Institutions, Capital Flows and
Financial Integration
James R. Lothian
Fordham University
Keynote Address to the
Conference on Emerging Markets Finance
Cass School of Business
London, May 5-6, 2005
Sponsored by: Cass School of Business, JIMF, ESRC and
EBRD
I. Introduction
• Focus of presentation: International capital flows –
in particular, capital flows from the developed to the
less developed countries.
• Why are such flows not larger?
• Question has puzzled economists for the past four
decades.
• What makes it especially puzzling today is the much
greater degree of financial integration now than then
• Adding to the puzzle: Fact that a century ago such
flows were substantial
II. The Lucas-Schultz Paradox
• Robert E. Lucas, Jr. (1990) poses the question “Why
doesn't capital flow from rich to poor countries?”
• It does not, he says, but should since such poor
countries lack capital when viewed by rich-country
standards.
• “If [the neoclassical model were even close ...return
differentials of this [58 times greater] magnitude,
investment goods would flow rapidly from the United
states and other wealthy countries to India and other
poor countries.”
Schultz’s view
• Theodore W. Schultz considered the same question but from a
different perspective.
• Schultz argued that the capital stock in poor countries was not
low but high and of the wrong kind.
• What was actually scarce were higher quality physical capital
and the increased human capital that farmers and other
workers needed to utilize it
• Rates of return to these higher quality inputs were high but
rates of return to the traditional inputs were low.
• The question, therefore, was why investments in the higher
quality inputs have not been made
III. Capital Market Integration
in Historical Perspective
• Three stylized facts of particular interest:
– First: Financial integration now is much
greater than 30 years ago and quite
probably greater than even 10 years ago.
– Second: Despite these increases it has
only recently returned to the level at which
it stood in 1913.
– Third: The time pattern of integration has
differed greatly between developed and
less developed countries.
Real interest rates historically
• Examine cross-country standard deviations of ex
post real interest rates
•
Can view the ex ante real interest differential as:
ρ-ρ′ = [ρκ-ρκ′ ] + [(ρ-ρκ ) - (ρ′-ρκ′]
where ρ and ρκ are real ex ante returns on financial
and physical assets and a prime indicates the
foreign country.
• The ex post differential can, therefore, be viewed as:
r-r′ = [ρκ-ρκ′ ] + [(ρ-ρκ ) - (ρ′-ρκ′)] + ε
where r-r′ is the ex post real interest differential and
ε is the relative error in inflation forecasts.
• Use quinquennial averages of data to lessen the
effects of these errors
• First r.h.s term reflects the degree of arbitrage
across countries; the second, the degree of financial
intermediation within the two countries.
Fig 1a. Real long-term interest rates, crosscountry standard deviations, 1800-2000
20
15
10
5
0
1800
1850
SD3
1900
SD5
1950
SD10
SD11
2000
Fig 1b. Real short-term interest rates, crosscountry standard deviations, 1800-2000
Real interest rate results
reflected in other data
• Equity returns (Lothian, 2002; Obstfeld and
Taylor, 2002),
• Quantity indicators such as capital flows and
stocks of foreign assets (Lothian, 2000;
Obstfeld and Taylor, 2004),
• Feldstein-Horioka savings-retention
coefficients (Obstfeld and Taylor, 2004),
• Trade flows (Grassman,1980; Lothian, 2000)
all tell a similar story to that of real interest
rates.
Fig 2. Real short-term interest rates, crosscountry standard deviations for 89
countries,1997-2003
14
12
10
8
6
4
2
0
1970-74
1980-84
1990-94
2000-03
OECD
OECD+Asia
OECD+Asia+Lat. Amer.
OECD+Asia+Lat. Amer.+Africa
The expanded data set
• Three features of the chart stand out:
– Increased cross-country divergences as the three nonOECD groups are added sequentially
– Declines for the OECD and for OECD plus Asia during the
last decade and a half
– Progressive narrowing of real-interest rate divergences in
the case of OECD versus Asia and the lack thereof for the
OECD versus the other two groups.
• Integration therefore much less complete for the
periphery vis-à-vis the OECD core, but increasing for
Asia, and perhaps some of Latin America-Caribbean,
but not for Africa.
Poor countries: Now and Then
• Quantity data tell very much the same story
with regard to recent years as the realinterest data.
• In 1997, 82 % of foreign capital investment
stocks were in countries with levels of
income that were 60% or greater that of U.S.
and only 14% in countries with income levels
40% or less that of U.S.
• Situation however was much different a
century ago
• In 1913, countries with incomes 40% or
less that of the U.S. had a 50% share of
the total and countries with income
60% or more that of the U.S. had a 46%
share.
Fig. 3a. Distribution of shares of world stock of
foreign investment capital by level of receiving country
income per capita (US=100)
Share of world stock of foreign capital
50%
40%
1913, gross stocks
1997, gross stocks
30%
20%
10%
0%
<20
20–40
40–60
60–80
Per capita income range of receiving region (U.S.=100)
>80
Fig. 3b. Distribution of ratios of world
foreign investment capital to income by level of
receiving country income per capita (US=100)
Average foreign capital to GDP ratio
50%
40%
1913, gross stocks
1997, gross stocks
30%
20%
10%
0%
<20
20–40
40–60
60–80
Per capita income range of receiving countries (U.S.=100)
>80
IV. Economic Growth and the
Lucas-Schultz Paradox
• Closely related to the question of why
capital does not flow from rich to poor
countries is the question of why poor
countries do not grow much more
rapidly.
• In the neoclassical model, capital flows
to equate real returns and real-income
convergence are two aspects of the
same process.
Growth accounting
• Standard equation takes the form:
dy = sL dL + sK dK + R
where:
dy is the change in the log of real output,
dL the change in the log of the labor force,
dK the change in log of the capital stock,
sL and sK are the shares of the two factors
R is the residual, the part of dy unexplained by the
weighted growth rates of L and K
The relative contributions
of K and L
• In most exercises, R is positive and
fairly substantial, often exceeding the
contribution of one or the other input
and at times the contributions of both.
• Terms applied to R: technological
change, human capital accumulation
and later total factor productivity (TFP).
Schultz, Transforming
Traditional Agriculture (1964)
• Technological improvements and human
capital accumulation simply different sides
of the same coin.
• Both are improvements in the quality of the
conventional labor and capital inputs.
• Standard growth models “not designed to
consider the differences in levels of the rates
of return to incentives to investment and
growth.”
• One of the reasons is that “the profitability of
new classes of factors of production have
been concealed under ‘technical change.’ ”
Harberger in AEA Presidential
Address 1998
• Harberger picks up on some of
Schultz’s theme.
• Conventional labels for R should be
replaced.
• A better way of viewing R was in terms
of “real cost reduction” rather than
“technical change” or “TFP.”
• Changes the focus from inventions and
externalities to microeconomics.
The focus on real cost
reductions
• Enables us to peel the onion a step
further and ask the next logical set of
questions:
– What factor or factors typically account for
these real cost reductions?
– Why do those factors operate more
strongly during some time periods and in
some places than in others?
Harberger: Government policies and
societal institutions are key
• Good policies – price stability, an absence of
distorting government intervention at the
levels of the firm and the household, open
international trade and the like – and good
institutions, the enforcement of private
property being key – enable growth.
• Provide incentive to engage in activities that
reduce real costs and also raise the rate of
return to investment.
• Bad policies and bad societal institutions
have reverse effects.
Policies and institutions
• Impact of institutional factors on growth has been
the theme of a much other literature in recent years:
North’s (1990), historical treatments, to DeSoto’s
(2000) descriptive account of the day-to-day
difficulties entrepreneurs faced in developing
countries, to econometric investigations of various
sorts (e.g., Barro, 1998).
• Recent cross-country study (2004) by Gwartney,
Holcombe, and Lawson (GHL) is particularly
germane.
The GHL Study
• Major feature of the study is the use of the Economic
Freedom of the World Index (EFW)
• EFW index is made up of 5 component indices: size
of government, legal system and property rights,
sound money, freedom to trade internationally, and
regulation, each of which, in turn, has anywhere
from 3 to 18 components.
• GHL use the EFW index as a regressor in crosscountry regressions along with other variables
common in the growth literature as controls to
investigate the impact of policies and institutions on
both on the level of real per capita GDP and its rate
of growth.
• GHL report statistically significant and economically
meaningful EFW effects in all instances.
• Find largely similar effects for the per-worker stocks
of physical and human capital, the rates of change of
both and the ratios of investment and foreign direct
investment to GDP.
• Rerun real GDP growth regressions using residuals
from these latter regressions in place of the actual
variables as regressors.
• Allowing for both direct and indirect EFW effects in
this way increases the estimated EFW impact
substantially.
V. Policies, Institutions and
Capital Flows
• I extend the GHL approach is to capital flows
• Use the EFW index and data from Lane and
Milesi-Ferretti (2001) and the World Bank’s
Global Development Finance data base.
• Find substantial differences in flows across
countries grouped by level of EFW index and
statistically significant relationships
R a ti o o f n e t fo r . i n v e s t. to G D P
Fig. 4a. Distribution of foreign investment
to GDP by level of EFW index in 1997
0.50
0.40
0.30
0.20
0.10
0.00
x<6
6<x<7.5
EFW range
x>7.5
P e r c a p i ta F D I i n U . S . d o l l a r s
Fig. 4b. Distribution of per capita FDI by
level of EFW index, 1997-2001
140
120
100
80
60
40
20
0
x<5
5<x<7
EFW range
x>7
Table 1. Cross-country regressions:
Foreign capital stocks on EFW index
Dependent variable
Ratio of for. invest.
to population
Nobs
64
Const. EFW
-23360 4038
-3.604 4.236
RSQ
0.224
SEE
7356
Ratio of net for. invest.
to GDP
64
-0.699 0.135
-2.840 3.736
0.184
0.279
Ratio of FDI to population
84
-207.2
-2.710
48.5 0.147
3.760
103.8
VI. Conclusions
• Let’s return to the question with which we started –
why capital flows to poor countries remain so sparse.
• Savers in rich countries, it seems, should be taking
much greater advantage of the high returns that in
principle should await them as they did a century
ago.
• I have argued that the reason it is not happening now
is due to the institutions that are in place and the
policies that have been pursued in many if not most
poor countries
• In this regard, the emerging market countries are, I
believe, the exception that proves the rule.