical
evidence that the Linder hypothesis will be less significant during times of economic
downturn. As explained above, the Linder hypothesis states that countries with similar
demand structures will trade more with each other then countries who differ in demand
structure, or consumer preferences. (Linder, 1961) In empirical research it is custom to use
GDP per capita as a proxy for consumer preferences, the reason for this will be explained in
detail in chapter 3. When testing the hypothesis empirically it means that one tries to prove
that high-income countries tend to trade more with each other, instead of trading with lowincome countries. This leads to the hypothesis that during an intentional crisis, when trade
volumes decline dramatically, the empirical evidence in favor of the Linder hypothesis is less
significant. Trade volumes between high income countries consist partly out of luxury goods
and consumer goods, while trade volumes between low-income countries and high-income
countries consist mostly out of agricultural products and raw materials. Especially agricultural
products have a low elasticity so even when overall trade volumes declines tremendously, it
won’t have a tremendous impact on the volume of trade in agricultural products. Returning to
the previous example of the German BMW and the American Hummer, above reasoning
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leads to the fact that less Americans will buy a BMW, and less Germans will buy a Hummer
because the volumes of international trade in luxury goods during a crises decrease
tremendously. However, both high income countries will continue to import vegetables, fruit
and coffee, resulting in less trade between high income countries and relatively more trade
between high income and low income countries. This could indicate that in times of crises the
Linder hypothesis is less significant, and the Heckser Ohlin proposition, which states
countries trade as a result of supply side differences, is more plausible.
The econometric method used to evaluate the data could influence the outcomes and
conclusion of the main research question. To overcome this shortcoming this thesis will use
several econometric approaches on the same dataset. These different approaches will be
discussed in greater detail in chapter 3.
1.4 Research question and hypotheses
Deriving from the above description and the corresponding aim the following problem
formulation is defined:
Is there any influence of an international crisis, as measured by international trade volume
and GDP growth, on the statistic and economic proof of the Linder hypothesis? If so, what
are the possible explanations for this?
In order to give a framework to the thesis the research question will be answered by several
narrowed down hypotheses:
Hypothesis 1. In years of economic prosperity the statistic and economic proof for the Linder
hypothesis is both significant and robust.
Hypothesis 2. During an economic crisis the statistic and economic proof for the Linder
hypothesis is less significant and robust.
Hypothesis 3. The outcomes of hypotheses one and two above, do not depend on the
statistical methods used to evaluate the data.
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1.5 Structure of the thesis
The aim of this thesis is to give a satisfying answer to the research question and the
corresponding three hypotheses. Chapter two provides a comprehensive literature review in
which the history on international trade theory and the concept of a gravity model is
explained, by using the current available literature about those subjects. Chapter two also
explains in detail the reason why the above hypotheses were chosen. Finally, chapter 2 will
cover a comprehensive review on the previous work that has been written about the Linder
hypothesis. Subsequently, chapter 3 explains the methodology and methods used in this
research. Several econometric approaches will be examined and compared in order to
construct a decent answer to the research question. Next, chapter 4 will provide with an
thorough overview of the results and analysis. The last chapter, 5, will contain the discussion,
the policy implications and the possibilities for further research. The last chapter, and
consequently this thesis, will conclude with an short overview and a extensive conclusion in
which the main research question will be answered and discussed.
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2. Literature review
2.1 Introduction
This chapter provides an extensive review of the current literature relating to the Linder
hypothesis. The first paragraph discusses the development of international trade theory and
the reason why the Linder hypothesis is such an important part of the international trade
theory. Subsequently, in the second paragraph the previous empirical work on the Linder
hypothesis is discussed and evaluated in great detail. The next section indicates were the gap
in the current literature can be found, resulting in the contribution this thesis will have on the
current literature. Finally, a conceptual model is presented that shows the expected relations
between the different variables in the model.
2.2 Development of international trade theory
The economic theories that focus on international trade can be roughly divided in three
sections; the classical theories, the neo-classical theories and the modern theories (Chipman,
1965). In this part the main theories from all three sections will be briefly explained, ending
with the appearance of the Linder hypothesis. While the classical approach, represented by
J.S. Mill, Adam Smith and David Ricardo, is characterized by oversimplifying factors on the
supply side, it has the advantage of emphasizing on the nature of problems involving
international specialization (Chipman, 1965). The neo-classical approach, including Marshall,
Lerner and Edgeworth, attempts to simplify the factors on both the supply and demand sides,
as represented by the ideas of opportunity costs and indifference curves. (Chipman, 1965).
The modern approach, represented by Heckser & Ohlin and later Lerner and Samuelson,
focuses on factor endowments and embody the most elaborate theoretical framework that has
been developed in international trade theory history. (Chipman, 1965).
The first theory on international trade within the classical approach, developed by Adam
Smith, was that of absolute advantage. The theory suggested that when a country A has an
absolute advantage over country B, it can produce more goods than country B with the same
amount of resources, using labor as the only form of resource. (Smith, 1776) This implies
that some countries might not participate in international trade, since they have no absolute
advantage in all exportable industries. In reality this theory does not hold, since all countries
are participating in international trade so the theory of absolute advantage does not hold
empirically. An answer to this problem was suggested by David Ricardo. He states that if two
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countries have relative different costs per unit of produced output international trade is
possible, even if country A is more efficient in all production processes (absolute advantage),
it can benefit from trading with country B as long as country B has different relative
efficiencies. This statement is known as the law of comparative advantage. According to
David Ricardo, the predominant distinguishable characteristic of international trade was the
immobility of endowment factors that determine the production of a country. Production
factors were considered to be mobile within countries and immobile between countries, and
the opposite holds for final goods. Further assumptions of Ricardo were that the domestic
markets are fully integrated and only one factor of production, labor, was used to produce
final goods. Within this model the labor supply is perfectly mobile within a country, so the
unit costs of each produced good is constant, only depending on the amount of labor needed
to produce it. When Ricardo wrote about the law of comparative advantage it was feasible and
understandable to assume international capital immobility. However, nowadays capital can
move relatively freely between many nations so the law of comparative advantage has
theoretically less power to explain international trade. Even thought comparative advantage
explains international trade, it does not explain on what terms the trade takes place. According
to Ricardo the price equilibrium ratio would settle half way between the comparative cost
ratios. This was formally proven by Mill, although he only proved this for ‘one extreme case’
in which demand is so fixed that no intermediate price ratio could ever exist.
The neo-classical approach did not really have an anchorman that started the new way of
economic thinking. In the early 1930’s many economists, independent from each other,
started publishing papers introducing new concepts trying to explain international trade. Some
suggest that this spontaneous development started with Haberler (1930), who pioneered with
work on the transformation curve, nowadays called the PPF; production possibilities frontier.
After this Viner (1937) combined the transformation curve with the community indifference
curve (he did not call it that way), resulting in the well known diagram that all graduate
students must know. From the community indifference curve Leontief (1933) and Lerner
(1934) constructed a countries offer curve. The derivation of the offer curve had been done
implicitly by Edgeworth (1881), however he did not bother with the geometrical details. The
offer curve indicates the amount of one commodity that a country will export (offer) for each
amount of different types of commodities that it imports.
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The modern approach seeks to explain international trade by the differences in factor
endowments between countries. This approach builds upon the earlier work of Ricardo and
his thoughts about comparative advantage. The difference is that Ricardo focuses on the
efficiency of production when explaining international trade flows, while the modern
approach focuses entirely on the international differences of factor endowments. Within this
context one must know that factor endowments are the ‘starting’ amount of labor and capital
available in the country. Off course, one can imagine an almost infinite number of factors of
production, however for the ease of calculation and reasoning only two factors of production,
labor and capital, were assumed. The most influential theory within this line of thought is that
developed by Eli Heckser and Bertil Ohlin, known as the Heckser-Ohlin theory (from here on
HO). They use a mathematical general equilibrium model on international trade in order to
reach the conclusion that countries export the goods produced with the relative abundant
factor, and import the goods produced with the relative scarce production factor. With the
assumption of only two production factors, country A being relatively labor abundant and
country B relatively capital abundant, this means that country A will export labor intensive
produced goods to country B, and imports capital intensive produced goods from country B.
The basic version of the model, which is used in most textbooks explaining the HO model,
contains two countries, two factors of production and two final goods. The theoretical
framework has variable factor proportions between different regions or countries. This
indicates that usually within the model the developed first world countries have a relatively
high capital to labor ratio compared to third world countries, making the initial endowment of
developed countries capital abundant. In contrast, the third world countries have a relatively
low capital to labor ratio, resulting in the fact that those countries are relatively labor
intensive. The rudimentary 2-2-2 model uses many assumptions, partly to simplify the
mathematics of the model. One of the basic assumptions is that both countries within the
theoretical framework have the same production technology. This means that the Ho model
produced an alternative explanation for international trade to the comparative advantage,
instead of a complementary one. However, this assumption is not realistic since countries can
have different levels of initial endowment of production factors as well as differences in
production technology. Another assumption is that production processes should exhibit
constant returns to scale, in order to reach a mathematical equilibrium. If the production
process instead exhibit increasing return to scale, full specialization would be the ending
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equilibrium due to economies of scale. Similar to Ricardo’s comparative advantage theory,
the HO model assumes perfect capital and labor mobility within countries, and no mobility
between countries. The main results of the model are captured within four famous theorems.
(Marrewijk, 2007)
Another theorem derived from the Heckser-Ohlin model is the Rybczynski theorem. This
proposition states that, when relative constant prices remain equal, an increase in the amount
of one production factor results in a more than proportional increase in the production of the
goods that uses this production factor intensively. Subsequently, the output of the other good
will suffer an absolute decline. Relating this proposition to the HO model of international
trade means that open trade between regions result in changes of relative factor endowments,
which, in turn, lead to an adjustment of total output and type of commodities that are traded
between those regions. (Marrewijk, 2007)
The next proposition deduced from the HO model is the Stolper-Samuelson theorem. This
proposition describes a relation between the relative prices of goods and the rewards of factor
production, wage for labor and rent for capital. The proposition states that a relative increase
in the price of a commodity results in an increase in the reward of the factor of production
which is intensively used by that commodity. For instance, if grain is considered an labor
intensive good, and the relative price of grain rises, then the proposition suggests that the
return of labor, wage, should increase correspondingly. (Marrewijk, 2007)
One if the propositions is the factor price equalization. This theorem states that if, due to free
trade, the relative prices of a good between two countries converge, the prices of the factors
will equalize. For instance, the introduction of the NAFTA (increased trade between North
America and Mexico) unskilled labor wages rose in Mexico and declined in the USA. In other
words, the factor reward started to converge. (Marrewijk, 2007)
The last, and for this thesis most important, proposition is the Heckser-Ohlin theorem, which
states that a country or region will export the commodity that uses the abundant factor of
production, and import the commodity that uses the scarce factor of production. When dealing
with the assumption of two factors of production, capital and labor this theorem changes in: a
capital abundant country will export capital intensive goods, and it imports labor intensive
goods. The reasoning behind this proposition is pretty straightforward. Remember at this
point the assumptions of different capital labor ratios between countries, and the setting of the
2-2-2 model. At first, in autarky (when countries do not trade with each other) the price of
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capital intensive commodities in a capital abundant country will be relative lower compared to
the same commodity in the other country, assuming this country is less capital abundant.
Once international trade between the two countries starts, the profit maximization of firms
ensure they want to sell their products in the market that have a higher price, which is as we
just deducted, the other country. This simple reasoning leads to the Heckser-Ohlin proposition
that the capital abundant country or region will export the capital intensive commodity, and
the labor abundant country or region will export the labor intensive commodity. (Marrewijk,
2007)
The Heckser-Ohlin proposition has made a tremendous impact on the development of
international trade theory. After the appearance of this theorem many authors provided
empirical studies investigating the validity of the proposition. Authors involved in the early
empirical work on the Heckser-Ohlin proposition viewed the testing process rather differently
than the authors who undertook the empirical tests in the more recent years. Recent empirical
research stresses that the need for empirical tests to be informed by theory in the sense that the
particular hypothesis being tested can be carefully derived from the underlying theory. Early
empirical testers of the HO theorem were aware of the fact that the underlying assumptions
needed for the proposition to hold in a theoretical way, did not necessarily had to be valid in
real life. The empirical investigations conducted by this early economists were aimed at
figuring out if the economic powers behind the theorem were adequately strong that it would
hold in real life. However, in doing so, the authors were not careful enough with their
statistical tests when determining the validity of the hypothesis itself.
There have been many empirical studies investigating the validity of the Heckser Ohlin
proposition. The first and most influential research was done by Wassily Leontief in 1953.
He used an input-output table, constructed by himself and specially designed for the United
states of America, in order to access how many indirect and direct capital and labor were used
for a representative bundle of United States export and import substitutes worth one million
dollar. Leontief started his work by acknowledging the widely assumed capital abundances of
the US.
Next, he measured the amount of labor and capital needed to produce a
representative one million dollar worth of US export, and compared that with a representative
one million dollar worth of imports, using the US labor and capital requirements for both sets
of representative goods. In order for this procedure to be proper when determining whether
the US has a surplus of capital and relative scarcity of labor, he points out that the relative
productivity of both labor and capital should be the same in this country and the rest of the
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world, or differ by a constant proportion, which is one of the key assumptions of the Ho
model. Surprisingly, Leontief found that the capital/labor ratio represented in a representative
one million dollar worth of US exports was less than that of the similar bundle of import
replacements. More specifically, he found that the quantity of capital per worker used directly
and indirectly in the production of one million dollar worth of exports in 1947 was $13,991.
The amount of capital per worker used to produce one million dollar worth of import
replacements in 1947 was $18,184. This means that the US imports relative capital intensive
products and exports relative labor intensive products. This contradicts the theorem suggested
by Heckser & Ohlin, who suggest that, theoretically, it should be the other way around, since
the US is relative capital abundant. This famous opposed empirical result is known as the
‘Leontief paradox’, since he was the first author to notice this result empirically. The
analytical explanation provided by Leontief was that the productivity of labor was much
higher in the US, than in other countries. According to him this was the result of American
entrepreneurship and exceptional organization within companies. He further suggested that if
the US had three times more productive labor units than the foreign trading partners, the US
should be considered as an labor abundant country, instead of capital abundant. (Leontief,
1933)
As might be expected, the empirical results questioning the empirical validity of the HO
theorem, specifically the Leontief paradox, resulted in a huge amount of new studies focusing
on the validity of the HO theorem. Many authors copied the paper written by Leontief, only
altered the countries and the year under investigation. Even Leontief himself copied the same
research on the same sample countries, only changing the sample year from 1947 to 1956.
This new study resulted in the same conclusions as before. Baldwin (1948) also investigated
the validity of the HO theorem on multiple occasions using the same theoretical framework
and sample countries as Leontief, reaching the same conclusion in disfavor of the HO
theorem. However, research conducted by Tatemoto & Ichimura (1959) with a sample of
Japanese trade, Roskamp (1963) with a sample of West German trade and Bharadwaj &
Bhagwati (1967) with a sample of Indian trade generated mixed conclusion in terms of the
consistency of trading patterns as predicted by the factor proportions theory.
At this point some authors tried explaining the Leontief paradox by trying to change the
model assumptions of the HO model slightly, hoping to find results that were consistent with
the HO theorem. Vanek (1963) argued that an additional production factor, natural resources,
should be added to the basic 2x2x2 model. He explains the additional production factor by
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arguing natural resources have a complementarity with capital and as such can explain the
seemingly strange empirical results obtained by Leontief. He states; ‘’it may well be that
capital is an relatively abundant factor in the US. Yet relatively less of its productive services
is exported than would be needed for replacing our imports because natural resources, which
are our scarce factor, can enter productive processes efficiently only in conjunction with large
amounts of capital (Vanek, 1963, p. 153).
However, this approach did not result in a
consistent prove for the HO theorem. Another approach adopted in order to overcome the
seemingly strange results of Leontief was to divide the aggregate labor supply used by
Leontief into labor groups based on different skills and education. Kravis (1956) points out
that the US export industries contains mostly high skilled labor, while import-competing
industries use less skilled labor. Kenen (1965), Keesing (1965, 1967) and Yahr (1968) all
provided further empirical evidence on the importance of dividing the aggregate labor supply
when determining international trade patterns. Kenen (1965) estimated the human capital
employed in export and import-competing production by capitalize the wage premium of both
skilled and unskilled labor. When he estimated human capital and used a discount factor of
less than 12.7 percent, adding this to the physical capital, the Leontief paradox disappeared in
the results. However, Kenen himself points out that due to market imperfections the
capitalization approach is doubtful for acquiring an accurate measure of human capital.
Baldwin (1971) also identified the importance of human capital within the setting of the
empirical testing of the HO theorem for US trade patterns. He showed that the average years
of education per worker and the average cost of education per worker were higher in US
export than in importing industries. Other possible explanations for the Leontief paradox
which were empirically investigated are the existence of non-similar production function
across countries (Posner, 1961), increasing returns to scale instead of constant returns to scale
(Hufbauer, 1970), non-homogeneous preferences of consumers and policy measures that
distort international trade patterns such as tariffs and subsidies (Travis, 1964). However, most
studies failed to provide consistent and reliable proof in favor of the HO model. Interestingly,
no authors have questioned the factor proportions theory, they only tried to modify the
assumptions of the model.
This resulted in different approaches and new theories trying to explain international trade
patterns. The trade models and theories emerging after Leontief’s paradox did not use
comparative advantage as the main factor explaining trade. Instead of modifying the
assumptions of the HO model, some authors tried explaining international trade based on
17
differences in demand structure. Within this new line of thought the most influential theory
originates from Linder (1961). In his book he stressed the importance of differences in
production functions, differences which, in turn, are created by international differences in
demand for numerous tradable commodities. He states that a country or region cannot achieve
comparative advantage of a tradable good that is not demanded in the domestic market. If this
is a essential condition for ensuring comparative advantage, it follows that intensive trade will
take place between countries with similar demand structures. According to Linder this is the
main reason for international trade to occur, people have different tastes based on their
income level, each country produces according to its country’s income distribution. Goods
that are produced and consumed by both countries are also traded between both countries.
Therefore, countries with similar income levels and preferences will trade more intensive with
each other. Some formal assumptions are constructed to give body to the theoretical
framework. The first one is that consumer preferences depend on per capita income. This
assumption is made to simplify the empirical testing of the Linder hypothesis. The next
assumption is that the domestic production curve depends on domestic preferences and trade
is a byproduct from the domestic production and consumption pattern. The dynamics of the
model can be explained by a simplified example.
The goods produced (and consumed) in country i are ranked in order of quality, A being the
lowest quality and E the highest. Country j has an income distribution that fits the demand for
goods C up until G. Then, according to Linder, trade would occur with goods C, D and E, for
those goods have an overlapping demand in both countries. If we introduce a third country (k)
to the example, which has an income distribution resulting in the production of E to J. In this
simple example country k will trade commodities E, F an G with country j and country k will
only trade good E with country i.
Figure 2.1 Overlapping demand structure Linder model.
18
Figure 2.1 graphically illustrates the simple example presented above. The figure shows the
overlapping demand structure within the Linder model. The publishment of the book written
by Linder, an essay on trade and transformation, resulted in an enormous increase of interest
from the academic world, and empirical research investigating the validity of the hypothesis.
2.3 Previous work on the Linder hypothesis
The first author that provided a method of testing for the Linder hypothesis was Linder
himself. However, he only creates the framework in which it is possible to test the hypothesis,
he does not provide any empirical conclusions based on statistical methods. Linder creates, on
the basis of trade and income statistics, a worldwide pattern of trade intensities, trying to
describe the influence of differences and similarities in per capita income on the intensity of
trade (Linder, 1961, p. 110) He points out that he does this exercise is not conducted to find
empirical evidence in favor of his hypothesis, but to provide a starting point for other authors
who wish to apply refined statistical methods in order to isolate the effects of differences in
income per capita levels on trade intensities. One of the authors who conducted such
empirical research based on the trade intensity matrix constructed by Linder was Fortune
(1971).
He used a very simple basic regression including two independent variables, the
distance between two trading countries and the Linder variable, which represents the
difference in GDP per capita between the trading countries. He regressed this on one
dependent variable, the standardized trade volume between the two countries. Fortune (1971)
concludes that the distance variable is a strong trade breaking force. The bigger the distance
between two countries, the less trade between those two countries takes place, which is a quit
obvious and intuitive result. The empirical results somewhat support the Linder hypothesis
concerning similarities in income levels as a prerequisite for international trade. However, the
19
low coefficients of the determination for all regression, even in cases where it is significant,
indicates that it is not the only determinant. As such, his final conclusion is that the Linder
hypothesis is a supplement rather than an alternative to other trade theories. Sailors, Qureshi
and Cross (1973) conducted a similar research about the relationship between trade intensities
and difference in per capita income levels. However. They used a slightly different
methodology and a completely different dataset compared to Linder (1961) and Fortune
(1971). Were Fortune (1971) use the basic multiple regression technique in his paper, Sailors,
Qureshi and Cross (1973) used a rank order correlation technique since data is believed not to
be precise enough for a regression analysis. He finds some empirical evidence in favor of the
Linder hypothesis, suggesting that trade will be more intensive when demand structure
between countries is similar. However, similar to Fortune (1971) he concludes that the
similarities in per capita income levels cannot fully explain the patters of international trade.
Other determinants, such as export restrictions, tariffs, and transportation costs, provide an
more comprehensive explanation in determining the patterns of international trade. One
critical remark conserning the empirical research conducted by Sailors, Qureshi and Cross
(1973) is that they measure correlation, a relative weak measure, as Linder (1961) implied
causality between representative demand and international trade patterns. To overcome this
problem Kohlhagen (1977) extends the past attempts at empirical verification by using simple
regression analysis with numerous measures of demand structures, including per capita GDP
and consumption indices, in order to explain bilateral trade flows. He reaches exactly the
same conclusion as all the authors who tested the Linder hypothesis before him. Greytak and
Mchugh (1977) also test the Linder hypothesis empirically and they differ from previous
authors in three important respects. First, the dataset in their paper is different from that of
Linder (1961). Second, the analysis is focused on manufactured products instead of all
products, and third, the analysis is pointed to regions within a certain country opposed to
countries. These changes result in a less favorable result, even no support for the Linder
hypothesis at all. Qureshi et al. (1980) extended the paper written by Greytak and Mchugh
(1977) using a much more elaborate and precise dataset constructed by the Harvard Economic
Research Project. However, the results are similar to that of Greytak and Mchugh (1977). In
the paper written by Kennedy & Mchugh, (1980) another approach is adopted trying to
eliminate the distance problem. They test the theory in terms of changes in propensities to
trade against changes in income differences between two point in time. This results in an
intertemporal test of the Linder hypothesis, of which they feel will be more robust than
previous empirical tests. This empirical test does not provide any evidence in favor of the
20
Linder hypothesis. Some suggestions of why this might be are provided in the conclusion of
their paper. This paper focuses on total trade, as opposed to trade in manufacturers, and the
process of holding constant the influence of distant might introduce new variables which are
unaccounted for. Some other empirical studies have been conducted in this period, none of
them with real changes made to the model and the underlying assumptions, and all papers
reach the same conclusion. To sum up, the empirical evidence is rather sporadically and
results in favor of the Linder hypothesis are mixed up until the early 1980s. The first authors
that used a gravity model approach when trying to prove the Linder hypothesis are Thursby
and Thursby (1987) They find an overwhelming support for the Linder hypothesis and
conclude that exchange rate variability also influences bilateral trade. The sample, containing
17 countries and a time period of 8 consecutive years, provides results in favor of the Linder
hypothesis for 15 countries. Hanink (1988) extends the basic gravity model of Thursby and
Thursby (1987) with a variable to incorporate hierarchical flows and an additional rationale
for existing geographical patterns of international trade. With these additional variables the
conclusion reached by Hanink (1988) remains positive with respect to Linder’s theorem.
Trade intensities is, according to his results, an increasing function of market homogeneity, a
decreasing function of distance and an increasing function of varieties across goods.
Bergstrand (1990) constructs a theoretical framework in which the Linder hypothesis can be
rationalized. He further tests this theoretical framework empirically and finds support for the
Linder hypothesis, however he points out that the results are not very significant and further
research is needed. Franscois and Kaplan (1996) again use a gravity model trying to explain
bilateral trade flows according to the Linder hypothesis. They do not only find empirical
evidence supporting the Linder hypothesis, he also finds that income driven demand shifts
have a tremendous impact on Linder type product characteristics. These results imply that as
income rise, the total volume of trade should rise, independent of changes in the intercountry
differences between income levels. Mcpherson et al (2001) provide with an empirical study
investigating the Linder hypothesis focused on developing countries. He finds that trade
intensifies between countries with similar GDP per capita for 5 out of 6 sample countries in
developing east Africa. Choi (2001) is the first author that used an large sample, containing 55
countries and compares the development of the Linder hypothesis over time. He finds that the
support for the Linder hypothesis is getting stronger over the past decades and concludes that
this might be because of increased globalization and more free trade areas.
2.4 Contributions to the existing literature
21
The empirical evidence in favor of the Linder hypothesis gets stronger in the past decades.
Some economists conclude that this might be the result of the increased globalization and
volumes of international trade. However, none of them have tried to find a relation between
the business cycle and the significance of the Linder hypothesis. This thesis contributes to
current literature in a way that it could create a relation between the significance of the Linder
hypothesis and the worldwide volumes of international trade. Besides that, this thesis has a
extensive data sample covering large parts of the world, with countries all over the world
selected in the sample, while other authors test the Linder hypothesis with a smaller sample of
countries. Moreover, this thesis covers a time period of 15 consecutive years, covering the
years from 1995 until 2010. The results will depend upon 15 separate regressions and the
linkages between them. Some authors conduct research considering multiple years with
intervals of decades with the only intention of proving or disproving the Linder hypothesis.
This study takes it further, by not only proving or disproving the hypothesis, but also by
linking the validity of the hypothesis with the economic prosperity and the total volume of
international trade. Besides that, the study uses recent data, which is a contribution to the
current literature. It is interesting to see how the significance of the Linder hypothesis has
developed in the past 15 years, especially since this time period contains two major
international crises, which may have had a tremendous impact on the empirical validity and
significance of the Linder hypothesis.
2.5 Research question and hypothesis
The research question and corresponding hypotheses are carefully constructed in a way that in
the conclusion a definitive answer to the research question is provided. One of the
assumptions, crucial for the results of this thesis, is that worldwide volumes of international
trade declines dramatically in times of economic crisis. This assumption is straightforward
and supported by data from all big institutions, for instance WTO and the IMF. This can be
traced back to figure 1.2, which graphically depicts this assumption. Another important
assumption needed to find prove for hypothesis one and two, are the differences in demand
elasticity’s between manufactured goods and agricultural products. Regmi (2002) states that
agricultural products have a relative low income elasticity when compared to manufactured
goods. The intuitive reasoning behind this that food is a primary good, needed regardless of
the current state of the economy, and most manufacturers are not primary goods. The next
assumption critical for this thesis is that developing countries export mostly agricultural
products and raw materials, and developed countries trade mostly in manufactured goods.
22
This assumption is supported by data obtained from the International Assessment of
Agricultural Knowledge, Science and Technology for Development Global report (2009)
These considerations lead to the first two hypothesis, for when an international crisis hits the
world economy, one might expect that the trade in primary products gets hit relatively less
than the trade in luxury goods, due to the differences in elasticity’s. This should result in a
less significant empirical validity of the Linder hypothesis, since this theorem suggests that
countries with similar GDP per capita trade more intensive with each other. In order to make
sure all empirical results derived from this thesis are robust, several econometric approaches
will be adopted. This is captured in the last hypothesis, since the differences in econometric
approaches should only result in small changes of the important coefficients.
2.6 Conceptual model
In this paragraph a conceptual model of the model is created in figure 2.2. In this model,
seven variables were used in total, consisting of six independent variables and one dependent
variable. The six independent variables consist out of a basic gravity model, combined with
some dummies and the most important variable, the Linder variable that measures the
difference in GDP per capita. How the variables are constructed is explained in detail in
chapter 3.
Difference GDP per capita
Distance between i & j
GDP i
Export from
country i to j
GDP j
Adjacency
Common language
Colonial ties
23
3. Research Methodology
3.1 Introduction
The next part of the paper explains which methods are used to answer the research question
and corresponding hypotheses. First, the theoretical foundation of the gravity model used for
the empirical estimation is presented. Subsequently, the econometric estimation methods are
explained in detail. The paragraph also contains the clarification on how the variables that are
used in this paper are constructed. Finally, in the last paragraph of this chapter sources of the
data and the methods of collecting them are presented. The summary statistics introduced in
this paragraph provide a quick overview of the basic data used for this research.
3.2 Gravity model
Gravity models have become the primary method of empirically investigating bilateral trade
flows and foreign direct investments. It is apparent that the similarity between the Newtonian
gravity model and the one used in empirical economic studies does not provide a thorough
explanation for the popularity of the gravity equation as a tool for modeling bilateral trade.
The utilization of the gravity equation to empirical analysis determining the flows of
international trade was initiated by Tinbergen (1962) and Linneman (1966). The basic and
early form of the gravity equation of international trade took the following (log-linear) form:
(1,1)
The import (IM) from country i to country j is determined by the income (Y) of both country i
and j, the population (P) of both countries, and the distance (DIST) between both countries.
The coefficients for α1 and α2 are supposed to be positive, while the other coefficient are
supposed to be negative. The volume of international trade if positively influenced by the
national incomes of both countries, and negatively influenced by the population numbers and
the distance between the countries. Equation (1,1) suggests that the use of the gravity equation
for empirical economic studies is focused on cross sectional research. Early empirical work
that applied the gravity equation of international trade had success in predicting bilateral trade
flows, with a high ‘goodness of fit’. (the R2 often was higher than 0.8).
Empirical studies using the gravity equation were conducted first, and after the success of
explaining international trade, the theoretical derivation followed quickly. It is interesting to
24
know that many theories of international trade can be the base for deriving the gravity
approach. One of the earliest attempts at deriving the gravity approach theoretically was done
by Leamer and Stern (1970). They used a probability model which incorporates the
characteristics of both aggregated demand and aggregated supply, however the authors do not
specify the determinants. After this first attempt many more followed. Anderson (1979) was
the first to use utility function to derive a complete model. He assumes people differentiate
with respect to the origin of the good. Bergstrand (1985, 1989, and 1990) also uses utility
function and constant elasticity of substitution preferences and intensifies the model by
introducing prices. Another critical improvement is made by Helpman and Krugman (1985)
who derive the gravity model under the assumption of increasing return to scale. As said
before, the same basic gravity equations can be derived from many international trade
theories. This finding leads to the main criticisms about the use of the gravity approach; one
cannot use the gravity approach when determining which trade theory has the upper hand,
since all theories can be theoretical derived from the empirical model. However, the gravity
model of international trade remains an critical tool for international trade modeling because
of its ease, empirical success and high degree of flexibility.
3.3 Empirical Approach and variable description
As the Linder hypothesis suggests bilateral trade patterns depends on the similarity of
preferences between consumers in both countries, a modified type of the gravity model can be
used in order to investigate the validity of the hypothesis. The proxy for consumer preferences
within this empirical investigation is the GNP per capita, as is explained in chapter 2. The
slightly modified gravity equation used for this purpose takes the following form;
Where:
25
Where
is the export between country i and j at time t. The dependent variable takes
the size of both countries in consideration by normalizing the value. The ‘Linder variable’ is
the single most important variable within this thesis. The coefficient that results from the
outcome of the ordinary least square regression and the corresponding statistical validity
determines the empirical validity of the Linder hypothesis. The absolute difference between
the per capita GDP of both countries divided by the sum of the importing and exporting
countries results in the Linder variable. The expected sign of the variable is negative, since the
greater the difference between per capita income in country i and per capita income in country
j, the smaller the trade flows between both countries should be, according to the Linder
hypothesis. The variable
adds both countries per capita GDP. The expected sign of
the coefficient is positive, meaning that richer countries (measured in per capita GDP) will
trade more with each other. The GDP of country i and country j are included too, as
customary within the gravity equation. The expected signs of these variables are positive. The
variable
depicts the distance between country i and j. This variable does not depend
on time since distance doesn’t change over time. One can reason that distance does change
over time due to shifts in the earth crust, however this takes thousands of years and is
neglectable within the time span of this study. The last three variables are dummies for
adjacency, common language and colonial ties, all not changed over time. Subscript t takes
the values for the years between 1995 and 2010, totaling 16 years.
Above specification can and will be evaluated on a yearly basis, however to give a complete
picture the same model will be estimated for the entire dataset. In order to reduce the bias in
the estimators another specification containing the robust standard errors will be provided.
Both specifications mentioned above will be combined with the multilateral resistance terms
in order to further reduce the bias that might be present. In order to determine the MR terms
for this dataset the article presented by Baiyer & Bergstrand (2006) containing a relative
simple linear solution to the problem associated with the creation of the MR terms will be
used.
The model set up by Baiyer & Bergstrand (2006) contains a Taylor approximation to
Anderson’s & Van Wincoop (2003) multilateral resistance terms. The estimations starts by
assuming the world is completely free of transportation costs and trade barriers. Next, a linear
corrections on the estimators is created in order to reduce the total bias. This leads to the
approximation of each countries individual multilateral resistance to trade with other countries
26
based on the GDP weighted average of the indicator of trade barriers with all other countries.
For example, the distance variable used in this thesis is transferred into the multilateral
distance terms as follows;
Above formula describes the calculations needed to transform the normal distance variable
into the variable corrected for multilateral resistance. The first part states that if two countries
are far apart from each other compared to the rest of the world the MR value will be larger.
The second terms states that if two countries are far from other countries compared to the
average distance between countries in the world the value will take a smaller value. This
process will be repeated for all barriers to trade in the basic model, resulting in the following
specification:
Again, this formula will be estimated for the ‘normal’ ordinary least squares and for the
variant with the standard robust errors. Finally, the data will be pooled and dummies are
added for all 16 years and all 54 countries. The outcomes of these regression are presented
and discussed in chapter 4. In order to address the hypothesis and the corresponding research
question the analysis must be conducted on a yearly basis. The results of the benchmark
regressions with pooled data and six different specifications assists in determining the correct
specification with which the hypotheses will be tested. From these early results based on the
pooled dataset, containing 43.372 observations, its becomes clear that adding the multilateral
resistance terms does change the Linder coefficient slightly, however it does not change the
associated probability level. The results of the benchmark regressions are discussed in detail
in chapter 4, however based on the results two specifications were chosen to conduct the
yearly analysis. The first specification used for the individual yearly analysis is the third
specification which includes the MR terms but does not use robust standard errors. The
second specification used to determine the yearly effects is the fixed effect model with robust
standard errors. The reasoning for these two specifications is explained in chapter 4. In order
to give a satisfying answer to the hypotheses the correlation between the results of the yearly
Linder coefficients and the yearly international trade volume and the yearly GDP growth must
be assessed. The Linder coefficients needed for the calculation of the correlation results from
27
the regression done in formula (1.1) and (1.2). The yearly changes in international trade
volume are calculated from the basic export data used for this thesis. The GDP changes also
results from the basic dataset used in this thesis. It is important to notice that the changes in
both trade volume and GDP are not calculated for the entire world, only the sample countries
used in this thesis are included.
3.3 Data collection
The dependent variable depicts the export from country i to country j. The data was obtained
from the United Nations Comtrade. This database contains data on both import and export
from almost all countries in the world and is online available. The GDP and GDP per capita
used in the other variables was obtained from the IMF website. The distance between two
countries is the distance between two great cities within this countries, which usually is the
capital. However, big countries can have great distance between the capital and other cities it
might be better to take a more central city. The distance variable can be calculated using the
longitude and latitude data for each city from the United nations website. Plug the longtitude
and latitude values of two places in the great circle formula and the formula produces the
distance between both cities. Fortunately, this calculations have been done before by Wei and
Frankel (1995). The variables distance and the two dummies adjacency and common language
are obtained from Wei’s homepage. The last dummy, colonial ties, was added manually.
3.4 Summary statistics
Appendix one contains the summary statistics and gives a short overview of the basic data
used in this thesis. The data on export contains gaps, as the total number of observations each
year should equal 2970. Especially in 2010 the data is very sporadically, This is due to the
fact that during the time period of obtaining the data, many countries did not provide the
United Nations with the necessary data yet. The regression results for this year should be
handled carefully.
4. Results and discussion
4.1 Introduction
28
The main part of chapter 4 discusses the results obtained from the regressions as proposed in
chapter 3. Paragraph 4.2 contains all the results and brief overview of the interesting
outcomes. Paragraph 4.3 continues by adding economic context to the obtained results and by
answering the hypotheses and the research question. Next, paragraph 4.4 embody the
recommendations for further research and provides some concluding remarks.
4.2 Results
In this paragraph the results will be presented and discussed. Table 1 contains the benchmark
regressions used to determine which specification is used for the remainder of the thesis. As
explained in the previous part 6 specifications were estimated and the results are shown in
table 1 below.
Table 1: Benchmark regressions.
Variable
c
GDPi
GDPj
DIST
LINDER
ADJ
COM
COL
Full panel
OLS
(1)
6.353***
(0.000)
0.261***
(0.000)
0.185***
(0.000)
-0.410***
(0.000)
-0.042***
(0.000)
0.250***
(0.000)
0.437***
(0.000)
-0.043**
(0.164)
Full Panel
OLS+SRE
(2)
6.353***
(0.000)
0.261***
(0.000)
0.185***
(0.000)
-0.410***
(0.000)
-0.042***
(0.000)
0.250***
(0.000)
0.437***
(0.000)
-0.043**
(0.048)
MRDIST
-
-
MRADJ
-
-
MRCOM
-
-
MRCOL
-
-
43.372
43.372
(1) + MR
(2) + MR
(3)
5.614***
(0.000)
0.336***
(0.000)
0.255***
(0.000)
-0.398***
(0.000)
-0.044***
(0.000)
0.262***
(0.000)
0.460***
(0.000)
0.099***
(0.002)
0.007***
(0.000)
-0.205***
(0.005
0.070***
(0.000)
-0.597***
(0.000)
(4)
5.614***
(0.000)
0.336***
(0.000)
0.255***
(0.000)
-0.398***
(0.000)
-0.045***
(0.000)
0.239***
(0.000)
0.460***
(0.000)
0.099***
(0.000)
0.007***
(0.000)
-0.205***
(0.000)
0.070***
(0.000)
-0.597***
(0.000)
43.372
43.372
Dummy (year)
Dummy(country)
N
(1) + fixed
effects
(5)
(2) + fixed
effects
(6)
-
-
0.053***
(0.002)
0.288***
(0.000)
-0.455***
(0.000)
-0.021***
(0.000)
0.150***
(0.000)
0.462***
(0.000)
0.129***
(0.000)
-0.009***
(0.000)
-0.273***
(0.000)
0.184***
(0.000)
-0.625***
(0.000)


0.053***
(0.006)
0.288***
(0.000)
-0.455***
(0.000)
-0.021***
(0.000)
0.150***
(0.000)
0.462***
(0.000)
0.129***
(0.000)
-0.009***
(0.000)
-0.273***
(0.000)
0.184***
(0.000)
-0.625***
(0.000)


43.372
43.372
29
DW
R2
Notes;
2.441
0.457
2.441
0.457
2.361
0.484
2.361
0.484
2.218
0.666
2.218
0.666
*** , ** and * indicate significance at the 1%, 5% and 10% levels, respectively. Corresponding p-values
are in parentheses. For further information about the dummy variables and the t-values, see appendix 2.
Some interesting results are obtained from table 1. The basic gravity model which consists of
the variables GDPi, GDPj, DIST and the dummies ADJ, COM and COL hold for all
specifications except for the dummy COL for the first specification. This could be explained
by the fact that the sample contains a random selection of countries from all over the world.
However, some countries that were colonized in the past are not included in the sample since
data on international trade provided by the United Nations Comtrade is very sporadic and not
accurate. Another interesting result is that the multilateral resistance terms are all very
significant, so the changes in coefficients of the basic gravity model as well as the Linder
coefficient, as a result of adding the MR terms, could indicate that a part of the bias of the
coefficients is reduced. All coefficients within the gravity model have the expected signs.
Both GDPi and GDPj have positive coefficients, indicating that the economic size of
countries have a positive effect on the volume of international trade, which is in line with all
previous results regarding the gravity model. The distance variable has an tremendous impact
on the volume of international trade, which became evident from previous work. This thesis
reinforce the suggestion that the distance between two countries has a negative impact on the
volume of international trade between countries. When looking at the statistical properties
involved in the benchmark regressions, one can see that the Durbin-Watson statistic is slightly
above 2, which indicates that the successive error terms are different in value to another
which, in turn, implies a possible underestimation of the statistical significance. Since the
significance is already very high for most variables and specifications this should not pose as
a problem. The goodness of fit increases when adding more variables, which is an obvious
result since more variables mean a bigger sample. The single most important variable within
these thesis, the Linder variable, is also significant at the 1% level for all specifications.
Furthermore the sign of the Linder coefficient is negative as expected beforehand. This
indicates that for the time period investigated in this thesis evidence in favor of the Linder
hypothesis is obtained. On itself, this is already an interesting result. It indicates that the
recent trend in literature, which finds proof in favor of the Linder hypothesis, is continued in
this thesis. However, this thesis takes it a bit further by combining the statistical and economic
proof of the Linder hypothesis with the development of international trade and GDP. In order
to assess this precise relationship a pooled data analysis does not suffice, since the differences
between the individual years determine the outcome of the research question. The pooled data
30
does provide a mean to induce the best method for evaluating the individual yearly
regressions. Since adding the MR terms does not lower the probability of the coefficients, it is
rational to keep the variables in the yearly regressions. Furthermore, the robust errors do not
influence the output therefore it is not needed to add them. This results in the selection of the
third specification for the yearly regressions. The fixed effect model does provide different
results, thus the sixth specification is also investigated for further testing.
In order to make the analysis more meaningful the data will be partly pooled, thus creating an
moving average of two or more years. The decision of which years should be pooled and
which not is based upon common economic sense. In total 5 different ways of pooling the
individual years in small moving averages is provided, with an economic explanation on why
these years are pooled.
1. In the basic dataset (see appendix 4) one can see that international trade declines in the
years 1998, 2001 and 2009. Not coincidental, these years are all associated with
international crises. The Asian financial crisis, the dot.com bubble and the financial
crisis in that respective order. These crises do not start or end on the first of January,
but develop over time. Also, the effects of crises often drag on even after the
international trade volume is recuperating. These considerations lead to the first
selection of moving averages. Take the year with the decline in international trade and
pool this year with the year before and after. The new data on which the correlations
are based can be found in appendix 5.
Table 2: Moving average outcomes (1)
Specification
Statistic(3)
Economic (3)
Statistic (6)
Economic (6)
Correlation coefficients
Int Trade
GDP
0.6224
0.6743
-0.3101
0.0682
-0.0601
0.3629
-0.5884
-0.1219
The outcomes in table 4 contain some values above 0.5 and below -0.5 indicating that some
correlation is found between the variables. Especially the statistic values for the third
specification have high correlation coefficients for both international trade and GDP. This
indicates that when GDP and international trade volume grows, the t-value of the Linder
coefficients gets higher. Since the t-values are negative this means a lower significance of the
Linder hypothesis, which totally contradicts the hypotheses constructed for this thesis. The
31
other value in the table below -0.5 is the correlation between the economic coefficient from
the sixth specification and the international trade. This means that if international trade
volumes grow, the economic impact of the Linder hypothesis becomes less important. A
similar, yet slightly different, moving average is created for the same dataset were only the
year after is pooled with the years in which trade volume declines. Also, the same analysis is
done with pooling the data with the year before. This results in two extra ways of pooling the
data with 2 year pool instead of 3 years. However, these results overlap entirely with the
correlation coefficients found in table 4. Therefore, these results are not included in the thesis
since it doesn’t add any new insights to the analysis.
2. The next way of pooling the data is not based on the international trade volume
changes, but on the GDP development in the past 16 years. All consecutive years of
growing GDP are pooled. The economic explanation behind this decision is that
consecutive years of GDP growth indicate an booming period, and when GDP declines
(compared to the previous year) a bump in the road is encountered. With these years
pooled one can distinguish between strong economic periods and weak periods, which
is interesting since the relates to the research question of this thesis. The pooled data is
presented in appendix 6.
Table 3: Moving average outcomes (2)
Specification
Statistic(3)
Economic (3)
Statistic (6)
Economic (6)
Correlation coefficients
Int Trade
GDP
-0.1813
-0.2974
0.0842
0.1517
-0.3752
-0.2443
-0.3868
-0.0042
At first sight, these results do not contribute anything to the thesis. None of the correlarion
coefficients are above 0.5 or below -0.5, indicating that with this method of pooling the years
no progress has been made towards answering the hypotheses. However, it is interesting to
see that the sign of the statistic correlation coefficients is negative again. The negative
correlation between the t-values and the GDP/Int trade is in line with the hypotheses set in
this thesis. Unfortunately the correlation coefficients are not low enough to be able to draw
good conclusions.
32
3. The third method of pooling the years is also based upon the GDP development
during the time span of this research. However, instead of pooling the consecutive
years of GDP growth, now first the average GDP growth is calculated. The average
growth of the sample countries over the past 16 years is (rounded) 3.5%. All
consecutive years with growth higher than 3.5% are pooled. This results in a
completely different selection of pooled years, but still makes economical sense by
capturing the booming years of the time sample. Again, full information is provided in
appendix 6.
Table 4: Moving average outcomes (3)
Specification
Statistic(3)
Economic (3)
Statistic (6)
Economic (6)
Correlation coefficients
Int Trade
GDP
-0.1888
-0.5930
0.0897
-0.0040
-0.3381
-0.3871
-0.3754
0.0299
The results in table 6 have some interesting impact. All correlation coefficients regarding the
statistic evidence have the correct signs, all negative. Most are not very strong, but one of
them is almost -0.6. This is in line with the expectations and hypotheses set forth in this
thesis. The economic correlation coefficients do not have the right values and half of them do
not even have the right sign.
4. The fouth method of pooling the data is based on international trade volume again.
It is basically the same method as method 3. This method is based on consecutive
years of growing international trade, calculated by the average growth in trade volume
(10% rounded). See appendix 6 for full information on which years are pooled to find
an moving average.
Table 5: Moving average outcomes (3)
Specification
Statistic(3)
Economic (3)
Statistic (6)
Economic (6)
Correlation coefficients
Int Trade
GDP
-0.2508
-0.3427
-0.0318
-0.1409
-0.2947
-0.1414
-0.2773
0.1878
33
This outcome is very similar with the outcome based on GDP instead of international trade
volume. Again, all statistic correlations have a negative sign.
5. The last method of pooling the individual years is based on the first two. However,
international crises often drag on longer than only one year. This indicates that it is
important to investigate what happens with the correlation coefficients if we add
another year after the crises to the pool. This method does not only pool the crises year
(t) but also t+1 and t+2.
Specification
Statistic(3)
Economic (3)
Statistic (6)
Economic (6)
Correlation coefficients
Int Trade
GDP
0.622
0.673
-0.304
0.013
-0.060
0.363
0.368
0.165
In the next paragraph the results shall be summed up and placed in economic context.
Furthermore a definitive answer to the hypotheses and the research question will be given.
4.3 Hypotheses and research question
The results presented above do not provide enough evidence in favor of the hypotheses put
forth in this thesis. The table below sums up how many correlations coefficients have the
correct sign and how many proceed the value of -0.5 or lower or 0.5 and higher.
Table 8: total summary
Specification
Statistic(3)
Economic (3)
Statistic (6)
Economic (6)
Correct sign
Int Trade
3 (5)
2 (5)
5 (5)
1(5)
GDP
3 (5)
3 (5)
3 (5)
3 (5)
Correct value + correct sign
Int Trade
GDP
0 (5)
1 (5)
0 (5)
0 (5)
0 (5)
0 (5)
0 (5)
0 (5)
Table 8 sums up the results from this research. It is interesting to see that often the right
correlation sign is obtained, but the correlation is not very strong in most cases. There is one
exception, that is the statistic correlation between the third specification and the GDP
development. This means that when worldwide GDP grows faster than the average of 3.5%
per year, the significance of the Linder hypothesis gets stronger. Especially the statistical
correlation coefficient has the correct sign often for both specifications. This could indicate
34
that there is some relation between the validity of the Linder hypothesis and the state of the
economy. However, for all but one observation the correlation coefficients are not big
enough. What is interesting to see is that the high correlation coefficients of the third
statistical specification have the wrong coefficient. This indicates that, when pooling the
crises years (t) with either t+1 or t+1 and t+2 the results show that an international crises
makes the statistical validity of the Linder hypothesis stronger, which is in contrast with the
hypothesis of this thesis. So when international trade volumes and GDP growth slows down,
international trade gets more based on similarities between GDP per capita.
This concludes that the hypotheses within this thesis are not supported. From this thesis it
became apparent that the Linder hypothesis is a valid trade theory and empirical support can
be found to support that statement. This thesis continues the current trend of finding strong
and robust proof in favor of the Linder hypotheses. However, the most important feature
within this thesis, the relation between the worldwide business cycle and the statistic and
economic proof in favor of the Linder hypothesis, is not found. The conclusion therefore must
be that, while the Linder hypothesis gets more and more support, the economic situation
seems to have little impact on the validity of the hypothesis. This results in a rejection of the
first two hypotheses set forth in chapter 1. The third hypotheses must be rejected as well,
since the differences between the two specifications investigated in detail are apparent. The
answer to the research question is a negative one. There is no influence of an international
crisis, as measured by GDP growth and international trade volume, on the statistic and
economic proof of the Linder hypothesis. Although this results seems quite disappointing, it
does provide new insights about the development of the Linder trade theory over time. The
next question is why the results are so disappointing. There are more than 200 countries in the
world that almost all participate in international trade. The sample used in this thesis only
consists of 54 countries. These countries do represents over 90% of all international trade
volume. The sample contains all major economies and even may minor countries. However,
the countries left out of the sample still represent approximately 10% of international trade
volumes. Building on the assumption that poor countries often export agricultural products
this could influence the outcomes of this thesis. However, to include all countries in the world
would be nearly impossible since this thesis focuses on bilateral trade patterns. The basic data
used to cover 54 countries contains already over 500.000 observation points. Besides that, the
time sample could be extended towards a larger period to cover more international crises.
35
4.4 Recommendations for further research
From this thesis it became apparent that the volume of international trade or the development
of GDP does not have an impact on the statistic or economic evidence of the Linder
hypothesis. There must be a reason for the fact that in early research there was no empirical
proof in favor of the Linder hypotheses, while recent literature and this thesis does find strong
evidence. This thesis rules out the possibility that the change of direction could not be
credited to the increased volumes of international trade or GDP growth. That does leave the
question why the only recently (1990’s) support in favor for the Linder hypothesis was
obtained. Possible other determinants that could contribute to this phenomena are migration
flows, FDI investment flows or free trade agreements.
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40
World Trade Organization International trade statistics data figure 1.1 (2011). Website:
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World
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(2011)
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figure
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yearly
http://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG
GDP
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Website:
Appendix
Appendix 1: Summary statistics
GDP per capita
Variable
Obs.
55.00
GDP PC 1995
55.00
GDP PC 1996
55.00
GDP PC 1997
55.00
GDP PC 1998
55.00
GDP PC 1999
55.00
GDP PC 2000
55.00
GDP PC 2001
55.00
GDP PC 2002
55.00
GDP PC 2003
55.00
GDP PC 2004
55.00
GDP PC 2005
55.00
GDP PC 2006
55.00
GDP PC 2007
55.00
GDP PC 2008
55.00
GDP PC 2009
55.00
GDP PC 2010
Source: Author’s calculation
Mean
13,297.74
13,636.83
13,113.19
12,903.49
13,144.88
12,981.33
12,708.11
13,408.10
15,702.91
17,912.44
19,290.88
20,576.45
23,431.91
25,184.73
22,475.23
23,793.36
Std. Dev.
12,478.88
12,412.76
11,670.42
11,723.55
12,024.83
11,776.16
11,551.34
12,510.39
14,762.19
16,739.50
17,890.60
18,853.47
21,369.78
22,592.11
19,825.65
20,581.75
Min
355.76
390.22
322.73
290.68
310.48
389.95
361.11
470.70
524.26
620.08
716.18
791.15
905.37
1,018.15
989.25
1,049.75
Max
44,874.60
43,093.27
37,323.35
38,344.56
37,544.78
37,390.55
37,821.70
42,206.16
49,228.14
56,219.31
65,203.29
72,074.46
82,086.88
93,235.22
78,182.77
84,443.63
41
GDP (billions US dollar)
Variable
Obs.
55
GDP 1995
55
GDP 1996
55
GDP 1997
55
GDP 1998
55
GDP 1999
55
GDP 2000
55
GDP 2001
55
GDP 2002
55
GDP 2003
55
GDP 2004
55
GDP 2005
55
GDP 2006
55
GDP 2007
55
GDP 2008
55
GDP 2009
55
GDP 2010
Source: Author’s calculation
Mean
512.28
522.28
518.79
517.34
539.22
553.67
548.97
569.60
639.05
715.45
767.84
825.09
924.73
1,005.77
961.77
1,040.14
St. Dev.
1,240.88
1,243.50
1,268.95
1,306.02
1,395.37
1,474.87
1,488.90
1,531.46
1,621.25
1,740.27
1,835.69
1,932.78
2,046.57
2,133.63
2,109.86
2,218.95
Min
6.70
7.33
7.42
7.91
7.27
7.09
6.38
5.09
5.57
6.93
7.49
9.28
12.22
16.60
12.09
12.59
Max
7,414.63
7,838.48
8,332.35
8,793.48
9,353.50
9,951.48
10,286.18
10,642.30
11,142.18
11,867.75
12,638.38
13,398.93
14,061.80
14,369.08
14,119.05
14,657.80
Distance & dummies
Variable
Obs.
2970
Distance
2970
Adjacency (=0,1)
Common lang. (=0,1) 2970
2970
Colonial ties. (=0,1)
Source: Author’s calculation
Mean
8312.43
0.04
0.15
0.06
St. Dev.
4771.22
0.19
0.36
0.15
Min
296.90
0
0
0
Max
19870.60
1
1
1
42
Appendix 2: Benchmark regressions
Specification 1: OLS
Source
SS
df
MS
Model
Residual
19530.8634
7
23183.2073 43364
2790.12335
.534618745
Total
42714.0707 43371
.984853259
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
_cons
.261267
.1846007
-.4097072
-.0420994
.2504466
.4375934
-.0430026
6.352919
Std. Err.
.0023659
.0023667
.0043024
.00339
.0204188
.0102139
.0308693
.0433114
t
110.43
78.00
-95.23
-12.42
12.27
42.84
-1.39
146.68
Number of obs
F( 7, 43364)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.164
0.000
=
43372
= 5218.90
= 0.0000
= 0.4572
= 0.4572
= .73118
[95% Conf. Interval]
.2566299
.1799619
-.41814
-.0487439
.2104254
.417574
-.1035069
6.268027
.2659042
.1892396
-.4012744
-.0354549
.2904678
.4576127
.0175017
6.43781
Number of obs
F( 7, 43364)
Prob > F
R-squared
Root MSE
=
43372
= 5427.04
= 0.0000
= 0.4572
= .73118
Specification 2: OLS + standard robust errors
Linear regression
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
_cons
.261267
.1846007
-.4097072
-.0420994
.2504466
.4375934
-.0430026
6.352919
Robust
Std. Err.
.0025518
.0023023
.0038609
.0033945
.0158241
.0099058
.0217794
.039243
t
102.39
80.18
-106.12
-12.40
15.83
44.18
-1.97
161.89
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.048
0.000
[95% Conf. Interval]
.2562656
.1800882
-.4172747
-.0487526
.2194312
.4181778
-.0856906
6.276001
.2662685
.1891133
-.4021398
-.0354462
.2814621
.4570089
-.0003146
6.429836
Specification 3: OLS + multilateral resistence terms
43
Source
SS
df
MS
Model
Residual
20689.8205
11
22024.2502 43360
1880.89278
.507939349
Total
42714.0707 43371
.984853259
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3345988
.2550091
-.3977378
-.0446281
.2622044
.4595572
.0989697
-.0069851
-.2050118
.0700773
-.5972322
5.614041
Std. Err.
.0028807
.0028131
.0042738
.0033096
.020106
.0102469
.0318459
.0003324
.0394552
.0101846
.0370969
.0455762
t
116.15
90.65
-93.06
-13.48
13.04
44.85
3.11
-21.01
-5.20
6.88
-16.10
123.18
Number of obs
F( 11, 43360)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.002
0.000
0.000
0.000
0.000
0.000
=
43372
= 3702.99
= 0.0000
= 0.4844
= 0.4842
=
.7127
[95% Conf. Interval]
.3289526
.2494954
-.4061145
-.0511149
.2227963
.439473
.0365511
-.0076367
-.2823448
.0501153
-.6699428
5.52471
.3402449
.2605228
-.3893611
-.0381413
.3016125
.4796414
.1613882
-.0063336
-.1276789
.0900394
-.5245216
5.703371
Specification 4: OLS + multilateral resistence terms + standard robust errors
Linear regression
Number of obs
F( 11, 43360)
Prob > F
R-squared
Root MSE
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3345988
.2550091
-.3977378
-.0446281
.2622044
.4595572
.0989697
-.0069851
-.2050118
.0700773
-.5972322
5.614041
Robust
Std. Err.
.0030406
.0027169
.0038991
.0032917
.0167217
.0102302
.0213478
.000274
.0300841
.0081972
.023541
.0433556
t
110.04
93.86
-102.01
-13.56
15.68
44.92
4.64
-25.49
-6.81
8.55
-25.37
129.49
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
=
43372
= 3799.34
= 0.0000
= 0.4844
=
.7127
[95% Conf. Interval]
.3286392
.2496839
-.4053802
-.05108
.2294296
.4395057
.0571275
-.0075222
-.2639772
.0540106
-.6433729
5.529063
.3405583
.2603343
-.3900954
-.0381762
.2949792
.4796087
.1408118
-.006448
-.1460465
.086144
-.5510914
5.699018
44
Specification 5: Fixed effect model + MR terms
45
Source
SS
df
MS
Model
Residual
28441.3065
80
14272.7642 43291
355.516331
.329693567
Total
42714.0707 43371
.984853259
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.053605
.2881495
-.4546731
-.0206381
.1504447
.461622
.1286356
-.009639
-.2726694
.1842156
-.624723
(omitted)
-.0241465
-.0049301
.0096467
-.0056777
.0272494
.0414848
.0313412
-.0232161
-.0396298
-.0567877
-.073685
-.108881
-.1209948
-.1631254
-.1463751
.8287134
1.306379
1.62841
1.347214
1.747135
1.301206
1.723526
.9279954
1.298563
.9482124
1.121506
1.313792
.7910695
1.286775
1.126581
.9786352
.2709597
-.3969421
.9617253
.9647805
.6431657
1.05057
1.032961
.7265113
.7400171
1.121556
1.366975
1.049614
.418112
(omitted)
.6473604
.5827717
-.1050557
-.3314374
-.3367187
.3149512
.0485729
.4091422
-.2067946
.2097512
-.1457972
-.1015956
-.7812747
1.297065
1.596203
.9150238
1.662578
1.403304
.581492
.5760381
1.530975
1.474549
.606099
.6167861
1.689749
6.702272
Std. Err.
t
Number of obs
F( 80, 43291)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
43372
= 1078.32
= 0.0000
= 0.6659
= 0.6652
= .57419
[95% Conf. Interval]
.0169453
.0028367
.0038983
.0027385
.0166797
.0088085
.0257754
.0003675
.0445157
.0115479
.0421674
3.16
101.58
-116.63
-7.54
9.02
52.41
4.99
-26.23
-6.13
15.95
-14.82
0.002
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.0203918
.2825894
-.4623137
-.0260055
.1177522
.4443571
.0781155
-.0103594
-.359921
.1615815
-.707372
.0868182
.2937095
-.4470324
-.0152706
.1831372
.4788869
.1791558
-.0089186
-.1854178
.2068498
-.5420741
.0162575
.016168
.0161124
.0159091
.0158445
.0158334
.015867
.0162487
.0170708
.0178813
.0188221
.0204353
.0217892
.0209065
.0234835
.0647566
.0752755
.0807596
.071946
.0899413
.0777014
.1059125
.0473946
.050558
.0443825
.0409236
.0570611
.0452096
.0493203
.0501897
.0580217
.0426797
.0339709
.0387539
.0333293
.0403615
.0642606
.0438204
.05095
.038809
.045585
.0638182
.0354169
.0383787
-1.49
-0.30
0.60
-0.36
1.72
2.62
1.98
-1.43
-2.32
-3.18
-3.91
-5.33
-5.55
-7.80
-6.23
12.80
17.35
20.16
18.73
19.43
16.75
16.27
19.58
25.68
21.36
27.40
23.02
17.50
26.09
22.45
16.87
6.35
-11.68
24.82
28.95
15.94
16.35
23.57
14.26
19.07
24.60
21.42
29.64
10.89
0.137
0.760
0.549
0.721
0.085
0.009
0.048
0.153
0.020
0.001
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
-.0560115
-.0366196
-.021934
-.0368598
-.0038062
.010451
.0002416
-.0550639
-.073089
-.0918354
-.1105767
-.1489346
-.163702
-.2041025
-.1924032
.7017893
1.158837
1.47012
1.206199
1.570848
1.148909
1.515935
.8351011
1.199469
.8612217
1.041295
1.201951
.7024579
1.190106
1.028208
.8649117
.1873068
-.4635257
.885767
.8994545
.5640564
.924618
.9470724
.6266484
.6639508
1.032209
1.24189
.9801963
.342889
.0077186
.0267594
.0412273
.0255044
.058305
.0725186
.0624409
.0086317
-.0061707
-.0217401
-.0367933
-.0688273
-.0782876
-.1221483
-.1003469
.9556375
1.45392
1.7867
1.48823
1.923421
1.453502
1.931116
1.02089
1.397658
1.035203
1.201717
1.425633
.8796811
1.383444
1.224954
1.092359
.3546127
-.3303584
1.037684
1.030107
.722275
1.176522
1.11885
.8263741
.8160834
1.210904
1.49206
1.119032
.4933351
.0603709
.0323355
.0391998
.0350918
.0367293
.0295668
.0353054
.0397041
.0353733
.0303673
.0297302
.0426833
.0325367
.0468356
.0421248
.0595991
.0599661
.0373917
.0350273
.0352234
.0372875
.0411356
.0329983
.0460436
.0747212
.0699037
10.72
18.02
-2.68
-9.44
-9.17
10.65
1.38
10.30
-5.85
6.91
-4.90
-2.38
-24.01
27.69
37.89
15.35
27.73
37.53
16.60
16.35
41.06
35.85
18.37
13.40
22.61
95.88
0.000
0.000
0.007
0.000
0.000
0.000
0.169
0.000
0.000
0.000
0.000
0.017
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.5290322
.5193935
-.181888
-.4002179
-.4087088
.2569997
-.0206263
.3313215
-.276127
.1502308
-.2040689
-.1852555
-.8450471
1.205266
1.513638
.7982083
1.545043
1.330015
.5128378
.5069995
1.457891
1.393923
.5414218
.5265397
1.543294
6.565259
.7656886
.6461499
-.0282234
-.2626569
-.2647286
.3729028
.1177721
.4869629
-.1374622
.2692717
-.0875255
-.0179356
-.7175022
1.388863
1.678768
1.031839
1.780113
1.476592
.6501462
.6450767
1.60406
1.555176
.6707763
.7070324
1.836204
6.839284
Specification 6: Fixed effect model + MR terms + standard robust errors.
46
Linear regression
Number of obs
F( 80, 43291)
Prob > F
R-squared
Root MSE
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.053605
.2881495
-.4546731
-.0206381
.1504447
.461622
.1286356
-.009639
-.2726694
.1842156
-.624723
(omitted)
-.0241465
-.0049301
.0096467
-.0056777
.0272494
.0414848
.0313412
-.0232161
-.0396298
-.0567877
-.073685
-.108881
-.1209948
-.1631254
-.1463751
.8287134
1.306379
1.62841
1.347214
1.747135
1.301206
1.723526
.9279954
1.298563
.9482124
1.121506
1.313792
.7910695
1.286775
1.126581
.9786352
.2709597
-.3969421
.9617253
.9647805
.6431657
1.05057
1.032961
.7265113
.7400171
1.121556
1.366975
1.049614
.418112
(omitted)
.6473604
.5827717
-.1050557
-.3314374
-.3367187
.3149512
.0485729
.4091422
-.2067946
.2097512
-.1457972
-.1015956
-.7812747
1.297065
1.596203
.9150238
1.662578
1.403304
.581492
.5760381
1.530975
1.474549
.606099
.6167861
1.689749
6.702272
Robust
Std. Err.
t
P>|t|
=
=
=
=
=
43372
967.17
0.0000
0.6659
.57419
[95% Conf. Interval]
.0195047
.0029563
.0038884
.0027356
.0164545
.0091182
.0193268
.0003332
.0331698
.0101616
.029866
2.75
97.47
-116.93
-7.54
9.14
50.63
6.66
-28.93
-8.22
18.13
-20.92
0.006
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.0153755
.2823551
-.4622945
-.0259999
.1181935
.4437501
.0907548
-.0102921
-.3376828
.1642986
-.6832609
.0918345
.2939439
-.4470517
-.0152762
.1826959
.4794939
.1665165
-.0089859
-.207656
.2041327
-.5661852
.015567
.0154908
.0156704
.0152501
.0152607
.0152191
.0151663
.0160578
.0168154
.0175981
.0187877
.0206841
.0219797
.0210831
.0234332
.0736985
.0853836
.0908243
.0811632
.1013947
.0857488
.1191182
.0527183
.0566181
.0501948
.0460317
.0644359
.0521502
.0553468
.0579789
.0679573
.048433
.0472965
.0442766
.0391464
.0466682
.0723152
.0486996
.0582011
.0489561
.0535139
.0722817
.0428546
.046347
-1.55
-0.32
0.62
-0.37
1.79
2.73
2.07
-1.45
-2.36
-3.23
-3.92
-5.26
-5.50
-7.74
-6.25
11.24
15.30
17.93
16.60
17.23
15.17
14.47
17.60
22.94
18.89
24.36
20.39
15.17
23.25
19.43
14.40
5.59
-8.39
21.72
24.65
13.78
14.53
21.21
12.48
15.12
20.96
18.91
24.49
9.02
0.121
0.750
0.538
0.710
0.074
0.006
0.039
0.148
0.018
0.001
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
-.0546581
-.0352922
-.0210676
-.0355682
-.0026618
.011655
.001615
-.0546897
-.0725884
-.0912803
-.1105092
-.1494223
-.1640755
-.2044487
-.1923046
.6842629
1.139025
1.450392
1.188133
1.548399
1.133136
1.490052
.8246665
1.187591
.8498297
1.031283
1.187496
.6888542
1.178294
1.012941
.8454377
.1760302
-.489644
.8749423
.8880529
.5516952
.9088307
.9375091
.6124361
.6440622
1.016668
1.225302
.9656182
.3272711
.0063651
.0254321
.0403609
.0242128
.0571606
.0713145
.0610675
.0082576
-.0066712
-.0222952
-.0368608
-.0683396
-.0779142
-.1218021
-.1004455
.9731639
1.473732
1.806427
1.506296
1.94587
1.469275
1.957
1.031324
1.409536
1.046595
1.211729
1.440087
.8932848
1.395256
1.240221
1.111833
.3658893
-.3042402
1.048508
1.041508
.7346362
1.192309
1.128413
.8405864
.835972
1.226445
1.508649
1.13361
.508953
.0699573
.0397547
.055375
.050195
.0534695
.0379126
.0625017
.0733329
.0443481
.038247
.040202
.0541661
.0551699
.0530086
.0475701
.0673016
.0681065
.0418455
.0401746
.0429211
.0421468
.0475135
.0378673
.0520443
.0850336
.0800823
9.25
14.66
-1.90
-6.60
-6.30
8.31
0.78
5.58
-4.66
5.48
-3.63
-1.88
-14.16
24.47
33.55
13.60
24.41
33.54
14.47
13.42
36.32
31.03
16.01
11.85
19.87
83.69
0.000
0.000
0.058
0.000
0.000
0.000
0.437
0.000
0.000
0.000
0.000
0.061
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.5102428
.5048517
-.2135918
-.4298206
-.4415199
.2406419
-.0739316
.2654083
-.2937177
.1347864
-.224594
-.2077622
-.8894087
1.193167
1.502964
.7831114
1.529088
1.321286
.502749
.4919119
1.448367
1.381422
.5318783
.5147782
1.523082
6.545309
.784478
.6606917
.0034804
-.2330543
-.2319175
.3892606
.1710774
.5528761
-.1198715
.2847161
-.0670005
.0045711
-.6731407
1.400962
1.689441
1.046936
1.796068
1.485322
.660235
.6601643
1.613584
1.567677
.6803197
.718794
1.856417
6.859235
Appendix 3: Yearly regressions
47
1995 (1) +MR DW= 1.06
Source
SS
df
MS
Model
Residual
1129.27471
1000.41532
11
2450
102.661337
.408332783
Total
2129.69002
2461
.865375873
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3919935
.2798633
-.3826757
-.0439143
.2522295
.4744433
.0564406
-.0096506
-.414064
.1088598
-.5529149
5.249187
Std. Err.
.0114775
.0111275
.0159073
.0130292
.0740859
.0386685
.1167734
.0009274
.1208787
.0307289
.1661915
.1692921
t
34.15
25.15
-24.06
-3.37
3.40
12.27
0.48
-10.41
-3.43
3.54
-3.33
31.01
Number of obs
F( 11, 2450)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.001
0.001
0.000
0.629
0.000
0.001
0.000
0.001
0.000
=
=
=
=
=
=
2462
251.42
0.0000
0.5303
0.5281
.63901
[95% Conf. Interval]
.3694869
.2580431
-.4138688
-.0694636
.1069519
.398617
-.1725441
-.0114691
-.651099
.0486026
-.8788053
4.917217
.4145002
.3016836
-.3514826
-.0183649
.397507
.5502696
.2854254
-.007832
-.1770289
.1691171
-.2270246
5.581158
1996 (1) +MR DW= 0.97
Source
SS
df
MS
Model
Residual
1278.53081
1141.92053
11
2540
116.230074
.449575012
Total
2420.45134
2551
.948824516
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.4135247
.2907667
-.4123023
-.0426821
.2290253
.4885463
.0490434
-.0102464
-.5468664
.1412099
-.5910659
5.295531
Std. Err.
.0119618
.0116636
.0165148
.0128612
.0768162
.0397797
.1212106
.0010899
.1305947
.0344316
.1679468
.1766569
t
34.57
24.93
-24.97
-3.32
2.98
12.28
0.40
-9.40
-4.19
4.10
-3.52
29.98
Number of obs
F( 11, 2540)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.001
0.003
0.000
0.686
0.000
0.000
0.000
0.000
0.000
=
=
=
=
=
=
2552
258.53
0.0000
0.5282
0.5262
.6705
[95% Conf. Interval]
.3900688
.2678956
-.4446862
-.0679016
.0783966
.4105424
-.1886383
-.0123836
-.8029494
.073693
-.9203925
4.949125
.4369806
.3136379
-.3799184
-.0174626
.3796541
.5665501
.2867251
-.0081093
-.2907834
.2087269
-.2617392
5.641937
1997 (1) + MR DW= 1.12
Source
SS
df
MS
Model
Residual
1399.76987
1223.82975
11
2605
127.251807
.469800289
Total
2623.59963
2616
1.00290506
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.4387128
.3036025
-.4205984
-.0520416
.2108036
.4827799
.0597994
-.0105744
-.6647366
.1634631
-.6535113
5.180439
Std. Err.
.0122899
.011846
.0166984
.0135232
.0776204
.0404998
.1228315
.0011796
.1436998
.037053
.1490594
.1776694
t
35.70
25.63
-25.19
-3.85
2.72
11.92
0.49
-8.96
-4.63
4.41
-4.38
29.16
Number of obs
F( 11, 2605)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.007
0.000
0.626
0.000
0.000
0.000
0.000
0.000
=
=
=
=
=
=
2617
270.86
0.0000
0.5335
0.5316
.68542
[95% Conf. Interval]
.4146139
.2803739
-.4533418
-.0785589
.0585997
.4033648
-.1810579
-.0128875
-.9465138
.0908068
-.945798
4.832051
.4628117
.3268311
-.387855
-.0255242
.3630076
.562195
.3006567
-.0082614
-.3829593
.2361194
-.3612245
5.528826
1998 (1) + MR DW= 0.785
48
Source
SS
df
MS
Model
Residual
1315.31522
1377.86271
11
2628
119.574111
.524300877
Total
2693.17793
2639
1.02052972
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.4155851
.2837714
-.3963683
-.0438923
.2401756
.4912318
.0821058
-.0109099
-.5598684
.1810714
-.6356255
5.212095
Std. Err.
.0130096
.0125487
.0176827
.0138535
.0819344
.0426634
.1298907
.001356
.1517321
.0413658
.1475257
.1906172
t
31.94
22.61
-22.42
-3.17
2.93
11.51
0.63
-8.05
-3.69
4.38
-4.31
27.34
Number of obs
F( 11, 2628)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.002
0.003
0.000
0.527
0.000
0.000
0.000
0.000
0.000
=
=
=
=
=
=
2640
228.06
0.0000
0.4884
0.4862
.72409
[95% Conf. Interval]
.390075
.259165
-.4310416
-.0710571
.0795131
.4075745
-.1725926
-.0135688
-.8573948
.0999586
-.9249038
4.83832
.4410951
.3083779
-.3616949
-.0167274
.4008382
.5748892
.3368041
-.0082511
-.262342
.2621842
-.3463471
5.58587
1999 (1) + MR DW= 0.98
Source
SS
df
MS
Model
Residual
1442.35137
1377.60991
11
2793
131.122852
.493236632
Total
2819.96128
2804
1.00569233
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.4035698
.310786
-.4037236
-.031953
.2165883
.4782892
.0629929
-.0113766
-.5357419
.2002628
-.7421018
5.207955
Std. Err.
.0121388
.0115976
.0165808
.0126747
.0777006
.0397478
.1245205
.0011961
.1534638
.037835
.1424506
.1794104
t
33.25
26.80
-24.35
-2.52
2.79
12.03
0.51
-9.51
-3.49
5.29
-5.21
29.03
Number of obs
F( 11, 2793)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.012
0.005
0.000
0.613
0.000
0.000
0.000
0.000
0.000
=
=
=
=
=
=
2805
265.84
0.0000
0.5115
0.5096
.70231
[95% Conf. Interval]
.3797678
.2880452
-.4362354
-.0568057
.0642319
.4003511
-.1811687
-.0137219
-.8366558
.1260754
-1.021421
4.856165
.4273717
.3335268
-.3712118
-.0071002
.3689447
.5562272
.3071544
-.0090312
-.2348281
.2744502
-.4627826
5.559746
2000 (1) +MR DW= 1.08
Source
SS
df
MS
Model
Residual
1508.83323
1465.88306
11
2857
137.166657
.513084727
Total
2974.71629
2868
1.03720931
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.4016095
.314259
-.416602
-.0415303
.2203438
.4579548
.0698535
-.0107444
-.5868841
.192875
-.8191984
5.329788
Std. Err.
.0122025
.0116787
.0167701
.0128987
.0791627
.0398315
.1257006
.0011737
.1705572
.0385734
.1511323
.1803274
t
32.91
26.91
-24.84
-3.22
2.78
11.50
0.56
-9.15
-3.44
5.00
-5.42
29.56
Number of obs
F( 11, 2857)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.001
0.005
0.000
0.578
0.000
0.001
0.000
0.000
0.000
=
=
=
=
=
=
2869
267.34
0.0000
0.5072
0.5053
.7163
[95% Conf. Interval]
.3776828
.2913595
-.4494847
-.0668221
.065122
.3798535
-.1766196
-.0130458
-.9213118
.1172404
-1.115538
4.976203
.4255362
.3371585
-.3837192
-.0162385
.3755657
.5360561
.3163267
-.008443
-.2524563
.2685096
-.5228591
5.683373
2001 (1) + MR DW= 1.02
49
Source
SS
df
MS
Model
Residual
1414.0888
1455.6136
11
2860
128.553527
.508955803
Total
2869.70239
2871
.99954803
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3819942
.2979346
-.4028261
-.03725
.2558599
.4405335
.0898386
-.0110024
-.4050827
.1945505
-.7640057
5.404414
Std. Err.
.0121355
.0116569
.0167493
.0132008
.0788266
.0396162
.1252603
.0012973
.1704146
.0411498
.1502949
.1803975
t
31.48
25.56
-24.05
-2.82
3.25
11.12
0.72
-8.48
-2.38
4.73
-5.08
29.96
Number of obs
F( 11, 2860)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.005
0.001
0.000
0.473
0.000
0.018
0.000
0.000
0.000
=
=
=
=
=
=
2872
252.58
0.0000
0.4928
0.4908
.71341
[95% Conf. Interval]
.358199
.2750779
-.4356681
-.0631341
.1012972
.3628542
-.155771
-.0135461
-.7392306
.1138643
-1.058703
5.050692
.4057894
.3207914
-.3699841
-.011366
.4104226
.5182127
.3354482
-.0084587
-.0709347
.2752368
-.4693083
5.758137
2002 (1) + MR DW= 0.98
Source
SS
df
MS
Model
Residual
1467.33937
1389.55216
11
2858
133.394488
.486197397
Total
2856.89153
2869
.995779549
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3827798
.3152074
-.3854159
-.0498374
.2985307
.4671909
.0556211
-.0122813
-.3863948
.2263829
-.868732
5.140421
Std. Err.
.0116495
.0112974
.0163768
.0123254
.0772602
.0387867
.1224864
.0013583
.1639407
.0419413
.1392163
.1788211
t
32.86
27.90
-23.53
-4.04
3.86
12.05
0.45
-9.04
-2.36
5.40
-6.24
28.75
Number of obs
F( 11, 2858)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.650
0.000
0.018
0.000
0.000
0.000
=
=
=
=
=
=
2870
274.36
0.0000
0.5136
0.5117
.69728
[95% Conf. Interval]
.3599376
.2930556
-.4175275
-.0740049
.1470393
.3911382
-.1845496
-.0149446
-.7078488
.1441446
-1.141707
4.78979
.405622
.3373592
-.3533044
-.0256699
.450022
.5432435
.2957918
-.009618
-.0649407
.3086212
-.5957573
5.491052
2003 (1) + MR DW= 1.23
. regress exp lngdpi lngdpj ldist linder adj com col mrdist mradj mrcom mrcol
Source
SS
df
MS
Model
Residual
1533.66262
1465.58964
11
2861
139.423874
.512264817
Total
2999.25226
2872
1.04430789
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3859462
.3249729
-.366072
-.0513643
.3371525
.509804
.0815837
-.0118058
-.3022363
.1825611
-.8396519
4.788321
Std. Err.
.0117598
.0114896
.0168407
.0128632
.0793909
.0399194
.1257508
.0014373
.16098
.0432121
.1383831
.1856229
t
32.82
28.28
-21.74
-3.99
4.25
12.77
0.65
-8.21
-1.88
4.22
-6.07
25.80
Number of obs
F( 11, 2861)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.517
0.000
0.061
0.000
0.000
0.000
=
=
=
=
=
=
2873
272.17
0.0000
0.5113
0.5095
.71573
[95% Conf. Interval]
.3628875
.3024442
-.3990932
-.0765863
.1814833
.4315303
-.1649877
-.0146239
-.6178849
.097831
-1.110993
4.424353
.4090048
.3475017
-.3330507
-.0261423
.4928216
.5880776
.328155
-.0089876
.0134124
.2672911
-.5683113
5.152289
2004 (1) +MR DW= 1.11
50
. regress exp lngdpi lngdpj ldist linder adj com col mrdist mradj mrcom mrcol
Source
SS
df
MS
Model
Residual
1455.18395
1397.49775
11
2833
132.28945
.493292533
Total
2852.6817
2844
1.00305264
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3769539
.309508
-.3605095
-.0513273
.3469283
.530103
.0868736
-.0108159
-.2361133
.1438361
-.7839169
4.785977
Std. Err.
.0116894
.0114727
.0165195
.0127501
.0778148
.0395256
.1244905
.0014505
.1589063
.0431609
.1291156
.184055
t
32.25
26.98
-21.82
-4.03
4.46
13.41
0.70
-7.46
-1.49
3.33
-6.07
26.00
Number of obs
F( 11, 2833)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.485
0.000
0.137
0.001
0.000
0.000
=
=
=
=
=
=
2845
268.18
0.0000
0.5101
0.5082
.70235
[95% Conf. Interval]
.3540332
.2870123
-.392901
-.0763278
.1943489
.4526011
-.1572276
-.0136601
-.547697
.0592062
-1.037087
4.425082
.3998745
.3320037
-.3281179
-.0263269
.4995078
.6076049
.3309747
-.0079718
.0754705
.228466
-.5307469
5.146873
2005 (1) +MR DW= 0.98
. regress exp lngdpi lngdpj ldist linder adj com col mrdist mradj mrcom mrcol
Source
SS
df
MS
Model
Residual
1480.00966
1332.86085
11
2835
134.546333
.47014492
Total
2812.87051
2846
.98835928
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3833631
.3129465
-.3823811
-.0363041
.3439343
.4849166
.1109464
-.0104797
-.2423192
.1389388
-.8380289
4.885482
Std. Err.
.0116022
.0114252
.0160332
.0119369
.0761105
.0386603
.1215209
.0015146
.1604888
.0444726
.1304151
.1799801
t
33.04
27.39
-23.85
-3.04
4.52
12.54
0.91
-6.92
-1.51
3.12
-6.43
27.14
Number of obs
F( 11, 2835)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.002
0.000
0.000
0.361
0.000
0.131
0.002
0.000
0.000
=
=
=
=
=
=
2847
286.18
0.0000
0.5262
0.5243
.68567
[95% Conf. Interval]
.3606135
.2905441
-.4138191
-.05971
.1946968
.4091115
-.127332
-.0134495
-.5570058
.0517368
-1.093747
4.532577
.4061127
.335349
-.3509432
-.0128983
.4931718
.5607217
.3492248
-.0075099
.0723673
.2261408
-.5823109
5.238387
2006 (1) + MR DW= 1.16
. regress exp lngdpi lngdpj ldist linder adj com col mrdist mradj mrcom mrcol
Source
SS
df
MS
Model
Residual
1475.67855
1534.12312
11
2865
134.152595
.535470549
Total
3009.80167
2876
1.04652353
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.385144
.3170898
-.3852403
-.0305976
.3566124
.4644417
.0612824
-.0094949
-.2861214
.1185121
-.8364684
4.821867
Std. Err.
.0125621
.0123975
.0170823
.0129507
.0811762
.0409549
.1284432
.0017566
.174612
.0504611
.1395638
.1935912
t
30.66
25.58
-22.55
-2.36
4.39
11.34
0.48
-5.41
-1.64
2.35
-5.99
24.91
Number of obs
F( 11, 2865)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.018
0.000
0.000
0.633
0.000
0.101
0.019
0.000
0.000
=
=
=
=
=
=
2877
250.53
0.0000
0.4903
0.4883
.73176
[95% Conf. Interval]
.3605123
.2927808
-.4187352
-.0559912
.1974428
.3841377
-.190568
-.0129392
-.6284994
.0195684
-1.110124
4.442274
.4097757
.3413988
-.3517455
-.0052041
.5157821
.5447456
.3131328
-.0060505
.0562565
.2174558
-.5628127
5.201459
2007 (1) + MR DW= 0.97
51
. regress exp lngdpi lngdpj ldist linder adj com col mrdist mradj mrcom mrcol
Source
SS
df
MS
Model
Residual
1340.45801
1450.65015
11
2815
121.859819
.515328651
Total
2791.10816
2826
.987653276
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3579766
.2959966
-.3741621
-.0442595
.325374
.4586737
.098432
-.0070352
-.1843649
.0376183
-.7661096
4.889225
Std. Err.
.0125891
.01252
.0169015
.0133381
.0805507
.0402424
.1261217
.0018667
.1737688
.0521371
.1346781
.1944336
t
28.44
23.64
-22.14
-3.32
4.04
11.40
0.78
-3.77
-1.06
0.72
-5.69
25.15
Number of obs
F( 11, 2815)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.001
0.000
0.000
0.435
0.000
0.289
0.471
0.000
0.000
=
=
=
=
=
=
2827
236.47
0.0000
0.4803
0.4782
.71786
[95% Conf. Interval]
.3332919
.2714474
-.4073027
-.0704129
.1674296
.3797662
-.1488683
-.0106954
-.525092
-.0646125
-1.030187
4.507978
.3826614
.3205458
-.3410215
-.0181061
.4833183
.5375813
.3457324
-.0033749
.1563623
.1398492
-.5020318
5.270472
2008 (1) + MR DW= 1.21
Source
SS
df
MS
Model
Residual
1263.2612
1449.58543
11
2810
114.841927
.515866699
Total
2712.84663
2821
.961661335
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3468888
.2845113
-.3823156
-.0364198
.2998537
.4653732
.1109959
-.0071947
-.1158826
.0380416
-.7393884
5.046324
Std. Err.
.0128612
.0127981
.0169701
.0130706
.0804662
.0402281
.126122
.0018027
.1714974
.0501213
.1517553
.1995414
t
26.97
22.23
-22.53
-2.79
3.73
11.57
0.88
-3.99
-0.68
0.76
-4.87
25.29
Number of obs
F( 11, 2810)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.005
0.000
0.000
0.379
0.000
0.499
0.448
0.000
0.000
=
=
=
=
=
=
2822
222.62
0.0000
0.4657
0.4636
.71824
[95% Conf. Interval]
.3216704
.2594167
-.4155908
-.0620487
.1420749
.3864936
-.1363053
-.0107294
-.4521561
-.0602367
-1.036951
4.655062
.3721071
.309606
-.3490404
-.0107909
.4576326
.5442527
.3582971
-.0036599
.2203909
.1363199
-.4418253
5.437587
2009 (1) + MR DW= 1.32
Source
SS
df
MS
Model
Residual
1234.06963
1258.73049
11
2761
112.188148
.455896591
Total
2492.80011
2772
.899278541
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3422685
.301047
-.3939129
-.042869
.2358089
.4082711
.2092256
-.0101905
-.0384398
.1215481
-.932776
5.110724
Std. Err.
.0120191
.0118903
.0160026
.0124354
.0757672
.0379514
.1198541
.0015673
.1617232
.04424
.1650558
.1857073
t
28.48
25.32
-24.62
-3.45
3.11
10.76
1.75
-6.50
-0.24
2.75
-5.65
27.52
Number of obs
F( 11, 2761)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.001
0.002
0.000
0.081
0.000
0.812
0.006
0.000
0.000
=
=
=
=
=
=
2773
246.08
0.0000
0.4951
0.4930
.6752
[95% Conf. Interval]
.3187012
.2777323
-.4252913
-.0672527
.0872427
.3338551
-.0257871
-.0132637
-.3555506
.0348012
-1.256421
4.746585
.3658357
.3243618
-.3625346
-.0184853
.3843751
.4826872
.4442383
-.0071173
.2786709
.208295
-.6091306
5.474864
52
2010 (1) + MR DW= 1.22
. regress exp lngdpi lngdpj ldist linder adj com col mrdist mradj mrcom mrcol
Source
SS
df
MS
Model
Residual
808.161164
666.600383
11
1809
73.4691967
.368491091
Total
1474.76155
1820
.810308542
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3270209
.2909494
-.4184638
-.0395017
.1792946
.3818755
.2085894
-.0079622
.0570986
.0528268
-.8843515
5.419697
Std. Err.
.0133605
.012991
.0177042
.0136462
.0800514
.0451711
.1269449
.0015762
.1666272
.0436912
.1737198
.2026538
t
24.48
22.40
-23.64
-2.89
2.24
8.45
1.64
-5.05
0.34
1.21
-5.09
26.74
Number of obs
F( 11, 1809)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.004
0.025
0.000
0.101
0.000
0.732
0.227
0.000
0.000
=
=
=
=
=
=
1821
199.38
0.0000
0.5480
0.5452
.60703
[95% Conf. Interval]
.3008173
.2654705
-.4531867
-.0662657
.0222917
.2932825
-.0403845
-.0110536
-.2697034
-.0328638
-1.225064
5.022237
.3532244
.3164282
-.383741
-.0127377
.3362976
.4704686
.4575633
-.0048707
.3839005
.1385174
-.543639
5.817158
1995 (2) + fixed effects DW= 1.793
53
Source
SS
df
MS
Model
Residual
1474.45773
655.23229
59
2402
24.9908091
.272786132
Total
2129.69002
2461
.865375873
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.3084969
.2593038
-.4396149
-.0196117
.1634647
.4610124
.106901
-.0088454
-.2444563
.1322243
-.2333244
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.1334858
-.020215
.1828371
.1617952
.1971893
-.0493035
(omitted)
-.0049153
(omitted)
.2554402
.4670717
.2766503
.128006
.4528487
.2418991
-.0567762
-.33493
-.2608788
.4739857
.4993716
.0372064
-.0269837
(omitted)
-.2451046
.1383827
.1313126
.1314925
.5223758
-.1634542
(omitted)
-.3773767
.0754913
(omitted)
-.5390519
-.237001
.0145081
-.249383
(omitted)
-.7820641
-.1377487
-.269488
(omitted)
-1.29662
.4069043
.9578432
-.1959212
.500208
.8008752
-.0003768
-.0948455
1.007044
.5050206
-.0601129
-.1316464
.225541
6.173077
Std. Err.
t
Number of obs
F( 59,
2402)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2462
91.61
0.0000
0.6923
0.6848
.52229
[95% Conf. Interval]
.025731
.0107244
.0146971
.0109609
.0625616
.0338918
.0959271
.0010532
.1373369
.0356346
.1867142
11.99
24.18
-29.91
-1.79
2.61
13.60
1.11
-8.40
-1.78
3.71
-1.25
0.000
0.000
0.000
0.074
0.009
0.000
0.265
0.000
0.075
0.000
0.212
.2580396
.2382737
-.4684353
-.0411055
.0407844
.3945523
-.0812074
-.0109107
-.5137675
.0623466
-.5994621
.3589542
.2803339
-.4107946
.001882
.2861451
.5274726
.2950094
-.0067801
.0248549
.2021019
.1328133
.1056261
.1133987
.1217095
.1129122
.1557074
.1313704
-1.26
-0.18
1.50
1.43
1.27
-0.38
0.206
0.859
0.133
0.152
0.205
0.707
-.3406135
-.2425845
-.0558293
-.0596203
-.1081455
-.3069145
.073642
.2021544
.4215036
.3832107
.5025242
.2083075
.1007762
-0.05
0.961
-.2025325
.192702
.0997878
.0988263
.1043619
.0990936
.100898
.1011818
.1032128
.0995096
.1244618
.0988795
.099114
.0985673
.1059971
2.56
4.73
2.65
1.29
4.49
2.39
-0.55
-3.37
-2.10
4.79
5.04
0.38
-0.25
0.011
0.000
0.008
0.197
0.000
0.017
0.582
0.001
0.036
0.000
0.000
0.706
0.799
.059761
.273278
.0720015
-.0663117
.2549926
.0434865
-.2591716
-.5300636
-.5049423
.2800878
.3050138
-.1560793
-.234839
.4511194
.6608654
.481299
.3223238
.6507048
.4403117
.1456191
-.1397965
-.0168152
.6678836
.6937293
.2304921
.1808715
.1005423
.1003138
.1002581
.1070108
.0999373
.0994535
-2.44
1.38
1.31
1.23
5.23
-1.64
0.015
0.168
0.190
0.219
0.000
0.100
-.4422632
-.0583278
-.0652888
-.0783505
.3264035
-.3584778
-.047946
.3350932
.3279139
.3413356
.718348
.0315695
.1024832
.1002727
-3.68
0.75
0.000
0.452
-.5783415
-.1211387
-.176412
.2721213
.1256666
.132207
.1084821
.11871
-4.29
-1.79
0.13
-2.10
0.000
0.073
0.894
0.036
-.7854781
-.4962526
-.19822
-.4821677
-.2926258
.0222506
.2272362
-.0165984
.1014585
.1049491
.113232
-7.71
-1.31
-2.38
0.000
0.189
0.017
-.9810193
-.3435488
-.4915306
-.583109
.0680515
-.0474454
.1089377
.1013467
.0983199
.1019148
.107145
.0983384
.0986658
.0985456
.0998435
.0991454
.1008704
.0993423
.1076826
.2074342
-11.90
4.01
9.74
-1.92
4.67
8.14
-0.00
-0.96
10.09
5.09
-0.60
-1.33
2.09
29.76
0.000
0.000
0.000
0.055
0.000
0.000
0.997
0.336
0.000
0.000
0.551
0.185
0.036
0.000
-1.510241
.2081682
.7650425
-.3957712
.2901018
.6080382
-.1938557
-.2880886
.8112561
.3106013
-.2579148
-.326452
.0143806
5.766308
-1.082998
.6056404
1.150644
.0039289
.7103142
.9937121
.1931022
.0983976
1.202833
.6994399
.1376891
.0631591
.4367013
6.579845
1996 (1) + fixed effects DW=1.86
54
Source
SS
df
MS
Model
Residual
1647.94956
772.501782
61
2490
27.0155665
.310241679
Total
2420.45134
2551
.948824516
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.314122
.2638363
-.4615514
-.0167295
.1646639
.4834152
.0776132
-.008719
-.3353901
.1485219
-.2483445
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.0850401
.0393994
.2761197
.2336689
.2239429
.0164709
(omitted)
.0856018
(omitted)
.2906612
.5514603
.3338729
.201328
.5234138
.3213066
.0045099
-.2538083
-.1096743
.5495241
.5892347
.0888868
.0731547
(omitted)
-.1898346
.2653691
.2489347
.1578488
.4625548
-.1521388
(omitted)
-.1036477
.1812602
-.2602275
-.5831784
-.5003206
.0759033
-.2106542
.4151724
-.8642522
-.1320882
-.0971346
(omitted)
-1.338897
.4561009
.9851831
-.0841028
.5670996
.8259174
.120925
-.0104722
1.043681
.5644634
-.0014132
-.1042341
.2240299
6.209485
Std. Err.
t
Number of obs
F( 61, 2490)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2552
87.08
0.0000
0.6808
0.6730
.55699
[95% Conf. Interval]
.0271637
.0114369
.0155046
.0110411
.0658589
.0353781
.101198
.0012481
.1503038
.0404347
.1901462
11.56
23.07
-29.77
-1.52
2.50
13.66
0.77
-6.99
-2.23
3.67
-1.31
0.000
0.000
0.000
0.130
0.012
0.000
0.443
0.000
0.026
0.000
0.192
.2608562
.2414095
-.4919547
-.0383802
.0355202
.4140416
-.1208277
-.0111664
-.6301234
.0692328
-.6212054
.3673879
.286263
-.4311481
.0049212
.2938077
.5527887
.2760541
-.0062715
-.0406569
.227811
.1245164
.1121661
.1196098
.1272073
.120474
.1633629
.1389839
-0.76
0.33
2.17
1.94
1.37
0.12
0.448
0.742
0.030
0.053
0.171
0.906
-.3049885
-.1951456
.0266768
-.0025705
-.0963982
-.2560651
.1349084
.2739444
.5255625
.4699084
.5442839
.2890069
.1063456
0.80
0.421
-.1229331
.2941366
.1053978
.1042826
.1101965
.1047876
.1069959
.1067087
.1099222
.1044735
.1300706
.1041148
.1041827
.1040574
.1125227
2.76
5.29
3.03
1.92
4.89
3.01
0.04
-2.43
-0.84
5.28
5.66
0.85
0.65
0.006
0.000
0.002
0.055
0.000
0.003
0.967
0.015
0.399
0.000
0.000
0.393
0.516
.0839848
.3469707
.1177866
-.0041519
.3136036
.1120596
-.2110385
-.4586722
-.3647319
.3453635
.384941
-.115161
-.147493
.4973375
.7559499
.5499591
.4068078
.733224
.5305536
.2200583
-.0489444
.1453833
.7536846
.7935285
.2929347
.2938024
.1065101
.1058965
.1060667
.1134242
.1040801
.1049933
-1.78
2.51
2.35
1.39
4.44
-1.45
0.075
0.012
0.019
0.164
0.000
0.147
-.3986921
.0577148
.0409467
-.0645667
.2584625
-.358022
.0190228
.4730233
.4569227
.3802643
.6666472
.0537444
.1092588
.1044028
.1089069
.1298476
.1341443
.112632
.1224455
.1389516
.1068119
.1087597
.1165108
-0.95
1.74
-2.39
-4.49
-3.73
0.67
-1.72
2.99
-8.09
-1.21
-0.83
0.343
0.083
0.017
0.000
0.000
0.500
0.085
0.003
0.000
0.225
0.405
-.3178952
-.0234651
-.4737848
-.8377988
-.7633665
-.1449588
-.4507597
.1426998
-1.073701
-.3453569
-.3256027
.1105997
.3859854
-.0466701
-.328558
-.2372746
.2967654
.0294514
.6876449
-.654803
.0811804
.1313336
.11389
.1075905
.104028
.107946
.1140268
.1036757
.1040898
.1038203
.1053349
.1048932
.1063062
.1051972
.1151868
.2189811
-11.76
4.24
9.47
-0.78
4.97
7.97
1.16
-0.10
9.91
5.38
-0.01
-0.99
1.94
28.36
0.000
0.000
0.000
0.436
0.000
0.000
0.245
0.920
0.000
0.000
0.989
0.322
0.052
0.000
-1.562226
.2451248
.7811928
-.295776
.3435024
.622618
-.0831864
-.2140552
.8371281
.3587766
-.2098709
-.3105172
-.001842
5.780081
-1.115568
.667077
1.189174
.1275704
.7906967
1.029217
.3250365
.1931108
1.250234
.7701503
.2070444
.102049
.4499017
6.638889
55
1997 (1) + fixed effects DW= 1.71
Source
SS
df
MS
Model
Residual
1803.75279
819.846835
62
2554
29.0927869
.321005026
Total
2623.59963
2616
1.00290506
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.373691
.27988
-.4658172
-.0144119
.1588862
.4706476
.0753787
-.0090302
-.3988762
.1594948
-.4110016
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.0402116
.1214299
.2877603
.2349954
.2294768
.1223282
(omitted)
.2260351
(omitted)
.4171667
.6788685
.5278766
.3043221
.6621341
.4441262
.1027307
-.1897689
.1078278
.69177
.7111521
.2412489
.172826
(omitted)
-.0652784
.4066918
.2828571
.1702376
.611249
.0018784
(omitted)
-.1169576
.3748757
-.3156155
-.2048941
-.3332884
.3738587
.0882439
.4423283
-.605541
.0983903
-.1381218
-.6151242
-1.078673
.5676775
1.047136
-.038867
.7004745
.9602812
.2588563
.2223858
1.153231
.8071852
.2352934
.0037088
.287132
5.777899
Std. Err.
t
Number of obs
F( 62,
2554)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2617
90.63
0.0000
0.6875
0.6799
.56657
[95% Conf. Interval]
.0280467
.011602
.0155645
.011588
.0661427
.0358807
.1020554
.0013393
.1657399
.0428409
.1740326
13.32
24.12
-29.93
-1.24
2.40
13.12
0.74
-6.74
-2.41
3.72
-2.36
0.000
0.000
0.000
0.214
0.016
0.000
0.460
0.000
0.016
0.000
0.018
.3186943
.2571297
-.4963375
-.0371347
.0291875
.4002893
-.1247412
-.0116564
-.7238744
.0754883
-.752261
.4286876
.3026303
-.4352968
.008311
.2885849
.5410058
.2754985
-.006404
-.073878
.2435013
-.0697423
.1147541
.1197158
.1258267
.1215006
.1659054
.1467497
-0.35
1.01
2.29
1.93
1.38
0.83
0.726
0.311
0.022
0.053
0.167
0.405
-.2652321
-.11332
.0410275
-.0032544
-.095846
-.1654323
.184809
.3561798
.5344931
.4732451
.5547995
.4100887
.1073175
2.11
0.035
.0155968
.4364733
.1065697
.1056706
.1112892
.1061849
.1079994
.1074459
.1120053
.1058572
.1317264
.1054247
.1055724
.10542
.1139369
3.91
6.42
4.74
2.87
6.13
4.13
0.92
-1.79
0.82
6.56
6.74
2.29
1.52
0.000
0.000
0.000
0.004
0.000
0.000
0.359
0.073
0.413
0.000
0.000
0.022
0.129
.208195
.4716598
.3096504
.0961049
.4503587
.2334362
-.1168997
-.3973436
-.1504736
.4850434
.5041358
.0345315
-.050592
.6261385
.8860773
.7461028
.5125393
.8739094
.6548161
.3223611
.0178058
.3661292
.8984965
.9181683
.4479662
.396244
.1082766
.1073959
.1077715
.1146518
.105305
.105086
-0.60
3.79
2.62
1.48
5.80
0.02
0.547
0.000
0.009
0.138
0.000
0.986
-.2775972
.1960998
.0715286
-.0545824
.4047572
-.204184
.1470404
.6172837
.4941855
.3950576
.8177407
.2079407
.112573
.1055768
.1079515
.1312098
.1335372
.1132561
.1228709
.1449086
.108001
.1103648
.1165936
.1075026
.1158272
.1081419
.1058818
.1104176
.1152222
.1050501
.1054956
.1052138
.1068259
.1056453
.1077257
.1066909
.1177965
.2216723
-1.04
3.55
-2.92
-1.56
-2.50
3.30
0.72
3.05
-5.61
0.89
-1.18
-5.72
-9.31
5.25
9.89
-0.35
6.08
9.14
2.45
2.11
10.80
7.64
2.18
0.03
2.44
26.07
0.299
0.000
0.003
0.119
0.013
0.001
0.473
0.002
0.000
0.373
0.236
0.000
0.000
0.000
0.000
0.725
0.000
0.000
0.014
0.035
0.000
0.000
0.029
0.972
0.015
0.000
-.3377013
.1678508
-.5272969
-.4621826
-.5951406
.1517757
-.1526929
.158178
-.8173194
-.1180232
-.3667493
-.8259252
-1.305798
.3556227
.8395135
-.2553842
.4745361
.7542892
.0519908
.0160729
.9437573
.600026
.0240548
-.2055007
.0561456
5.343223
.1037861
.5819006
-.1039341
.0523944
-.0714361
.5959418
.3291807
.7264786
-.3937626
.3148038
.0905058
-.4043231
-.8515482
.7797323
1.254759
.1776501
.9264129
1.166273
.4657219
.4286988
1.362706
1.014344
.446532
.2129182
.5181184
6.212575
1998 (1) + fixed effects DW= 1.635
56
Source
SS
df
MS
Model
Residual
1816.58932
876.588604
62
2577
29.2998278
.340158558
Total
2693.17793
2639
1.02052972
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.3346047
.257188
-.463386
-.0141616
.1674083
.4854722
.0729114
-.0102295
-.1960804
.2102685
-.3916984
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
.0161128
.2301133
.3967822
.3432583
.4927765
.1749413
(omitted)
.3058747
(omitted)
.4761167
.7403137
.4986624
.3607776
.728942
.523749
.3081524
-.1446813
-.0629245
.7559246
.847728
.2668557
.2403728
(omitted)
.0027818
.4083972
.341585
.2698255
.6779535
-.0033232
(omitted)
-.0720344
.2998085
-.2161628
-.1878993
-.4461873
.2975772
-.2981421
.3923886
-.6711829
.1103323
-.0627359
-.6698904
-.6043805
1.119368
1.141652
.0185317
1.087292
1.214752
.3281884
.4078
1.278581
1.06582
.3425032
.0325481
.4374461
6.003815
Std. Err.
t
Number of obs
F( 62,
2577)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2640
86.14
0.0000
0.6745
0.6667
.58323
[95% Conf. Interval]
.0286997
.0119898
.0160582
.0115109
.0680128
.0367889
.1051452
.0015003
.1712328
.0470014
.1679792
11.66
21.45
-28.86
-1.23
2.46
13.20
0.69
-6.82
-1.15
4.47
-2.33
0.000
0.000
0.000
0.219
0.014
0.000
0.488
0.000
0.252
0.000
0.020
.2783279
.2336775
-.4948742
-.0367332
.0340431
.4133334
-.1332664
-.0131715
-.5318482
.1181042
-.7210864
.3908816
.2806986
-.4318977
.00841
.3007735
.557611
.2790891
-.0072876
.1396875
.3024328
-.0623105
.1182448
.1236116
.1294885
.1257742
.171052
.1522007
0.14
1.86
3.06
2.73
2.88
1.15
0.892
0.063
0.002
0.006
0.004
0.250
-.2157517
-.0122748
.1428701
.0966295
.1573632
-.1235068
.2479774
.4725014
.6506943
.5898871
.8281898
.4733895
.1104762
2.77
0.006
.0892435
.5225058
.1096671
.1086623
.1149611
.1090409
.1111816
.1107901
.1145407
.1088217
.1320163
.1080946
.1088803
.1079097
.118015
4.34
6.81
4.34
3.31
6.56
4.73
2.69
-1.33
-0.48
6.99
7.79
2.47
2.04
0.000
0.000
0.000
0.001
0.000
0.000
0.007
0.184
0.634
0.000
0.000
0.013
0.042
.2610721
.5272395
.2732368
.1469609
.5109277
.3065023
.0835512
-.3580681
-.3217932
.5439635
.6342263
.0552573
.0089589
.6911612
.953388
.7240879
.5745943
.9469564
.7409957
.5327536
.0687055
.1959443
.9678857
1.06123
.4784541
.4717867
.1118373
.1096753
.1104082
.1177408
.1081782
.1073689
0.02
3.72
3.09
2.29
6.27
-0.03
0.980
0.000
0.002
0.022
0.000
0.975
-.2165183
.1933365
.1250872
.0389493
.4658284
-.2138612
.222082
.6234579
.5580828
.5007017
.8900786
.2072149
.1159033
.1084341
.1101099
.1322439
.1362916
.1147449
.1226297
.1400495
.1100057
.1118131
.1181305
.1091708
.1198226
.1084842
.1087711
.1139316
.1146326
.1082304
.1082978
.1084748
.1097196
.1079381
.1102273
.110103
.1223835
.2285802
-0.62
2.76
-1.96
-1.42
-3.27
2.59
-2.43
2.80
-6.10
0.99
-0.53
-6.14
-5.04
10.32
10.50
0.16
9.49
11.22
3.03
3.76
11.65
9.87
3.11
0.30
3.57
26.27
0.534
0.006
0.050
0.155
0.001
0.010
0.015
0.005
0.000
0.324
0.595
0.000
0.000
0.000
0.000
0.871
0.000
0.000
0.002
0.000
0.000
0.000
0.002
0.768
0.000
0.000
-.2993074
.0871817
-.4320756
-.4472143
-.7134394
.0725756
-.538605
.1177676
-.8868915
-.1089203
-.2943763
-.8839618
-.8393388
.9066434
.9283644
-.2048751
.8625103
1.002525
.1158289
.1950935
1.063434
.8541654
.1263601
-.1833512
.1974662
5.555595
.1552386
.5124353
-.00025
.0714157
-.1789352
.5225788
-.0576793
.6670096
-.4554743
.3295848
.1689045
-.455819
-.3694222
1.332093
1.35494
.2419384
1.312073
1.426979
.5405478
.6205065
1.493729
1.277474
.5586462
.2484473
.677426
6.452034
57
1999 (1) + fixed effects DW= 1.69
Source
SS
df
MS
Model
Residual
1919.64746
900.313822
64
2740
29.9944915
.328581687
Total
2819.96128
2804
1.00569233
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.3515833
.2993375
-.4612838
-.0042647
.1358116
.4682987
.0731122
-.0118912
-.3856911
.2495249
-.5199069
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.2454186
.04824
.2693854
.1493779
.3459878
-.0272131
(omitted)
.150013
.4883369
.2766611
.5260878
.298713
.1839952
.5114537
.3174872
.024991
-.2811058
-.1942734
.5907137
.616642
.0793027
.0509576
.3912281
-.1058004
.294586
.1780985
.2885894
.5488458
-.1193494
(omitted)
-.5105885
.2586389
-.5528891
-.2401845
-.3603972
.1939889
-.1745924
.2689224
-.8061354
-.0152722
-.2704057
-.727329
-.8395436
.7375707
.9552013
-.1743255
.7540417
.9946817
.169063
.1863737
1.070501
.8703646
.2502846
-.1500853
.2768779
5.882049
Std. Err.
t
Number of obs
F( 64,
2740)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2805
91.28
0.0000
0.6807
0.6733
.57322
[95% Conf. Interval]
.0263296
.011188
.0153289
.010678
.0653776
.0345698
.1020966
.0013359
.1756778
.0427558
.1637435
13.35
26.76
-30.09
-0.40
2.08
13.55
0.72
-8.90
-2.20
5.84
-3.18
0.000
0.000
0.000
0.690
0.038
0.000
0.474
0.000
0.028
0.000
0.002
.2999554
.2773997
-.4913411
-.0252026
.0076173
.4005133
-.1270819
-.0145107
-.7301655
.1656881
-.84098
.4032112
.3212754
-.4312265
.0166731
.2640059
.5360841
.2733064
-.0092717
-.0412167
.3333617
-.1988338
.1174845
.120767
.1253144
.1227956
.1677621
.1492801
-2.09
0.40
2.15
1.22
2.06
-0.18
0.037
0.690
0.032
0.224
0.039
0.855
-.4757858
-.1885637
.0236651
-.0914034
.0170349
-.319926
-.0150514
.2850436
.5151057
.3901593
.6749407
.2654998
.1085823
.1097321
.1077503
.1064526
.1135078
.1072067
.1095346
.1090145
.1139178
.1067584
.1235466
.1055969
.1053335
.1057355
.1168087
.1055512
.1096313
.1072416
.1084985
.1123328
.1047114
.104762
1.38
4.45
2.57
4.94
2.63
1.72
4.67
2.91
0.22
-2.63
-1.57
5.59
5.85
0.75
0.44
3.71
-0.97
2.75
1.64
2.57
5.24
-1.14
0.167
0.000
0.010
0.000
0.009
0.086
0.000
0.004
0.826
0.009
0.116
0.000
0.000
0.453
0.663
0.000
0.335
0.006
0.101
0.010
0.000
0.255
-.0628984
.2731708
.0653809
.3173523
.0761436
-.026219
.2966749
.1037282
-.1983825
-.490441
-.4365273
.3836562
.4101008
-.1280267
-.1780845
.1842602
-.3207687
.0843035
-.0346485
.068324
.3435244
-.3247699
.3629245
.703503
.4879412
.7348232
.5212825
.3942094
.7262325
.5312462
.2483645
-.0717707
.0479804
.7977712
.8231832
.2866321
.2799997
.598196
.1091679
.5048685
.3908456
.5088549
.7541671
.0860711
.1158229
.1051312
.1074067
.1241781
.1286501
.109174
.1172543
.1318263
.1058693
.1075188
.1119088
.1066597
.1135538
.107242
.1068071
.1129405
.1156779
.1051896
.1053294
.1052115
.1068984
.1058445
.1063504
.1080698
.1204897
.2111626
-4.41
2.46
-5.15
-1.93
-2.80
1.78
-1.49
2.04
-7.61
-0.14
-2.42
-6.82
-7.39
6.88
8.94
-1.54
6.52
9.46
1.61
1.77
10.01
8.22
2.35
-1.39
2.30
27.86
0.000
0.014
0.000
0.053
0.005
0.076
0.137
0.041
0.000
0.887
0.016
0.000
0.000
0.000
0.000
0.123
0.000
0.000
0.109
0.077
0.000
0.000
0.019
0.165
0.022
0.000
-.7376975
.0524946
-.7634953
-.4836767
-.6126581
-.0200828
-.4045082
.0104334
-1.013727
-.2260984
-.4898399
-.9364705
-1.062203
.5272874
.7457707
-.3957826
.5272169
.7884226
-.0374702
-.0199281
.8608911
.6628215
.0417495
-.3619918
.040618
5.467995
-.2834795
.4647832
-.3422829
.0033077
-.1081363
.4080606
.0553234
.5274113
-.5985437
.1955539
-.0509715
-.5181874
-.6168839
.947854
1.164632
.0471317
.9808665
1.200941
.3755961
.3926756
1.28011
1.077908
.4588196
.0618211
.5131378
6.296103
2000 (1) + fixed effects DW= 1.77
58
Source
SS
df
MS
Model
Residual
2025.66064
949.055654
64
2804
31.6509474
.338464927
Total
2974.71629
2868
1.03720931
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.3550491
.3043936
-.4720599
-.0107219
.1252969
.4585112
.0990785
-.0110173
-.4450101
.2372042
-.6698241
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.3015972
.0774202
.2831119
.1706848
.3000157
.0546649
(omitted)
.2332604
.561797
.3203614
.6681056
.4141259
.1390334
.5752146
.3381256
.147506
-.2085859
-.1857959
.6040178
.6877937
.1127605
.0629546
.4210924
-.1599948
.2754574
.1997651
.2618886
.6431624
-.1865676
(omitted)
-.4707961
.2726281
-.6456085
-.086868
-.2224635
.1751703
-.1875744
.1990282
-.9350268
-.05394
-.2534334
-.5231021
-.9319399
.7570195
.9758409
-.1325463
.6905936
.9523655
.2105854
.2078459
1.054114
.9220002
.292692
-.1447427
.3387722
5.935077
Std. Err.
t
Number of obs
F( 64, 2804)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2869
93.51
0.0000
0.6810
0.6737
.58178
[95% Conf. Interval]
.0269096
.0113105
.0154111
.0108108
.0661946
.0345458
.1025409
.0013079
.1983434
.0426857
.1729692
13.19
26.91
-30.63
-0.99
1.89
13.27
0.97
-8.42
-2.24
5.56
-3.87
0.000
0.000
0.000
0.321
0.058
0.000
0.334
0.000
0.025
0.000
0.000
.3022845
.2822159
-.5022781
-.0319198
-.0044982
.3907735
-.1019847
-.0135818
-.8339239
.1535056
-1.008984
.4078138
.3265713
-.4418417
.0104761
.255092
.5262488
.3001417
-.0084528
-.0560962
.3209027
-.3306642
.1215012
.1215135
.1237896
.1237459
.1722184
.1518987
-2.48
0.64
2.29
1.38
1.74
0.36
0.013
0.524
0.022
0.168
0.082
0.719
-.539838
-.1608447
.040384
-.0719575
-.0376719
-.2431796
-.0633564
.315685
.5258397
.4133271
.6377032
.3525093
.1097945
.1110799
.1090085
.1077193
.1151576
.1091404
.111105
.1104373
.1162574
.1079943
.1229979
.106852
.1062856
.1074795
.1190771
.1076083
.1120467
.109074
.110753
.114257
.105741
.1060244
2.12
5.06
2.94
6.20
3.60
1.27
5.18
3.06
1.27
-1.93
-1.51
5.65
6.47
1.05
0.53
3.91
-1.43
2.53
1.80
2.29
6.08
-1.76
0.034
0.000
0.003
0.000
0.000
0.203
0.000
0.002
0.205
0.054
0.131
0.000
0.000
0.294
0.597
0.000
0.153
0.012
0.071
0.022
0.000
0.079
.0179743
.3439904
.1066164
.4568886
.1883237
-.0749702
.3573588
.1215789
-.0804527
-.4203423
-.4269715
.3945012
.4793877
-.0979865
-.1705329
.2100929
-.3796973
.061584
-.0174005
.0378523
.4358243
-.3944614
.4485465
.7796035
.5341063
.8793226
.6399281
.3530371
.7930705
.5546722
.3754646
.0031705
.0553798
.8135344
.8961997
.3235074
.2964421
.6320919
.0597076
.4893309
.4169306
.485925
.8505005
.0213262
.1203344
.1058537
.1079246
.1234553
.1274844
.1099123
.1147816
.129549
.106645
.1084259
.1127379
.1077556
.1131465
.109201
.1086929
.1157883
.1199727
.1064785
.1063385
.106295
.1076582
.1072998
.107223
.1099489
.1231809
.2117091
-3.91
2.58
-5.98
-0.70
-1.75
1.59
-1.63
1.54
-8.77
-0.50
-2.25
-4.85
-8.24
6.93
8.98
-1.14
5.76
8.94
1.98
1.96
9.79
8.59
2.73
-1.32
2.75
28.03
0.000
0.010
0.000
0.482
0.081
0.111
0.102
0.125
0.000
0.619
0.025
0.000
0.000
0.000
0.000
0.252
0.000
0.000
0.048
0.051
0.000
0.000
0.006
0.188
0.006
0.000
-.7067491
.0650691
-.8572282
-.3289405
-.4724362
-.0403468
-.4126393
-.0549929
-1.144138
-.2665426
-.4744911
-.7343905
-1.153799
.5428971
.7627147
-.3595853
.4553499
.7435814
.0020758
-.0005784
.8430171
.7116057
.082448
-.3603317
.0972378
5.519956
-.2348431
.4801872
-.4339889
.1552046
.0275091
.3906874
.0374905
.4530492
-.7259161
.1586627
-.0323757
-.3118138
-.7100811
.9711419
1.188967
.0944926
.9258373
1.16115
.4190949
.4162702
1.265212
1.132395
.502936
.0708464
.5803065
6.350199
2001 (1) + fixed effects DW= 1.76
59
Source
SS
df
MS
Model
Residual
1919.89542
949.806977
64
2807
29.9983659
.33837085
Total
2869.70239
2871
.99954803
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.3455081
.287978
-.4615064
-.0120076
.1460204
.4369673
.1209407
-.0111077
-.3323916
.2394972
-.6120983
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.2381307
.130337
.3336778
.2360878
.2845847
.0813089
(omitted)
.3059355
.6325212
.3760217
.6511689
.4546421
.224116
.6022562
.4058959
.2711553
-.1805819
-.0598614
.6024439
.7478124
.1836503
.1028401
.5087624
.1259251
.2827392
.2840285
.4231832
.7352314
-.1350768
(omitted)
-.4585699
.2987745
-.4892216
-.0879854
.1065168
.2553284
-.1962265
.0353237
-.8042725
.0668653
-.1632488
-.6130126
-.9337213
.7984497
.9867199
-.0534946
.7165535
.9827995
.275429
.3107274
1.094019
1.000848
.3409782
-.1211119
.3906274
5.92489
Std. Err.
t
Number of obs
F( 64, 2807)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2872
88.66
0.0000
0.6690
0.6615
.5817
[95% Conf. Interval]
.0280952
.0113076
.015443
.0111037
.0661952
.0345089
.1025812
.0014529
.2001556
.0462954
.1727317
12.30
25.47
-29.88
-1.08
2.21
12.66
1.18
-7.65
-1.66
5.17
-3.54
0.000
0.000
0.000
0.280
0.027
0.000
0.239
0.000
0.097
0.000
0.000
.2904188
.2658059
-.4917872
-.0337799
.0162241
.3693019
-.0802015
-.0139566
-.7248586
.1487207
-.9507923
.4005974
.3101501
-.4312256
.0097647
.2758166
.5046326
.322083
-.0082588
.0600754
.3302737
-.2734043
.1202343
.1206835
.1229583
.1231728
.1718941
.1513203
-1.98
1.08
2.71
1.92
1.66
0.54
0.048
0.280
0.007
0.055
0.098
0.591
-.4738873
-.1063003
.09258
-.0054306
-.0524669
-.2154013
-.002374
.3669744
.5747756
.4776062
.6216363
.3780192
.108844
.1100334
.1082305
.1071743
.11431
.1084055
.1100718
.1095058
.1145051
.1074874
.1268621
.1066319
.1068251
.107024
.1183825
.1065685
.1090132
.1078758
.109379
.1122559
.1058505
.105685
2.81
5.75
3.47
6.08
3.98
2.07
5.47
3.71
2.37
-1.68
-0.47
5.65
7.00
1.72
0.87
4.77
1.16
2.62
2.60
3.77
6.95
-1.28
0.005
0.000
0.001
0.000
0.000
0.039
0.000
0.000
0.018
0.093
0.637
0.000
0.000
0.086
0.385
0.000
0.248
0.009
0.009
0.000
0.000
0.201
.0925132
.4167667
.1638024
.4410204
.230502
.0115536
.3864264
.1911759
.0466326
-.3913442
-.3086138
.393359
.5383488
-.0262034
-.1292855
.2998019
-.0878289
.0712153
.069557
.2030708
.5276787
-.342305
.5193579
.8482758
.588241
.8613174
.6787821
.4366785
.8180861
.6206159
.4956781
.0301804
.1888909
.8115287
.957276
.3935039
.3349656
.7177229
.3396792
.4942631
.4984999
.6432956
.9427841
.0721513
.119831
.1063431
.1075381
.1276346
.1323525
.1126372
.1143773
.1319708
.1062942
.1094453
.1145434
.1077762
.1145162
.1082615
.1077964
.1148039
.1182324
.1062348
.1064421
.1063462
.107208
.1065623
.1075391
.1097508
.1234667
.2189517
-3.83
2.81
-4.55
-0.69
0.80
2.27
-1.72
0.27
-7.57
0.61
-1.43
-5.69
-8.15
7.38
9.15
-0.47
6.06
9.25
2.59
2.92
10.20
9.39
3.17
-1.10
3.16
27.06
0.000
0.005
0.000
0.491
0.421
0.023
0.086
0.789
0.000
0.541
0.154
0.000
0.000
0.000
0.000
0.641
0.000
0.000
0.010
0.004
0.000
0.000
0.002
0.270
0.002
0.000
-.6935356
.090256
-.7000834
-.3382526
-.1530011
.0344683
-.4204986
-.223446
-1.012695
-.1477361
-.3878466
-.8243411
-1.158266
.5861695
.7753517
-.2786031
.4847223
.7744932
.0667164
.1022027
.8838047
.7918994
.1301146
-.3363123
.1485328
5.495568
-.2236042
.5072931
-.2783598
.1622818
.3660348
.4761885
.0280455
.2940933
-.5958498
.2814667
.0613489
-.4016841
-.7091769
1.01073
1.198088
.1716139
.9483846
1.191106
.4841417
.5192521
1.304233
1.209796
.5518418
.0940884
.632722
6.354213
60
2002 (1) fixed effects DW= 1.79
Source
SS
df
MS
Model
Residual
1944.15458
912.736947
64
2805
30.3774153
.325396416
Total
2856.89153
2869
.995779549
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.3746253
.3078117
-.4636005
-.0264519
.144813
.4391449
.1033027
-.0126464
-.4369493
.2930354
-.8310604
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.2708124
.1323824
.3725108
.2147455
.3050162
.1517632
(omitted)
.3283712
.6380743
.4096804
.6449222
.4416902
.1432018
.5787925
.4209415
.2488656
-.2309733
.0729134
.5701797
.7660211
.2048903
.0690158
.6826438
.0858199
.2978517
.8917807
.5242718
.7743985
-.0123196
(omitted)
-.4252362
.3200833
-.1952896
.124217
.1609958
.6249286
-.209164
.4099736
-.6577928
.1502669
-.0554424
-.4965988
-.8434671
.7354909
1.011129
.0167063
.6779895
1.011171
.3450582
.3548623
1.127559
1.006914
.3874814
-.0812336
.4521831
5.632179
Std. Err.
t
Number of obs
F( 64,
2805)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2870
93.36
0.0000
0.6805
0.6732
.57044
[95% Conf. Interval]
.0278462
.0109726
.0151616
.0103237
.0650798
.0338857
.1006436
.0015298
.1929545
.0479802
.1608183
13.45
28.05
-30.58
-2.56
2.23
12.96
1.03
-8.27
-2.26
6.11
-5.17
0.000
0.000
0.000
0.010
0.026
0.000
0.305
0.000
0.024
0.000
0.000
.3200241
.2862966
-.4933294
-.0466947
.0172038
.3727016
-.0940404
-.0156461
-.8152964
.1989554
-1.146395
.4292265
.3293269
-.4338715
-.0062091
.2724222
.5055883
.3006458
-.0096467
-.0586022
.3871154
-.5157262
.1165723
.1181691
.1209011
.1207764
.1673901
.1485186
-2.32
1.12
3.08
1.78
1.82
1.02
0.020
0.263
0.002
0.076
0.069
0.307
-.4993885
-.0993247
.1354467
-.0220742
-.023204
-.1394535
-.0422362
.3640896
.6095749
.4515651
.6332363
.4429799
.1062873
.1074233
.1057552
.1047748
.1116359
.1060947
.1075514
.1069172
.1120559
.1052251
.1256186
.1044493
.1046642
.1047214
.1158119
.1039774
.1069719
.1051538
.1034354
.1087051
.1040066
.1034493
3.09
5.94
3.87
6.16
3.96
1.35
5.38
3.94
2.22
-2.20
0.58
5.46
7.32
1.96
0.60
6.57
0.80
2.83
8.62
4.82
7.45
-0.12
0.002
0.000
0.000
0.000
0.000
0.177
0.000
0.000
0.026
0.028
0.562
0.000
0.000
0.051
0.551
0.000
0.422
0.005
0.000
0.000
0.000
0.905
.1199621
.4274377
.2023145
.4394788
.2227933
-.0648298
.3679046
.2112973
.0291452
-.4372998
-.1734009
.3653745
.5607945
-.0004485
-.1580695
.4787639
-.1239317
.091665
.6889637
.3111218
.5704614
-.2151642
.5367804
.8487109
.6170462
.8503656
.6605871
.3512335
.7896804
.6305858
.4685859
-.0246468
.3192277
.7749849
.9712477
.4102291
.296101
.8865237
.2955714
.5040383
1.094598
.7374218
.9783356
.1905249
.1159329
.1045112
.104776
.1279171
.1359114
.1168859
.1131629
.1305121
.1040506
.1076997
.1132264
.1053404
.1125692
.1063559
.1048956
.111544
.1161967
.1040568
.104489
.1042513
.1049687
.1042752
.1051728
.1069809
.1212361
.2194218
-3.67
3.06
-1.86
0.97
1.18
5.35
-1.85
3.14
-6.32
1.40
-0.49
-4.71
-7.49
6.92
9.64
0.15
5.83
9.72
3.30
3.40
10.74
9.66
3.68
-0.76
3.73
25.67
0.000
0.002
0.062
0.332
0.236
0.000
0.065
0.002
0.000
0.163
0.624
0.000
0.000
0.000
0.000
0.881
0.000
0.000
0.001
0.001
0.000
0.000
0.000
0.448
0.000
0.000
-.6525587
.1151566
-.4007355
-.1266041
-.1055006
.3957375
-.4310549
.1540642
-.8618163
-.0609118
-.2774579
-.7031513
-1.064194
.5269471
.8054483
-.2020103
.4501499
.8071349
.1401751
.1504452
.9217349
.8024503
.1812574
-.291003
.2144621
5.201934
-.1979137
.5250099
.0101562
.3750382
.4274922
.8541197
.0127269
.6658829
-.4537693
.3614456
.1665732
-.2900462
-.6227403
.9440347
1.216809
.2354229
.9058292
1.215206
.5499414
.5592793
1.333383
1.211378
.5937054
.1285357
.689904
6.062423
2003 (1) + fixed effects DW=1.72
61
Source
SS
df
MS
Model
Residual
2023.33243
975.919827
64
2808
31.6145693
.347549796
Total
2999.25226
2872
1.04430789
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.3751359
.319878
-.4580736
-.034355
.1422471
.4680604
.1640031
-.0126364
-.4089817
.2789197
-.8498677
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.2952921
.1223336
.3858567
.1804426
.3357256
.1579816
(omitted)
.3123276
.5977617
.3676595
.6009574
.4422898
.1392124
.5596171
.4069327
.0922264
-.2678032
-.15966
.4520334
.6739618
.1655554
.0048752
.5248595
.0781187
.2651656
.8328372
.5680626
.8283905
.1448786
(omitted)
-.4281598
.3120784
.014972
.2612729
.2318108
.6992231
-.748517
.3285219
-.4367287
.0230228
-.1242362
-.486628
-.799758
.6803476
1.079993
.0220346
.715277
1.0394
.3543181
.3571817
1.174576
1.025783
.3422111
-.0026151
.5629108
5.417457
Std. Err.
t
Number of obs
F( 64,
2808)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2873
90.96
0.0000
0.6746
0.6672
.58953
[95% Conf. Interval]
.0284585
.0111733
.0156811
.0108272
.0673003
.0350868
.1040287
.00163
.188097
.0504612
.1611432
13.18
28.63
-29.21
-3.17
2.11
13.34
1.58
-7.75
-2.17
5.53
-5.27
0.000
0.000
0.000
0.002
0.035
0.000
0.115
0.000
0.030
0.000
0.000
.3193343
.2979694
-.4888213
-.0555852
.010284
.3992619
-.0399773
-.0158326
-.777804
.1799749
-1.165839
.4309376
.3417867
-.427326
-.0131248
.2742101
.5368588
.3679835
-.0094402
-.0401593
.3778645
-.5338968
.1189197
.1225542
.1267024
.1252482
.1703339
.1527385
-2.48
1.00
3.05
1.44
1.97
1.03
0.013
0.318
0.002
0.150
0.049
0.301
-.528471
-.1179718
.1374174
-.0651452
.0017335
-.1415094
-.0621132
.3626389
.6342959
.4260303
.6697178
.4574726
.1094723
.1105662
.1089216
.1078736
.1150217
.109116
.1104573
.1098499
.115482
.1086487
.1282834
.1076193
.1075664
.1078656
.11932
.1075473
.1106204
.1075716
.1065577
.1118232
.1073992
.1067406
2.85
5.41
3.38
5.57
3.85
1.28
5.07
3.70
0.80
-2.46
-1.24
4.20
6.27
1.53
0.04
4.88
0.71
2.47
7.82
5.08
7.71
1.36
0.004
0.000
0.001
0.000
0.000
0.202
0.000
0.000
0.425
0.014
0.213
0.000
0.000
0.125
0.967
0.000
0.480
0.014
0.000
0.000
0.000
0.175
.0976734
.3809624
.1540849
.3894378
.2167542
-.0747433
.3430314
.1915381
-.1342117
-.4808425
-.4111994
.2410126
.4630447
-.0459485
-.2290884
.3139798
-.1387868
.0542381
.6238979
.3487987
.6178012
-.0644193
.5269819
.8145609
.581234
.8124769
.6678254
.3531681
.7762028
.6223274
.3186645
-.0547639
.0918794
.6630543
.8848788
.3770593
.2388389
.7357392
.2950242
.476093
1.041777
.7873265
1.03898
.3541765
.1169275
.1081089
.1076233
.1341192
.1413609
.1241573
.1158478
.1406966
.1075922
.1108081
.1167572
.1084286
.1157225
.1095298
.107185
.1141812
.1186449
.1072009
.1077735
.1077032
.1075729
.1072437
.1082533
.1096142
.1247426
.2303294
-3.66
2.89
0.14
1.95
1.64
5.63
-6.46
2.33
-4.06
0.21
-1.06
-4.49
-6.91
6.21
10.08
0.19
6.03
9.70
3.29
3.32
10.92
9.56
3.16
-0.02
4.51
23.52
0.000
0.004
0.889
0.052
0.101
0.000
0.000
0.020
0.000
0.835
0.287
0.000
0.000
0.000
0.000
0.847
0.000
0.000
0.001
0.001
0.000
0.000
0.002
0.981
0.000
0.000
-.6574323
.1000974
-.1960568
-.0017092
-.045371
.4557744
-.9756724
.0526427
-.6476964
-.1942508
-.3531748
-.6992358
-1.026668
.4655805
.8698241
-.2018528
.4826369
.8291992
.1429948
.1459964
.9636463
.815499
.129947
-.2175475
.3183143
4.965825
-.1988873
.5240593
.2260009
.524255
.5089925
.9426718
-.5213616
.604401
-.225761
.2402963
.1047024
-.2740201
-.5728484
.8951147
1.290163
.2459221
.947917
1.2496
.5656413
.5683671
1.385506
1.236068
.5544753
.2123174
.8075073
5.869089
2004 (1) + fixed effects DW=1.67
62
Source
SS
df
MS
Model
Residual
1951.76299
900.918702
63
2781
30.980365
.323954945
Total
2852.6817
2844
1.00305264
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.3724897
.3045184
-.4376765
-.0339894
.1730945
.5033851
.1466927
-.0120263
-.3328856
.2549585
-.7412549
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.2129863
.1494085
.4451599
.2379283
.3853705
.1536333
(omitted)
.4037069
.6587728
.4452995
.682543
.5371319
.1840088
.6572315
.4775204
.1140609
-.233279
.0438511
.4862157
.6795724
.2151495
.0510433
.5228965
.1206688
.3957705
.8139493
.6587402
.8756705
.1666613
(omitted)
-.4286325
.4282592
-.3444786
.3426316
.2959216
.7310711
-.1496795
(omitted)
-.3882289
.1024111
-.0781252
-.4420012
-.794563
.7556898
1.167575
.1177692
.8212503
1.115173
.3789772
.4311188
1.263985
1.13074
.4286525
.1848329
.6633657
5.18755
Std. Err.
t
Number of obs
F( 63,
2781)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2845
95.63
0.0000
0.6842
0.6770
.56917
[95% Conf. Interval]
.0277539
.0109928
.0151454
.010569
.0648899
.0341577
.1013409
.0016244
.1825611
.0500152
.1486559
13.42
27.70
-28.90
-3.22
2.67
14.74
1.45
-7.40
-1.82
5.10
-4.99
0.000
0.000
0.000
0.001
0.008
0.000
0.148
0.000
0.068
0.000
0.000
.3180694
.2829635
-.4673738
-.0547133
.0458572
.436408
-.0520182
-.0152115
-.6908545
.1568879
-1.032742
.42691
.3260734
-.4079791
-.0132656
.3003318
.5703622
.3454036
-.0088411
.0250834
.3530291
-.4497679
.1147087
.118741
.1230891
.1214684
.1642352
.1486573
-1.86
1.26
3.62
1.96
2.35
1.03
0.063
0.208
0.000
0.050
0.019
0.301
-.4379091
-.083421
.2038047
-.0002491
.0633353
-.1378566
.0119365
.382238
.6865152
.4761057
.7074057
.4451232
.1057246
.1068163
.105193
.1041711
.111115
.105374
.1067423
.1059302
.1120529
.1050221
.123925
.1039022
.1037217
.1041143
.1155284
.1042281
.1076707
.1038005
.1028404
.1084457
.103315
.1028931
3.82
6.17
4.23
6.55
4.83
1.75
6.16
4.51
1.02
-2.22
0.35
4.68
6.55
2.07
0.44
5.02
1.12
3.81
7.91
6.07
8.48
1.62
0.000
0.000
0.000
0.000
0.000
0.081
0.000
0.000
0.309
0.026
0.723
0.000
0.000
0.039
0.659
0.000
0.263
0.000
0.000
0.000
0.000
0.105
.1964002
.4493255
.2390352
.4782824
.3192557
-.0226105
.4479293
.2698105
-.1056543
-.4392082
-.1991431
.2824824
.4761931
.0110004
-.1754868
.3185242
-.0904537
.1922366
.612298
.4460979
.6730887
-.0350933
.6110136
.8682201
.6515638
.8868036
.7550081
.390628
.8665337
.6852302
.3337761
-.0273497
.2868453
.689949
.8829517
.4192985
.2775734
.7272688
.3317914
.5993044
1.015601
.8713825
1.078252
.368416
.1124093
.1043638
.1035824
.1304883
.1354423
.1201344
.111515
-3.81
4.10
-3.33
2.63
2.18
6.09
-1.34
0.000
0.000
0.001
0.009
0.029
0.000
0.180
-.6490467
.2236208
-.5475848
.086768
.030344
.4955094
-.3683401
-.2082184
.6328976
-.1413724
.5984953
.5614992
.9666328
.068981
.1043034
.1069546
.1128232
.1060873
.1112857
.1055417
.1032812
.110331
.1145489
.1034403
.1038842
.1040567
.1044147
.1034962
.1043203
.1059228
.1212885
.2265683
-3.72
0.96
-0.69
-4.17
-7.14
7.16
11.30
1.07
7.17
10.78
3.65
4.14
12.11
10.93
4.11
1.74
5.47
22.90
0.000
0.338
0.489
0.000
0.000
0.000
0.000
0.286
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.081
0.000
0.000
-.5927488
-.1073073
-.2993508
-.6500191
-1.012774
.5487417
.9650589
-.0985697
.5966408
.9123455
.1752791
.2270826
1.059247
.9278033
.2240994
-.0228624
.4255412
4.743292
-.1837089
.3121296
.1431005
-.2339833
-.5763521
.9626378
1.37009
.3341081
1.04586
1.318001
.5826752
.635155
1.468723
1.333678
.6332056
.3925282
.9011903
5.631809
2005 (1) + fixed effects DW= 1.67
63
Source
SS
df
MS
Model
Residual
1961.81882
851.051687
63
2783
31.1399813
.305803696
Total
2812.87051
2846
.98835928
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.374354
.3069667
-.453771
-.0248123
.187104
.4548916
.1657546
-.0119223
-.2865164
.2563607
-.793118
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.1922874
.173169
.4475305
.2411869
.4017898
.1900532
(omitted)
.4176806
.6951354
.4558306
.724999
.5795583
.1900662
.6842526
.505564
.1582372
-.1808261
-.0226804
.5015481
.6987341
.2211931
.0511575
.5820194
.0610033
.4544293
.773747
.6048406
.8262511
.1350951
(omitted)
-.2235224
.4736544
-.4165765
.249578
.2736515
.7395404
-.0999069
(omitted)
-.3658712
.2166746
-.0322245
-.4006618
-.6986792
.7792122
1.2063
.1624949
.8296005
1.142368
.399469
.3891659
1.269071
1.169687
.4783344
.1875068
.7182706
5.243097
Std. Err.
t
Number of obs
F( 63,
2783)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2847
101.83
0.0000
0.6974
0.6906
.553
[95% Conf. Interval]
.0274274
.0109074
.0146479
.0098665
.0631342
.03321
.0984457
.0016876
.1844696
.0514497
.1494533
13.65
28.14
-30.98
-2.51
2.96
13.70
1.68
-7.06
-1.55
4.98
-5.31
0.000
0.000
0.000
0.012
0.003
0.000
0.092
0.000
0.120
0.000
0.000
.320574
.2855792
-.4824928
-.0441587
.0633093
.3897728
-.0272793
-.0152313
-.6482275
.1554773
-1.086168
.4281341
.3283542
-.4250492
-.0054658
.3108987
.5200104
.3587886
-.0086133
.0751948
.3572442
-.5000675
.1121325
.1152146
.118663
.1179121
.1590313
.1441558
-1.71
1.50
3.77
2.05
2.53
1.32
0.086
0.133
0.000
0.041
0.012
0.187
-.4121586
-.0527457
.2148541
.0099828
.0899585
-.09261
.0275838
.3990836
.680207
.472391
.7136211
.4727163
.1026333
.103684
.1021685
.1011715
.1078583
.1028452
.103469
.1026945
.1094715
.1020166
.1188237
.1010231
.1008341
.1011211
.1125534
.101481
.1056727
.1009395
.1000304
.1066358
.1002405
.0999725
4.07
6.70
4.46
7.17
5.37
1.85
6.61
4.92
1.45
-1.77
-0.19
4.96
6.93
2.19
0.45
5.74
0.58
4.50
7.74
5.67
8.24
1.35
0.000
0.000
0.000
0.000
0.000
0.065
0.000
0.000
0.148
0.076
0.849
0.000
0.000
0.029
0.649
0.000
0.564
0.000
0.000
0.000
0.000
0.177
.2164356
.4918302
.2554969
.5266203
.3680679
-.0115944
.4813689
.3041988
-.0564163
-.3808619
-.2556719
.3034604
.5010169
.0229132
-.1695391
.3830338
-.1462016
.2565055
.5776057
.3957474
.6296979
-.0609328
.6189256
.8984407
.6561643
.9233778
.7910487
.3917268
.8871363
.7069291
.3728908
.0192097
.210311
.6996359
.8964513
.419473
.2718542
.781005
.2682082
.6523531
.9698883
.8139338
1.022804
.3311229
.1097532
.1013541
.1006245
.127636
.1320915
.1153176
.1081887
-2.04
4.67
-4.14
1.96
2.07
6.41
-0.92
0.042
0.000
0.000
0.051
0.038
0.000
0.356
-.4387284
.2749176
-.6138828
-.0006929
.0146442
.5134236
-.3120452
-.0083164
.6723912
-.2192703
.4998489
.5326587
.9656571
.1122314
.1012855
.1043466
.110455
.1032671
.107411
.1027592
.1003765
.1078845
.1127583
.1005549
.1009601
.1010924
.1015198
.1006516
.1014609
.1035665
.1194137
.2236509
-3.61
2.08
-0.29
-3.88
-6.50
7.58
12.02
1.51
7.36
11.36
3.96
3.85
12.50
11.62
4.71
1.81
6.01
23.44
0.000
0.038
0.771
0.000
0.000
0.000
0.000
0.132
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.070
0.000
0.000
-.5644735
.0120701
-.2488066
-.6031497
-.9092924
.5777203
1.00948
-.0490467
.6085021
.9451987
.2015048
.1909423
1.070009
.9723279
.2793883
-.0155683
.4841223
4.804558
-.1672688
.4212791
.1843576
-.1981739
-.488066
.9807041
1.40312
.3740366
1.050699
1.339538
.5974333
.5873896
1.468132
1.367047
.6772806
.3905818
.9524189
5.681635
2006 (1) + fixed effects DW= 1.82
64
Source
SS
df
MS
Model
Residual
2000.54918
1009.25249
64
2812
31.2585809
.358909136
Total
3009.80167
2876
1.04652353
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.3752349
.318855
-.4619982
-.0128822
.18197
.4362733
.1308433
-.011605
-.3818342
.2540238
-.8282708
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.2330241
.1244115
.4390911
.1980989
.3463585
.1504529
(omitted)
.3998585
.6356897
.3483643
.6781841
.5309379
.1719621
.6060424
.4526113
.1549277
-.3319983
-.1468416
.3985295
.6993935
.1692568
-.0288557
.6032405
.0219959
.3294343
.7330835
.4942045
.8039134
.0959836
(omitted)
-.2551987
.4553449
-.4891848
.225695
.2089354
.6650022
-.126259
-.421919
-.5086545
.1303374
-.0467406
-.4461301
-.9741616
.6361123
1.163841
.1210976
.7521361
1.084628
.2898577
.2872854
1.197615
1.106669
.5026251
.0889654
.6942714
5.273168
Std. Err.
t
Number of obs
F( 64,
2812)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2877
87.09
0.0000
0.6647
0.6570
.59909
[95% Conf. Interval]
.0299538
.0120037
.0158335
.0108839
.0683324
.0356727
.1056146
.0019795
.203636
.059512
.1618352
12.53
26.56
-29.18
-1.18
2.66
12.23
1.24
-5.86
-1.88
4.27
-5.12
0.000
0.000
0.000
0.237
0.008
0.000
0.215
0.000
0.061
0.000
0.000
.3165012
.295318
-.4930446
-.0342233
.0479834
.3663261
-.0762466
-.0154863
-.7811253
.1373322
-1.145599
.4339685
.342392
-.4309518
.008459
.3159567
.5062206
.3379331
-.0077236
.0174568
.3707153
-.5109431
.121399
.1245012
.1278549
.1276196
.1700264
.1554198
-1.92
1.00
3.43
1.55
2.04
0.97
0.055
0.318
0.001
0.121
0.042
0.333
-.4710641
-.1197113
.1883921
-.0521387
.0129694
-.1542954
.005016
.3685344
.6897901
.4483365
.6797477
.4552013
.1109298
.1119593
.1104616
.109475
.1165
.111419
.111875
.1108573
.1181399
.1104183
.1303421
.1093478
.1094966
.1093831
.1217869
.1096809
.1144165
.109322
.1083377
.1161815
.1084194
.1082481
3.60
5.68
3.15
6.19
4.56
1.54
5.42
4.08
1.31
-3.01
-1.13
3.64
6.39
1.55
-0.24
5.50
0.19
3.01
6.77
4.25
7.41
0.89
0.000
0.000
0.002
0.000
0.000
0.123
0.000
0.000
0.190
0.003
0.260
0.000
0.000
0.122
0.813
0.000
0.848
0.003
0.000
0.000
0.000
0.375
.1823464
.416159
.1317704
.4635247
.3025038
-.0465092
.3866769
.2352414
-.0767219
-.5485074
-.4024174
.1841194
.4846917
-.0452224
-.2676564
.3881774
-.2023529
.1150749
.5206541
.266395
.5913238
-.1162701
.6173706
.8552204
.5649583
.8928435
.759372
.3904334
.8254079
.6699811
.3865773
-.1154892
.1087341
.6129395
.9140954
.3837361
.209945
.8183037
.2463447
.5437936
.945513
.7220141
1.016503
.3082374
.1190125
.1096095
.1096555
.1374198
.141737
.1249705
.1162165
.1296234
.109486
.1131461
.1203013
.1119636
.1167581
.1121548
.1086302
.1168421
.122884
.1088713
.1092732
.1093175
.109967
.1091222
.1100691
.1122637
.1316166
.2461143
-2.14
4.15
-4.46
1.64
1.47
5.32
-1.09
-3.25
-4.65
1.15
-0.39
-3.98
-8.34
5.67
10.71
1.04
6.12
9.96
2.65
2.63
10.89
10.14
4.57
0.79
5.27
21.43
0.032
0.000
0.000
0.101
0.141
0.000
0.277
0.001
0.000
0.249
0.698
0.000
0.000
0.000
0.000
0.300
0.000
0.000
0.008
0.009
0.000
0.000
0.000
0.428
0.000
0.000
-.4885594
.2404217
-.7041982
-.0437588
-.0689836
.4199591
-.3541371
-.6760857
-.7233355
-.0915204
-.2826285
-.6656691
-1.203102
.4161983
.9508381
-.1080072
.5111842
.8711528
.0755939
.0729347
.9819911
.892701
.2868007
-.1311621
.4361965
4.790585
-.021838
.670268
-.2741714
.4951488
.4868544
.9100453
.1016192
-.1677523
-.2939735
.3521951
.1891472
-.226591
-.7452214
.8560263
1.376844
.3502025
.993088
1.298104
.5041216
.5016361
1.413239
1.320636
.7184496
.3090929
.9523464
5.755751
2007 (1) + fixed effects DW= 1.39
65
Source
SS
df
MS
Model
Residual
1843.26683
947.841325
63
2763
29.2582037
.343047892
Total
2791.10816
2826
.987653276
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.3411437
.2995913
-.4404969
-.0252412
.1664049
.4543854
.1544534
-.01025
-.1912862
.1925099
-.6865868
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.2235703
.0605584
.3556256
.1769028
.3312708
.0325499
(omitted)
.3485848
.5980219
.2814382
.5885298
.5143612
.1109833
.5447413
.4185151
.0187691
-.4225848
-.1877619
.3188317
.5834488
.0827833
-.0347527
.5352436
-.0374799
.2553591
.6659786
.3778808
.7127002
-.1116485
(omitted)
-.243734
.3770615
-.9389432
.1269138
.2261189
.4867307
-.3081909
-.315056
-.5155804
.0386612
-.1158667
(omitted)
-1.035557
.5400511
1.076513
.0237026
.7221295
.9492797
.1482279
.2030504
1.054024
1.031847
.4033927
.0385224
.6720732
5.344784
Std. Err.
t
Number of obs
F( 63,
2763)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2827
85.29
0.0000
0.6604
0.6527
.5857
[95% Conf. Interval]
.0293142
.0120643
.0156416
.0111929
.0676045
.0348706
.1033462
.0021031
.2015576
.0622945
.1565399
11.64
24.83
-28.16
-2.26
2.46
13.03
1.49
-4.87
-0.95
3.09
-4.39
0.000
0.000
0.000
0.024
0.014
0.000
0.135
0.000
0.343
0.002
0.000
.2836637
.2759353
-.4711673
-.0471886
.0338444
.3860104
-.0481901
-.0143739
-.5865049
.0703614
-.9935338
.3986238
.3232474
-.4098265
-.0032939
.2989654
.5227604
.3570969
-.0061262
.2039326
.3146584
-.3796398
.1181805
.1227106
.1263675
.1260415
.1644759
.153033
-1.89
0.49
2.81
1.40
2.01
0.21
0.059
0.622
0.005
0.161
0.044
0.832
-.4553013
-.1800554
.1078414
-.0702423
.0087627
-.2675207
.0081608
.3011722
.6034098
.4240478
.6537788
.3326205
.1086414
.1096054
.1080584
.1071334
.1144573
.1091453
.109705
.1083653
.116266
.1081612
.1258049
.1069135
.1067763
.1069394
.11947
.1070944
.1128592
.1067427
.1060328
.1151615
.105906
.1057891
3.21
5.46
2.60
5.49
4.49
1.02
4.97
3.86
0.16
-3.91
-1.49
2.98
5.46
0.77
-0.29
5.00
-0.33
2.39
6.28
3.28
6.73
-1.06
0.001
0.000
0.009
0.000
0.000
0.309
0.000
0.000
0.872
0.000
0.136
0.003
0.000
0.439
0.771
0.000
0.740
0.017
0.000
0.001
0.000
0.291
.1355583
.3831052
.0695549
.3784601
.2899307
-.1030313
.3296292
.20603
-.2092079
-.6346699
-.4344431
.1091932
.3740794
-.1269059
-.2690121
.3252505
-.2587768
.0460556
.4580671
.1520694
.5050373
-.3190823
.5616114
.8129386
.4933216
.7985995
.7387917
.3249978
.7598534
.6310003
.2467462
-.2104997
.0589193
.5284702
.7928183
.2924726
.1995068
.7452367
.183817
.4646626
.8738901
.6036922
.9203631
.0957852
.1160908
.1068604
.1078394
.1347521
.1354918
.1208541
.1142207
.1205377
.1066738
.1102624
.1172405
-2.10
3.53
-8.71
0.94
1.67
4.03
-2.70
-2.61
-4.83
0.35
-0.99
0.036
0.000
0.000
0.346
0.095
0.000
0.007
0.009
0.000
0.726
0.323
-.4713676
.1675271
-1.150397
-.1373112
-.0395565
.2497572
-.5321574
-.5514091
-.7247488
-.1775438
-.3457546
-.0161004
.5865959
-.7274893
.3911389
.4917943
.7237041
-.0842244
-.078703
-.3064121
.2548662
.1140212
.1148193
.1101516
.1060887
.1151035
.1204501
.1063325
.1067176
.1065716
.1073704
.1068315
.1072694
.1105876
.1328789
.2452829
-9.02
4.90
10.15
0.21
6.00
8.93
1.39
1.91
9.82
9.66
3.76
0.35
5.06
21.79
0.000
0.000
0.000
0.837
0.000
0.000
0.165
0.057
0.000
0.000
0.000
0.728
0.000
0.000
-1.260697
.3240633
.8684921
-.2019951
.4859481
.7407805
-.0610263
-.0059177
.8434899
.8223695
.1930565
-.1783202
.4115211
4.863828
-.8104167
.7560389
1.284534
.2494002
.9583108
1.157779
.3574822
.4120185
1.264558
1.241325
.613729
.255365
.9326252
5.825741
2008 (1) + Fixed effects DW=1.48
66
Source
SS
df
MS
Model
Residual
1774.18625
938.660377
63
2758
28.1616865
.340340964
Total
2712.84663
2821
.961661335
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.3434395
.2914561
-.4447462
-.0256529
.1531578
.459029
.1547993
-.0106789
-.1399259
.1929534
-.6407352
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.1806142
.0317779
.3174632
.1491835
.3162481
.0037592
(omitted)
.3057708
.571297
.2927148
.5528626
.4687847
.1211891
.5511499
.3862505
.017489
-.4535532
-.1714703
.2806682
.6216688
.0701432
-.0719582
.3325418
.0154501
.2185444
.6157132
.3585878
.667299
-.1663684
(omitted)
-.1824016
.3251785
-1.202834
.1050448
.3511434
.4620598
-.3600717
-.0221397
-.2691054
.1270592
-.0636308
(omitted)
-1.122068
.5332173
1.075738
.0799134
.8100924
.9029337
.1295053
.0714745
1.087476
1.042904
.3186323
.0027164
.641771
5.379055
Std. Err.
t
Number of obs
F( 63,
2758)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2822
82.75
0.0000
0.6540
0.6461
.58339
[95% Conf. Interval]
.0298362
.0123193
.015626
.0109965
.0672242
.0347071
.1028918
.0020204
.1966926
.0599166
.1753184
11.51
23.66
-28.46
-2.33
2.28
13.23
1.50
-5.29
-0.71
3.22
-3.65
0.000
0.000
0.000
0.020
0.023
0.000
0.133
0.000
0.477
0.001
0.000
.284936
.2673002
-.4753861
-.0472151
.0213429
.3909744
-.0469536
-.0146407
-.5256055
.0754675
-.9845039
.401943
.315612
-.4141063
-.0040907
.2849727
.5270836
.3565521
-.0067172
.2457537
.3104394
-.2969666
.1165827
.1222909
.1258719
.1249446
.1627081
.1495254
-1.55
0.26
2.52
1.19
1.94
0.03
0.121
0.795
0.012
0.233
0.052
0.980
-.4092125
-.2080131
.0706505
-.0958109
-.0027939
-.2894338
.047984
.2715689
.5642758
.394178
.6352901
.2969522
.1083351
.1091426
.1077452
.1069938
.1138317
.1089522
.1089723
.1081363
.1153161
.1079281
.1327911
.1065927
.1075313
.1068414
.118324
.1064983
.1123338
.1068212
.106129
.1155021
.1062535
.1058156
2.82
5.23
2.72
5.17
4.12
1.11
5.06
3.57
0.15
-4.20
-1.29
2.63
5.78
0.66
-0.61
3.12
0.14
2.05
5.80
3.10
6.28
-1.57
0.005
0.000
0.007
0.000
0.000
0.266
0.000
0.000
0.879
0.000
0.197
0.009
0.000
0.512
0.543
0.002
0.891
0.041
0.000
0.002
0.000
0.116
.0933446
.3572875
.0814455
.3430666
.2455806
-.092447
.3374744
.1742142
-.2086257
-.6651812
-.4318504
.0716587
.4108188
-.139354
-.3039708
.1237173
-.2048167
.0090867
.4076128
.1321086
.4589546
-.3738542
.518197
.7853066
.5039842
.7626586
.6919888
.3348252
.7648255
.5982868
.2436037
-.2419252
.0889097
.4896778
.8325188
.2796404
.1600545
.5413663
.2357169
.428002
.8238136
.5850671
.8756434
.0411173
.1147271
.10715
.1087409
.1352051
.1342664
.1205303
.1149813
.1184605
.1067048
.1113114
.1188848
-1.59
3.03
-11.06
0.78
2.62
3.83
-3.13
-0.19
-2.52
1.14
-0.54
0.112
0.002
0.000
0.437
0.009
0.000
0.002
0.852
0.012
0.254
0.593
-.4073613
.1150762
-1.416055
-.1600686
.0878706
.2257209
-.5855299
-.2544199
-.4783348
-.0912031
-.296743
.0425581
.5352809
-.9896118
.3701582
.6144162
.6983986
-.1346135
.2101404
-.0598761
.3453214
.1694814
.1156319
.1101104
.1061265
.1139878
.1163316
.1063991
.1069302
.1067568
.107557
.1067197
.1075239
.1109254
.1351175
.2538267
-9.70
4.84
10.14
0.70
6.96
8.49
1.21
0.67
10.11
9.77
2.96
0.02
4.75
21.19
0.000
0.000
0.000
0.483
0.000
0.000
0.226
0.503
0.000
0.000
0.003
0.980
0.000
0.000
-1.348802
.3173101
.867642
-.1435966
.5819864
.6943038
-.080166
-.1378569
.8765751
.8336452
.1077968
-.2147888
.3768293
4.881346
-.8953342
.7491246
1.283833
.3034234
1.038198
1.111564
.3391767
.2808059
1.298376
1.252163
.5294677
.2202217
.9067127
5.876765
2009 (1) + fixed effects DW=1.71
67
Source
SS
df
MS
Model
Residual
1679.47585
813.324262
62
2710
27.0883202
.300119654
Total
2492.80011
2772
.899278541
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.3463211
.3108212
-.4426078
-.022377
.1374093
.4244719
.2128699
-.0134167
-.1450976
.2618576
-.8633444
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.303503
-.0235366
.2741064
.0675845
.2042067
.0187954
(omitted)
.2018614
.4748237
.2254727
.3978776
.417635
.0409106
.4616405
.3009011
-.1304727
-.5480697
-.2607488
.2519688
.5022768
-.0461502
-.1449642
.3985903
-.0407874
.0463361
.4814826
.2598122
.5822069
-.072081
(omitted)
-.2298118
.1698876
-1.578901
.0280825
.2743804
.3217788
-.2220511
-.1154868
-.3831215
-.0807949
-.2555724
(omitted)
(omitted)
.3634312
.9734713
-.0253503
.7460651
.7964202
-.0185576
-.0459535
.9392682
.9029624
.2726131
-.0082757
.577818
5.344898
Std. Err.
t
Number of obs
F( 62,
2710)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
2773
90.26
0.0000
0.6737
0.6663
.54783
[95% Conf. Interval]
.0282143
.0114652
.0147137
.0104241
.0632117
.0327599
.0976943
.0017675
.1866485
.0531149
.1907524
12.27
27.11
-30.08
-2.15
2.17
12.96
2.18
-7.59
-0.78
4.93
-4.53
0.000
0.000
0.000
0.032
0.030
0.000
0.029
0.000
0.437
0.000
0.000
.2909973
.2883398
-.471459
-.042817
.0134613
.3602351
.0213071
-.0168825
-.5110853
.1577077
-1.237379
.4016448
.3333025
-.4137566
-.001937
.2613573
.4887088
.4044328
-.009951
.2208902
.3660074
-.4893096
.1095194
.1150429
.1174195
.1170476
.15538
.1385186
-2.77
-0.20
2.33
0.58
1.31
0.14
0.006
0.838
0.020
0.564
0.189
0.892
-.5182531
-.2491174
.0438656
-.1619272
-.1004686
-.2528174
-.088753
.2020441
.5043471
.2970962
.5088819
.2904083
.1020538
.1028439
.1014997
.1008553
.1068977
.102222
.1021592
.1021427
.1085957
.101778
.1300941
.1004724
.1016422
.100772
.1113286
.1006124
.1049694
.1007674
.1000631
.1087843
.1002543
.0998157
1.98
4.62
2.22
3.95
3.91
0.40
4.52
2.95
-1.20
-5.38
-2.00
2.51
4.94
-0.46
-1.30
3.96
-0.39
0.46
4.81
2.39
5.81
-0.72
0.048
0.000
0.026
0.000
0.000
0.689
0.000
0.003
0.230
0.000
0.045
0.012
0.000
0.647
0.193
0.000
0.698
0.646
0.000
0.017
0.000
0.470
.0017503
.2731634
.0264481
.2001165
.2080257
-.1595305
.2613225
.1006156
-.3434115
-.7476401
-.5158426
.0549585
.3029728
-.2437479
-.3632618
.2013055
-.2466155
-.1512526
.2852749
.0465036
.3856243
-.2678037
.4019725
.6764841
.4244973
.5956387
.6272443
.2413516
.6619584
.5011865
.0824661
-.3484993
-.0056551
.448979
.7015808
.1514475
.0733333
.595875
.1650408
.2439248
.6776903
.4731208
.7787896
.1236416
.106842
.1009117
.1052935
.1262257
.128814
.1131852
.1095826
.1117791
.100342
.1045829
.1120507
-2.15
1.68
-15.00
0.22
2.13
2.84
-2.03
-1.03
-3.82
-0.77
-2.28
0.032
0.092
0.000
0.824
0.033
0.005
0.043
0.302
0.000
0.440
0.023
-.4393118
-.0279842
-1.785365
-.2194258
.0217968
.0998406
-.4369249
-.3346676
-.5798761
-.2858652
-.4752859
-.0203118
.3677593
-1.372437
.2755908
.5269639
.5437169
-.0071772
.1036941
-.186367
.1242754
-.0358589
.1045249
.1001025
.1078917
.1095087
.100409
.1008122
.1006898
.1014223
.1007165
.1018967
.1035542
.1296493
.2374217
3.48
9.72
-0.23
6.81
7.93
-0.18
-0.46
9.26
8.97
2.68
-0.08
4.46
22.51
0.001
0.000
0.814
0.000
0.000
0.854
0.648
0.000
0.000
0.008
0.936
0.000
0.000
.1584745
.7771863
-.2369087
.5313361
.5995343
-.2162341
-.24339
.7403954
.7054735
.0728101
-.2113289
.3235965
4.879352
.5683879
1.169756
.1862081
.960794
.9933062
.179119
.151483
1.138141
1.100451
.4724162
.1947774
.8320395
5.810444
2010 (1) + fixed effects DW=1.57
68
Source
SS
df
MS
Model
Residual
966.240052
508.521495
44
1776
21.9600012
.28632967
Total
1474.76155
1820
.810308542
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.3668888
.3108487
-.4235457
-.0307948
.1341654
.4336621
.1972334
-.012103
-.1821471
.213408
-.7899634
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.3134748
.048294
.3115993
.1247765
.2024777
.0451682
(omitted)
(omitted)
.6063308
.3232438
.48232
(omitted)
.0959899
.5132908
.366998
-.1730505
-.3894236
(omitted)
.3806428
.5226199
.0907914
(omitted)
(omitted)
-.0106343
(omitted)
(omitted)
.2278545
(omitted)
-.0678298
(omitted)
-.2144141
.2605597
(omitted)
.288026
.2019013
(omitted)
(omitted)
.1250895
-.2641356
-.0328859
(omitted)
(omitted)
(omitted)
.3527821
(omitted)
(omitted)
(omitted)
.7705231
.1148773
(omitted)
(omitted)
.9752015
.4591475
(omitted)
.5896923
4.948089
Std. Err.
t
Number of obs
F( 44, 1776)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
1821
76.69
0.0000
0.6552
0.6466
.5351
[95% Conf. Interval]
.0250894
.013894
.0176085
.0124894
.0725732
.0424867
.1125398
.0020994
.2282699
.0629292
.2442206
14.62
22.37
-24.05
-2.47
1.85
10.21
1.75
-5.76
-0.80
3.39
-3.23
0.000
0.000
0.000
0.014
0.065
0.000
0.080
0.000
0.425
0.001
0.001
.3176809
.2835985
-.4580811
-.0552902
-.0081724
.3503328
-.023491
-.0162205
-.6298531
.0899849
-1.268953
.4160967
.3380989
-.3890102
-.0062994
.2765032
.5169914
.4179577
-.0079854
.2655588
.3368311
-.3109734
.1238896
.1293416
.1280324
.1305648
.1775168
.1580235
-2.53
0.37
2.43
0.96
1.14
0.29
0.011
0.709
0.015
0.339
0.254
0.775
-.5564596
-.2053837
.0604893
-.1313004
-.1456861
-.2647635
-.07049
.3019717
.5627094
.3808534
.5506415
.3550998
.1127074
.1097404
.1071681
5.38
2.95
4.50
0.000
0.003
0.000
.3852777
.10801
.2721312
.8273839
.5384777
.6925089
.1129634
.1129606
.1131799
.125113
.1098116
0.85
4.54
3.24
-1.38
-3.55
0.396
0.000
0.001
0.167
0.000
-.1255653
.2917411
.1450181
-.4184347
-.6047972
.3175451
.7348406
.5889779
.0723338
-.17405
.1060012
.1050949
.1079925
3.59
4.97
0.84
0.000
0.000
0.401
.1727425
.3164972
-.1210143
.5885431
.7287425
.3025971
.1192708
-0.09
0.929
-.2445603
.2232917
.123305
1.85
0.065
-.0139836
.4696927
.1083055
-0.63
0.531
-.2802495
.1445898
.1226543
.1043653
-1.75
2.50
0.081
0.013
-.454976
.0558679
.0261477
.4652514
.1147415
.1118322
2.51
1.81
0.012
0.071
.0629835
-.0174353
.5130685
.4212378
.1189711
.1080386
.1038618
1.05
-2.44
-0.32
0.293
0.015
0.752
-.1082485
-.4760318
-.2365902
.3584276
-.0522393
.1708184
.1199143
2.94
0.003
.117594
.5879701
.1074468
.1058527
7.17
1.09
0.000
0.278
.5597876
-.0927317
.9812587
.3224862
.1104045
.1032387
8.83
4.45
0.000
0.000
.7586651
.2566654
1.191738
.6616295
.1458482
.2218946
4.04
22.30
0.000
0.000
.3036402
4.512887
.8757444
5.383291
Appendix 4: Basic data correlations
69
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
GDP
3.2698
3.7414
4.2356
2.5368
3.5271
4.7013
2.1983
2.8286
3.6254
4.9436
4.4471
5.0732
5.1535
3.373
0.4863
2.9789
INT trade Econ (3) Stat (3) Econ (6) Stat (6)
19.37124
-0.044
-3.37
-0.02
-1.79
4.628195
-0.043
-3.32
-0.017
-1.52
3.479548
-0.052
-3.85
-0.014
-1.24
-1.60973
-0.044
-3.17
-0.014
-1.23
3.835666
-0.032
-2.52
-0.004
-0.4
13.02521
-0.042
-3.22
-0.011
-0.99
-4.10471
-0.035
-2.82
-0.012
-1.08
4.861896
-0.05
-4.04
-0.026
-2.56
16.85151
-0.051
-3.99
-0.034
-3.17
21.51331
-0.051
-4.03
-0.034
-3.22
13.78824
-0.036
-3.04
-0.025
-2.51
15.48289
-0.031
-2.36
-0.013
-1.18
15.5783
-0.044
-3.32
-0.025
-2.26
15.11429
-0.036
-2.79
-0.026
-2.33
-22.3008
-0.043
-3.45
-0.022
-2.15
21.68983
-0.04
-2.89
-0.031
-2.47
Appendix 5: Pooled regressions
Pooled specification (3) data 1997-1999 DW: 1.23
Source
SS
df
MS
Model
Residual
4149.54576
3987.59457
11
8050
377.231432
.495353363
Total
8137.14032
8061
1.00944552
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.4186292
.2991923
-.4063498
-.0414886
.2224665
.4839821
.0693629
-.0109269
-.5862173
.1814962
-.6776603
5.200775
Std. Err.
.0071935
.0069145
.009796
.0076845
.0456387
.0236338
.0725734
.0007149
.0861879
.0222806
.084365
.1053074
t
58.20
43.27
-41.48
-5.40
4.87
20.48
0.96
-15.28
-6.80
8.15
-8.03
49.39
Number of obs
F( 11, 8050)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.339
0.000
0.000
0.000
0.000
0.000
=
=
=
=
=
=
8062
761.54
0.0000
0.5100
0.5093
.70381
[95% Conf. Interval]
.404528
.2856382
-.4255526
-.0565523
.1330028
.4376536
-.0728996
-.0123283
-.755168
.1378205
-.8430375
4.994345
.4327303
.3127465
-.387147
-.0264249
.3119302
.5303105
.2116255
-.0095254
-.4172667
.2251718
-.5122832
5.407205
70
Pooled specification (3) data 2000-2002 DW: 1.36
Source
SS
df
MS
Model
Residual
4385.70573
4315.76684
11
8599
398.700521
.501891713
Total
8701.47256
8610
1.01062399
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.388089
.3084307
-.4016384
-.0430428
.2584864
.4555997
.0719344
-.0111804
-.4640527
.200595
-.8168658
5.297633
Std. Err.
.0069115
.0066485
.0095918
.0073788
.0452296
.0227328
.0718069
.0007296
.0969306
.0232251
.0845891
.1037001
t
56.15
46.39
-41.87
-5.83
5.71
20.04
1.00
-15.33
-4.79
8.64
-9.66
51.09
Number of obs
F( 11, 8599)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.316
0.000
0.000
0.000
0.000
0.000
=
=
=
=
=
=
8611
794.40
0.0000
0.5040
0.5034
.70844
[95% Conf. Interval]
.3745409
.295398
-.4204406
-.0575071
.1698256
.4110379
-.0688244
-.0126105
-.6540599
.1550682
-.9826808
5.094356
.4016371
.3214634
-.3828362
-.0285786
.3471472
.5001615
.2126932
-.0097503
-.2740455
.2461219
-.6510508
5.50091
Pooled specification (3) data 2008-2010 DW: 1.23
. regress exp lngdpi lngdpj ldist linder adj com col mrdist mradj mrcom mrcol
Source
SS
df
MS
Model
Residual
3304.86334
3381.6096
11
7404
300.442122
.45672739
Total
6686.47294
7415
.901749553
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3391581
.2920221
-.3956919
-.0394147
.244147
.4252075
.1655213
-.0085946
-.0397054
.0740312
-.8368577
5.171969
Std. Err.
.0073757
.007282
.0097986
.007579
.0459092
.0236328
.0723404
.00096
.0971551
.0268108
.0941779
.1138593
t
45.98
40.10
-40.38
-5.20
5.32
17.99
2.29
-8.95
-0.41
2.76
-8.89
45.42
Number of obs
F( 11, 7404)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.022
0.000
0.683
0.006
0.000
0.000
=
=
=
=
=
=
7416
657.81
0.0000
0.4943
0.4935
.67582
[95% Conf. Interval]
.3246997
.2777472
-.4149
-.0542716
.1541518
.3788805
.0237136
-.0104765
-.230157
.0214744
-1.021473
4.948772
.3536166
.306297
-.3764838
-.0245578
.3341421
.4715346
.307329
-.0067127
.1507461
.126588
-.6522422
5.395165
Pooled specification (3) data 1998-1999 DW: 1.42
Source
SS
df
MS
Model
Residual
2754.89063
2758.63441
11
5433
250.444603
.507755276
Total
5513.52504
5444
1.01277095
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.4094653
.2976606
-.4000546
-.0375271
.2277573
.4845586
.0725392
-.0111601
-.54704
.1911791
-.6891415
5.209134
Std. Err.
.0088694
.0085142
.0120922
.0093501
.0563645
.0290817
.0898531
.0008973
.1075284
.0278626
.1023992
.1306141
t
46.17
34.96
-33.08
-4.01
4.04
16.66
0.81
-12.44
-5.09
6.86
-6.73
39.88
Number of obs
F( 11, 5433)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.420
0.000
0.000
0.000
0.000
0.000
=
=
=
=
=
=
5445
493.24
0.0000
0.4997
0.4986
.71257
[95% Conf. Interval]
.3920776
.2809694
-.4237602
-.055857
.1172602
.4275469
-.1036089
-.0129192
-.7578387
.1365573
-.8898849
4.953078
.426853
.3143518
-.3763489
-.0191973
.3382544
.5415704
.2486872
-.009401
-.3362414
.2458009
-.4883981
5.46519
71
Pool specification (3) 2001-2002 DW: 1.12
Source
SS
df
MS
Model
Residual
2879.38546
2847.21984
11
5730
261.762314
.496897006
Total
5726.6053
5741
.997492649
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3819625
.3062087
-.3942329
-.0437874
.2772136
.4538486
.0733203
-.0115584
-.3985386
.2086478
-.8184778
5.27673
Std. Err.
.0083968
.0081036
.0117005
.0090045
.0551424
.027701
.0875316
.0009361
.118043
.0293051
.1021305
.1268944
t
45.49
37.79
-33.69
-4.86
5.03
16.38
0.84
-12.35
-3.38
7.12
-8.01
41.58
Number of obs
F( 11, 5730)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.402
0.000
0.001
0.000
0.000
0.000
=
=
=
=
=
=
5742
526.79
0.0000
0.5028
0.5019
.70491
[95% Conf. Interval]
.3655017
.2903227
-.4171704
-.0614396
.1691137
.3995441
-.0982749
-.0133935
-.6299476
.1511988
-1.018692
5.027969
.3984234
.3220947
-.3712955
-.0261352
.3853136
.5081531
.2449154
-.0097233
-.1671297
.2660968
-.6182633
5.525491
Pool specification (3) 2009-2010 DW: 1.21
Source
SS
df
MS
Model
Residual
2045.31082
1928.02764
11
4582
185.937347
.420782985
Total
3973.33846
4593
.865085665
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3346874
.2958697
-.4036319
-.0415891
.2111286
.4000813
.2040309
-.009171
.0005722
.0902177
-.91172
5.247719
Std. Err.
.0089414
.0088003
.0119191
.0092404
.0554233
.0290601
.0876848
.0011202
.1169605
.0313782
.1204078
.1375174
t
37.43
33.62
-33.86
-4.50
3.81
13.77
2.33
-8.19
0.00
2.88
-7.57
38.16
Number of obs
F( 11, 4582)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.020
0.000
0.996
0.004
0.000
0.000
=
=
=
=
=
=
4594
441.88
0.0000
0.5148
0.5136
.64868
[95% Conf. Interval]
.3171579
.2786169
-.426999
-.0597048
.1024723
.3431096
.0321265
-.0113671
-.2287267
.0287012
-1.147777
4.978118
.3522168
.3131225
-.3802648
-.0234735
.3197849
.457053
.3759353
-.0069748
.2298712
.1517342
-.6756626
5.517319
Pool specification (3) 1997-1998 DW:0.99
Source
SS
df
MS
Model
Residual
2711.46082
2605.35945
11
5245
246.496438
.496732021
Total
5316.82027
5256
1.01157159
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.4265217
.2930657
-.4081103
-.0472717
.22616
.4869241
.071558
-.0106896
-.6117194
.1712157
-.6425818
5.199906
Std. Err.
.0089381
.0086174
.0121521
.0096753
.0564134
.0294039
.0893405
.0008922
.1043813
.0276194
.1047447
.1301278
t
47.72
34.01
-33.58
-4.89
4.01
16.56
0.80
-11.98
-5.86
6.20
-6.13
39.96
Number of obs
F( 11, 5245)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.423
0.000
0.000
0.000
0.000
0.000
=
=
=
=
=
=
5257
496.24
0.0000
0.5100
0.5090
.70479
[95% Conf. Interval]
.4089992
.2761719
-.4319334
-.0662393
.1155662
.4292801
-.1035865
-.0124387
-.8163501
.11707
-.8479251
4.944801
.4440442
.3099595
-.3842871
-.028304
.3367538
.544568
.2467025
-.0089404
-.4070886
.2253613
-.4372386
5.45501
72
Pool specification (3) 2001-2002 DW: 1.26
Source
SS
df
MS
Model
Residual
2921.05895
2923.51173
11
5729
265.550813
.510300528
Total
5844.57067
5740
1.01821789
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3915778
.3058425
-.4096732
-.0393854
.2380885
.4494508
.0799128
-.0108293
-.4965913
.1927087
-.7906557
5.368872
Std. Err.
.0085958
.0082395
.0118418
.0092175
.0558176
.0280666
.0886633
.0008688
.1204026
.0280575
.10648
.1274146
t
45.55
37.12
-34.60
-4.27
4.27
16.01
0.90
-12.47
-4.12
6.87
-7.43
42.14
Number of obs
F( 11, 5729)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.367
0.000
0.000
0.000
0.000
0.000
=
=
=
=
=
=
5741
520.38
0.0000
0.4998
0.4988
.71435
[95% Conf. Interval]
.3747269
.28969
-.4328877
-.0574552
.1286649
.3944296
-.0939009
-.0125324
-.7326259
.1377054
-.9993967
5.119091
.4084288
.3219949
-.3864588
-.0213156
.347512
.5044719
.2537265
-.0091262
-.2605567
.247712
-.5819147
5.618653
Pool specification (3) 2008-2009 DW: 1.24
Source
SS
df
MS
Model
Residual
2497.11922
2710.94425
11
5583
227.010838
.485571243
Total
5208.06347
5594
.931008843
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3447586
.2929928
-.3880298
-.0394144
.2682904
.4366488
.157946
-.0088366
-.0722167
.0825363
-.8238782
5.076191
Std. Err.
.0087836
.0087115
.0116583
.0090178
.055245
.0276429
.0869654
.0011862
.1177748
.0332365
.1112795
.1360994
t
39.25
33.63
-33.28
-4.37
4.86
15.80
1.82
-7.45
-0.61
2.48
-7.40
37.30
Number of obs
F( 11, 5583)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.069
0.000
0.540
0.013
0.000
0.000
=
=
=
=
=
=
5595
467.51
0.0000
0.4795
0.4784
.69683
[95% Conf. Interval]
.3275394
.2759149
-.4108846
-.0570928
.1599887
.382458
-.01254
-.011162
-.3031012
.0173799
-1.042029
4.809383
.3619779
.3100707
-.3651751
-.021736
.376592
.4908395
.3284319
-.0065111
.1586678
.1476927
-.605727
5.342999
Pool specification (3) 1995-1997 DW: 1.11
. regress exp lngdpi lngdpj ldist linder adj com col mrdist mradj mrcom mrcol
Source
SS
df
MS
Model
Residual
3797.7687
3378.06784
11
7619
345.2517
.443374175
Total
7175.83654
7630
.94047661
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.4140764
.2904971
-.4056605
-.0458762
.2296989
.4831579
.0539407
-.0100689
-.5337838
.1351914
-.5933404
5.252133
Std. Err.
.0068717
.0066573
.0094653
.0075879
.0440385
.022915
.0695276
.0006068
.0758121
.0194451
.0922638
.1008177
t
60.26
43.64
-42.86
-6.05
5.22
21.08
0.78
-16.59
-7.04
6.95
-6.43
52.10
Number of obs
F( 11, 7619)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.438
0.000
0.000
0.000
0.000
0.000
=
=
=
=
=
=
7631
778.69
0.0000
0.5292
0.5286
.66586
[95% Conf. Interval]
.4006061
.2774469
-.4242152
-.0607507
.1433712
.4382382
-.0823526
-.0112583
-.6823964
.0970736
-.774203
5.054502
.4275467
.3035473
-.3871059
-.0310018
.3160265
.5280775
.190234
-.0088794
-.3851712
.1733091
-.4124779
5.449763
73
Pool specification (3) 2002-2004 DW: 1.15
Source
SS
df
MS
Model
Residual
4413.67693
4297.36768
11
8576
401.243357
.501092314
Total
8711.04462
8587
1.01444563
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3729252
.3080725
-.3723479
-.0518124
.3231407
.5001791
.0796732
-.0110536
-.2812311
.1719508
-.8078387
5.00159
Std. Err.
.0067074
.006551
.0096068
.0073232
.0452947
.0228392
.0719961
.0008164
.09328
.0247087
.0783871
.1054052
t
55.60
47.03
-38.76
-7.08
7.13
21.90
1.11
-13.54
-3.01
6.96
-10.31
47.45
Number of obs
F( 11, 8576)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.268
0.000
0.003
0.000
0.000
0.000
=
=
=
=
=
=
8588
800.74
0.0000
0.5067
0.5060
.70788
[95% Conf. Interval]
.359777
.295231
-.3911795
-.0661676
.2343522
.4554088
-.0614565
-.0126539
-.4640823
.1235158
-.9614962
4.794971
.3860733
.3209141
-.3535162
-.0374571
.4119293
.5449495
.2208029
-.0094533
-.0983798
.2203858
-.6541811
5.20821
Pool specification (3) 2006-2007 DW: 1.26
Source
SS
df
MS
Model
Residual
2808.41167
2994.16721
11
5692
255.310152
.526030782
Total
5802.57888
5703
1.01746079
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3685603
.3036455
-.3804063
-.0374076
.3400546
.4603515
.0808935
-.0080502
-.2278828
.0737922
-.7930277
4.890796
Std. Err.
.0088501
.0087678
.0120212
.00929
.0572153
.0287221
.0900579
.0012763
.1230251
.0361867
.0969588
.1368467
t
41.64
34.63
-31.64
-4.03
5.94
16.03
0.90
-6.31
-1.85
2.04
-8.18
35.74
Number of obs
F( 11, 5692)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.369
0.000
0.064
0.041
0.000
0.000
=
=
=
=
=
=
5704
485.35
0.0000
0.4840
0.4830
.72528
[95% Conf. Interval]
.3512107
.2864572
-.4039724
-.0556195
.2278909
.4040452
-.0956544
-.0105523
-.4690588
.0028524
-.9831039
4.622524
.3859098
.3208337
-.3568402
-.0191957
.4522183
.5166578
.2574413
-.0055482
.0132933
.144732
-.6029514
5.159067
Pool specification (3) 1996-1997 DW: 1.18
Source
SS
df
MS
Model
Residual
2676.69164
2367.40609
11
5157
243.335603
.459066529
Total
5044.09773
5168
.976025102
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.4260439
.2972164
-.4163913
-.0473507
.2197545
.4858439
.0535687
-.0104185
-.6025148
.1523978
-.6203105
5.237448
Std. Err.
.0085618
.008301
.0117342
.0093153
.0545651
.028359
.0862146
.0007993
.0966644
.0251696
.1110951
.1251648
t
49.76
35.80
-35.49
-5.08
4.03
17.13
0.62
-13.04
-6.23
6.05
-5.58
41.84
Number of obs
F( 11, 5157)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.534
0.000
0.000
0.000
0.000
0.000
=
=
=
=
=
=
5169
530.07
0.0000
0.5307
0.5297
.67754
[95% Conf. Interval]
.4092592
.2809429
-.4393952
-.0656126
.1127836
.4302482
-.1154485
-.0119854
-.7920181
.1030547
-.8381041
4.992072
.4428287
.3134899
-.3933873
-.0290887
.3267253
.5414395
.2225859
-.0088517
-.4130115
.2017409
-.4025169
5.482824
74
Pool specification (3) 1999-2000 DW: 1.27
Source
SS
df
MS
Model
Residual
2951.13071
2844.99293
11
5662
268.28461
.502471377
Total
5796.12365
5673
1.02170345
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.4027301
.3126541
-.4100843
-.0366457
.2184421
.4679238
.0668984
-.0110652
-.5653255
.1970438
-.7814033
5.267344
Std. Err.
.0085932
.0082209
.0117824
.0090309
.0554166
.0281127
.088395
.0008365
.1139463
.0269305
.1036101
.1270657
t
46.87
38.03
-34.80
-4.06
3.94
16.64
0.76
-13.23
-4.96
7.32
-7.54
41.45
Number of obs
F( 11, 5662)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.449
0.000
0.000
0.000
0.000
0.000
=
=
=
=
=
=
5674
533.93
0.0000
0.5092
0.5082
.70885
[95% Conf. Interval]
.3858842
.2965379
-.4331823
-.0543498
.1098043
.4128122
-.1063896
-.0127051
-.788704
.1442498
-.9845187
5.018247
.419576
.3287702
-.3869862
-.0189416
.3270799
.5230353
.2401865
-.0094252
-.3419471
.2498378
-.5782878
5.516441
Number of obs
F( 11, 14257)
Prob > F
R-squared
Adj R-squared
Root MSE
=
14269
= 1278.76
= 0.0000
= 0.4966
= 0.4962
= .71515
Pool specification (3) 2003-2007 DW: 1.31
Source
SS
df
MS
Model
Residual
7194.08756
11
7291.60145 14257
654.00796
.511440096
Total
14485.689 14268
1.01525715
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3614443
.2959721
-.3767851
-.0434725
.335923
.4849853
.0919899
-.0088039
-.2029376
.0984907
-.7598983
5.021494
Std. Err.
.0052754
.00519
.0074991
.0057347
.0355475
.0179291
.056369
.0007042
.0741062
.0206377
.060303
.0831614
t
68.52
57.03
-50.24
-7.58
9.45
27.05
1.63
-12.50
-2.74
4.77
-12.60
60.38
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.103
0.000
0.006
0.000
0.000
0.000
[95% Conf. Interval]
.3511038
.2857989
-.3914843
-.0547133
.2662453
.4498419
-.0185007
-.0101843
-.3481954
.0580382
-.8781001
4.858487
.3717847
.3061452
-.362086
-.0322317
.4056007
.5201288
.2024805
-.0074235
-.0576797
.1389433
-.6416965
5.184502
Number of obs
F( 11, 17079)
Prob > F
R-squared
Adj R-squared
Root MSE
=
17091
= 1482.30
= 0.0000
= 0.4884
= 0.4881
= .71813
Pool specification (3) 2003-2008 DW: 1.24
Source
SS
df
MS
Model
Residual
8408.78736
11
8807.79938 17079
764.435215
.515709314
Total
17216.5867 17090
1.00740706
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3499903
.2850615
-.3792743
-.0426492
.3274188
.478769
.0952728
-.007871
-.1714424
.0740713
-.7208969
5.129133
Std. Err.
.0048242
.0047529
.0068799
.0052681
.0326244
.0164291
.0516302
.0006547
.0680577
.0190579
.0561373
.0763548
t
72.55
59.98
-55.13
-8.10
10.04
29.14
1.85
-12.02
-2.52
3.89
-12.84
67.18
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.065
0.000
0.012
0.000
0.000
0.000
[95% Conf. Interval]
.3405345
.2757452
-.3927597
-.0529752
.2634716
.4465662
-.0059276
-.0091542
-.3048425
.0367159
-.8309318
4.979469
.3594462
.2943777
-.365789
-.0323232
.3913659
.5109718
.1964732
-.0065877
-.0380422
.1114267
-.6108619
5.278796
75
Pool specification (3) 1997-1999 DW: 1.33
Source
SS
df
MS
Model
Residual
4149.54576
3987.59457
11
8050
377.231432
.495353363
Total
8137.14032
8061
1.00944552
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.4186292
.2991923
-.4063498
-.0414886
.2224665
.4839821
.0693629
-.0109269
-.5862173
.1814962
-.6776603
5.200775
Std. Err.
.0071935
.0069145
.009796
.0076845
.0456387
.0236338
.0725734
.0007149
.0861879
.0222806
.084365
.1053074
t
58.20
43.27
-41.48
-5.40
4.87
20.48
0.96
-15.28
-6.80
8.15
-8.03
49.39
Number of obs
F( 11, 8050)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.339
0.000
0.000
0.000
0.000
0.000
=
=
=
=
=
=
8062
761.54
0.0000
0.5100
0.5093
.70381
[95% Conf. Interval]
.404528
.2856382
-.4255526
-.0565523
.1330028
.4376536
-.0728996
-.0123283
-.755168
.1378205
-.8430375
4.994345
.4327303
.3127465
-.387147
-.0264249
.3119302
.5303105
.2116255
-.0095254
-.4172667
.2251718
-.5122832
5.407205
Pool specification (3) 2000-2002 DW: 1.41
Source
SS
df
MS
Model
Residual
4385.70573
4315.76684
11
8599
398.700521
.501891713
Total
8701.47256
8610
1.01062399
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.388089
.3084307
-.4016384
-.0430428
.2584864
.4555997
.0719344
-.0111804
-.4640527
.200595
-.8168658
5.297633
Std. Err.
.0069115
.0066485
.0095918
.0073788
.0452296
.0227328
.0718069
.0007296
.0969306
.0232251
.0845891
.1037001
t
56.15
46.39
-41.87
-5.83
5.71
20.04
1.00
-15.33
-4.79
8.64
-9.66
51.09
Number of obs
F( 11, 8599)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.316
0.000
0.000
0.000
0.000
0.000
=
=
=
=
=
=
8611
794.40
0.0000
0.5040
0.5034
.70844
[95% Conf. Interval]
.3745409
.295398
-.4204406
-.0575071
.1698256
.4110379
-.0688244
-.0126105
-.6540599
.1550682
-.9826808
5.094356
.4016371
.3214634
-.3828362
-.0285786
.3471472
.5001615
.2126932
-.0097503
-.2740455
.2461219
-.6510508
5.50091
Pool specification (3) 2000-2002 DW: 1.41
Source
SS
df
MS
Model
Residual
3304.86334
3381.6096
11
7404
300.442122
.45672739
Total
6686.47294
7415
.901749553
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
_cons
.3391581
.2920221
-.3956919
-.0394147
.244147
.4252075
.1655213
-.0085946
-.0397054
.0740312
-.8368577
5.171969
Std. Err.
.0073757
.007282
.0097986
.007579
.0459092
.0236328
.0723404
.00096
.0971551
.0268108
.0941779
.1138593
t
45.98
40.10
-40.38
-5.20
5.32
17.99
2.29
-8.95
-0.41
2.76
-8.89
45.42
Number of obs
F( 11,
7404)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
0.000
0.000
0.000
0.000
0.000
0.000
0.022
0.000
0.683
0.006
0.000
0.000
=
=
=
=
=
=
7416
657.81
0.0000
0.4943
0.4935
.67582
[95% Conf. Interval]
.3246997
.2777472
-.4149
-.0542716
.1541518
.3788805
.0237136
-.0104765
-.230157
.0214744
-1.021473
4.948772
.3536166
.306297
-.3764838
-.0245578
.3341421
.4715346
.307329
-.0067127
.1507461
.126588
-.6522422
5.395165
76
Pooled specification (6) data 1997-1999
77
Source
SS
df
MS
Model
Residual
5519.64511
2617.49522
67
7994
82.3827628
.327432477
Total
8137.14032
8061
1.00944552
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
-.2058365
.2790353
-.4633351
-.0102846
.1530759
.4749805
.0744743
-.0103451
-.3229089
.2052493
-.4436933
(omitted)
(omitted)
(omitted)
.0048827
-.0049207
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
1.81757
2.500014
2.90716
2.504517
3.309794
2.452397
3.374223
1.51402
1.965739
1.566276
1.656058
2.08798
1.403393
2.02985
1.851228
1.802801
.8335691
-.5820368
1.48126
1.312469
1.175264
2.025043
1.518197
1.344725
1.292939
1.737333
2.242602
1.347174
.8605109
(omitted)
1.542081
.8556475
.4592363
-.734998
-.9214239
.3711037
.3335681
.6452608
.074151
.387545
-.1374342
.2163508
-.665109
1.938033
2.212092
1.628768
2.555684
1.834168
.9580012
.9849319
1.977406
1.923439
.7411561
1.114282
2.499874
7.589836
Std. Err.
t
Number of obs
F( 67,
7994)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
8062
251.60
0.0000
0.6783
0.6756
.57222
[95% Conf. Interval]
.0809934
.0066497
.0089956
.0064521
.0382452
.0205414
.0592913
.0007963
.0978612
.0252957
.0967508
-2.54
41.96
-51.51
-1.59
4.00
23.12
1.26
-12.99
-3.30
8.11
-4.59
0.011
0.000
0.000
0.111
0.000
0.000
0.209
0.000
0.001
0.000
0.000
-.3646047
.2660002
-.4809688
-.0229324
.0781053
.4347141
-.0417522
-.0119061
-.5147425
.1556632
-.6333501
-.0470683
.2920704
-.4457013
.0023633
.2280465
.515247
.1907008
-.008784
-.1310754
.2548355
-.2540366
.0160427
.0157639
0.30
-0.31
0.761
0.755
-.0265651
-.035822
.0363306
.0259806
.2840521
.3490762
.3817603
.3340667
.4347051
.3516314
.4962859
.1975841
.2219698
.1825846
.1599748
.2473472
.1749672
.2124545
.2162669
.2487064
.1640825
.1025164
.1333119
.1069374
.1562287
.2787335
.1749003
.2131584
.1491854
.2226329
.2962074
.124652
.145801
6.40
7.16
7.62
7.50
7.61
6.97
6.80
7.66
8.86
8.58
10.35
8.44
8.02
9.55
8.56
7.25
5.08
-5.68
11.11
12.27
7.52
7.27
8.68
6.31
8.67
7.80
7.57
10.81
5.90
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
1.260754
1.815734
2.15881
1.84966
2.457658
1.763108
2.401373
1.126704
1.530621
1.208363
1.342466
1.603115
1.060412
1.613384
1.427288
1.315271
.5119247
-.7829956
1.219933
1.102844
.8690149
1.478653
1.175346
.9268793
1.000496
1.300915
1.661958
1.102823
.5747029
2.374387
3.184295
3.65551
3.159375
4.161929
3.141687
4.347073
1.901336
2.400858
1.92419
1.969651
2.572845
1.746375
2.446316
2.275167
2.29033
1.155213
-.381078
1.742586
1.522094
1.481513
2.571434
1.861047
1.762571
1.585381
2.173752
2.823245
1.591524
1.146319
.2656189
.1020781
.1364137
.1018778
.1052969
.0664682
.0990638
.0909912
.1297468
.0808153
.0666175
.144499
.0728331
.1755231
.1806524
.2539961
.2554618
.1298851
.1214008
.1219661
.13446
.1596894
.0939544
.1794481
.3205898
.268541
5.81
8.38
3.37
-7.21
-8.75
5.58
3.37
7.09
0.57
4.80
-2.06
1.50
-9.13
11.04
12.25
6.41
10.00
14.12
7.89
8.08
14.71
12.04
7.89
6.21
7.80
28.26
0.000
0.000
0.001
0.000
0.000
0.000
0.001
0.000
0.568
0.000
0.039
0.134
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
1.021398
.6555477
.1918299
-.9347051
-1.127833
.2408087
.1393772
.4668943
-.1801866
.2291259
-.2680219
-.0669049
-.807881
1.593962
1.857966
1.130869
2.054912
1.57956
.7200241
.7458465
1.71383
1.610406
.5569809
.762517
1.871435
7.063426
2.062763
1.055747
.7266427
-.535291
-.7150145
.5013988
.527759
.8236272
.3284885
.545964
-.0068464
.4996065
-.522337
2.282104
2.566218
2.126666
3.056456
2.088777
1.195978
1.224017
2.240983
2.236472
.9253312
1.466047
3.128314
8.116246
Pooled specification (6) data 2000-2002
78
Source
SS
df
MS
Model
Residual
5875.1512
2826.32136
67
8543
87.688824
.33083476
Total
8701.47256
8610
1.01062399
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
-.1390997
.2990806
-.4658887
-.016722
.1389278
.4451444
.1073771
-.0112784
-.4186119
.2481037
-.7020479
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
.0119421
.007073
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
1.503901
2.204605
2.590174
2.205137
2.930547
2.235642
3.095216
1.411686
1.833066
1.404589
1.562201
1.92334
1.239638
1.812212
1.65333
1.702491
.731484
-.4947438
1.418144
1.227665
1.058371
1.778058
1.418787
1.218404
1.162856
1.584296
2.049284
1.329632
.670375
(omitted)
1.300094
.7852125
.3912643
-.4755292
-.5864723
.2996262
.2971035
.652541
-.0430051
.3662177
-.1169049
.2867491
-.6108985
1.826084
2.032567
1.527941
2.317177
1.749128
.9087793
.9340273
1.831628
1.862121
.8341963
.9806963
2.462481
7.33262
Std. Err.
t
Number of obs
F( 67,
8543)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
8611
265.05
0.0000
0.6752
0.6726
.57518
[95% Conf. Interval]
.064535
.0064131
.0088111
.0061584
.0378147
.0197123
.0585549
.0008105
.1129286
.0259225
.096777
-2.16
46.64
-52.88
-2.72
3.67
22.58
1.83
-13.92
-3.71
9.57
-7.25
0.031
0.000
0.000
0.007
0.000
0.000
0.067
0.000
0.000
0.000
0.000
-.265604
.2865094
-.4831606
-.0287939
.0648019
.4065035
-.0074047
-.0128672
-.6399793
.1972893
-.8917543
-.0125954
.3116518
-.4486168
-.0046501
.2130537
.4837853
.2221588
-.0096897
-.1972446
.2989182
-.5123415
.0151981
.0152284
0.79
0.46
0.432
0.642
-.0178499
-.0227783
.0417342
.0369243
.2391397
.2794559
.3022561
.2676435
.3524199
.2896732
.4111928
.1595504
.1713949
.149226
.1344081
.2035951
.153303
.1718805
.1763472
.2025629
.1378498
.0872207
.1250672
.0906339
.1324552
.2297967
.1311529
.1687353
.131351
.1598516
.2231723
.1020907
.1199384
6.29
7.89
8.57
8.24
8.32
7.72
7.53
8.85
10.69
9.41
11.62
9.45
8.09
10.54
9.38
8.40
5.31
-5.67
11.34
13.55
7.99
7.74
10.82
7.22
8.85
9.91
9.18
13.02
5.59
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
1.03513
1.656804
1.997679
1.680491
2.239719
1.667813
2.289179
1.098928
1.49709
1.11207
1.298728
1.524244
.9391271
1.475284
1.307647
1.305418
.4612651
-.6657174
1.172982
1.050001
.7987265
1.327601
1.161696
.8876417
.9053761
1.270948
1.611813
1.12951
.4352667
1.972673
2.752406
3.182669
2.729783
3.621375
2.803471
3.901253
1.724443
2.169041
1.697108
1.825673
2.322435
1.540149
2.149139
1.999013
2.099563
1.001703
-.3237702
1.663306
1.405329
1.318015
2.228515
1.675879
1.549166
1.420335
1.897644
2.486756
1.529755
.9054833
.236305
.0900493
.1263613
.0892727
.103119
.0645194
.0940087
.0961124
.1174119
.0764663
.0657881
.1259171
.0773526
.1521002
.1496863
.2152707
.220381
.1184849
.1042651
.1052775
.1159164
.1316464
.0910485
.1564769
.276407
.2191934
5.50
8.72
3.10
-5.33
-5.69
4.64
3.16
6.79
-0.37
4.79
-1.78
2.28
-7.90
12.01
13.58
7.10
10.51
14.76
8.72
8.87
15.80
14.14
9.16
6.27
8.91
33.45
0.000
0.000
0.002
0.000
0.000
0.000
0.002
0.000
0.714
0.000
0.076
0.023
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.8368791
.6086941
.1435657
-.6505252
-.7886104
.1731525
.1128237
.4641374
-.2731608
.2163252
-.2458654
.0399213
-.7625282
1.527931
1.739146
1.105959
1.885177
1.516869
.7043945
.7276579
1.604403
1.604062
.6557192
.6739638
1.920656
6.902948
1.763309
.9617309
.6389629
-.3005332
-.3843342
.4260999
.4813832
.8409446
.1871506
.5161102
.0120557
.533577
-.4592687
2.124237
2.325988
1.949924
2.749177
1.981387
1.113164
1.140397
2.058852
2.12018
1.012673
1.287429
3.004305
7.762292
Pooled specification (6) data 2008-2010
79
Source
SS
df
MS
Model
Residual
4413.68799
2272.78495
66
7349
66.8740604
.309264519
Total
6686.47294
7415
.901749553
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.0323938
.3032559
-.4385292
-.0256778
.1419916
.4410771
.1863676
-.0121091
-.1417577
.223981
-.7448279
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
.0331475
-.0102766
(omitted)
-.9850742
-.5103617
-.1507017
-.4826608
-.0779477
-.551392
(omitted)
-.8662921
-.5253668
-.925535
-.8078199
-.445397
-1.038988
-.5899988
-.7088238
-.9078738
-1.663356
-2.357724
-1.009071
-.9438479
-1.261471
-.8073206
-.8693958
-.969879
-1.206865
-.6451199
-.377561
-.7740649
-1.386321
-1.754629
-1.048529
-1.228545
-2.579913
-1.993473
-1.875992
-1.528463
-1.709248
-1.366322
-1.680911
-1.591391
-1.967753
(omitted)
-2.617464
-.5973452
-.2965686
-.7329661
-.0977346
-.5059163
-1.338939
-1.388647
-.3490824
-.2685051
-1.125814
-1.066466
.2795208
8.286377
Std. Err.
t
Number of obs
F( 66, 7349)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
7416
216.24
0.0000
0.6601
0.6570
.55612
[95% Conf. Interval]
.1030929
.0071455
.0091317
.0064517
.0388484
.0206968
.0598074
.001121
.1158787
.0334951
.1123846
0.31
42.44
-48.02
-3.98
3.66
21.31
3.12
-10.80
-1.22
6.69
-6.63
0.753
0.000
0.000
0.000
0.000
0.000
0.002
0.000
0.221
0.000
0.000
-.1696979
.2892486
-.4564299
-.0383251
.0658375
.4005055
.0691279
-.0143066
-.3689132
.158321
-.9651339
.2344855
.3172632
-.4206284
-.0130306
.2181457
.4816487
.3036073
-.0099116
.0853979
.2896411
-.5245218
.0177861
.0202344
1.86
-0.51
0.062
0.612
-.0017183
-.0499419
.0680134
.0293887
.2496464
.1918673
.1693885
.2141617
.1491734
.2106368
-3.95
-2.66
-0.89
-2.25
-0.52
-2.62
0.000
0.008
0.374
0.024
0.601
0.009
-1.474453
-.8864766
-.4827517
-.9024791
-.3703703
-.9643004
-.4956956
-.1342467
.1813484
-.0628425
.2144749
-.1384835
.3781531
.360044
.4010356
.4260658
.3052163
.3757606
.3674986
.3549668
.279344
.3990174
.7208794
.4344952
.4921238
.430441
.2460598
.4136638
.3241307
.4479488
.4003448
.2314141
.4661526
.425904
.5815949
.2875737
.4878949
.4014237
.6948575
.7027388
.6354324
.4743505
.4511491
.4543963
.5243599
.6003729
-2.29
-1.46
-2.31
-1.90
-1.46
-2.77
-1.61
-2.00
-3.25
-4.17
-3.27
-2.32
-1.92
-2.93
-3.28
-2.10
-2.99
-2.69
-1.61
-1.63
-1.66
-3.26
-3.02
-3.65
-2.52
-6.43
-2.87
-2.67
-2.41
-3.60
-3.03
-3.70
-3.03
-3.28
0.022
0.145
0.021
0.058
0.145
0.006
0.108
0.046
0.001
0.000
0.001
0.020
0.055
0.003
0.001
0.036
0.003
0.007
0.107
0.103
0.097
0.001
0.003
0.000
0.012
0.000
0.004
0.008
0.016
0.000
0.002
0.000
0.002
0.001
-1.607581
-1.231156
-1.71168
-1.643031
-1.043709
-1.775587
-1.310401
-1.404661
-1.455468
-2.445545
-3.770855
-1.860807
-1.908552
-2.105259
-1.289668
-1.680295
-1.605268
-2.084973
-1.42991
-.8311989
-1.687858
-2.221215
-2.894722
-1.612256
-2.184958
-3.366818
-3.355593
-3.253561
-2.774092
-2.639111
-2.250703
-2.571658
-2.619286
-3.144656
-.1250036
.1804227
-.1393901
.0273912
.1529145
-.3023894
.1304039
-.012987
-.3602794
-.8811676
-.9445936
-.1573363
.0208559
-.4176832
-.3249728
-.0584962
-.3344898
-.3287572
.1396707
.0760769
.1397279
-.5514276
-.6145362
-.4848023
-.2721306
-1.793007
-.631353
-.4984221
-.2828329
-.7793848
-.48194
-.7901637
-.563495
-.79085
.4855471
.3419915
.4412909
.2641314
.300704
.4400306
.4665775
.4674326
.4545679
.4130324
.4859474
.3606305
.1386243
.9965493
-5.39
-1.75
-0.67
-2.78
-0.33
-1.15
-2.87
-2.97
-0.77
-0.65
-2.32
-2.96
2.02
8.32
0.000
0.081
0.502
0.006
0.745
0.250
0.004
0.003
0.443
0.516
0.021
0.003
0.044
0.000
-3.569276
-1.267747
-1.161625
-1.250739
-.6872007
-1.368503
-2.253564
-2.304949
-1.240166
-1.078167
-2.078411
-1.773406
.0077774
6.332855
-1.665653
.0730562
.5684882
-.2151928
.4917315
.3566699
-.4243131
-.4723448
.5420012
.5411568
-.1732179
-.3595269
.5512641
10.2399
Pooled specification (6) data 1998-1999
80
Source
SS
df
MS
Model
Residual
3727.98043
1785.54462
66
5378
56.4845519
.33200904
Total
5513.52504
5444
1.01277095
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
-.189567
.2790151
-.462303
-.0087573
.1501845
.4768827
.0730694
-.0110939
-.2878658
.2301634
-.4577882
(omitted)
(omitted)
(omitted)
.0099516
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
1.736046
2.433525
2.835926
2.438435
3.261973
2.37355
3.265928
1.49107
1.931481
1.533797
1.636495
2.010063
1.369363
1.985723
1.813175
1.764997
.8136842
-.5774437
1.493228
1.291883
1.152903
1.972396
1.491906
1.319435
1.267396
1.692621
2.177875
1.330742
.8135024
(omitted)
1.455403
.8149965
.4479688
-.6699984
-.9137503
.36315
.2453697
.6250844
.0526975
.4207552
-.1016597
.1718658
-.5374917
1.922591
2.178557
1.576723
2.531193
1.826853
.9477693
.9795052
1.950425
1.915767
.7790474
1.08666
2.473357
7.524957
Std. Err.
t
Number of obs
F( 66,
5378)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
5445
170.13
0.0000
0.6762
0.6722
.5762
[95% Conf. Interval]
.1399807
.0081459
.0110514
.0077982
.046975
.0251119
.0730017
.0009936
.1217057
.0314618
.1168276
-1.35
34.25
-41.83
-1.12
3.20
18.99
1.00
-11.17
-2.37
7.32
-3.92
0.176
0.000
0.000
0.261
0.001
0.000
0.317
0.000
0.018
0.000
0.000
-.4639858
.2630458
-.4839682
-.0240448
.0580946
.4276532
-.0700435
-.0130418
-.5264583
.1684855
-.6868176
.0848518
.2949844
-.4406379
.0065303
.2422745
.5261121
.2161824
-.0091461
-.0492733
.2918414
-.2287588
.0159924
0.62
0.534
-.0214
.0413032
.4927962
.6073297
.6617469
.5806942
.7519805
.6119446
.8630998
.341216
.3693591
.3143735
.2753645
.4306901
.2989632
.3673501
.3744068
.4273923
.2811761
.1445506
.2296633
.1671967
.2693551
.4863083
.2825315
.3686608
.2536555
.3844107
.5032188
.204457
.2431397
3.52
4.01
4.29
4.20
4.34
3.88
3.78
4.37
5.23
4.88
5.94
4.67
4.58
5.41
4.84
4.13
2.89
-3.99
6.50
7.73
4.28
4.06
5.28
3.58
5.00
4.40
4.33
6.51
3.35
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.004
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.001
.7699659
1.242913
1.538634
1.300039
1.787787
1.173891
1.573903
.8221487
1.207387
.9174978
1.096669
1.165736
.7832738
1.265568
1.079186
.9271345
.2624652
-.8608214
1.042995
.9641092
.6248577
1.019035
.9380297
.5967106
.7701287
.9390201
1.191362
.9299232
.3368501
2.702126
3.624138
4.133218
3.57683
4.73616
3.573209
4.957954
2.159992
2.655574
2.150097
2.176321
2.85439
1.955452
2.705878
2.547164
2.602859
1.364903
-.294066
1.943461
1.619656
1.680948
2.925757
2.045782
2.04216
1.764664
2.446222
3.164388
1.73156
1.290155
.4656765
.1614869
.2334613
.1462068
.1595072
.0857845
.1532835
.1247035
.222917
.1269159
.0834234
.2421829
.0968699
.273153
.3072497
.4418204
.4304044
.20574
.2003138
.1961762
.2192265
.2612571
.1499579
.3113395
.5610962
.4378971
3.13
5.05
1.92
-4.58
-5.73
4.23
1.60
5.01
0.24
3.32
-1.22
0.71
-5.55
7.04
7.09
3.57
5.88
8.88
4.73
4.99
8.90
7.33
5.20
3.49
4.41
17.18
0.002
0.000
0.055
0.000
0.000
0.000
0.109
0.000
0.813
0.001
0.223
0.478
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.5424887
.4984168
-.00971
-.9566228
-1.226449
.1949777
-.0551281
.380615
-.3843101
.1719485
-.2652034
-.3029107
-.7273959
1.3871
1.576223
.7105761
1.687426
1.423519
.555073
.5949204
1.520652
1.403598
.4850691
.4763088
1.373381
6.666502
2.368318
1.131576
.9056475
-.3833739
-.6010516
.5313224
.5458675
.8695539
.4897051
.6695618
.0618841
.6466423
-.3475874
2.458081
2.780891
2.44287
3.37496
2.230186
1.340466
1.36409
2.380198
2.427937
1.073026
1.697012
3.573333
8.383413
Pooled specification (6) data 2001 2002
81
Source
SS
df
MS
Model
Residual
3857.17711
1869.42819
66
5675
58.4420774
.329414659
Total
5726.6053
5741
.997492649
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
-.1370273
.2977473
-.4626254
-.0197489
.1453981
.4380644
.1123316
-.0117671
-.3936434
.26367
-.7247839
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
.0049182
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
1.460949
2.17459
2.562657
2.177816
2.856721
2.207191
3.045556
1.388288
1.806977
1.379001
1.509156
1.891718
1.210038
1.754023
1.631979
1.683205
.6901581
-.493405
1.38165
1.203864
1.040649
1.746011
1.395515
1.213788
1.10156
1.565928
2.030135
1.293083
.6475655
(omitted)
1.260896
.7466
.4193809
-.5044107
-.5611202
.2792966
.2384953
.6186258
-.0458155
.3726691
-.1170246
.2493037
-.6586768
1.784232
1.978774
1.516008
2.265169
1.712282
.881468
.9145865
1.784449
1.83026
.8399927
.9592068
2.459063
7.335337
Std. Err.
t
Number of obs
F( 66,
5675)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
5742
177.41
0.0000
0.6736
0.6698
.57395
[95% Conf. Interval]
.0850998
.0078387
.0107787
.0075287
.0462375
.0240912
.0715818
.0010471
.1382884
.033113
.1172462
-1.61
37.98
-42.92
-2.62
3.14
18.18
1.57
-11.24
-2.85
7.96
-6.18
0.107
0.000
0.000
0.009
0.002
0.000
0.117
0.000
0.004
0.000
0.000
-.3038553
.2823805
-.4837557
-.0345081
.054755
.3908365
-.0279962
-.0138199
-.6647415
.198756
-.9546313
.0298008
.3131142
-.4414951
-.0049897
.2360413
.4852923
.2526593
-.0097143
-.1225453
.3285841
-.4949365
.015329
0.32
0.748
-.0251326
.034969
.3042996
.3591596
.3885824
.3439182
.4500834
.3717319
.5325862
.1998926
.2157411
.1864566
.1673167
.2596203
.1926723
.2144899
.2229938
.2560449
.1725157
.1176001
.1572755
.1094756
.164968
.2949475
.1578539
.2053525
.1602411
.1854801
.2778551
.1209732
.1462065
4.80
6.05
6.59
6.33
6.35
5.94
5.72
6.95
8.38
7.40
9.02
7.29
6.28
8.18
7.32
6.57
4.00
-4.20
8.78
11.00
6.31
5.92
8.84
5.91
6.87
8.44
7.31
10.69
4.43
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.864405
1.4705
1.800887
1.503605
1.974386
1.478454
2.001483
.996422
1.384042
1.013475
1.181151
1.382763
.8323267
1.333541
1.194826
1.181259
.3519614
-.7239462
1.07333
.9892498
.7172487
1.167801
1.086061
.8112187
.7874264
1.202316
1.485433
1.055929
.360945
2.057492
2.87868
3.324427
2.852027
3.739057
2.935928
4.089628
1.780154
2.229912
1.744527
1.83716
2.400673
1.58775
2.174505
2.069132
2.185151
1.028355
-.2628638
1.689971
1.418478
1.364049
2.32422
1.704969
1.616358
1.415694
1.92954
2.574837
1.530237
.9341861
.302081
.1082751
.1528616
.1208801
.1443471
.0829245
.1127918
.1170685
.141381
.0912571
.0801438
.1590175
.0912898
.1909507
.1853626
.2740725
.2799192
.1454652
.1255525
.1267806
.1399757
.1617878
.1134654
.1982386
.3579503
.2945757
4.17
6.90
2.74
-4.17
-3.89
3.37
2.11
5.28
-0.32
4.08
-1.46
1.57
-7.22
9.34
10.68
5.53
8.09
11.77
7.02
7.21
12.75
11.31
7.40
4.84
6.87
24.90
0.000
0.000
0.006
0.000
0.000
0.001
0.035
0.000
0.746
0.000
0.144
0.117
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.6687016
.5343393
.1197138
-.7413819
-.8440958
.1167328
.0173803
.3891268
-.3229764
.1937704
-.2741371
-.0624314
-.8376397
1.409896
1.615392
.9787208
1.716421
1.427115
.6353372
.6660481
1.510043
1.513094
.6175571
.5705834
1.757344
6.757856
1.85309
.9588606
.7190479
-.2674395
-.2781447
.4418604
.4596104
.8481247
.2313453
.5515679
.0400879
.5610388
-.479714
2.158569
2.342155
2.053295
2.813918
1.997449
1.127599
1.163125
2.058855
2.147426
1.062428
1.34783
3.160782
7.912818
Pooled specification (6) data 2009-2010
82
Source
SS
df
MS
Model
Residual
2648.40014
1324.93832
64
4529
41.3812521
.292545445
Total
3973.33846
4593
.865085665
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
-.0125902
.3105711
-.4349978
-.0255505
.1354487
.4287474
.2071439
-.0128344
-.1564084
.2410273
-.8358419
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.0171059
(omitted)
.8468922
1.385523
1.752513
1.38402
1.8382
1.345035
1.997825
.9219925
1.27768
.8586301
.928869
1.399857
.7434835
1.192473
1.100057
.9045459
.1225682
-.7353728
.7627944
.775809
.4994938
1.056378
1.007022
.8476054
.5239564
1.121789
1.486322
.9866053
.4477025
(omitted)
.7810185
.506451
-.9197997
-.3031274
-.2618591
.1388563
.13851
.4114787
.104576
.1001528
-.3139514
(omitted)
(omitted)
1.199889
1.472053
1.124703
1.737915
1.233846
.4075502
.3601229
1.389834
1.501032
.6268715
.7545935
2.227894
6.707274
Std. Err.
t
Number of obs
F( 64,
4529)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
.1753293
.0087988
.0112475
.0079691
.0475204
.025816
.0734686
.0013464
.1437554
.0404142
.1494983
-0.07
35.30
-38.68
-3.21
2.85
16.61
2.82
-9.53
-1.09
5.96
-5.59
0.943
0.000
0.000
0.001
0.004
0.000
0.005
0.000
0.277
0.000
0.000
.0251693
-0.68
.5821083
.6844534
.7258838
.6446475
.8063894
.6584059
.9825941
.3654017
.3879368
.3178701
.2745822
.4899062
.3592203
.3727298
.4012806
.5349847
.3212723
.2775029
.2558122
.1762535
.2697876
.5949248
.3157616
.4501152
.2551858
.3303092
.6217945
.2245693
.2866379
1.45
2.02
2.41
2.15
2.28
2.04
2.03
2.52
3.29
2.70
3.38
2.86
2.07
3.20
2.74
1.69
0.38
-2.65
2.98
4.40
1.85
1.78
3.19
1.88
2.05
3.40
2.39
4.39
1.56
.5101279
.1881037
.3398333
.2142229
.2342754
.1384352
.207284
.2405118
.2478209
.1375284
.113001
.4346734
.2659506
.5697051
.4975716
.256632
.2177036
.224731
.2453026
.306671
.1770302
.3854525
.8104546
.7257457
=
=
=
=
=
=
4594
141.45
0.0000
0.6665
0.6618
.54087
[95% Conf. Interval]
-.3563212
.2933212
-.4570484
-.0411739
.0422854
.3781354
.0631096
-.015474
-.438239
.1617958
-1.128932
.3311409
.3278209
-.4129472
-.0099272
.2286119
.4793594
.3511782
-.0101949
.1254223
.3202588
-.5427522
0.497
-.06645
.0322382
0.146
0.043
0.016
0.032
0.023
0.041
0.042
0.012
0.001
0.007
0.001
0.004
0.039
0.001
0.006
0.091
0.703
0.008
0.003
0.000
0.064
0.076
0.001
0.060
0.040
0.001
0.017
0.000
0.118
-.2943241
.0436605
.3294266
.1201968
.2572837
.0542383
.0714607
.2056268
.5171341
.2354496
.390554
.4394016
.0392365
.4617403
.3133511
-.1442851
-.5072822
-1.279414
.2612776
.4302662
-.0294215
-.1099654
.3879756
-.03484
.0236678
.4742213
.2673013
.54634
-.1142477
1.988108
2.727386
3.175599
2.647844
3.419117
2.635832
3.924188
1.638358
2.038225
1.481811
1.467184
2.360312
1.44773
1.923205
1.886763
1.953377
.7524187
-.1913316
1.264311
1.121352
1.028409
2.22272
1.626069
1.730051
1.024245
1.769356
2.705343
1.426871
1.009653
1.53
2.69
-2.71
-1.42
-1.12
1.00
0.67
1.71
0.42
0.73
-2.78
0.126
0.007
0.007
0.157
0.264
0.316
0.504
0.087
0.673
0.467
0.005
-.2190812
.137676
-1.586039
-.7231088
-.7211532
-.1325442
-.2678678
-.0600417
-.3812738
-.16947
-.5354885
1.781118
.875226
-.2535607
.116854
.197435
.4102567
.5448877
.8829992
.5904258
.3697756
-.0924143
2.76
5.54
1.97
3.49
4.81
1.87
1.60
5.67
4.89
3.54
1.96
2.75
9.24
0.006
0.000
0.048
0.000
0.000
0.061
0.109
0.000
0.000
0.000
0.050
0.006
0.000
.3477166
.9506598
.0078029
.7624315
.7307221
-.0192551
-.0804595
.9089216
.8998071
.279806
-.0010814
.6390076
5.284458
2.05206
1.993446
2.241603
2.713398
1.73697
.8343555
.8007053
1.870747
2.102257
.973937
1.510268
3.816781
8.13009
Pooled specification (6) data 1997-1998
83
Source
SS
df
MS
Model
Residual
3608.74978
1708.07049
64
5192
56.3867153
.328981218
Total
5316.82027
5256
1.01157159
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
-.2507588
.2682245
-.4643328
-.0138883
.1640445
.4783358
.0743903
-.0095018
-.3016362
.1816324
-.4000052
(omitted)
(omitted)
-.0031449
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
1.974932
2.668301
3.079622
2.669484
3.470998
2.623132
3.568115
1.589804
(omitted)
1.65051
1.726851
2.219584
1.472553
2.135014
1.957211
1.927842
.8833401
-.6421243
1.498325
1.36148
1.235262
2.152797
(omitted)
1.426479
1.336271
1.844537
2.394084
1.393786
.9348199
(omitted)
1.726477
.8832921
.536493
-.8326249
-1.015038
.3643227
.3208633
.6379745
.1033588
.3700139
-.1603434
.2445848
-.7326084
2.006022
2.297338
1.741806
2.664513
1.877232
1.004117
1.016307
2.042024
1.973479
.7202349
1.193598
2.620022
7.801461
Std. Err.
t
Number of obs
F( 64,
5192)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
5257
171.40
0.0000
0.6787
0.6748
.57357
[95% Conf. Interval]
.1008752
.0083102
.0111512
.0081388
.0473194
.0256315
.0730755
.0009959
.1187322
.0315293
.12036
-2.49
32.28
-41.64
-1.71
3.47
18.66
1.02
-9.54
-2.54
5.76
-3.32
0.013
0.000
0.000
0.088
0.001
0.000
0.309
0.000
0.011
0.000
0.001
-.4485167
.2519331
-.4861938
-.0298437
.0712785
.4280874
-.0688684
-.0114542
-.5344014
.1198217
-.6359614
-.053001
.284516
-.4424718
.0020672
.2568105
.5285843
.217649
-.0075495
-.068871
.2434432
-.164049
.0162178
-0.19
0.846
-.0349386
.0286489
.3408513
.4238414
.4659188
.4052846
.5277212
.424536
.6051541
.234989
5.79
6.30
6.61
6.59
6.58
6.18
5.90
6.77
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
1.30672
1.837394
2.166225
1.874955
2.436442
1.790863
2.381758
1.129126
2.643144
3.499209
3.993019
3.464012
4.505554
3.455401
4.754472
2.050481
.2162307
.1876538
.2956186
.2062701
.2530347
.2584647
.2978799
.1926929
.1387413
.1520302
.1254683
.1822305
.3342839
7.63
9.20
7.51
7.14
8.44
7.57
6.47
4.58
-4.63
9.86
10.85
6.78
6.44
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
1.226607
1.35897
1.640047
1.068177
1.63896
1.450511
1.343872
.505581
-.9141155
1.200282
1.115509
.8780132
1.49746
2.074413
2.094731
2.799121
1.876929
2.631068
2.46391
2.511812
1.261099
-.370133
1.796368
1.607451
1.59251
2.808135
.2560447
.1749184
.267766
.3718456
.148367
.1753118
5.57
7.64
6.89
6.44
9.39
5.33
0.000
0.000
0.000
0.000
0.000
0.000
.9245237
.9933573
1.319603
1.665111
1.102924
.5911348
1.928435
1.679185
2.369471
3.123058
1.684648
1.278505
.3140718
.1210214
.1567604
.1352841
.1355975
.0808904
.1154731
.1086465
.148372
.0923789
.0827202
.1688635
.0860459
.2086132
.2157189
.3030104
.3051427
.1537308
.1431938
.1414524
.1595707
.1900332
.1080203
.2120235
.3852126
.3408438
5.50
7.30
3.42
-6.15
-7.49
4.50
2.78
5.87
0.70
4.01
-1.94
1.45
-8.51
9.62
10.65
5.75
8.73
12.21
7.01
7.18
12.80
10.38
6.67
5.63
6.80
22.89
0.000
0.000
0.001
0.000
0.000
0.000
0.005
0.000
0.486
0.000
0.053
0.148
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
1.110764
.6460393
.2291766
-1.097839
-1.280866
.2057435
.0944873
.4249815
-.1875129
.1889124
-.3225099
-.0864589
-.9012947
1.597052
1.874438
1.147778
2.066305
1.575855
.7233967
.7390007
1.729199
1.600934
.5084698
.7779431
1.864843
7.133263
2.34219
1.120545
.8438094
-.5674112
-.7492102
.5229019
.5472393
.8509674
.3942305
.5511155
.0018231
.5756284
-.5639221
2.414992
2.720238
2.335834
3.262721
2.178609
1.284837
1.293613
2.35485
2.346024
.9320001
1.609254
3.375201
8.469658
Pooled specification (6) data 2001-2002
84
Source
SS
df
MS
Model
Residual
3939.6492
1904.92147
66
5674
59.6916546
.335728141
Total
5844.57067
5740
1.01821789
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
-.0667986
.2956664
-.4668483
-.011213
.1357743
.4478359
.109745
-.0109467
-.392419
.2351617
-.6375741
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.0126231
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
1.255932
1.886319
2.236701
1.907585
2.562208
1.89083
2.627323
1.241329
1.651306
1.246607
1.448928
1.707152
1.103497
1.65101
1.459954
1.478871
.6144199
-.4577442
1.308664
1.1519
.921507
1.528824
1.261976
1.029305
1.070105
1.368323
1.788218
1.253084
.5371064
(omitted)
1.042719
.7277384
.2103699
-.4244274
-.4799125
.2827914
.2583627
.4902146
-.1793024
.2977163
-.142448
.1556891
-.653622
1.683342
1.899284
1.267805
2.091299
1.64046
.8145551
.8330444
1.736551
1.7361
.7318399
.8148903
2.121891
7.158011
Std. Err.
t
Number of obs
F( 66,
5674)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
5741
177.80
0.0000
0.6741
0.6703
.57942
[95% Conf. Interval]
.1822698
.0079536
.0108643
.0077106
.0466196
.0243152
.0722305
.0009653
.1401524
.0311421
.121704
-0.37
37.17
-42.97
-1.45
2.91
18.42
1.52
-11.34
-2.80
7.55
-5.24
0.714
0.000
0.000
0.146
0.004
0.000
0.129
0.000
0.005
0.000
0.000
-.424117
.2800743
-.4881465
-.0263288
.044382
.4001688
-.0318545
-.012839
-.6671714
.1741112
-.8761603
.2905199
.3112585
-.4455501
.0039028
.2271666
.495503
.2513444
-.0090543
-.1176667
.2962121
-.3989878
.0154083
-0.82
0.413
-.0428293
.0175831
.6710989
.7831224
.8473544
.7490767
.9986638
.8032542
1.153078
.4318334
.4672531
.4003852
.3537354
.561713
.4104741
.4705802
.4817618
.5601067
.3621769
.1684855
.3181265
.2052241
.3469296
.636656
.3567776
.4636678
.3546627
.498266
.6366407
.2584075
.3147491
1.87
2.41
2.64
2.55
2.57
2.35
2.28
2.87
3.53
3.11
4.10
3.04
2.69
3.51
3.03
2.64
1.70
-2.72
4.11
5.61
2.66
2.40
3.54
2.22
3.02
2.75
2.81
4.85
1.71
0.061
0.016
0.008
0.011
0.010
0.019
0.023
0.004
0.000
0.002
0.000
0.002
0.007
0.000
0.002
0.008
0.090
0.007
0.000
0.000
0.008
0.016
0.000
0.026
0.003
0.006
0.005
0.000
0.088
-.0596787
.3510998
.5755627
.4391085
.6044456
.3161445
.3668499
.3947705
.735311
.4616993
.7554715
.6059801
.2988109
.7284931
.5155165
.3808481
-.0955852
-.7880402
.6850142
.7495821
.2413923
.2807353
.5625552
.1203392
.3748304
.3915317
.540159
.7465064
-.0799221
2.571542
3.421538
3.89784
3.376062
4.519971
3.465515
4.887796
2.087887
2.5673
2.031515
2.142385
2.808324
1.908183
2.573527
2.404391
2.576894
1.324425
-.1274481
1.932313
1.554218
1.601622
2.776913
1.961396
1.938272
1.765379
2.345115
3.036277
1.759661
1.154135
.6633145
.2084228
.3488849
.168955
.2035155
.0844225
.214071
.1878704
.3116234
.1501398
.0857988
.3261695
.1473166
.403444
.4085554
.5996919
.6115386
.304282
.2618371
.2626243
.2999563
.3473685
.1979963
.4217421
.7720726
.5464419
1.57
3.49
0.60
-2.51
-2.36
3.35
1.21
2.61
-0.58
1.98
-1.66
0.48
-4.44
4.17
4.65
2.11
3.42
5.39
3.11
3.17
5.79
5.00
3.70
1.93
2.75
13.10
0.116
0.000
0.547
0.012
0.018
0.001
0.228
0.009
0.565
0.047
0.097
0.633
0.000
0.000
0.000
0.035
0.001
0.000
0.002
0.002
0.000
0.000
0.000
0.053
0.006
0.000
-.2576314
.3191501
-.4735779
-.7556438
-.8788806
.1172911
-.1612982
.1219168
-.7902034
.0033849
-.3106464
-.4837279
-.9424189
.8924374
1.09836
.09218
.89245
1.043951
.3012543
.3182003
1.148522
1.055125
.3436916
-.0118854
.6083341
6.086776
2.343069
1.136327
.8943177
-.0932111
-.0809443
.4482917
.6780236
.8585123
.4315987
.5920477
.0257504
.795106
-.3648251
2.474246
2.700209
2.443431
3.290149
2.236969
1.327856
1.347888
2.32458
2.417075
1.119988
1.641666
3.635449
8.229246
Pooled specification (6) data 2008-2009
85
Source
SS
df
MS
Model
Residual
3448.67319
1759.39028
65
5529
53.0565106
.318211301
Total
5208.06347
5594
.931008843
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.0338753
.3012879
-.4435923
-.0240378
.1454013
.4416595
.1830364
-.0121986
-.1338549
.2301733
-.736437
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
.0433888
(omitted)
(omitted)
.7791558
1.232278
1.598666
1.270585
1.673842
1.196997
1.738053
.8818355
1.214415
.82333
.9636441
1.301862
.7186957
1.167222
1.039992
.8646974
.0756039
-.6240871
.7395045
.8277068
.4864279
.9385319
.8830292
.7773168
.5436474
1.106757
1.374342
.9795914
.3415312
(omitted)
.703101
.5191028
-.8285087
-.2864866
-.0696815
.2276231
.0398994
.3233893
.0455302
.1882663
-.2160944
(omitted)
-.8650162
1.161382
1.456239
1.013497
1.653423
1.27351
.4047818
.3638281
1.404396
1.477326
.60313
.6816805
2.00768
6.573293
Std. Err.
t
Number of obs
F( 65,
5529)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
5595
166.73
0.0000
0.6622
0.6582
.5641
[95% Conf. Interval]
.1688961
.0083684
.0106968
.0075501
.0459916
.0237882
.0707173
.0013291
.1350496
.0396781
.1277115
0.20
36.00
-41.47
-3.18
3.16
18.57
2.59
-9.18
-0.99
5.80
-5.77
0.841
0.000
0.000
0.001
0.002
0.000
0.010
0.000
0.322
0.000
0.000
-.2972274
.2848826
-.4645622
-.0388389
.0552397
.3950253
.0444027
-.0148041
-.3986052
.1523886
-.9868018
.364978
.3176933
-.4226224
-.0092368
.2355628
.4882936
.3216701
-.0095931
.1308955
.3079581
-.4860722
.0194608
2.23
0.026
.0052379
.0815398
.5600822
.6715289
.711677
.6343406
.770495
.6510665
.9498061
.349535
.3831468
.3157095
.2760172
.4719572
.3543582
.3666647
.3857399
.5057529
.3221329
.2357796
.2682932
.1637187
.2687632
.5731727
.2912221
.4351047
.2363237
.3126236
.5832867
.2074692
.2616877
1.39
1.84
2.25
2.00
2.17
1.84
1.83
2.52
3.17
2.61
3.49
2.76
2.03
3.18
2.70
1.71
0.23
-2.65
2.76
5.06
1.81
1.64
3.03
1.79
2.30
3.54
2.36
4.72
1.31
0.164
0.067
0.025
0.045
0.030
0.066
0.067
0.012
0.002
0.009
0.000
0.006
0.043
0.001
0.007
0.087
0.814
0.008
0.006
0.000
0.070
0.102
0.002
0.074
0.021
0.000
0.018
0.000
0.192
-.3188255
-.0841825
.2034991
.0270281
.163369
-.0793492
-.1239404
.1966096
.4632965
.2044153
.4225418
.37664
.0240144
.4484152
.2837901
-.1267771
-.5559033
-1.086308
.2135443
.5067539
-.0404537
-.185112
.3121194
-.0756594
.0803601
.4938919
.2308708
.5728703
-.1714795
1.877137
2.548739
2.993832
2.514142
3.184315
2.473343
3.600046
1.567061
1.965533
1.442245
1.504746
2.227083
1.413377
1.886029
1.796194
1.856172
.7071111
-.1618663
1.265465
1.14866
1.01331
2.062176
1.453939
1.630293
1.006935
1.719622
2.517813
1.386312
.8545419
.4989486
.1664606
.3123478
.2088356
.2232886
.1187711
.1987069
.2292019
.2160425
.1193829
.085862
1.41
3.12
-2.65
-1.37
-0.31
1.92
0.20
1.41
0.21
1.58
-2.52
0.159
0.002
0.008
0.170
0.755
0.055
0.841
0.158
0.833
0.115
0.012
-.2750345
.1927746
-1.440833
-.6958866
-.5074149
-.0052149
-.3496443
-.1259366
-.377998
-.045771
-.3844178
1.681236
.845431
-.2161842
.1229133
.3680519
.460461
.4294431
.7727152
.4690584
.4223037
-.0477711
.1975106
.3945765
.2466469
.5409222
.4805733
.2427586
.204878
.2056943
.2261301
.2843103
.1841399
.3790708
.7628358
.6773841
-4.38
2.94
5.90
1.87
3.44
5.25
1.98
1.77
6.21
5.20
3.28
1.80
2.63
9.70
0.000
0.003
0.000
0.061
0.001
0.000
0.048
0.077
0.000
0.000
0.001
0.072
0.009
0.000
-1.252215
.3878568
.9727138
-.0469234
.7113109
.7976081
.0031404
-.0394136
.9610921
.919966
.2421434
-.0614472
.5122225
5.245354
-.4778178
1.934907
1.939764
2.073917
2.595536
1.749412
.8064232
.7670697
1.8477
2.034686
.9641166
1.424808
3.503138
7.901232
Pooled specification (6) data 1995-1997
86
Source
SS
df
MS
Model
Residual
4910.77794
2265.05859
65
7565
75.5504299
.299412901
Total
7175.83654
7630
.94047661
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.0811503
.2672104
-.4560494
-.0168779
.1620314
.4731569
.0853897
-.0088072
-.319529
.1458877
-.2959804
.0299552
(omitted)
.0200716
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
.7553217
1.113157
1.424437
1.216265
1.563851
1.044199
1.473275
.6907198
(omitted)
.8517132
1.011554
1.116708
.7084914
1.171744
.989732
.758993
.1972951
-.3594583
.8835852
.880417
.5487835
.9061115
(omitted)
.4417764
.6647025
.860864
1.067861
.8511963
.3132783
(omitted)
.5335628
.4529147
-.0178809
-.7119023
-.604293
.1692246
.0673163
.5284231
-.4609469
.0586736
-.1826031
-.3317994
-1.156665
1.079692
1.501435
.622121
1.400201
1.243774
.4432096
.3728858
1.438625
1.137607
.2520237
.4124351
1.166849
6.811601
Std. Err.
t
Number of obs
F( 65, 7565)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
7631
252.33
0.0000
0.6843
0.6816
.54719
[95% Conf. Interval]
.1228099
.0064483
.0087839
.0064393
.0373482
.0201804
.057425
.0006867
.0863757
.0224774
.1044614
.017357
0.66
41.44
-51.92
-2.62
4.34
23.45
1.49
-12.83
-3.70
6.49
-2.83
1.73
0.509
0.000
0.000
0.009
0.000
0.000
0.137
0.000
0.000
0.000
0.005
0.084
-.1595912
.25457
-.4732683
-.0295007
.0888186
.4335977
-.0271793
-.0101533
-.4888493
.1018259
-.5007537
-.0040693
.3218918
.2798509
-.4388304
-.0042552
.2352442
.5127161
.1979586
-.0074612
-.1502086
.1899496
-.0912071
.0639798
.0152983
1.31
0.190
-.0099174
.0500606
.4147315
.5245083
.5786822
.4948843
.6621249
.5013093
.7261324
.2941379
1.82
2.12
2.46
2.46
2.36
2.08
2.03
2.35
0.069
0.034
0.014
0.014
0.018
0.037
0.042
0.019
-.0576672
.0849751
.2900591
.2461544
.2659029
.0614935
.0498538
.1141279
1.568311
2.141339
2.558814
2.186375
2.8618
2.026904
2.896696
1.267312
.2660173
.225789
.36504
.2494669
.3111645
.3256105
.3664092
.2306533
.1506113
.1627865
.1489906
.2163668
.4112446
3.20
4.48
3.06
2.84
3.77
3.04
2.07
0.86
-2.39
5.43
5.91
2.54
2.20
0.001
0.000
0.002
0.005
0.000
0.002
0.038
0.392
0.017
0.000
0.000
0.011
0.028
.3302454
.5689445
.4011284
.2194669
.5617752
.351445
.0407292
-.2548494
-.6546984
.5644785
.588354
.1246446
.099958
1.373181
1.454163
1.832288
1.197516
1.781713
1.628019
1.477257
.6494397
-.0642183
1.202692
1.17248
.9729224
1.712265
.302083
.2013916
.3170493
.4502824
.1666904
.2126422
1.46
3.30
2.72
2.37
5.11
1.47
0.144
0.001
0.007
0.018
0.000
0.141
-.1503902
.269919
.2393593
.1851828
.5244368
-.1035595
1.033943
1.059486
1.482369
1.95054
1.177956
.730116
.3605639
.1322418
.1705234
.1498899
.1351049
.0645469
.1162668
.1201552
.1531463
.0850071
.0665125
.2126919
.0763693
.299761
.2522136
.3594048
.4000094
.1949351
.1656203
.1732081
.1901676
.2573616
.1126777
.2456922
.4523279
.3950528
1.48
3.42
-0.10
-4.75
-4.47
2.62
0.58
4.40
-3.01
0.69
-2.75
-1.56
-15.15
3.60
5.95
1.73
3.50
6.38
2.68
2.15
7.57
4.42
2.24
1.68
2.58
17.24
0.139
0.001
0.916
0.000
0.000
0.009
0.563
0.000
0.003
0.490
0.006
0.119
0.000
0.000
0.000
0.083
0.000
0.000
0.007
0.031
0.000
0.000
0.025
0.093
0.010
0.000
-.1732426
.1936841
-.3521541
-1.005728
-.8691361
.0426948
-.1605989
.2928855
-.7611562
-.107964
-.312986
-.7487344
-1.30637
.492077
1.007027
-.0824121
.6160711
.8616469
.1185479
.0333498
1.065844
.6331073
.0311442
-.0691898
.2801605
6.037188
1.240368
.7121453
.3163922
-.4180764
-.3394498
.2957545
.2952314
.7639606
-.1607376
.2253111
-.0522202
.0851357
-1.00696
1.667307
1.995844
1.326654
2.18433
1.625901
.7678713
.7124218
1.811406
1.642108
.4729033
.89406
2.053537
7.586014
Pooled specification (6) data 2002-2004
87
Source
SS
df
MS
Model
Residual
5899.75462
2811.29
67
8520
88.056039
.329963615
Total
8711.04462
8587
1.01444563
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
-.1110573
.3102074
-.4532723
-.0312498
.1532336
.4700921
.1375227
-.0124138
-.379721
.2753961
-.8047584
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.033015
-.0262373
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
1.392881
2.133154
2.545353
2.124685
2.76898
2.186043
2.888951
1.397326
1.783186
1.373979
1.485974
1.888067
1.155856
1.750943
1.609828
1.575283
.6726061
-.4803011
1.321136
1.20284
1.028027
1.69592
1.415672
1.241697
1.015877
1.571426
2.036854
1.31644
.7254836
(omitted)
1.141287
.7349657
.4133395
-.356629
-.5405015
.3077109
.0600496
.812792
.0226895
.3519723
-.109906
.2840014
-.5613062
1.733187
1.932623
1.527617
2.252201
1.718359
.8858332
.8892952
1.795512
1.838333
.9071127
1.029795
2.531919
7.059446
Std. Err.
t
Number of obs
F( 67,
8520)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
8588
266.87
0.0000
0.6773
0.6747
.57442
[95% Conf. Interval]
.1042111
.0063409
.0088192
.006076
.0378336
.0197785
.0586817
.0009156
.1076863
.0284076
.0900126
-1.07
48.92
-51.40
-5.14
4.05
23.77
2.34
-13.56
-3.53
9.69
-8.94
0.287
0.000
0.000
0.000
0.000
0.000
0.019
0.000
0.000
0.000
0.000
-.3153364
.2977777
-.4705602
-.0431603
.0790705
.4313214
.0224923
-.0142086
-.5908123
.2197104
-.9812049
.0932218
.322637
-.4359845
-.0193394
.2273966
.5088629
.2525531
-.0106191
-.1686296
.3310819
-.6283118
.0212283
.0340107
-1.56
-0.77
0.120
0.440
-.0746277
-.0929066
.0085976
.040432
.3608815
.4349705
.4674693
.416545
.5273682
.4441868
.6287074
.2345009
.2557652
.2173845
.1921802
.3106415
.2243754
.2558533
.2604725
.3124094
.2071377
.1197432
.1871883
.1243018
.1901094
.3611328
.1912218
.2546403
.1628844
.1684095
.3189814
.1231874
.1488444
3.86
4.90
5.44
5.10
5.25
4.92
4.60
5.96
6.97
6.32
7.73
6.08
5.15
6.84
6.18
5.04
3.25
-4.01
7.06
9.68
5.41
4.70
7.40
4.88
6.24
9.33
6.39
10.69
4.87
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.001
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.6854656
1.280506
1.629
1.308156
1.73521
1.315329
1.656532
.9376478
1.281824
.9478524
1.109255
1.279134
.7160254
1.249409
1.099239
.9628847
.266566
-.7150268
.9542019
.9591786
.6553664
.9880124
1.040831
.74254
.6965842
1.241302
1.411573
1.074963
.4337126
2.100296
2.985801
3.461706
2.941214
3.802749
3.056757
4.12137
1.857005
2.284548
1.800105
1.862694
2.497
1.595686
2.252478
2.120417
2.187681
1.078646
-.2455754
1.688071
1.446502
1.400687
2.403828
1.790513
1.740854
1.33517
1.901549
2.662135
1.557917
1.017255
.3429863
.1039001
.1417826
.1448989
.1785521
.1033656
.1150454
.1298345
.1282484
.0855489
.0656853
.1755881
.0862309
.226185
.1927618
.3234499
.3315385
.1562571
.1300966
.1266159
.1454614
.1800935
.1292522
.2235285
.4290298
.3489301
3.33
7.07
2.92
-2.46
-3.03
2.98
0.52
6.26
0.18
4.11
-1.67
1.62
-6.51
7.66
10.03
4.72
6.79
11.00
6.81
7.02
12.34
10.21
7.02
4.61
5.90
20.23
0.001
0.000
0.004
0.014
0.002
0.003
0.602
0.000
0.860
0.000
0.094
0.106
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.468951
.5312964
.1354113
-.6406661
-.8905068
.1050892
-.1654673
.558285
-.2287084
.1842756
-.2386651
-.0601939
-.7303397
1.289809
1.554763
.8935764
1.602305
1.412057
.6308123
.6410973
1.510372
1.485306
.6537471
.5916247
1.690916
6.375459
1.813624
.938635
.6912677
-.072592
-.1904961
.5103325
.2855664
1.067299
.2740874
.519669
.0188531
.6281966
-.3922728
2.176564
2.310483
2.161657
2.902097
2.024661
1.140854
1.137493
2.080652
2.19136
1.160478
1.467965
3.372921
7.743434
Pooled specification (6) data 2006-2007
88
Source
SS
df
MS
Model
Residual
3836.95138
1965.6275
66
5637
58.135627
.348700994
Total
5802.57888
5703
1.01746079
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.0511719
.309355
-.4513556
-.0184803
.1744187
.4457055
.1421098
-.010935
-.2828657
.2235903
-.7579134
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
.0350034
(omitted)
(omitted)
(omitted)
(omitted)
.8257398
1.326758
1.708094
1.360298
1.753382
1.350496
1.764223
1.011208
1.318685
.8994044
1.139136
1.387746
.7906062
1.277886
1.125471
1.004027
.2017969
-.4322118
.882543
.9500333
.6172232
1.019047
1.132832
.789911
.6852242
1.218518
1.460859
1.148386
.4329929
(omitted)
.7105641
.6695638
-.2397673
-.2117929
-.2165389
.3619766
.1082036
.028212
-.2063748
.2309356
-.1351591
.0440177
-.7264479
1.265972
1.585826
1.04001
1.699342
1.436813
.5661109
.58009
1.52554
1.574702
.7752299
.7287013
1.991215
6.449094
Std. Err.
t
Number of obs
F( 66, 5637)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
5704
166.72
0.0000
0.6612
0.6573
.59051
[95% Conf. Interval]
.2978588
.0084696
.011092
.0077709
.0479077
.0248571
.0736412
.0014326
.1424052
.0427607
.1121453
0.17
36.53
-40.69
-2.38
3.64
17.93
1.93
-7.63
-1.99
5.23
-6.76
0.864
0.000
0.000
0.017
0.000
0.000
0.054
0.000
0.047
0.000
0.000
-.532746
.2927512
-.4731002
-.0337142
.0805011
.3969759
-.0022553
-.0137436
-.5620348
.1397629
-.9777613
.6350898
.3259587
-.429611
-.0032464
.2683363
.494435
.2864749
-.0081265
-.0036966
.3074178
-.5380654
.0488829
0.72
0.474
-.0608259
.1308327
1.025895
1.199842
1.274343
1.140214
1.37426
1.224357
1.715453
.6231514
.6857255
.5726524
.497372
.8428766
.6351089
.6863163
.6740637
.8936751
.5676074
.2690496
.5151309
.3103351
.4832567
1.022549
.5527272
.7781796
.3898054
.5106303
.9972555
.3869121
.4364671
0.80
1.11
1.34
1.19
1.28
1.10
1.03
1.62
1.92
1.57
2.29
1.65
1.24
1.86
1.67
1.12
0.36
-1.61
1.71
3.06
1.28
1.00
2.05
1.02
1.76
2.39
1.46
2.97
0.99
0.421
0.269
0.180
0.233
0.202
0.270
0.304
0.105
0.055
0.116
0.022
0.100
0.213
0.063
0.095
0.261
0.722
0.108
0.087
0.002
0.202
0.319
0.040
0.310
0.079
0.017
0.143
0.003
0.321
-1.185409
-1.025394
-.7901098
-.8749598
-.940696
-1.049715
-1.598726
-.2104085
-.0256006
-.2232147
.1640951
-.2646166
-.4544518
-.0675577
-.1959529
-.7479204
-.910932
-.9596526
-.127312
.341657
-.3301459
-.985543
.0492735
-.7356205
-.0789444
.217486
-.4941458
.3898894
-.4226507
2.836889
3.67891
4.206297
3.595556
4.44746
3.750706
5.127172
2.232825
2.662971
2.022023
2.114176
3.040108
2.035664
2.623331
2.446896
2.755974
1.314526
.0952291
1.892398
1.55841
1.564592
3.023638
2.21639
2.315442
1.449393
2.21955
3.415863
1.906883
1.288636
.934393
.2588141
.4662929
.3841345
.4280362
.2220817
.326577
.3894312
.3082963
.1640622
.0974992
.5183243
.2834927
.6628553
.4585539
.9432895
.9362574
.4158496
.34668
.3357696
.3969191
.497058
.3235873
.6510149
1.269874
1.155892
0.76
2.59
-0.51
-0.55
-0.51
1.63
0.33
0.07
-0.67
1.41
-1.39
0.08
-2.56
1.91
3.46
1.10
1.82
3.46
1.63
1.73
3.84
3.17
2.40
1.12
1.57
5.58
0.447
0.010
0.607
0.581
0.613
0.103
0.740
0.942
0.503
0.159
0.166
0.932
0.010
0.056
0.001
0.270
0.070
0.001
0.103
0.084
0.000
0.002
0.017
0.263
0.117
0.000
-1.121206
.1621885
-1.153881
-.9648445
-1.055655
-.0733891
-.5320131
-.735223
-.8107541
-.0906895
-.326295
-.9720975
-1.282203
-.0334799
.6868837
-.8092001
-.1360832
.6215876
-.1135153
-.0781478
.7474256
.6002771
.1408742
-.5475385
-.498227
4.1831
2.542334
1.176939
.6743463
.5412586
.6225767
.7973423
.7484203
.7916471
.3980046
.5525606
.0559769
1.060133
-.1706931
2.565423
2.484768
2.889221
3.534767
2.252038
1.245737
1.238328
2.303654
2.549127
1.409586
2.004941
4.480656
8.715088
.
Pooled specification (6) data 1996-1997
89
Source
SS
df
MS
Model
Residual
3444.21588
1599.88185
64
5104
53.8158732
.313456475
Total
5044.09773
5168
.976025102
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.0472045
.2716655
-.4637171
-.0159138
.161401
.4774617
.0762285
-.0088597
-.3616871
.153503
-.3299314
(omitted)
-.0202494
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
.9240303
1.32401
1.650807
1.418769
1.79374
1.267182
1.742256
.8303824
(omitted)
.9649314
1.124487
1.284827
.8328115
1.322289
1.132476
.9273454
.3085902
-.3324363
.9889469
.976939
.6566219
1.094431
(omitted)
.5865693
.7983852
1.017075
1.242512
.9114044
.4095809
(omitted)
.7644197
.5569187
.08028
-.7134174
-.6978017
.2362544
.1620951
.6014062
-.3898762
.112435
-.141836
-.2241043
-1.115252
1.218621
1.612721
.7944734
1.582085
1.341223
.5538523
.4966149
1.532831
1.275335
.3348329
.5257746
1.351703
6.928451
Std. Err.
t
Number of obs
F( 64,
5104)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
5169
171.69
0.0000
0.6828
0.6788
.55987
[95% Conf. Interval]
.181653
.008098
.0109454
.0079635
.0465077
.0251039
.0716031
.0009084
.1108543
.0292268
.1270045
0.26
33.55
-42.37
-2.00
3.47
19.02
1.06
-9.75
-3.26
5.25
-2.60
0.795
0.000
0.000
0.046
0.001
0.000
0.287
0.000
0.001
0.000
0.009
-.3089133
.2557899
-.4851749
-.0315257
.070226
.4282472
-.0641442
-.0106405
-.5790091
.096206
-.5789146
.4033223
.287541
-.4422593
-.0003018
.2525759
.5266763
.2166012
-.0070788
-.1443652
.2108
-.0809482
.0156558
-1.29
0.196
-.0509415
.0104427
.6084257
.7654443
.8431837
.7295575
.9633514
.7394905
1.071877
.4211561
1.52
1.73
1.96
1.94
1.86
1.71
1.63
1.97
0.129
0.084
0.050
0.052
0.063
0.087
0.104
0.049
-.268745
-.1765893
-.0021945
-.0114766
-.0948422
-.1825364
-.3590821
.0047359
2.116806
2.824609
3.303809
2.849015
3.682322
2.716901
3.843595
1.656029
.3824733
.3215533
.528908
.3632436
.4537939
.466412
.5401612
.3337796
.2194144
.2376619
.2144103
.3109055
.6000161
2.52
3.50
2.43
2.29
2.91
2.43
1.72
0.92
-1.52
4.16
4.56
2.11
1.82
0.012
0.000
0.015
0.022
0.004
0.015
0.086
0.355
0.130
0.000
0.000
0.035
0.068
.2151196
.4941043
.2479403
.1206983
.4326585
.218108
-.1316021
-.345761
-.7625825
.5230275
.5566029
.0471139
-.0818576
1.714743
1.754869
2.321713
1.544925
2.21192
2.046843
1.986293
.9629413
.09771
1.454866
1.397275
1.26613
2.27072
.4432531
.2934773
.465411
.6645534
.2410946
.3070166
1.32
2.72
2.19
1.87
3.78
1.33
0.186
0.007
0.029
0.062
0.000
0.182
-.282397
.2230438
.1046697
-.0602979
.4387556
-.1923033
1.455536
1.373727
1.92948
2.545322
1.384053
1.011465
.5390283
.1868411
.2394038
.2137077
.192095
.0799996
.1623224
.1472892
.2244987
.1125073
.0825875
.2982608
.1004924
.4396497
.3722186
.528195
.5857844
.2849387
.2357947
.2512825
.2768563
.3703256
.1545335
.3607772
.6742203
.5803305
1.42
2.98
0.34
-3.34
-3.63
2.95
1.00
4.08
-1.74
1.00
-1.72
-0.75
-11.10
2.77
4.33
1.50
2.70
4.71
2.35
1.98
5.54
3.44
2.17
1.46
2.00
11.94
0.156
0.003
0.737
0.001
0.000
0.003
0.318
0.000
0.083
0.318
0.086
0.452
0.000
0.006
0.000
0.133
0.007
0.000
0.019
0.048
0.000
0.001
0.030
0.145
0.045
0.000
-.2923069
.19063
-.389054
-1.132376
-1.07439
.079421
-.1561264
.3126561
-.8299899
-.1081275
-.3037429
-.8088235
-1.31226
.3567194
.8830135
-.2410153
.4336966
.7826208
.0915936
.0039934
.9900736
.549338
.031881
-.1815034
.0299424
5.790754
1.821146
.9232074
.549614
-.2944587
-.321213
.3930879
.4803166
.8901563
.0502375
.3329975
.020071
.3606148
-.9182435
2.080523
2.342429
1.829962
2.730474
1.899825
1.016111
.9892363
2.075588
2.001332
.6377848
1.233053
2.673465
8.066148
Pooled specification (6) data 1999-2000
90
Source
SS
df
MS
Model
Residual
3942.54716
1853.57648
66
5607
59.7355631
.330582573
Total
5796.12365
5673
1.02170345
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
-.0962371
.3015522
-.4666124
-.0075267
.1300692
.4634853
.0862871
-.0114266
-.4098498
.2422522
-.5910427
(omitted)
(omitted)
(omitted)
(omitted)
-.0343932
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
1.404367
2.05373
2.43288
2.064415
2.841665
2.034947
2.858215
1.313899
1.732925
1.33638
1.509849
1.786195
1.190388
1.768348
1.563163
1.52565
.6899552
-.4792007
1.390076
1.193752
.9923507
1.67015
1.34236
1.100889
1.166106
1.466172
1.892934
1.269526
.6461035
(omitted)
1.135874
.7833021
.2392903
-.4701799
-.6660175
.3392406
.3306676
.6396367
-.0895027
.3419451
-.1310045
.1853525
-.5663799
1.766723
2.001769
1.348401
2.250548
1.71797
.8542606
.8818149
1.820501
1.796077
.7516289
.8977918
2.209382
7.188796
Std. Err.
t
Number of obs
F( 66,
5607)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
5674
180.70
0.0000
0.6802
0.6764
.57496
[95% Conf. Interval]
.1791893
.0079047
.010819
.007557
.046307
.0243227
.0720171
.0009294
.130587
.0300032
.1183408
-0.54
38.15
-43.13
-1.00
2.81
19.06
1.20
-12.29
-3.14
8.07
-4.99
0.591
0.000
0.000
0.319
0.005
0.000
0.231
0.000
0.002
0.000
0.000
-.4475176
.2860558
-.4878218
-.0223414
.0392896
.4158033
-.0548944
-.0132486
-.6658508
.1834343
-.8230365
.2550434
.3170485
-.445403
.007288
.2208487
.5111673
.2274686
-.0096046
-.1538488
.3010702
-.3590488
.0154803
-2.22
0.026
-.0647405
-.0040459
.6733468
.7975712
.8641324
.7633109
1.008567
.8119134
1.14465
.4540918
.4877729
.4211154
.3719915
.5751261
.4177462
.4944786
.4985648
.5788583
.3807768
.1415581
.3256826
.2296719
.3657928
.6477722
.3812589
.4980879
.3599916
.515024
.6495966
.279483
.3281644
2.09
2.57
2.82
2.70
2.82
2.51
2.50
2.89
3.55
3.17
4.06
3.11
2.85
3.58
3.14
2.64
1.81
-3.39
4.27
5.20
2.71
2.58
3.52
2.21
3.24
2.85
2.91
4.54
1.97
0.037
0.010
0.005
0.007
0.005
0.012
0.013
0.004
0.000
0.002
0.000
0.002
0.004
0.000
0.002
0.008
0.070
0.001
0.000
0.000
0.007
0.010
0.000
0.027
0.001
0.004
0.004
0.000
0.049
.0843462
.4901814
.7388459
.56803
.864483
.4432828
.6142577
.4237028
.7767008
.5108309
.7806014
.6587251
.3714437
.7989779
.5857829
.3908638
-.0565146
-.7567094
.7516117
.7435056
.2752552
.4002653
.5949448
.1244441
.4603833
.4565256
.6194728
.7216309
.0027743
2.724387
3.617278
4.126914
3.5608
4.818846
3.626612
5.102173
2.204094
2.689148
2.161929
2.239096
2.913665
2.009332
2.737717
2.540543
2.660436
1.436425
-.2016919
2.02854
1.643997
1.709446
2.940034
2.089775
2.077334
1.871829
2.475819
3.166395
1.817421
1.289433
.6527476
.2207412
.3440983
.1478302
.17212
.1001777
.2214863
.1880987
.321721
.1700432
.0960892
.3324036
.1519275
.4138752
.4203337
.6036694
.6141155
.307028
.2763204
.2840136
.3124477
.3671096
.2070942
.4240304
.7617297
.519499
1.74
3.55
0.70
-3.18
-3.87
3.39
1.49
3.40
-0.28
2.01
-1.36
0.56
-3.73
4.27
4.76
2.23
3.66
5.60
3.09
3.10
5.83
4.89
3.63
2.12
2.90
13.84
0.082
0.000
0.487
0.001
0.000
0.001
0.136
0.001
0.781
0.044
0.173
0.577
0.000
0.000
0.000
0.026
0.000
0.000
0.002
0.002
0.000
0.000
0.000
0.034
0.004
0.000
-.1437643
.3505639
-.4352756
-.7599843
-1.003439
.1428535
-.1035313
.2708903
-.7202004
.0085945
-.3193766
-.4662872
-.8642165
.9553669
1.177752
.1649757
1.046644
1.116076
.3125657
.3250382
1.207983
1.076401
.345644
.066528
.7160973
6.170377
2.415512
1.21604
.9138562
-.1803755
-.3285957
.5356276
.7648665
1.008383
.5411951
.6752957
.0573676
.8369923
-.2685432
2.578078
2.825786
2.531827
3.454453
2.319864
1.395955
1.438592
2.433019
2.515754
1.157614
1.729056
3.702667
8.207215
Pooled specification (6) data 2003-2007
91
Source
SS
df
MS
Model
Residual
9743.86506
69
4741.82395 14199
141.215436
.333954782
Total
14485.689 14268
1.01525715
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.0034044
.3090296
-.4505221
-.026226
.1699199
.4639191
.1522628
-.0115425
-.3069736
.2428097
-.7774435
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
.0677598
.0540103
.0396715
.0285838
(omitted)
(omitted)
(omitted)
(omitted)
1.015062
1.607256
1.990114
1.619735
2.097202
1.64437
2.117614
1.149166
1.488205
1.091505
1.271812
1.565564
.9214246
1.461234
1.299892
1.193919
.4065398
-.4149755
1.055385
1.051722
.7763743
1.258596
1.227588
.9668755
.8235558
1.34873
1.692782
1.225782
.5769878
(omitted)
.8293972
.6958843
.0585622
-.2284635
-.3072079
.3819975
.0759782
.2808056
-.0928371
.2878526
-.1207298
.1257856
-.5916673
1.452149
1.718017
1.216616
1.903712
1.556965
.7163995
.7100683
1.648211
1.679987
.8254396
.864425
2.171705
6.569088
Std. Err.
t
Number of obs
F( 69, 14199)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
14269
422.86
0.0000
0.6727
0.6711
.57789
[95% Conf. Interval]
.066234
.0050671
.0068638
.0047455
.0295516
.0154299
.0457497
.0007859
.0848283
.0239255
.0692496
0.05
60.99
-65.64
-5.53
5.75
30.07
3.33
-14.69
-3.62
10.15
-11.23
0.959
0.000
0.000
0.000
0.000
0.000
0.001
0.000
0.000
0.000
0.000
-.1264229
.2990974
-.4639761
-.0355277
.1119949
.4336746
.0625875
-.013083
-.4732482
.1959126
-.9131818
.1332318
.3189617
-.4370682
-.0169242
.2278449
.4941637
.2419382
-.0100019
-.1406989
.2897068
-.6417052
.0381298
.0292061
.0232606
.0184397
1.78
1.85
1.71
1.55
0.076
0.064
0.088
0.121
-.0069796
-.0032376
-.0059223
-.0075605
.1424993
.1112582
.0852653
.0647281
.2323998
.2743325
.2923207
.2619079
.3213396
.281055
.3916336
.1493017
.1627817
.1387693
.1228705
.1964188
.1473513
.1626118
.162114
.203852
.1357813
.0775489
.1240507
.0859412
.1209476
.2326947
.1322982
.1743171
.1012073
.1176077
.2153797
.0908069
.1023426
4.37
5.86
6.81
6.18
6.53
5.85
5.41
7.70
9.14
7.87
10.35
7.97
6.25
8.99
8.02
5.86
2.99
-5.35
8.51
12.24
6.42
5.41
9.28
5.55
8.14
11.47
7.86
13.50
5.64
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.003
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.5595282
1.069528
1.417127
1.106361
1.467334
1.093466
1.349961
.8565154
1.169131
.8194991
1.03097
1.180558
.6325968
1.142494
.9821275
.7943427
.1403906
-.5669816
.8122296
.883266
.5393011
.8024841
.9682662
.6251912
.6251762
1.118204
1.270609
1.047789
.3763829
1.470596
2.144984
2.563101
2.133109
2.727069
2.195275
2.885268
1.441817
1.807278
1.363511
1.512654
1.950571
1.210252
1.779975
1.617657
1.593496
.6726891
-.2629694
1.298541
1.220178
1.013447
1.714708
1.48691
1.30856
1.021935
1.579257
2.114954
1.403776
.7775926
.2141378
.0721568
.1024908
.0998354
.1133161
.0714783
.0846166
.1041343
.0810503
.0607176
.0515765
.1201929
.0719809
.1494372
.1164299
.2110751
.2124037
.1024504
.0886966
.0848845
.0972489
.1178561
.0876708
.1480776
.2786956
.2692605
3.87
9.64
0.57
-2.29
-2.71
5.34
0.90
2.70
-1.15
4.74
-2.34
1.05
-8.22
9.72
14.76
5.76
8.96
15.20
8.08
8.37
16.95
14.25
9.42
5.84
7.79
24.40
0.000
0.000
0.568
0.022
0.007
0.000
0.369
0.007
0.252
0.000
0.019
0.295
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.4096589
.5544475
-.1423332
-.4241539
-.5293223
.2418906
-.0898815
.0766887
-.2517063
.1688382
-.2218264
-.1098082
-.7327592
1.159232
1.489799
.8028807
1.487373
1.356149
.5425424
.5436835
1.45759
1.448974
.6535933
.5741734
1.625425
6.041302
1.249135
.8373211
.2594577
-.0327731
-.0850934
.5221044
.241838
.4849225
.0660321
.4068669
-.0196332
.3613794
-.4505754
1.745065
1.946235
1.63035
2.320051
1.757781
.8902565
.876453
1.838832
1.911
.997286
1.154677
2.717985
7.096874
92
Pooled specification (6) data 2003-2008
Source
SS
df
MS
Model
Residual
11498.5173
70
5718.06948 17020
164.264532
.335961779
Total
17216.5867 17090
1.00740706
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.0606416
.3057893
-.4496022
-.0260716
.1670014
.4630421
.1523053
-.0113307
-.2744775
.2328311
-.7538385
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
-.0213197
-.0416121
-.0594258
-.0965951
-.1117398
(omitted)
(omitted)
.8095986
1.335815
1.69908
1.364561
1.78
1.355733
1.744054
1.003788
1.329581
.9522933
1.147633
1.377206
.7880096
1.301652
1.14181
.9961692
.2604486
-.3868122
.9199012
.9721445
.652465
1.032849
1.067446
.8109128
.7220988
1.23533
1.481546
1.132691
.4583566
(omitted)
.6526202
.6372257
-.1295898
-.1669801
-.1788239
.4068045
.0103353
.2735786
-.1158147
.2602036
-.1145299
.0113502
-.6665148
1.30385
1.600846
1.028018
1.706434
1.450716
.618625
.6077927
1.554422
1.573531
.7398123
.7284065
1.92816
6.474193
Std. Err.
t
Number of obs
F( 70, 17020)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
17091
488.94
0.0000
0.6679
0.6665
.57962
[95% Conf. Interval]
.0497238
.0046779
.0062922
.0043605
.0270888
.0141168
.0418548
.0007303
.0775936
.0221398
.0644329
1.22
65.37
-71.45
-5.98
6.16
32.80
3.64
-15.51
-3.54
10.52
-11.70
0.223
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
-.0368222
.2966202
-.4619357
-.0346186
.1139045
.4353717
.0702657
-.0127623
-.426569
.1894347
-.8801336
.1581055
.3149585
-.4372687
-.0175247
.2200983
.4907125
.234345
-.0098992
-.122386
.2762274
-.6275434
.0171255
.0202197
.0240519
.0304578
.0356919
-1.24
-2.06
-2.47
-3.17
-3.13
0.213
0.040
0.013
0.002
0.002
-.0548874
-.0812448
-.1065699
-.1562955
-.1816996
.012248
-.0019794
-.0122816
-.0368948
-.04178
.1756479
.2065129
.2197727
.1970453
.2403634
.2113092
.2933854
.1144984
.1242163
.106588
.0953225
.1490301
.1137881
.1237277
.1236825
.155171
.1049287
.0658245
.0958428
.0686118
.0936388
.1761872
.1010496
.1340151
.0803535
.0934549
.1656433
.0730285
.0819461
4.61
6.47
7.73
6.93
7.41
6.42
5.94
8.77
10.70
8.93
12.04
9.24
6.93
10.52
9.23
6.42
2.48
-5.88
9.60
14.17
6.97
5.86
10.56
6.05
8.99
13.22
8.94
15.51
5.59
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.013
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.4653106
.9310284
1.268303
.9783319
1.308863
.9415447
1.168988
.7793593
1.086104
.7433697
.9607911
1.085092
.5649732
1.059132
.8993799
.6920181
.0547775
-.5158351
.7320394
.8376582
.4689233
.6875039
.8693785
.5482293
.5645977
1.052149
1.156868
.9895479
.2977338
1.153887
1.740602
2.129858
1.75079
2.251137
1.769921
2.31912
1.228217
1.573058
1.161217
1.334475
1.669321
1.011046
1.544171
1.384241
1.30032
.4661197
-.2577893
1.107763
1.106631
.8360066
1.378194
1.265514
1.073596
.8795999
1.418512
1.806224
1.275835
.6189793
.1616965
.0605094
.0839983
.0791813
.0869271
.0586115
.0702896
.0855737
.0670859
.0527283
.0472476
.0959635
.0621396
.1160778
.0897529
.1609227
.1593145
.0816981
.0716039
.0694678
.0776242
.0922835
.0707803
.1155495
.2127591
.1825356
4.04
10.53
-1.54
-2.11
-2.06
6.94
0.15
3.20
-1.73
4.93
-2.42
0.12
-10.73
11.23
17.84
6.39
10.71
17.76
8.64
8.75
20.02
17.05
10.45
6.30
9.06
35.47
0.000
0.000
0.123
0.035
0.040
0.000
0.883
0.001
0.084
0.000
0.015
0.906
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.3356783
.5186211
-.2942352
-.3221837
-.34921
.2919198
-.1274397
.1058454
-.2473101
.1568508
-.20714
-.1767482
-.7883148
1.076325
1.424921
.7125934
1.394161
1.290579
.478274
.4716286
1.402271
1.392646
.6010756
.5019175
1.51113
6.116404
.969562
.7558304
.0350556
-.0117764
-.0084377
.5216892
.1481103
.4413118
.0156806
.3635565
-.0219198
.1994486
-.5447147
1.531374
1.776771
1.343444
2.018707
1.610853
.7589761
.7439568
1.706574
1.754417
.8785491
.9548956
2.34519
6.831982
Pooled specification (6) data 1997-1999
93
Source
SS
df
MS
Model
Residual
5519.64511
2617.49522
67
7994
82.3827628
.327432477
Total
8137.14032
8061
1.00944552
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
-.2058365
.2790353
-.4633351
-.0102846
.1530759
.4749805
.0744743
-.0103451
-.3229089
.2052493
-.4436933
(omitted)
(omitted)
(omitted)
.0048827
-.0049207
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
1.81757
2.500014
2.90716
2.504517
3.309794
2.452397
3.374223
1.51402
1.965739
1.566276
1.656058
2.08798
1.403393
2.02985
1.851228
1.802801
.8335691
-.5820368
1.48126
1.312469
1.175264
2.025043
1.518197
1.344725
1.292939
1.737333
2.242602
1.347174
.8605109
(omitted)
1.542081
.8556475
.4592363
-.734998
-.9214239
.3711037
.3335681
.6452608
.074151
.387545
-.1374342
.2163508
-.665109
1.938033
2.212092
1.628768
2.555684
1.834168
.9580012
.9849319
1.977406
1.923439
.7411561
1.114282
2.499874
7.589836
Std. Err.
t
Number of obs
F( 67,
7994)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
8062
251.60
0.0000
0.6783
0.6756
.57222
[95% Conf. Interval]
.0809934
.0066497
.0089956
.0064521
.0382452
.0205414
.0592913
.0007963
.0978612
.0252957
.0967508
-2.54
41.96
-51.51
-1.59
4.00
23.12
1.26
-12.99
-3.30
8.11
-4.59
0.011
0.000
0.000
0.111
0.000
0.000
0.209
0.000
0.001
0.000
0.000
-.3646047
.2660002
-.4809688
-.0229324
.0781053
.4347141
-.0417522
-.0119061
-.5147425
.1556632
-.6333501
-.0470683
.2920704
-.4457013
.0023633
.2280465
.515247
.1907008
-.008784
-.1310754
.2548355
-.2540366
.0160427
.0157639
0.30
-0.31
0.761
0.755
-.0265651
-.035822
.0363306
.0259806
.2840521
.3490762
.3817603
.3340667
.4347051
.3516314
.4962859
.1975841
.2219698
.1825846
.1599748
.2473472
.1749672
.2124545
.2162669
.2487064
.1640825
.1025164
.1333119
.1069374
.1562287
.2787335
.1749003
.2131584
.1491854
.2226329
.2962074
.124652
.145801
6.40
7.16
7.62
7.50
7.61
6.97
6.80
7.66
8.86
8.58
10.35
8.44
8.02
9.55
8.56
7.25
5.08
-5.68
11.11
12.27
7.52
7.27
8.68
6.31
8.67
7.80
7.57
10.81
5.90
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
1.260754
1.815734
2.15881
1.84966
2.457658
1.763108
2.401373
1.126704
1.530621
1.208363
1.342466
1.603115
1.060412
1.613384
1.427288
1.315271
.5119247
-.7829956
1.219933
1.102844
.8690149
1.478653
1.175346
.9268793
1.000496
1.300915
1.661958
1.102823
.5747029
2.374387
3.184295
3.65551
3.159375
4.161929
3.141687
4.347073
1.901336
2.400858
1.92419
1.969651
2.572845
1.746375
2.446316
2.275167
2.29033
1.155213
-.381078
1.742586
1.522094
1.481513
2.571434
1.861047
1.762571
1.585381
2.173752
2.823245
1.591524
1.146319
.2656189
.1020781
.1364137
.1018778
.1052969
.0664682
.0990638
.0909912
.1297468
.0808153
.0666175
.144499
.0728331
.1755231
.1806524
.2539961
.2554618
.1298851
.1214008
.1219661
.13446
.1596894
.0939544
.1794481
.3205898
.268541
5.81
8.38
3.37
-7.21
-8.75
5.58
3.37
7.09
0.57
4.80
-2.06
1.50
-9.13
11.04
12.25
6.41
10.00
14.12
7.89
8.08
14.71
12.04
7.89
6.21
7.80
28.26
0.000
0.000
0.001
0.000
0.000
0.000
0.001
0.000
0.568
0.000
0.039
0.134
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
1.021398
.6555477
.1918299
-.9347051
-1.127833
.2408087
.1393772
.4668943
-.1801866
.2291259
-.2680219
-.0669049
-.807881
1.593962
1.857966
1.130869
2.054912
1.57956
.7200241
.7458465
1.71383
1.610406
.5569809
.762517
1.871435
7.063426
2.062763
1.055747
.7266427
-.535291
-.7150145
.5013988
.527759
.8236272
.3284885
.545964
-.0068464
.4996065
-.522337
2.282104
2.566218
2.126666
3.056456
2.088777
1.195978
1.224017
2.240983
2.236472
.9253312
1.466047
3.128314
8.116246
Pooled specification (6) data 2000-2002
94
Source
SS
df
MS
Model
Residual
5875.1512
2826.32136
67
8543
87.688824
.33083476
Total
8701.47256
8610
1.01062399
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
-.1390997
.2990806
-.4658887
-.016722
.1389278
.4451444
.1073771
-.0112784
-.4186119
.2481037
-.7020479
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
.0119421
.007073
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
1.503901
2.204605
2.590174
2.205137
2.930547
2.235642
3.095216
1.411686
1.833066
1.404589
1.562201
1.92334
1.239638
1.812212
1.65333
1.702491
.731484
-.4947438
1.418144
1.227665
1.058371
1.778058
1.418787
1.218404
1.162856
1.584296
2.049284
1.329632
.670375
(omitted)
1.300094
.7852125
.3912643
-.4755292
-.5864723
.2996262
.2971035
.652541
-.0430051
.3662177
-.1169049
.2867491
-.6108985
1.826084
2.032567
1.527941
2.317177
1.749128
.9087793
.9340273
1.831628
1.862121
.8341963
.9806963
2.462481
7.33262
Std. Err.
t
Number of obs
F( 67, 8543)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
8611
265.05
0.0000
0.6752
0.6726
.57518
[95% Conf. Interval]
.064535
.0064131
.0088111
.0061584
.0378147
.0197123
.0585549
.0008105
.1129286
.0259225
.096777
-2.16
46.64
-52.88
-2.72
3.67
22.58
1.83
-13.92
-3.71
9.57
-7.25
0.031
0.000
0.000
0.007
0.000
0.000
0.067
0.000
0.000
0.000
0.000
-.265604
.2865094
-.4831606
-.0287939
.0648019
.4065035
-.0074047
-.0128672
-.6399793
.1972893
-.8917543
-.0125954
.3116518
-.4486168
-.0046501
.2130537
.4837853
.2221588
-.0096897
-.1972446
.2989182
-.5123415
.0151981
.0152284
0.79
0.46
0.432
0.642
-.0178499
-.0227783
.0417342
.0369243
.2391397
.2794559
.3022561
.2676435
.3524199
.2896732
.4111928
.1595504
.1713949
.149226
.1344081
.2035951
.153303
.1718805
.1763472
.2025629
.1378498
.0872207
.1250672
.0906339
.1324552
.2297967
.1311529
.1687353
.131351
.1598516
.2231723
.1020907
.1199384
6.29
7.89
8.57
8.24
8.32
7.72
7.53
8.85
10.69
9.41
11.62
9.45
8.09
10.54
9.38
8.40
5.31
-5.67
11.34
13.55
7.99
7.74
10.82
7.22
8.85
9.91
9.18
13.02
5.59
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
1.03513
1.656804
1.997679
1.680491
2.239719
1.667813
2.289179
1.098928
1.49709
1.11207
1.298728
1.524244
.9391271
1.475284
1.307647
1.305418
.4612651
-.6657174
1.172982
1.050001
.7987265
1.327601
1.161696
.8876417
.9053761
1.270948
1.611813
1.12951
.4352667
1.972673
2.752406
3.182669
2.729783
3.621375
2.803471
3.901253
1.724443
2.169041
1.697108
1.825673
2.322435
1.540149
2.149139
1.999013
2.099563
1.001703
-.3237702
1.663306
1.405329
1.318015
2.228515
1.675879
1.549166
1.420335
1.897644
2.486756
1.529755
.9054833
.236305
.0900493
.1263613
.0892727
.103119
.0645194
.0940087
.0961124
.1174119
.0764663
.0657881
.1259171
.0773526
.1521002
.1496863
.2152707
.220381
.1184849
.1042651
.1052775
.1159164
.1316464
.0910485
.1564769
.276407
.2191934
5.50
8.72
3.10
-5.33
-5.69
4.64
3.16
6.79
-0.37
4.79
-1.78
2.28
-7.90
12.01
13.58
7.10
10.51
14.76
8.72
8.87
15.80
14.14
9.16
6.27
8.91
33.45
0.000
0.000
0.002
0.000
0.000
0.000
0.002
0.000
0.714
0.000
0.076
0.023
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.8368791
.6086941
.1435657
-.6505252
-.7886104
.1731525
.1128237
.4641374
-.2731608
.2163252
-.2458654
.0399213
-.7625282
1.527931
1.739146
1.105959
1.885177
1.516869
.7043945
.7276579
1.604403
1.604062
.6557192
.6739638
1.920656
6.902948
1.763309
.9617309
.6389629
-.3005332
-.3843342
.4260999
.4813832
.8409446
.1871506
.5161102
.0120557
.533577
-.4592687
2.124237
2.325988
1.949924
2.749177
1.981387
1.113164
1.140397
2.058852
2.12018
1.012673
1.287429
3.004305
7.762292
Pooled specification (6) data 2008-2010
95
Source
.
SS
df
MS
Model
Residual
4413.68799
2272.78495
66
7349
66.8740604
.309264519
Total
6686.47294
7415
.901749553
exp
Coef.
lngdpi
lngdpj
ldist
linder
adj
com
col
mrdist
mradj
mrcom
mrcol
dum1995
dum1996
dum1997
dum1998
dum1999
dum2000
dum2001
dum2002
dum2003
dum2004
dum2005
dum2006
dum2007
dum2008
dum2009
dum2010
dumcan
dumfra
dumger
dumita
dumjap
dumunk
dumusa
dumaus
dumbel
dumden
dumfin
dumdut
dumnor
dumswe
dumswi
dumaut
dumgre
dumice
dumire
dumnew
dumpor
dumspa
dumsaf
dumtur
dumisr
dumarg
dumbra
dumchi
dumcol
dumequ
dummex
dumper
dumven
dumbol
dumpar
dumuru
dumalg
dumnig
dumegy
dummor
dumtun
dumira
dumkuw
dumind
dumhko
dumini
dumkor
dummal
dumpak
dumphi
dumsin
dumtha
dumhun
dumpol
dumchn
_cons
.0323938
.3032559
-.4385292
-.0256778
.1419916
.4410771
.1863676
-.0121091
-.1417577
.223981
-.7448279
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
(omitted)
.0331475
-.0102766
(omitted)
.769555
1.244267
1.603927
1.271968
1.676681
1.203237
1.754629
.8883371
1.229262
.8290942
.9468092
1.309232
.7156412
1.16463
1.045805
.8467554
.091273
-.6030949
.7455577
.8107812
.4931581
.9473085
.8852333
.7847502
.5477639
1.109509
1.377068
.9805643
.3683077
(omitted)
.7061
.5260846
-.8252837
-.238844
-.1213625
.2261665
.0453814
.3883075
.0737184
.1632384
-.2131239
(omitted)
-.8628351
1.157284
1.458061
1.021663
1.656895
1.248713
.4156904
.3659824
1.405547
1.486124
.6288149
.6881629
2.03415
6.531748
Std. Err.
t
Number of obs
F( 66, 7349)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
=
=
=
=
=
7416
216.24
0.0000
0.6601
0.6570
.55612
[95% Conf. Interval]
.1030929
.0071455
.0091317
.0064517
.0388484
.0206968
.0598074
.001121
.1158787
.0334951
.1123846
0.31
42.44
-48.02
-3.98
3.66
21.31
3.12
-10.80
-1.22
6.69
-6.63
0.753
0.000
0.000
0.000
0.000
0.000
0.002
0.000
0.221
0.000
0.000
-.1696979
.2892486
-.4564299
-.0383251
.0658375
.4005055
.0691279
-.0143066
-.3689132
.158321
-.9651339
.2344855
.3172632
-.4206284
-.0130306
.2181457
.4816487
.3036073
-.0099116
.0853979
.2896411
-.5245218
.0177861
.0202344
1.86
-0.51
0.062
0.612
-.0017183
-.0499419
.0680134
.0293887
.3474275
.4086092
.4333108
.3858799
.4747556
.3974699
.5815949
.221764
.2360281
.19628
.1725374
.2942332
.2207477
.2287247
.2407986
.3173313
.1982384
.158924
.1646012
.1142916
.1685257
.3549103
.1876614
.2719394
.1564273
.2000346
.3658608
.1401954
.1723705
2.22
3.05
3.70
3.30
3.53
3.03
3.02
4.01
5.21
4.22
5.49
4.45
3.24
5.09
4.34
2.67
0.46
-3.79
4.53
7.09
2.93
2.67
4.72
2.89
3.50
5.55
3.76
6.99
2.14
0.027
0.002
0.000
0.001
0.000
0.002
0.003
0.000
0.000
0.000
0.000
0.000
0.001
0.000
0.000
0.008
0.645
0.000
0.000
0.000
0.003
0.008
0.000
0.004
0.000
0.000
0.000
0.000
0.033
.0884974
.4432763
.754514
.5155331
.7460243
.4240822
.6145362
.453616
.7665797
.4443291
.6085864
.7324507
.2829123
.7162643
.573771
.224695
-.2973312
-.9146316
.4228922
.5867369
.1627994
.2515824
.5173632
.2516709
.2411214
.717384
.659876
.7057411
.0304121
1.450612
2.045259
2.453341
2.028404
2.607339
1.982392
2.894722
1.323058
1.691945
1.213859
1.285032
1.886014
1.14837
1.612996
1.51784
1.468816
.4798771
-.2915582
1.068223
1.034825
.8235168
1.643035
1.253103
1.317829
.8544063
1.501634
2.09426
1.255387
.7062032
.308736
.1175153
.2004411
.1368047
.1432978
.0943644
.137409
.1530158
.1465461
.0914815
.0810652
2.29
4.48
-4.12
-1.75
-0.85
2.40
0.33
2.54
0.50
1.78
-2.63
0.022
0.000
0.000
0.081
0.397
0.017
0.741
0.011
0.615
0.074
0.009
.1008888
.2957208
-1.218206
-.5070205
-.4022673
.0411852
-.2239798
.0883527
-.213554
-.0160915
-.3720349
1.311311
.7564484
-.4323618
.0293326
.1595423
.4111479
.3147425
.6882623
.3609909
.3425684
-.0542129
.1449159
.2541726
.1621399
.3354882
.2994154
.1594514
.1357419
.1392545
.150832
.1847278
.1195242
.2391175
.4732286
.4318309
-5.95
4.55
8.99
3.05
5.53
7.83
3.06
2.63
9.32
8.04
5.26
2.88
4.30
15.13
0.000
0.000
0.000
0.002
0.000
0.000
0.002
0.009
0.000
0.000
0.000
0.004
0.000
0.000
-1.146912
.6590328
1.14022
.3640101
1.069954
.9361422
.1495972
.0930036
1.109873
1.124004
.3945131
.219424
1.106486
5.685235
-.5787583
1.655535
1.775901
1.679316
2.243835
1.561283
.6817836
.6389612
1.701221
1.848244
.8631167
1.156902
2.961814
7.37826
96
Appendix 6: Pooled data correlations
INT
GDP
trade
Econ (3) Stat (3) Econ (6) Stat (6)
1995
3.2698 19.37124
-0.044
-3.37
-0.02
-1.79
1996
3.7414 4.628195
-0.043
-3.32
-0.017
-1.52
19971999
-0.041
-5.4
-0.01
-1.59
3.433167 1.901828
20002002
-0.043
-5.83
-0.017
-2.72
3.242733 4.594133
2003
3.6254 16.85151
-0.051
-3.99
-0.034
-3.17
2004
4.9436 21.51331
-0.051
-4.03
-0.034
-3.22
2005
4.4471 13.78824
-0.036
-3.04
-0.025
-2.51
2006
5.0732 15.48289
-0.031
-2.36
-0.013
-1.18
2007
5.1535 15.5783
-0.044
-3.32
-0.025
-2.26
20082010
2.2794 4.834431
-0.039
-5.2
-0.026
-3.98
INT
trade
GDP
Econ (3) Stat (3) Econ (6) Stat (6)
19951997
3.748933 9.159662
-0.046
-6.05
-0.017
-2.62
1998
2.5368 -1.60973
-0.044
-3.17
-0.014
-1.23
19992000
4.1142 8.430438
-0.037
-4.06
-0.007
-1
2001
2.1983 -4.10471
-0.035
-2.82
-0.012
-1.08
20022004
3.7992 14.40891
-0.052
-7.08
-0.031
-5.14
2005
4.4471 13.78824
-0.036
-3.04
-0.025
-2.51
20062007
5.11335 15.5306
-0.037
-4.03
-0.018
-2.38
2008
3.373 15.11429
-0.036
-2.79
-0.026
-2.33
2009
0.4863 -22.3008
-0.043
-3.45
-0.022
-2.15
2010
2.9789 21.68983
-0.04
-2.89
-0.031
-2.47
97
INT
GDP
trade
Econ (3) Stat (3) Econ (6) Stat (6)
1995
3.2698 19.37124
-0.044
-3.37
-0.02
-1.79
19961997
3.9885 4.053872
-0.047
-5.08
-0.016
-2
1998
2.5368 -1.60973
-0.044
-3.17
-0.014
-1.23
19992000
4.1142 8.430438
-0.037
-4.06
-0.008
-1
2001
2.1983 -4.10471
-0.035
-2.82
-0.012
-1.08
2002
2.8286 4.861896
-0.05
-4.04
-0.026
-2.56
20032007
4.64856 16.64285
-0.043
-7.58
-0.026
-5.53
2008
3.373 15.11429
-0.036
-2.79
-0.026
-2.33
2009
0.4863 -22.3008
-0.043
-3.45
-0.022
-2.15
2010
2.9789 21.68983
-0.04
-2.89
-0.031
-2.47
GDP
3.2698
3.7414
4.2356
2.5368
3.5271
4.7013
2.1983
2.8286
INT
trade
Econ (3) Stat (3) Econ (6) Stat (6)
19.37124
-0.044
-3.37
-0.02
-1.79
4.628195
-0.043
-3.32
-0.017
-1.52
3.479548
-0.052
-3.85
-0.014
-1.24
-1.60973
-0.044
-3.17
-0.014
-1.23
3.835666
-0.032
-2.52
-0.004
-0.4
13.02521
-0.042
-3.22
-0.011
-0.99
-4.10471
-0.035
-2.82
-0.012
-1.08
4.861896
-0.05
-4.04
-0.026
-2.56
1995
1996
1997
1998
1999
2000
2001
2002
20032008
4.435967 16.38809
2009
0.4863 -22.3008
2010
2.9789 21.68983
1995
1996
19971999
20002002
2003
2004
2005
2006
2007
20082010
-0.043
-0.043
-0.04
-8.1
-3.45
-2.89
-0.026
-0.022
-0.031
-5.98
-2.15
-2.47
INT
GDP
trade
Econ (3) Stat (3) Econ (6) Stat (6)
3.2698 19.37124
-0.044
-3.37
-0.02
-1.79
3.7414 4.628195
-0.043
-3.32
-0.017
-1.52
3.433167 1.901828
-0.042
-5.4
-0.103
-1.59
3.242733
3.6254
4.9436
4.4471
5.0732
5.1535
4.594133
16.85151
21.51331
13.78824
15.48289
15.5783
-0.043
-0.051
-0.051
-0.036
-0.031
-0.044
-5.83
-3.99
-4.03
-3.04
-2.36
-3.32
-0.017
-0.034
-0.034
-0.025
-0.013
-0.025
-2.72
-3.17
-3.22
-2.51
-1.18
-2.26
2.2794 4.834431
-0.037
-5.2
-0.026
-3.98
98
Appendix 7 Correlation matrixes
1e pooled regression based on negative trade
gdp
gdp
inttrade
econ3
stat3
econ6
stat6
1
0.5886
0.0682
0.6743
-0.1219
0.3629
inttrade
1
-0.3031
0.6224
-0.5884
-0.0601
econ3
stat3
1
0.2793
0.6405
0.428
1
-0.0763
0.4733
econ6
stat6
1
0.7614
1
2e pooled regression based on GDP
gdp
gdp
inttrade
econ3
stat3
econ6
stat6
1
0.8219
0.1517
-0.2974
-0.0042
-0.2443
inttrade
1
0.0842
-0.1813
-0.3868
-0.3752
econ3
stat3
1
0.8001
0.3353
0.6801
1
0.15
0.7186
econ6
stat6
1
0.7672
1
3e pooled regression based on average GDP
gdp
gdp
inttrade
econ3
stat3
econ6
stat6
1
0.7696
-0.004
-0.593
0.0299
-0.3871
inttrade
1
0.0897
-0.1888
-0.3754
-0.3381
econ3
1
0.3608
0.2534
0.2629
stat3
1
0.1084
0.7939
econ6
stat6
1
0.6452
1
4e pooled regression based on average international trade volume
gdp
gdp
inttrade
econ3
stat3
econ6
1
0.7329
-0.1409
-0.3427
0.1878
inttrade
1
-0.0318
-0.2508
-0.2773
econ3
1
0.2978
0.4143
stat3
1
0.4369
econ6
stat6
1
99
stat6
-0.1414
-0.2947
0.24
0.9263
0.7104
1
5e pooled regression based on international crises
gdp
gdp
inttrade
econ3
stat3
econ6
stat6
1
0.5886
0.0145
0.6743
0.1653
0.3629
inttrade
1
-0.3066
0.6224
0.3676
-0.0601
econ3
1
0.2573
0.1699
0.3397
stat3
1
0.4674
0.4733
econ6
1
-0.1178
stat6
1
100