V, 2 0 {
POLICY RESEARCH WORKING PAPER 2823
Real Exchange Rate Uncertainty
and Private Investment
in Developing Countries
Luis Serven
The World Bank
Latin America and the Caribbean Region
Office of the Chief Economiest
April 2002
I POLICY RESEARCH WORKING PAPER 2823
Abstract
Serv6n examines empirically the link between real uncertainty is not uniform, however. There is some
exchange rate uncertainty and private investment in evidence of threshold effects, so that uncertainty only
developing countries using a large cross country-time matters when it exceeds some critical level. In addition,
series data set. He builds a GARCH-based measure of the negative impact of real exchange rate uncertainty on
real exchange rate volatility and finds that it has a strong investment is significantly larger in economies that are
negative impact on investment, after controlling for highly open and in those with less developed financial
other standard investment determinants and taking into systems.
account their potential endogeneity. The impact of
This paper-a product of the Office of the Chief Economist, Latin America and the Caribbean Region-is part of a larger
effort in the region to assess the effects of macroeconomic volatility. Copies of the paper are available free from the World
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fax 202-522-7528, email address psoto@worldbank.org. Policy Research Working Papers are also posted on the Web at
http://econ.worldbank.org. The author may be contacted at Iserven@worldbank.org. April 2002. (18 pages)
The Policy Research Working Paper Series disseminates the fndings of work in progress to encourage the exchange of ideas about
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countries they represent.
Produced by the Research Advisory Staff
Forthcoming, Review Of Economics and Statistics
Real exchange rate uncertainty and private investment
in developing countries
Luis Serven*
The World Bank
April 2002
JEL classification codes: E22, C23
* I thank Michael Gavin, Nornan Loayza, Fabio Schiantarelli, two anonymous referees and the co-editor
for helpful comments and suggestions on an earlier draft. Charles Chang provided excellent research
assistance.
1. Introduction
Developing economies suffer from a high degree of macroeconomic uncertainty.
Growth, inflation, real exchange rates and other key macroeconomic variables are much
more volatile than in industrial economies, and the consequences of this excess volatility
for aggregate performance in several dimensions -- growth, investment and trade -- have
attracted some attention in recent empirical literature.' In the case of investment, this
concern has been renewed by recent theoretical work identifying several channels
through which uncertainty can impact on investment, under various assumptions about
risk aversion, adjustment costs to investment and other factors (see Caballero 1991 and
Abel and Eberly 1994). However, some of these effects of uncertainty operate in
mutually opposing directions, and their magnitude depends on a variety of factors
identified in the literature. As a result, the sign of the investment-uncertainty relationship
is indeterminate on theoretical grounds.
This paper examines empirically the link between real exchange rate uncertainty
and private investment in LDCs. The high real exchange rate volatility that characterizes
developing economies creates an uncertain environment for investment decisions by
making absolute and relative sectoral profitability (i.e., in the traded vs. nontraded goods
sectors) and the cost of new capital goods (because of their high import content) all
harder to predict.2 Using a large cross country-time series dataset, the paper examines the
The excess volatility of LDCs is amply documented by Easterly, Islam and Stiglitz (2000), who also
examine the consequences for growth. The literature exploring the impact on trade is summarized by
Arize, Osang and Slottje (2000), while that on investment is reviewed by Serven (1998).
2The volatility of real exchange rates in LDCs is documented for example, by Interamerican Development
Bank (1995). Serven (1998) finds in a principal components framework that the real exchange rate
plays a leading role to summarize the combined volatility of five key macro variables -- GDP growth,
inflation, the terms of trade, the relative price of capital goods and the real exchange rate itself.
impact of real exchange rate uncertainty on private investment controlling for standard
investment determinants, and assesses the role of key features of the economy - such as
the degree of openness and financial development, the income level and technological
factors -- that may tend to augment or mitigate such impact.
The paper is organized as follows. Section 2 summarizes briefly the relevant
analytical literature as well as the empirical studies on real exchange rate uncertainty and
investment. Section 3 lays out the paper's econometric methodology, and section 4
presents the empirical results. Section 5 concludes.
2. Real exchange rate uncertainty and investment: a brief overview
Many developing economies experience high real exchange rate volatility. This
translates into a high degree of uncertainty for private investors regarding both the
profitability and the cost of investment. Volatile real exchange rates are associated with
erratic swings in the relative profitability of investment in the traded and nontraded goods
sectors of the economy. In turn, the cost of new capital goods also becomes uncertain
with real exchange rate volatility, due to the high import content of investment in
developing countries (Serven 1999).
The impact of uncertainty on private investment decisions has received
considerable attention in the literature. Much of the recent analytical work focuses on the
case of risk-neutral investors, under which the critical factor shaping the impact of
uncertainty on investment is the relationship between the expected marginal revenue
product of capital and the uncertain variable - typically prices or output demand. In the
familiar scenario of the constant-returns, perfectly competitive firm with capital as the
2
only fixed factor, marginal profitability is a convex function of output prices, and
Jensen's inequality implies that higher price uncertainty raises the expected profitability
of capital, thereby increasing the desired capital stock and hence investment (Hartman
1972, Abel 1983).
Recent literature has shifted the analytical focus to the adjustment costs implied
by the acquisition and installation of capital, emphasizing the irreversible nature of most
fixed investment projects (Dixit and Pindyck 1994), which makes investment adjustment
costs asymmetric - larger for downward than for upward adjustment. Under appropriate
conditions, this creates a range of inaction: investment takes place only when the
difference between expected profitability and the cost of capital exceeds a certain
threshold. The reason is that firms become reluctant to invest due to the risk of getting
stuck with too much capital if events turn unfavorable. Even disturbances that raise the
profitability of all investment projects, but make their relative ranking more uncertain,
can lead to inaction - and hence depress aggregate investment as investors try to avoid
the 'irreversible mistake' of investing in the wrong activity (Bernanke 1983).
However, irreversibility per se is not sufficient to turn around the positive impact
of uncertainty on investment following from the convexity of the profit function. Indeed,
even under asymmetric adjustment costs it can be shown that optimal investment by a
competitive firm continues to be a non-decreasing function of uncertainty (Caballero
1991, Abel and Eberly 1994). Reversing this result requires that the marginal revenue
product of capital be a decreasing function of the capital stock, as happens under
imperfect competition or decreasing returns to scale. Under such conditions, the
profitability threshold mentioned above rises with the extent of uncertainty, and if this
3
effect is powerful enough it may outweigh the rise in expected profitability stemming
from the convexity of the profit function, leading to reduced investment.3 Even in this
scenario, however, the theoretical predictions of the irreversibility approach concern the
ex-ante investment decision, and hence refer mostly to the short-term. In the longer term,
a "hangover effect" (Abel and Eberly 1995, 1999) comes into play: higher degrees of
irreversibility and/or uncertainty make it more likely that firms will ex-post find
themselves stuck with excessive capital, making the long-run capital stock and
investment higher than they would have been otherwise.
Of course, if investors are risk-averse rather than risk-neutral, then uncertainty has
an independent, adverse effect on investment decisions, which makes it more likely that
the overall impact of uncertainty on investment be negative (Zeira 1990).4 On the whole,
however, the theoretical literature implies that the uncertainty--investment link is
ambiguous and may be shaped by a variety of factors. Lee and Shin (2000) emphasize the
role of variable inputs - the larger their output share, the stronger the above-mentioned
convexity effect and the more likely is investment to rise with uncertainty. Also, the
uncertainty-investment link might exhibit 'threshold effects', so that at low uncertainty
the relationship could be positive, but turns negative when uncertainty rises beyond some
critical level (see Sarkar 2000 for details). Likewise, with risk averse investors the ability
to diversify risk is another likely determinant of the impact of uncertainty on investment
3 The assumption that the marginal profitability of capital declines with the capital stock obviously cannot
apply to a constant-returns perfectly competitive firm, for which the marginal profitability of capital
is, by construction, unrelated to the level of capital. However, such assumption does hold for
imperfectly competitive firms and, perhaps more importantly, also for a free-entry perfectly
competitive industry taken as a whole (Caballero and Pindyck, 1996).
4 Disappointment aversion, a concept introduced by Gul (1991) also contributes to make a negative
uncertainty-investment link more likely. On this see Aizenmann and Marion (1995).
4
decisions: better-developed financial markets offering enhanced risk diversification
opportunities should reduce the adverse effects of sector-specific volatility - such as that
associated with the real exchange rate -- on aggregate investment. Finally, in the case of
real exchange rate uncertainty an additional ingredient is the degree of openness of the
economy. Other things equal, the impact on real exchange rate volatility on investment is
likely to be bigger in economies more exposed to foreign trade.5
Against this analytical background, several empirical studies have examined the
impact of real exchange rate uncertainty on aggregate investment,6 some focusing on
industrial economies (e.g., Goldberg 1993 on U.S. industry-level investment; Darby et.
al. 1999 on aggregate investment in five OECD economies) and others considering also a
few developing economies (Pindyck and Solimano 1993, Serven and Solimano 1993,
Bleaney 1996). To date, however, no study offers an assessment of the impact of real
exchange rate uncertainty on private investment in a large sample of developing
countries, nor have existing studies systematically examined how such impact may itself
depend on the factors identified by the theoretical literature just cited. These tasks are
taken up below.
3. Data and methodological issues
To explore the empirical relation between investment and real exchange rate
volatility, I draw from a large cross-country time-series data set on private investment
5 Easterly, Islam and Stiglitz (2000) show that more open economies and economies with less-developed
financial systems tend to display higher aggregate volatility. Caballero (2000) develops a model
underscoring the role of underdeveloped financial systems in the amplification of volatility in LDCs.
6Apart from the real exchange rate, a number of empirical studies examine the impact of other sources of
uncertainty on investment; see Serven (1998) and Carruth, Dickerson and Henley (2000).
5
and its determinants comprising 61 developing countries and spanning the years 1970 to
1995. The panel is unbalanced, with the number of observations per country ranging from
a minimum of 5 to a maximum of 24; see Serven (1998) for further details. To measure
real exchange rate uncertainty (rather than just sample variability), I use a GARCH (1,1)
specification in a simple equation in which the (log) real exchange rate follows an AR(1)
process with trend, which can have different parameters for each country.7 I take the
conditional variance from the GARCH procedure as the relevant measure of real
exchange rate uncertainty. It displays a strong negative association with the private
investment / GDP ratio: the full-sample correlation is -0.30, with a standard error of .03.
I next assess the impact of uncertainty on investment controlling for conventional
investment determinants. I use an empirical specification with the (log of the) private
fixed investment / GDP ratio as dependent variable. In addition to real exchange rate
uncertainty, the explanatory variables include the relative price of capital goods,
measured by the (log of the) ratio of the investment deflator to the GDP deflator, and the
real interest rate8; both should exert a negative effect on investment. However, in view of
the pervasive role of interest rate controls and non-price rationing mechanisms in
developing-country financial markets over the sample period - that may render observed
interest rates uninformative as to the true marginal cost of funds - I also add among the
regressors a measure of the overall tightness of credit markets, namely the flow of private
7 This specification is in line with evidence that real exchange rates appear to be trend stationary over
comparable panel samples; see Lothian and Taylor (1996) and Frankel and Rose (1996). Using
instead an equation in difference form leads to very similar qualitative results, however. See Serven
(1998) for a comparison of this GARCH-based uncertainty measure with simpler ones derived from
the residuals of recursive AR(p) equation estimates.
8 Two alternative measures of the inflation rate were used to construct the real interest rate: (i) the current
GDP inflation rate, and (ii) a simple average of the current plus one-period ahead inflation rates. The
empirical results were simnilar in both cases; those reported below use the latter definition.
6
credit relative to nominal GDP, which should be expected to exert a positive effect on
private investment.9 Finally, since I am working with annual information, inertia needs
to be taken into consideration, and thus I include the lagged dependent variable among
the regressors.
The conventional approach to the estimation of this type of dynamic equation in a
panel context is based on the difference GMM estimator proposed by Arellano and Bond
(1991), which uses 'internal' instruments to deal with the correlation between the lagged
endogenous variable and the time-invariant component of the disturbance. The procedure
involves taking differences of the original equation (to remove the time-invariant
component of the disturbance) and then using as predetermined instruments lagged
values of the levels of the right-hand side variables. In particular, if the time-varying
component of the disturbance is serially uncorrelated, the second- and higher-order lags
of the regressors (including the endogenous variable) become valid instruments."' This
approach has a major drawback, however: if the regressors display persistence over time,
their lagged levels may be very poor instruments for their differences. A better alternative
is the system GMM estimator of Arellano and Bover (1995) and Blundell and Bond
(1998), which combines the equation in differences -- instrumented with lagged levels of
the regressors -- with the equation in levels, instrumented with lagged differences of the
regressors. The latter become valid instruments under additional stationarity assumptions
9 Alternative specifications used instead the (log of the) real private credit stock or its first difference, with
qualitative results similar to those below. Other experiments attempted to capture standard accelerator
effects by adding current and lagged GDP to the equation, but they were not significant once the
dependent variable is expressed in terms of the log of the investment/GDP ratio.
Provided the time dimension of the data is long enough, this approach can easily accommodate serial
correlation of order k, under which regressors lagged at least k+2 periods are valid instruments.
7
regarding the time-invariant disturbance.'" In the present framework, I use this approach
to deal not only with endogeneity of the lagged dependent variable, but also with the
potential endogeneity of the other regressors, given that credit, interest rates and so on
may be jointly determined with investment. As long as the model is overidentified,
validity of the assumptions underlying the system estimator can be tested through Sargan
tests of orthogonality between the instruments and the residuals, and through tests of
second- or higher-order residual autocorrelation.'2
4. Empirical results
As usual in this kind of cross-country sample outliers are a concem, and to
remove them I drop from the sample those observations for which any of the variables
lies beyond 10 standard deviations away from the sample mean. This leads to the removal
of a dozen data points; use of more stringent criteria leads to dropping additional
observations but causes little change in the parameter estimates.
The regressions assume that all the explanatory variables are endogenous, and in
consequence they are all instrumented. For the differenced equation in the GMM system,
the standard investment determinants are instrumented using the second and third lags of
their levels. However, this is not possible with the GARCH-based real exchange rate
uncertainty measure because its construction employs future as well as past information,
and hence its lagged values may be correlated with the time-varying disturbance. To
remedy this, I construct a 'naive' measure of real exchange rate uncertainty by computing
Letting a, denote the time-invariant disturbance and z an explanatory variable, the requirement is that
E[ai I z] = E[ai I zis] for all t and s; see Arellano and Bover (1995) and Blundell and Bond (1998).
8
the 3-year variance of the forecast errors from an AR(1) real exchange rate equation
estimated recursively - i.e., using current and lagged real exchange rate information
only.13 I use the second and third lags of this naive backward-looking uncertainty
measure to instrument the first difference of the GARCH-based real exchange rate
uncertainty indicator. Finally, as additional instrument I use the current and two lagged
values of the terms of trade. In tum, for the levels equation in the GMM system I use as
instruments once-lagged differences of the conventional regressors and the terms of trade
plus the naive uncertainty measure.
The first column of Table 1 reports the system GMM estimates of the basic
specification. 14 On the whole, the parameters are very well determined and highly
significant. They reveal negative and significant effects on investment of both the relative
price of capital goods and the real interest rate. In turn, the credit flow/GDP ratio has a
strong positive impact. As for real exchange rate uncertainty, it carries a negative and
highly significant coefficient. Finally, the relatively large magnitude of the coefficient on
the lagged dependent variable suggests a considerable degree of inertia in the investment
/ GDP ratio. In turn, the diagnostic statistics are supportive of the chosen specification:
the Sargan test shows no evidence against the validity of the instruments, and the serial
correlation tests reveal strong first-order autocorrelation of the differenced residuals, as
expected, but no traces of higher-order autocorrelation. Thus, on the whole the results in
12 Notice that if the time-varying disturbance in the original equation is serially uncorrelated, differencing
will induce first-order (but no higher-order) serial correlation.
3 The AR(1) equation includes a time trend and is estimated separately for each country; see Serven
(1998).
4 All regressions include a set of year dummies, which were always highly significant.
9
column 1 are strongly supportive of a negative impact of real exchange rate uncertainty
on private investment.
Columns 2 and 3 of Table 1 explore the possibility of nonlinearities and threshold
effects regarding the impact of real exchange rate uncertainty, to verify the assertions
from the theoretical literature that the effects of uncertainty may depend on its level.
Column 2 adds to the basic specification of column 1 a quadratic term in the conditional
variance of the real exchange rate. Its parameter estimate turns out positive but highly
imprecise, while the other parameters show very little change.
Column 3 takes a different approach to search for threshold effects, which
consists in distinguishing between high- and low-uncertainty countries, according to
whether their average level of real exchange rate uncertainty is above or below the
sample median, respectively, and allowing each group to carry a different coefficient on
the uncertainty variable in the regressions.15 While the results in column 3 show that this
specification causes little change in the parameter estimates of the standard investment
regressors, the pattem of the uncertainty coefficients is revealing: the impact of real
exchange rate uncertainty is negative and significant only when uncertainty is high. At
low uncertainty, the parameter estimate is positive, although very imprecise - so
imprecise that it is not possible to reject at conventional significance levels the null
hypothesis that the two parameters are equal. With this caveat, these results are consistent
with the existence of threshold effects, as argued by Sarkar (2000).
15 1
It makes little difference if the high and low distinction is made instead in terms of observations, rather
than countries, above and below median real exchange rate uncertainty. The resulting parameter
estimates are similar but somewhat less precise than those reported in the text. Likewise, using the
mean instead of the median yields similar results as well.
10
Table 2 assesses how the impact of real exchange rate uncertainty on investment
is shaped by different ingredients mentioned in the literature. The approach is similar to
that just described: in each case, I interact the exchange rate uncertainty measure with
dummy variables defining two country groups in the sample, according to the level of the
variable of interest - income, technology, financial depth and openness.
Column 1 does this with real per capita income, allowing different impacts of real
exchange rate uncertainty in higher-income developing countries (those with 1995 per
capita income above the sample median) and the rest. The underlying idea is that
uncertainty might have a larger adverse impact in poorer economies, often characterized
by less-diversified production structures and weaker institutional and policy frameworks
that render them more vulnerable to disturbances. The estimates in column 1 show that
the impact of uncertainty is about 50 percent larger in poorer countries. In rich countries
the impact is also negative, but smaller and insignificant - although the estimate is
imprecise and not significantly different from that for poor countries. The remaining
parameters are virtually unchanged relative to those in Table 1.
Column 2 turns to the role of technological factors. As noted earlier, under
irreversibility the impact of uncertainty on investment is more likely to be negative the
smaller the output share of variable inputs. Unfortunately, aggregate data on factor shares
exist for very few countries, and hence I focus instead on the aggregate capital / labor
ratio, available from Kraay et. al. (2000). Under the assumption that countries share a
common constant-returns CES technology combining labor and capital into value added,
the share of labor should be higher (lower) in countries with a higher capital labor ratio if
the elasticity of substitution is smaller (greater) than one. As with income, I classify
11
countries into two groups according to their 1995 capital/labor ratio. The estimates in
column 3 show that the coefficient on real exchange rate uncertainty is negative and
roughly similar for both groups, which prevents any clearcut inference on the role of
technological factors. Like with income, the uncertainty impact is significantly different
from zero only for low capital / labor countries, which is unsurprising given that the
capital / labor ratio and per capita income are highly correlated (their sample correlation
exceeds .9).
Column 3 focuses on financial depth, measured by the ratio of credit to the private
sector to GDP. 16 As noted above, the presumption is that better-developed financial
systems should reduce the impact of real exchange rate volatility on investment, by
making it easier for risk-averse investors to diversify the risks associated with their
investment projects. As before, I distinguish between countries whose average financial
depth is above the median and those below the median. The parameter estimates confirm
this presumption: with high financial depth, the negative impact of uncertainty is small
and insignificant, while with low depth it is four times larger and highly significant.
Further, a Wald test of equality of the two estimates yields a p-value of 6 percent,
confirming that they are significantly different from each other. The other parameters
show no visible change relative to previous specifications.
Since higher-income countries are typically characterized by a higher degree of
financial development,'7 the results in column 3 suggest that the (weak) differential
impact of uncertainty according to income level found in column 1 might actually be due
16 This is the preferred summary indicator of financial depth in the growth literature; see Levine, Loayza
and Beck (2000). However, similar results obtain (but sample coverage is smaller) using instead the
ratio of liquid liabilities to GDP.
12
to the different degree of financial development of rich and poor economies. This is
explored in column 4, which adds to the specification in column 1 a differential effect
arising from low financial development.. The results continue to show a negative
contribution of low financial depth, while the coefficients on the income-based variables
are now insignificant both individually and jointly (the Wald test of joint significance
yields a p-value of .804). This suggests that once financial depth is taken into
consideration income levels do not matter for the impact of real exchange rate uncertainty
on investment.
Finally, in column 5 I examine the role of trade openness, which as customary is
measured by the sum of imports plus exports over GDP. Other things equal, the impact of
real exchange rate volatility should be greater in economies with greater exposure to
foreign trade. The parameter estimates in column 5, however, run counter this
presumption. The negative impact of uncertainty is virtually the same regardless of the
degree of openness, and significant only for the less-open economies.
This result appears somewhat puzzling and warrants further inspection. As with
income, one cause for suspicion is the correlation between openness and financial depth
(equal to .41 in the sample). The openness indicator in column 5 may be partly capturing
the effects of financial depth. Since the two variables presumably have opposing effects
for the impact of real exchange rate uncertainty, the estimates provide an inaccurate
assessment of the role of openness.
Proceeding like in the case of income in column 4 - that is, allowing a different
uncertainty coefficient for countries with low financial depth, in addition to the separate
17 The sample correlation between financial depth and per capita income is .52.
13
coefficients for more and less open economies - yields the estimation results in column 6.
Low financial depth continues to be associated with a negative and significant effect of
real exchange rate uncertainty on investment. In addition, the coefficients on the high and
low-openness country groups now differ in sign: positive (and significant) for low
openness and negative but insignificant at high openness. Furthermore, the difference
between the two coefficients is highly statistically significant (a Wald test of equality
yields a p-value of .01). Thus, once account is taken of the effects of financial depth,
higher (lower) openness is indeed associated with a stronger (weaker) deterrent effect of
real exchange rate uncertainty on investment, as expected. Specifically, the estimates in
column 4 indicate that in economies characterized by underdeveloped financial systems
or high openness to trade (or both) the impact of real exchange rate uncertainty on
investment is negative, while in less-open economies with well-developed financial
systems the impact is significantly positive.
4. Concluding remarks
This paper has explored empirically the impact of real exchange rate uncertainty
on private investment in a large developing-country panel data set. On theoretical
grounds, its sign is ambiguous, and the analytical literature suggests that it may be highly
nonlinear and /or depend on economic features such as the output share of variable
inputs, the degree of financial market development and trade openness.
The paper finds a negative and highly significant impact of real exchange rate
uncertainty on private investment in the overall sample, after controlling for standard
investment determinants. However, closer inspection suggests that this impact is larger at
14
higher levels of uncertainty - in line with analytical literature underscoring 'threshold
effects'. Moreover, the investment effect of real exchange rate uncertainty is shaped by
the degree of trade openness and financial development: higher openness and weaker
financial systems are associated with a significantly negative uncertainty-investment link.
Conversely, under conditions of high financial development and low openness real
exchange rate uncertainty may actually have a positive impact on private investment.
REFERENCES
Abel, Andrew B., "Optimal Investment Under Uncertainty," American Economic Review 73
(March): 228-233 (1983).
and Janice C. Eberly, "A Unified Model of Investment Under Uncertainty," American
Economic Review 1369-84 (December, 1994).
"Optimal Investment With Costly Reversibility," NBER Working Paper 5091 (1995).
"The Effects of Irreversibility and Uncertainty on Capital Accumulation," Journal of
Monetary Economics 44, 339-377 (1999).
Arize, Augustine, Thomas Osang and Daniel Slottje, "Exchange rate volatility and foreign trade:
evidence from thirteen LDCs," Journal of Business and Economic Statistics 18, 10-17
(2000).
Aizenman, Joshua, and Nancy Marion, "Volatility, Investment and Disappointment Aversion,"
NBER Working Paper 5386 (1995).
Arellano, Manuel, and Stephen Bond, "Some Tests of Specification for Panel Data: Monte Carlo
evidence and an application to employment equations," Review of Economic Studies 58,
277-97 (1991).
Arellano, Manuel, and Olympia Bover, "Another Look at the Instrumental Variable Estimation
of Error-Components Models," Journal of Econometrics 68, 29-51 (1995).
Bemanke, Ben, "Irreversibility, uncertainty and cyclical investment," Quarterly Journal of
Economics (1983).
Bleaney, Michael, "Macroeconomic Stability, Investment and Growth in Developing Countries,"
Journal of Development Economics 48, 461-77 (1996).
Blundell, Robert and Stephen Bond, "Initial Conditions and Moment Restrictions in Dynamic
Panel Data Models," Journal of Econometric (1998).
Caballero, Ricardo J., "On the Sign of the Investment-Uncertainty Relationship," American
Economic Review 81, No. 1, 279-88 (March, 1991).
15
"Macroeconomic volatility in Latin America: a view and three case studies," NBER
Working Paper 7782 (2000).
and Robert S. Pindyck, "Uncertainty, Investment, and Industry Evolution," International
Economic Review 37, No. 3 (August, 1996).
Carruth, Alan, Andy Dickerson and Andrew Henley, "What do we know about investment under
uncertainty?," Journal of Economic Surveys 14, 119-153 (2000).
Darby, Julia et. al., "The Impact of Exchange Rate Uncertainty on the Level of Investment,"
Economic Journal 109, C55-C67 (1999).
Dixit, Avinash, and Robert S. Pindyck, "Investment Under Uncertainty," Princeton University
Press. Princeton, New Jersey (1994).
Easterly, William, Roumeen Islam and Joseph Stiglitz, "Explaining Growth Volatility," in Annual
World Bank Conference on Development Economics 2000, Oxford University Press
(2000).
Frankel, Jeffrey and Andy Rose, "A panel project on purchasing power parity: mean reversion
within and between countries," Journal of International Economics 40, 209-224 (1996).
Goldberg, Linda, "Exchange Rates and Investment in United States Industry," Review of
Economics and Statistics 75, 575-588 (1993).
Gul, Faruk, "A Theory of Disappointment Aversion," Econometrica 59, 667-686 (1991).
Hartman, Richard, "The Effects of Price and Cost Uncertainty on Investment," Journal of
Economic Theory 5: 258-266 (October, 1972).
Interamerican Development Bank, "Overcoming volatility in Latin America, " (1995).
Kraay, Aart, Norman Loayza, Luis Serven and Jaume Ventura, "Country portfolios," NBER
Working Paper 7795 (2000).
Lee, Jaewoo and Kwanho Shin, "The Role of a Variable Input in the Relationship Between
Investment and Uncertainty," American Economic Review 90, 667-680 (2000).
Levine, Ross, Norman Loayza and Thorsten Beck, "Financial intermediation and growth:
causality and causes," World Bank Policy Research Working Paper 2059 (2000).
Lothian, James and Mark Taylor, "Real Exchange Rate Behavior: the Recent Float from the
Perspective of the Last Two Centuries," Journal of Political Economy 104, 488-509
(1996).
Pindyck, Robert S. and Andres. Solimano, "Economic Instability and Aggregate Investment,"
NBER MacroeconomicsAnnual 8, 259-303 (1993).
Sarkar, Sudipto, "On the Investment-uncertainty Relationship in a Real Options Model," Journal
of Economic Dynamics and Control 24, 219-225 (2000).
Serven, Luis. "Macroeconomic uncertainty and private investment in LDCs: an empirical
investigation," World Bank Policy Research Working Paper 2035 (1998).
"Terms of trade shocks and optimal investment: another look at the Laursen-Metzler
effect," Journal of International Money and Finance (1999).
Serven, Luis and Andres Solimano, "Striving for growth after adjustment: the role of capital
formation, " Washington DC: The World Bank (1993).
Zeira, Joseph, "Cost Uncertainty and the Rate of Investment," Journal of Economic
Dynamics and Control 14, 53-63 (1990).
16
Table 1
Real exchange rate uncertainty and investment: system GMM estimates
(dependent variable: real private investment / GDP a)
Equation 1 2 3
Constant -1.064** -1.031** -1.092**
(0.115) (0.117) (0.116)
Lagged private investment/ GDP a 0.647** 0. 660** 0.644**
(0.043) (0.043) (0. 043)
Relative price of capitala -0.553** -0.546** -0.602**
(0.109) (0.111) (0.148)
Credit flow to priv. sector/GDP 3.229** 3.196** 3.364**
(1.004) (1.004) (0.960)
Real interest rate -0.826** -0.831** -0.758**
(0.194) (0.193) (0.200)
Real exchange rate (RER) uncertaintyb -1.831** -3.421**
(0.703) (0.375)
RER uncertainty squared 4.848
(3.406)
High RER uncertainty' -1.634**
(0.710)
Low RER uncertainty' 3.544
(8.1,53)
Wald test of joint significance (p-value) 0.000 0.000 0.000
Sargan test (p-value) 0.457 0.319 0. 433
lst-order autocorrelation (p-value) 0.000 0.000 0.000
2nd-order autocorrelation (p-value) 0.320 0.259 0.354
Number of observations (Countries) 815 (61) 815 (61) 815 (61)
Notes to table 1: Standard errors (in brackets) are heteroskedasticity consistent. One (*) and
two (* *) stars denote statistical significance at the 10 and 5 percent level, respectively.
a. Expressed in logs.
b. Measured by the conditional variance from GARCH (1,1) estimates
c. Higher and lower than the average of the median country, respectively.
17
Table 2
Factors shaping the investment impact of uncertainty: system GMM estimates
(dependent variable: real private investment / GDP a)
Eauation 1 2 3 4 5 6
Constant -1.062** -1.071** -1.068** -1.104** -1.102** -1.124**
(0.120) (0.120) (0.113) (0.125) (0.113) (0.137)
Lagged private investment/ GDP a 0.644** 0.644** 0.647** 0.642** 0.648** 0.642**
(0.046) (0.046) (0.043) (0.050) (0.039) (0.047)
Relative price of capital' -0.563** -0.548** -0.568** -0.727** -0.674** -0.628 * *
(0.122) (0.113) (0.121) (0.128) (0.122) (0.135)
Credit flow to priv. sector/GDP 3.053** 3.223** 3.207** 3.033** 3.398** 3.732**
(0.967) (1.002) (1.003) (0.948) (0.990) (1.000)
Real interest rate -0.844** -0.852** -0.819** -0.951** -0.790** -0.898**
(0.235) (0.238) (0.204) (0.237) (0.213) (0.232)
RER uncertainty x high income' -1.219 -1.533
(2.438) (2.358)
RER uncertainty x low income c -1.835** 0.400
(0.669) (1.845)
RER uncertainty x high k/l ratio' -2.176
(2.280)
RER uncertainty x low k/l ratio c -1.822* *
(0.701)
RER uncertainty x high fin depth -0.822
(1.093)
RER uncertainty x low fin depthc -3.369** -3.616* -7.294**
(0.957) (1.889) (1.990)
RER uncertainty x high openness -1.702 -1.658
(1.367) (1.568)
RER uncertainty x low openness c -1.964** 5.064**
(0.786) (2.059)
Wald test of joint signif. (p-value) 0.000 0.000 0.000 0.000 0.000 0.000
Sargan test (p-value) 0.319 0.398 0.427 0.336 0.418 0.511
1st-order autocorrelation (p-value) 0.000 0.000 0.000 0.000 0.000 0.000
2nd-order autocorrelation (p-value) 0.271 0.325 0.232 0.192 0.310 0.201
Number of observations (Countries) 815 (61) 815 (61) 815 (61) 815 (61) 815 (61) 815 (61)
Notes to table 2: Standard errors (in brackets) are heteroskedasticity consistent. One (*) and two (**) stars denote
statistical significance at the 10 and 5 percent level, respectively.
a,b, c: see Table 1
For variable definitions, see text.
18
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