2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
ECONOMIC GROWTH AND SOCIAL DEVELOPMENT: A PUZZLE
Dr Rukhsana Kalim
Professor of Economics, University of Mangement and Technology, Lahore, Pakistan,
e-mail: drrukhsana@umt.edu.pk. Cell: 042-03054440614
Muhammad Shahbaz
Lecturer, COMSATS, Institute of Information Technology, Lahore, Pakistan,
shahbazmohd@live.com.
Cell: 042- 0334-3664657
Acknowledgement
I am highly indebted to the University of Management and Technology, Lahore
(Pakistan) for providing me all the possible facilities to complete this paper.
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
1
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
ABSTRACT
Policy makers of developing countries usually face a dilemma of mismatch between
economic growth and social development. They target to achieve high rate of economic
growth with the proposition of its positive impact on social development. The growth
experience of developing countries has been confused and puzzled as contrary to the
expectations, the living standard of masses did not improve. The main aim of the present
paper is to investigate the causal relationship between economic growth and social
development in Pakistan for the period of 1971-2005. ARDL bounds testing approach
has been used to examine cointegration between the two parameters while Ng-Perron is
used to handle the problem of unit root. Finally, Toda and Yamamotoo (1996) and
variance decomposition method is applied to find out direction of causality between
economic growth and social development.
Our empirical evidence reveals that bivariate causal relationship is found between
economic growth and social development. Nevertheless, the effect of social development
on economic growth is much greater than the effect of economic growth on social
development. This indicates that trickle up hypothesis may be active dominantly in case
of Pakistan over the study period.
Keywords: Economic growth, Social Development
JEL Classification: O11, O16
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
2
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
ECONOMIC GROWTH AND SOCIAL DEVELOPMENT: A PUZZLE
ABSTRACT
Policy makers of developing countries usually face a dilemma of mismatch between
economic growth and social development. They target to achieve high rate of economic
growth with the proposition of its positive impact on social development. The growth
experience of developing countries has been confused and puzzled as contrary to the
expectations, the living standard of masses did not improve. The main aim of the present
paper is to investigate the causal relationship between economic growth and social
development in Pakistan for the period of 1971-2005. ARDL bounds testing approach
has been used to examine cointegration between the two parameters while Ng-Perron is
used to handle the problem of unit root. Finally, Toda and Yamamotoo (1996) and
variance decomposition method is applied to find out direction of causality between
economic growth and social development.
Our empirical evidence reveals that bivariate causal relationship is found between
economic growth and social development. Nevertheless, the effect of social development
on economic growth is much greater than the effect of economic growth on social
development. This indicates that trickle up hypothesis may be active dominantly in case
of Pakistan over the study period.
Keywords: Economic growth, Social Development
JEL Classification: O11, O16
INTRODUCTION
Economic growth and social development of the country reflect the well-being of
individuals. The general belief is that economic growth is panacea for all the economic
miseries via its positive impact on social development. The underlying proposition
behind economic growth is that higher per capita income raises the living standard of
people. The growth experience of developing countries revealed mixed trend. The East
Asian countries like Korea, Taiwan, Malaysia, Indonesia, Thailand and Philippines
experienced high growth rate and were successful in eradicating poverty. Contrary to this
the South Asian Countries like Pakistan, India, Nepal, Bangladesh etc. could not uproot
the poverty despite their satisfactory growth rates. These countries experienced different
growth models and witnessed spectacular growth rate in Gross Domestic Product.
Nevertheless, the benefits of economic growth in these countries had not been transmitted
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
3
2010 Oxford Business & Economics Conference Program
effectively to the poor segments of the society.
ISBN : 978-0-9742114-1-9
The poverty condition of masses
remained deplorable.
Since the beginning of the 1970s, the focus has been shifted from economic growth to
social development. The argument put forward was to target social development than
economic growth as the former would improve the living conditions of people (Sen,
1985). UNDP's Human Development Report (1990) clearly states that the main objective
of the development is to provide such environment to individuals that would guarantee
healthy, long and productive life. There is no denying fact that economic growth and
social development are knitted together and there is causal relationship between the two.
The Millennium Declaration signed by 189 countries in September 2000 set the
Millennium Development Goals like eradicating extreme poverty and hunger, achieving
universal primary education, reducing child mortality, and combating certain diseases etc
(The World Bank, 2008). The prime emphasis to achieve the Millennium Development
goals has been placed on creating such an environment in developing countries that
would enhance the development process and be helpful in eliminating poverty (The
World Bank, 2008).
The empirical evidence about the direction of causality between economic growth and
social development is still inconclusive (the discussion is followed in economic literature
section). This paper is an attempt to test the trickle down and trickle up hypothesis in the
case of Pakistan using new developed index of social development. Time series data of
34 years spanning from 1971-2005 is used.
The paper is organized into different sections. Section II discusses the causal relationship
between economic growth and social development both from theoretical as well as
empirical point of view. Section III briefs the growth and social development of Pakistan
in historical perspective. Section IV discusses the procedure of developing social
development index. Section V explains methodology of testing the causal relationship
between economic growth and social development. Section VI discusses results. The
final section VII concludes the findings and gives some policy implications.
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
4
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
II. LITERATURE REVIEW
The causal relationship between economic growth and social development is based on the
proposition that both are imperative for the progress of the economy. The economic
literature mentions two approaches regarding the causal relationship between economic
growth and social development “trickle down” and “trickle up”. “Trickle down” model of
development remained powerful for a longer period of time. The model is based on
Rostovian stages of development model, in which the economy experiences different
stages of development finally to reach to a modern developed society. A group of
researchers believes that the distribution of material well being is improved by the
increase in per capita income (Hagen, 1980; Ram, 1985). Goldstein (1985) in his model
assumes that economic factors will strongly affect at least one component of basic needs,
infant mortality rates. Ram (1985) sees the improvement in basic needs fulfillment
because of the increase in average per capita income. Bruno et al (1996) and Deininger
and Squire (1996) advocate that economic growth reduces poverty but the extent of
reduction in poverty depends on the level of income distribution. Jamal (1989) finds in
his empirical study that social development is the outcome of economic growth in
Pakistan.
The empirical study for the period of 1971-72 to 2003-04 by Iqbal and
Khurrum(2006) supports trickle down hypothesis for Pakistan and concludes that real
economic development is the cause of social development. Contrary to this, Shahbaz
(2010) concludes in his empirical study that economic growth in Pakistan increases
income inequality which is a major obstacle in social development.
Trickle up proposition is based on the assumption that social development enhances
economic growth. Streeten (1977) propagated the basic needs approach for economic
growth. According to him public services can play effective role in satisfying the basic
needs of individuals. He also views the role of improved education, and health in
economic growth (Streeten, 1981).
There is another opinion that acceleration of
economic growth takes place mainly because of the development of basic human capital
(Hicks (1979, 1980). According to Thompson (1991) economic growth depends on social
development. Temple and Johnson (1998) test the predictive power of social
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
5
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
development indexes developed in the early 1960s to explain economic growth. Their
results suggest the importance of “social capability” for economic growth.
According to Srinivasan, (1977) economic growth and social development are
interwoven. The new paradigm shift rejects the income as the sole measurement of
development or of the quality of life. Different indices of development have been
constructed that include various parameters of development. For example, UNDP (1999)
uses "Human Development Index" that includes variables like life expectancy, literacy
education and income. Human Poverty Index by excluding income includes access to
safe water, access to health services, and underweight children under five as a measure of
standard of living. Sen (1985, 1992) suggests a broader measure of the well-being of
people and uses "functionings" – or the ability to do things approach. Kenny (2005)
makes an effort to estimate the relationship between GDP/per capita growth and growth
in subjective well being in his cross-country analysis. By applying regression techniques
his results for low income countries show a positive relationship between income and
social well-being. Donglin (1996) in his study explains the past 15-year development of
Changzhou city of China and social development. He includes science and technology,
education, physical culture, public and social security, public health care, livelihoods,
standards of living and family life in the development process and concludes that
economic growth does not inevitably result in sustainable development (Donglin, 1996).
In the nutshell, the economic literature shows mixed evidence on the direction of
causality between economic growth and social development.
III. ECONOMIC GROWTH AND SOCIAL DEVELOPMENT IN PAKISTAN
Pakistan's growth experience was spectacular during the 1960s. Import substitution
industrialization policy was adopted and the era of 1958-1968 was called 'the Decade of
Development' with average GDP growth rate of 6.8%. The benefits of this high growth
could not be trickled down to the poor segment of the society. High income inequality
brought political unrest in the economy (see for details Zaidi, 2005). Proponents of high
income inequality argued that inequality would lead to growth via generating more
savings in the economy (Papanek, 1967). The era of 1970s witnessed slow growth
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
6
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
because of many national and international factors. Economic growth on average, showed
a mixed trend in the subsequent year. For example, it was 4.8% in the 1970, and 6.5% in
the 1980s, 4.6% in the 1990s and in the era of 2000-2008 (Pakistan Economic Survey,
2007-08). According to Zaidi (2005) Pakistan presents a development paradox, despite
respectable economic growth its social sector development is disappointing. The growth
did not transmit trickle down effect on social sector development.
The United Nations Development Programme’s (UNDP) Human Development Report
2009 has ranked Pakistan 141 out of 182 countries in terms of the human development
index (HDI). The Human Poverty Index (HPI-1), value of 33.4% for Pakistan, ranks 101st
among 135 countries in year 2007. The under-five years mortality rate is 97 per 1,000
live births in 2006 as compared to India and Bangladesh where it is 57 and 52
respectively. Life expectancy at birth is 66 which is almost the same in India and
Bangladesh. Adult literacy rate is 64% and 35% in male and female respectively which
is mush lower than her neighboring country like India. In perspective of the slow-paced
progress of the country, it is obvious that its progress is falling behind the UN millennium
development goals (MGD) targets.
One may say that fruits of economic growth have not been transmitted to the masses of
the society in Pakistan.
The economic growth record shows an upward trend over a period of time. Social
development index is following the pace of economic growth at a very sluggish rate
(Figure 1) with the exception of one year, 2000-2001 when social development index
dropped down rapidly. Structural changes and political factors brought the sudden fall in
the social development index.
Figure-1 Trends in Economic Growth and Social Development
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
7
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
Social Development and Economic Growth
220
200
Indices
180
160
140
120
100
80
1970
1975
1980
1985
1990
Years
Social Development
1995
2000
2005
Economic Growth
Economic growth has pulled up the social development that was lagging much behind the
rate of economic growth. From social development perspective, economic growth did not
bring any change in the standard of living of masses
IV. CONSTRUCTION OF SOCIAL DEVELOPMENT INDEX (SDI)
In order to test causality between economic growth and social development the
appropriate indicators for the two are to be selected. As far as economic growth is
concerned, the standard measure is per capita gross domestic product.
For Social
development, the relevant economic literature uses various variables as a proxy for social
development. Some seem to generate index to indicate social development (Mazumdar,
1996) and some use human development index as proxy for social development (UNDP,
2009, Shahbaz, 2010). Many problems are encountered in the construction of social
development index. For example, if index is based on subsets then there will be a
problem of multicolinearity. This leads to influence the reliability and predicting power
of the model. The excessive variables in the model may increase the cost to process and
collect the data of relevant variables. It is necessary for an analyst to reduce
multicolinearity by using appropriate procedure to generate a reasonable proxy or index
for necessary variables to be used in the model for more reliable and accurate results.
Principal component analysis (PCA) is an appropriate way to generate a suitable proxy
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
8
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
by using relevant variables. It is very useful to generate an index when we have subsets
of measurements that are computed on identical levels which are highly interrelated. In
doing so, we find a suitable variable which describes the explaining power of all
variables included in subsets and combination of weights (scale). Keeping above, the
present study uses the principal component analysis (PCA) approach to generate an index
of social development for Pakistan using time series of all variables.
Three broad categories for measuring SDI are taken viz; Demographic, Health; and
Education. Demographic category includes telephone lines per 1000; urban population as
a percentage of total population, life expectancy at birth, infant mortality rate. In the
health category variables taken are; physician per 1000 of population and calories intake
per capita as percentage of requirement; two variables pupil teacher ratio, and adult
literacy rate as a percentage of total population over age 15 years are included in the
category of education.
Hence total eight variables have been included in the
measurement of SDI. The choice of variables depends on the availability of data. The
justification for the inclusion of these variables in the construction of SDI is followed
below:
Telephone Lines (TL): The greater access to telephone lines to a number of populations
indicates the progress towards human development.
Urban Population (UP): The underlying assumption behind the urban population as a
percentage of total population is that this percentage of population enjoys many facilities
associated with cities like medical, sanitation, and educational facilities (Mazumdar,
1996). Moreover urbanization is replica of economic development of a country.
Life Expectancy at Birth (LEB): Life expectancy at birth reflects general conditions of
health, nutrition, and income level. High rate of LEB shows better health facilities.
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
9
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
Infant Mortality Rate (IMR): Nutrition and sanitary conditions of the country are
reflected by the infant mortality rate. It also shows how effective is the system of
vaccination and protection against contagious diseases in the country.
Physicians (Phys): An important aspect of social development is the availability of
health services. If the ratio of physicians to population is high it means better health
services are provided to the citizens. In poor countries this ratio is expected to be low as
compared to rich countries. Physician per thousand of population, therefore, reflects a
general picture of the health care facilities available in a country.
Calories Intake (CAL): There is some minimum requirement of calorie intake per
person for good health. Calorie intake below the minimum requirement in any country
shows the dismal picture of social development there. Malnutrition is the outcome of low
calorie intake which in turns affects the productivity.
Pupil Teacher Ratio (PTR): Pupil teacher ratio indicates the quality of education.
Higher ratio means that number of pupil assigned to one teacher is high that affects the
quality of education.
Adult Literacy Rate (ALR): This indicator also reflects the quality of life. High adult
literacy rate shows that one of the basic human rights is provided to the people of the
country. Thirty four year annual data is collected for the period of 1971-2005. The data
for all variables has been collected from different World Development Indicators (WDICD-ROM, 2008)1.
V. METHODOLOGY AND DATA
In the present study, two different approaches are applied to find out order of integration
and cointegration between social development and economic growth. The methodological
backgrounds of both tests have described respectively.
1
The data on SDI is available from authors upon request.
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
10
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
Ng-Perron Unit Root Test
Ng-Perron (2001) developed a test statistics wherein GLS is applied to de-trend the
series Dtd . The critical values of the tests are based on those of Philip-Perron (1988)
Z  and Z t statistics, Bhargava (1986) R1 statistics, and the Elliot, Rotherberg and Stock
(1996). The following annotations are used:
k 
T
 (D
d
t 1
t 2
(2)
)2 / T 2
The de-trended GLS tailored statistics is given by:
MZ ad  (T 1 ( DTd ) 2  f  ) /( 2k )
MZ td  MZ a  MSB
MSB d  (k / f  )1 / 2

2

 2
MPTd  (ck  c T 1 ( DTd ) 2 / f  , and , (c k  (1  c)T 1 ( DTd ) 2 / f  …

(3)
ARDL Bound Testing for Cointegration
The ARDL bound testing method is applied to confirm the existence of cointegration
between two macroeconomic series. Let
xt
represent a time series vector
xt  {GDPC, SDI } is applied within an unrestricted vector autoregression (VAR)
framework:
q
zt      j zt   t
(4)
j 1
where, z t  [ y t , xt ]' ;  is a vector of constant,   [ y ,  x ]' and  is a matrix of vector
autoregressive (VAR) parameters of lag j. Following Pesaran, Shin and Smith [PSS]
(2001), a pair of time series yt and xt may be stationary at either I(0) or I(1) or integrated
at
mixed
order
of
integration
i.e.
I(0)
/
I(1).
The
error
terms
vector
 t  [ y ,t ,  x,t ]' ~ N (0, ) , where  is positive definite. Equation-4 in its modified form
can be written as a vector error correction model as given below:
q 1
z t    z t 1    j z t   t
(5)
j 1
where,   1  L , and
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
11
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
yy , jyx,
j  
xy, jxx,
q
j


k

j
k  j 1

Here,  is the long run multiplier matrix written as follows:
q
yyyx 
 j  


(
I

j)


j 1
x yx x
(6)
(7)
I represent an identity matrix. The diagonal essentials for the matrix are left unrestricted.
This entails that every variables may be integrated at either I(0) or I(1). Using said
procedure, one can find maximum number of cointegrating equations which includes
both yt and xt , such that either yx or xy can be non-zero, or zero. To check the affect of
economic growth on social development in long span of time, the restriction
xy  0 indicates that economic growth has no long run impact on social development.
Under this assumption (that is xy  0 ), Equation-7 can be rewritten as follows:
q 1
q 1
j 1
j 1
yt      T  1 yt 1   2 xt 1   y, j yt  j   x, j yt  j  xt   t
(8)
where;
   y   '  x ; 1  yy ; 2  yx   'xx ;  y, j  yy , j   'xy , j
and  x. j   yx, j   ' xx, j .
Simply for empirical estimations we are going to estimate two empirical models such as
q 1
q 1
j 1
j 1
GDPCt     T T   GDPCGDPCt 1   SDI SDI t 1    GDPC GDPCt  j    SDI SDI t  j   t
q 1
q 1
j 1
j 1
SDI t      T T   SDI SDI t 1   GDPCGDPCt 1    SDI SDI t  j    GDPC GDPCt  j   t
(9)
(10)
The ARDL model of PSS (2001) is represented by an unrestricted error correction model
(UECM). Both equations 9 and 10 can be estimated by ordinary least squares. The Fstatistics is used to test the long run relation among the series. The null hypothesis
is:  GDPC   GDPC   SDI   SDI  0 against the alternate  GDPC   GDPC   SDI   SDI  0 .
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
12
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
We may posit that there is long run association is existed between variables whether
underlying variables are integrated at I(0) or I(0) if generated upper critical bound is less
than our calculated F-statistics. The decision of no cointegration is accepted if calculated
F-statistics is less than lower critical bound. Finally, it is documented that the decision
about cointegration is unconvincing when calculated F-statistics is between lower and
upper critical bounds. Furthermore, the decision about cointegration is made based on
upper critical value if running variables are stationary at 1st difference. If running
variables are integrated at I(0) then decision about cointegrated is taken basing on lower
critical bounds. In doing so, ARDL bounds testing approach is used to investigate long
run association between the variables. In terms of the PSS (2001), the distribution of Fstatistics is based on the order of integration of the series. The ARDL bound testing
calculates (p + 1)k number of regressions, where p refers to the appropriate order of the
lag and k to the number of actors in the equation to be estimated. The stability test is
conducted by employing CUSUM and CUSUMsq.
Toda and Yamamoto (1995) approach is being employed to examine the direction of
causal relation between economic growth and evolution of social development in the case
of Pakistan. This approach solves the problem of unacceptable asymptotic critical bounds
when causality tests are applied over the non-stationary time series. Toda and Yamamoto
(1995) causality approach is applicable if variables are stationary at different order of
integration (Zapata and Rambaldi, 1997). The augmented approach of non-causality
developed by Toda and Yamamoto (1995) is applicable in level vector auto regressions
(VARs) irrespective of whether variables are integrated at same order of integration or
not. VAR can be estimated with out true lag order k but it is applicable with (k  d ) lag
order where d indicates possible order of integration for variables. The Toda and
Yamamoto (1995) causality test is examined by performing hypothesis exercise
disregarding the additional lags k  1,..., k  d in vector auto regression (VAR). The TodaYamamoto causality technique involves the estimation of the following models:
GDPC    
k  d max
 GDPC
i 1
2
t 1
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK

k  d max
 SDI
i 1
3
t i
 1
(11)
13
2010 Oxford Business & Economics Conference Program
SDI    
k  d max
k  d max
i 1
i 1
  2 SDI t i 
ISBN : 978-0-9742114-1-9
  GDPC
3
t i
 2
(12)
Where, GDPC and SDI indicate economic growth and social development repetitively. In
the models, each variable is regressed on each other with lag order starting from 1
towards k  d max , 1 and  2 are the error terms, k indicates the maximum number of
lags to be taken while d shows order of integration of running variables. Since the
procedure requires a VAR only in levels, it does not lead to a loss of information as it
would happen in the case of differencing. For this reason, the procedure can be used only
as a long-run test.
V1. RESULTS
The report on descriptive statistics and correlation matrix between variables is briefed in
Table-1. The empirical evidence by Jarque-Bera confirms that economic growth and
social development are normally distributed. The correlation coefficient indicates high
correlation between economic growth and social development over the time period taken
for the case of Pakistan.
Table-1 Descriptive Statistics and Correlation Matrix
Variables
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
Jarque-Bera
Probability
GDPC
SDI
GDPC
9.96034
10.0392
10.3356
9.54057
0.25798
-0.34805
1.61914
3.48737
0.17487
1.00000
0.88693
SDI
4.76237
4.76489
4.99886
4.60362
0.11378
0.39900
2.17751
1.91525
0.38380
0.88693
1.00000
The relevant economic literaure indicates that ARDL bounds tesing appriach is
applicable without distinguishing the intgertaing order of running actors in the model. In
other word, there is no problem if variables are integrated at I(0), I(1) or variabes are
stationary at mixed order. Sezgin and Yildirim (2002) have noted that alternative
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
14
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
cointegration approcah requires that variables should be stationary at same level of
integration to exmaine cointegration among the variables. But ARDL abounds testing
approch for cointegration is till applicable if variables are staionary at ambegious
integrating order i.e. I(1) or I(0). Ouattara (2004) probes that F-value generated by PSS
(2001) is based on assumptions such as variables should be inetgarted at I(0) or I(1). The
generated value of F-values becomes useless if any variables is stationary at 2nd
difference i.e. integrated at I(2). İt indicates that there is need to apply unit root test. The
application of unit root tests ensures us that no variable is integrated at I(2).
In doing, Ng-Perron (2001) test is applied to ensure that EC and SDI are integrated at I(1)
or I(0) or integrated at mixed order of integration. The Ng-Perron test is more suitable for
small sample data set and provides results with high explanatory power as compared to
other traditional tests such as ADF (Dicky and Fuller, 1979), P-P (Philip and Perron,
1989) and DF-GLS (Elliot et al. 1996). Mentioned tests have poor properties and poor
size (Harris and Sollis, 2003). Results of Ng-Perron unit root are reported in Table-2. The
empirical results show that economic growth (GDPC) and social development (SDI) are
stationary at I(1) rather than at I(0). The similarity of integrating order leads us to apply
ARDL bounds testing approach to examine cointegration between economic growth and
social development in Pakistan. The existence of cointegration will confirm the long run
relationship between both variables.
Table-2 Ng-Perron Unit Test with Intercept and Trend
Variables
MZa
GDPC
-2.7940
ΔGDPC -20.2917**
SDI
-12.0898
ΔSDI
-23.2106**
MZt
-1.1428
-3.1564
-2.3999
-3.3999
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
MSB
0.4090
0.1555
0.1985
0.1464
MPT
31.4097
4.6631
7.8464
3.9657
15
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
Table-3 Lag Length Selection
Lag
LogL
AIC
SC
1
147.2503
-8.3088
-8.0394
2
148.1657
-8.3736*
-7.9201*
* indicates lag order selected by the criterion
LogL: Log likelihood
AIC: Akaike information criteionr
SC: Schwarz information criterion
The two step procedure of ARDL bound testing by PSS (2001) requires lag length of
variables. The order of lag length has been selected by estimating 1st difference of the
conditional error correction version of ARDL. The Akaike Information Criteria (AIC) is
used to select the lag order of variables. It is also revealed in empirical literature that the
calculation of ARDL F-statistics is sensitive to the selection of lag order in the model
(see for example, Bahmani-Oskooee and Brooks 1999; Bahmani-Oskooee et al 2006 and
Bahmani-Oskooee and Harvey 2006). Based on the results, the appropriate lag length is
selected as 2. It shows the number of total regressions generated by following ARDL
methodology that is (2+1)2 = 9 in every estimated equation. Table-3 indicates the
appropriate lags based on estimates that we can not take lag more than 2 in such sample
data set. The appropriate selection of lag order is necessary for unbiased and reliable
results.
The empirical results reported in Table-4 reveals cointegration between economic growth
and social development. We have used critical bounds generated by Turner (2006). The
main reason is that critical values developed by PSS (2001) and Narayan (2005) are less
suitable for small data set. The calculated F-statistics is 6.1150. It entails that upper
critical bounds is less than calculated F-statistics at 10 % level of significance. If we
compare our calculated F-value with critical values developed by PSS (2001) then
cointegration is existed at 5% significance level. It is concluded that both criterion show
cointegration. This implies long run relationship between economic growth and social
development for the case of Pakistan over the period.
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
16
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
Table-4 ARDL Bound Testing Procedure for Cointegration
Dependent Variable
Lag
GDPC
SDI
Pesaran et al (2001) a
Critical
Lower
Upper
Values
Bound
Bound
1%
6.84
7.84
5%
4.94
5.73
10 %
4.04
4.78
F-Statistic
2
4.4767
6.1150*
Turner (2006) b
Lower
Upper
Bound
Bound
7.763
8.922
5.264
6.198
4.214
5.039
* indicates significance at 10 % level with unrestricted intercept and trend
a
Critical values are obtained from Pesaran et al (2001).
b Critical Values are from Turner. P (2006)
The direction of causal association between economic growth and social development
(one-way causality or bivariate causality) is examined by applying Granger causality.
Actually, when long run relation or cointegration is found between the variables then
investigation of causal relation is necessary but not sufficient condition (Morley, 2006). It
is documented that cointegration between the variables suggests that there must be causal
relation at least running from one side.
Table-5 Granger- Causality Analysis
Direction of Causality at lag 1
Null Hypothesis
F-Statistic Probability
SDI does not Granger Cause GDPC
3.55324
0.06883
GDPC does not Granger Cause SDI
6.26370
0.01781
SDI does not Granger Cause GDPC
3.45242
0.04569
GDPC does not Granger Cause SDI
3.31720
0.05095
Direction of Causality at lag 2
It is argued by Groenewold et al. (2007) that Granger-causality test is applicable whether
variables are integrated at different orders of integration if long run relationship is found.
The use of Granger causality test is justifiable after establishing cointegration and stable
long run relationship between underlying variables. The empirical evidence on the
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
17
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
direction of causality is reported in Table-5. The results are on the basis of both lags.
Results based on lag-2 are more appropriate and indicate bivariate causality between
economic growth and social development. Although, there is two-way causal relationship
between said variables but strong causality is running from social development to
economic growth. This indicates that trickle up hypothesis is more active dominantly in
case of Pakistan over the study period.
Variance decomposition is a better option as compared to impulse response function to
investigate the response of regressand variable due to innovative shocks of forcing or
regressor or independent variables. This approach is used to explain how much of
predicted error variance for any variable is described by innovative shocks by each
forcing variable in the system over the time periods. The empirical evidence about
explanation of one variable through its innovative shocks and innovative shocks of other
variables is reported in Table-6. The results indicates that economic growth (GDPC) is
explained 100% by its innovative shocks at initial time horizon while 0.000% by social
development (SDI) innovative shocks but social development is described 99.17556% by
its shocks and rest is by economics growth (GDPC).
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
18
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
Table-6 Variance Decomposition Approach
Variance Decomposition of GDPC
Period
S.E.
GDPC
SDI
1
0.017939
100.0000
0.000000
2
0.025474
99.28721
0.712791
3
0.033479
91.74363
8.256366
4
0.041771
83.45230
16.54770
5
0.049568
77.40263
22.59737
6
0.056618
73.28632
26.71368
7
0.062932
70.45005
29.54995
8
0.068601
68.43330
31.56670
9
0.073721
66.95035
33.04965
10
0.078378
65.82557
34.17443
11
0.082642
64.94878
35.05122
12
0.086569
64.24895
35.75105
13
0.090205
63.67889
36.32111
14
0.093587
63.20641
36.79359
15
0.096743
62.80890
37.19110
Table-7: Variance Decomposition Approach
Variance Decomposition of SDI
Period
S.E.
GDPC
SDI
1
0.043346
0.824436
99.17556
2
0.052467
0.662033
99.33797
3
0.054046
0.923809
99.07619
4
0.054427
2.053766
97.94623
5
0.054959
3.758551
96.24145
6
0.055741
5.672853
94.32715
7
0.056667
7.574573
92.42543
8
0.057649
9.365149
90.63485
9
0.058634
11.01323
88.98677
10
0.059598
12.51741
87.48259
11
0.060527
13.88766
86.11234
12
0.061419
15.13721
84.86279
13
0.062271
16.27931
83.72069
14
0.063086
17.32603
82.67397
15
0.063864
18.28804
81.71196
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
19
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
Table-6 and 7 shows that how Variance Decomposition method breaks forecast error
variance of running variables into its components using VAR mechanism. In doing so,
innovative shocks indicate accurate explanations basing on their association. The forecast
error variance decomposition approach of unrestricted VAR (3) is used to estimate the
forecast error over a 15-year time period. It is noted that economic growth (GDPC) is
explained almost 63% by its innovative while 37% portion of economic growth is
described by innovative shocks of social development (SDI) at 15th time period. Table-7
reports that innovative shocks of economic growth (GDPC) elucidate social development
(SDI) 18% while rest (almost 82%) is enlightened by innovative shocks of social
development (SDI). This result also supports the findings of Granger causality test that
trickle-up hypothesis is dominantly active in the case of Pakistan.
VI1. CCONCLUSION AND POLICY IMPLICATIONS
Policy makers of developing countries usually face a dilemma of mismatch between
economic growth and social development. They target to achieve high rate of economic
growth with the proposition of its positive impact on social development. The growth
experience of developing countries has been confused and puzzled as contrary to the
expectations, the living standard of masses did not improve. The economic literature has
discussed two hypotheses “trickle-up” and “trickle-down” regarding the nexus between
economic growth and social development. The former hypothesis propagates that social
development causes a change in economic growth. The latter rests on the assumption that
economic growth is a prerequisite for social development of the economy.
The paper has examined the causal relationship between economic growth and social
development in Pakistan. Cointegration test supported the long-run relation between
economic growth and social development. The Granger Causality test shows that there is
bi-directional causality from economic growth to SDI and from SDI to economic growth.
The variance decomposition approach tells that the share of SDI to the variations in GDP
per capita is 37 percent and the share of GDP per capita to the SDI variation is 18
percent. These results show that the response of SDI to economic growth is much higher
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
20
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
than the other way round. Contrary to the study done by Jamal (1989) that supported the
trickle down hypothesis in case of Pakistan, the results in the present study do not reject
exclusively trickle down or trickle up hypothesis. However as the effect of SDI on GDP
per capita is greater than the effect of GDP per capita on SDI, trickle up hypothesis may
be stronger in case of Pakistan.
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
21
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
References
Bahmani-Oskooee, M, and Harvey, H. (2006). How Sensitive are Malaysia’s Bilateral
Trade Flows to Depreciation?. Applied Economics, (38), 1279-1286.
Bahmani-Oskooee, M., and Brooks, T. J. (1999). Bilateral J–Curve between US and Her
Trading Partners. Weltwirtschaftliches Archiv, (135), 156–165.
Bahmani-Oskooee, M., Economidou, C., and Goswami, G. (2006). Bilateral J-Curve
between the UK vis-à-vis Her Major Trading Partners. Applied Economics, (38), 879 –
888.
Bhargava, A. (1986), “On the Theory of Testing for Unit Roots in Observed Time
Series”, The Review of Economic Studies, pp: 369-384.
Bruno, M., Ravallion, M. and Squire L.(1996), ‘Equity and Growth in Developing
Countries: Old and New Perspectives on the Policy issues’, Policy Research Working
paper Series 1563, The World Bank.
Donglin, Z.(1996), 'Rapid Economic Growth and the Coordinated Social development:
Changzhou, China, Royal Swedis Academy of Sciences, Ambio, Vol. 25, 2.
Deininger, . and Squire, L. (1996), ‘A New data set, Measuring Income Inequality’,
World bank Economic Review, Vol 10.
Dickey, D., Fuller, W.A. (1979), “Distribution of the Estimates for Autoregressive Time
Series with Unit Root”, Journal of the American Statistical Association, 74, pp: 427-31.
Elliott, G., Rothenberg, T.J. and Stock, J.H. (1996), “Efficient Tests for an
Autoregressive Unit Root”, Econometrica, 64, pp: 813–836.
Goldstein, J.S. (1985), Basic Human needs: The Plateau Curve” World development, Vol.
13, 5, 595-609.
Groenewold, N. and Tang, S. H. K. (2007). Killing the Goose that Lays the Golden Egg:
Institutional Change and Economic Growth in Hong Kong. Economic Inquiry, Online
Early Articles. Published article online: 22-Feb-2007.
Hagen E.E., (1980), The Economics of Development, IL; Richard D. Irwin.
Harris, R., and Sollis, R. (2003), “Applied Time Series Modeling and Forecasting” ,
Wiley, West Sussex.
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
22
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
Hicks N.L., (1979), “Is there a Trade-off between Growth and Basic needs?” Finance
and Development, June Vol. 17, 2, 17-20.
Jamal, H. (1998), “The Social Development and Economic Performance of Pakistan
1960-1997”, Paper presented in AERC Conference, University of Karachi
Kenny, C. (2005), ‘Does Development Make You happy? Subjective well being and
Economic Growth in Developing Countries’, Social Indicators Research, 73:199-219.
Mazumdar K. (1996), “An Analysis of Causal Flow between Social development and
Economic Growth: The Social Development index”, American Journal of Economics and
sociology, Inc. Vol. 55, 3, pp. 361-383.
Morley. B, (2006), "Causality between Economic Growth and Migration: an ARDL
Bounds Testing Approach", Economics Letters, (90), 72–76.
Ng. S, and Perron. P, (2001), “Lag Length Selection and the Construction of Unit Root
Test with Good Size and Power”, Econometrica, 69, pp: 1519–1554.
Ouattara, B., (2004), “Foreign Aid and Fiscal Policy in Senegal”. Mimeo University of
Manchester.
Pesaran MH, Shin Y, Smith RJ., (2000), “Structural Analysis of Vector Error Correction
Models with Exogenous I(1) Variables”, Journal of Econometrics, 97, pp: 293–343.
Phillips, P.C.B., Perron, P. (1988), “Testing for a Unit Root in Time Series Regression”,
Biometrica, 75, pp: 335-446.
Ram, R.1985), “The Role of real Income Level and Income Distribution in Fulfillment of
Basic Needs: World Development, Vol. 3, 5, 589-94.
Sezgin. S and Yildirm. J, (2002), “The Demand for Turkish Defence Expenditure”,
Defence and Peace Economics, 13, pp: 121–128.
Sen, A.K. (1985), "The Standard of Living" Cambridge University Press, Cambridge.
Sen A.K. (1992), "Inequality reexamined", Harvard University Press, Cambridge.
Shahbaz. M, (2010), "Income Inequality-Economic growth and Non-Linearity: A Case of
Pakistan", International Journal of Social Economics, 37 (9).
Srinivasan, T.N. (1977), "Development Poverty and Basic Human Needs: Some Issues",
Food Research Institute Studies, Vol 16, No.2, 11-28.
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
23
2010 Oxford Business & Economics Conference Program
ISBN : 978-0-9742114-1-9
Streeten P., (1977), “The distinctive Features of a Basic Needs Approach to
Development,” International development Review, Vol. 3, 8-16.
Streeten P. (1981), First Things First”, London, Oxford UP.
Temple, J. and Johnson P. A. (1998), ‘Social Capability and Economic Growth’, The
Quarterly Journal of Economics, Vol. 113, 8, 965-990.
Toda, H.Y. and Yamamoto, T. (1995), "Statistical Inferences in Vector Autoregressions
with Possibly Integrated Processes", Journal of Econometrics, (66), 225-50.
Turner, P. (2006) Response surfaces for an F-test for cointegration. Applied Economics
Letters, 13, pp. 479-482.
UNDP (1990), Human Development Report, 1990, New York: UN.
UNDP (1999), Human Development Report, 1999, New York: UN.
Zapata, H. O. and Rambaldi, A. N. (1997), "Monte Carlo Evidence on Cointegration and
Causation", Oxford Bulletin of Economics and Statistics, (52), 285-298.
June 28-29, 2010
St. Hugh’s College, Oxford University, Oxford, UK
24