Undervaluation, Financial Development,
and Economic Growth
∗
JINGXIAN ZOU AND YAQI WANG
This paper analyzes the effect of undervaluation on economic growth in the
presence of borrowing constraints. Based on a two-sector, small open-economy
model, we show that undervaluation can promote economic growth by partly
correcting distortions in financial markets through the channels of increased
within-sector productivity and the relative share of the tradable sector in an
economy. Such an effect is magnified amid tight borrowing constraints. We
empirically test the theoretical conclusions using cross-economy data for the
period 1980–2011. For economies whose level of financial development lies
at the 25th percentile of our sample, a 50% undervaluation can boost the
economic growth rate by 0.3 percentage points. There is an additional 0.045
percentage point increase in economic growth with a 10% decline in the financial
development measure.
Keywords: economic growth, financial development, undervaluation
JEL codes: F31, F36, F43
I. Introduction
There have been heated discussions over the effects of undervaluation
on economic growth. On one side of the debate,
there is a consensus that
overvaluation, especially those of a large magnitude, can do great harm to economic
growth. First, overvaluation discourages investment by lowering returns in the
tradable sector (Bhaduri and Marglin 1990, Gala 2008). Second, overvaluation
is often associated with problems like an unsustainable current account deficit
or significant macroeconomic volatility (Dornbusch and Fischer 1980). Severe
balance-of-payment crises due to exchange rate overvaluation were observed in
many Latin American (e.g., Chile and Mexico) and African economies (e.g., Gabon
and Zambia) in the early 1980s, as well as in Argentina, Brazil, and Mexico in the
1990s (Ngongang 2011). In developing economies, the deterioration in the current
account deficit may encourage the government to tighten import quotas, which
∗Jingxian Zou: PhD candidate, National School of Development, Peking University. E-mail: zoujingxian@gmail.com;
Yaqi Wang (corresponding author): Assistant Professor, School of Finance, Central University of Finance and
Economics. E-mail: yakisunny@126.com. The authors would like to thank the managing editor and anonymous
referees for helpful comments. The authors also acknowledge funding support from the National Science Foundation
for Young Research Scholars (Grant No. 71303021) and the Central University of Finance and Economics (Grant No.
020250315030). The usual disclaimer applies.
Asian Development Review, vol. 34, no. 1, pp. 116–143
C(cid:3) 2017 Asian Development Bank
and Asian Development Bank Institute
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UNDERVALUATION, FINANCIAL DEVELOPMENT, AND ECONOMIC GROWTH 117
increases the probability of rent-seeking and corruption (Krueger 1974, Bleaney
and Greenaway 2001).
On the other side, several empirical works (Dooley, Folkerts-Landau,
and Garber 2004; Levy-Yeyati and Sturzenegger 2007; Rodrik 2008) find that
undervaluation can play a significant role in promoting economic growth.1 The
reasons suggested in these papers diverge, with the former group emphasizing
the role of capital deepening and savings accumulation driven by undervaluation,
while the latter group views undervaluation as a correction for institutional defects
and market failure. Even though there is no consensus on how undervaluation
might promote economic growth, a consistent empirical fact is that the growth
effect of undervaluation is much more prominent in developing economies than in
developed economies. However, the existing literature does not provide a sound
answer as to why there is such a difference in undervaluation’s growth effect
between developing and developed economies. Keeping this question in mind, the
explanation we put forward in this paper is centered on an economy’s level of financial
development.
In the theoretical discussion below, we illustrate how borrowing constraints
might amplify the growth effect of real currency undervaluation. Our model is
closely related to that of Aghion et al. (2009), which show that, in the presence of a
liquidity shock and wage stickiness, volatility in the real exchange rate will reduce
the success probability of firms’ research and development activities, thus lowering
the aggregate growth rate. Such an effect is magnified in developing economies
due to the existence of borrowing constraints. Based on their work, we establish a
two-sector (tradable and nontradable), small open-economy model. There are two
sources driving economic growth in our model: technological progress within the
tradable sector and resource reallocation from the nontradable to the tradable sector.
We also introduce firms’ financial constraints in our model. At the end of the first
period, each individual firm faces a stochastic liquidity shock after which only firms
with sufficient funds can conduct the research and development needed to achieve
a technology upgrade.
One of our conclusions is that if the exchange rate is sustained at the
expected equilibrium level, the tradable sector suffers greater distortion due to
binding financial constraints, as reflected in the lower probability of a technology
upgrade in the tradable sector, which is driven by the difference in output elasticity
of production between the tradable and nontradable sectors. If instead the policy of
undervaluation is adopted under the assumption of wage stickiness, then domestic
currency undervaluation is equivalent to an unexpected windfall for exporters.
1For example, the People’s Republic of China has long been accused of manipulating its exchange rate
by undervaluing the renminbi to promote exports and economic growth (Frankel 2003, Krugman 2003, Goldstein
2004).
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118 ASIAN DEVELOPMENT REVIEW
Increased domestic product prices, coupled with sticky wages, can effectively
raise a firm’s profit, which effectively relaxes the financial constraint and facilitates
technological progress, leading to a within-sector productivity increase. Moreover,
since the tradable sector is typically the sector with the faster rate of technological
progress, the expansion of the tradable sector will accelerate the resource reallocation
effect between sectors. In sum, domestic currency undervaluation can be seen as
a way to correct a distortion in the finance sector by increasing both within-sector
productivity and resource allocation efficiency between sectors.
How significant such a promotion effect can be depends on the level of
development of an economy’s financial market. Specifically, the impact corresponds
to the tightness of the financial constraint. In an economy that is characterized as
having sufficient financial liquidity, all of its firms can survive a liquidity shock
by engaging in intertemporal borrowing. Under such circumstances, there is no
room for domestic currency undervaluation as a means of relaxing the financial
constraint. Following such logic, we propose that the effect of domestic currency
undervaluation on economic growth should be more significant at lower levels of
financial development, which partly explains why developing economies have a
preference for undervaluation.
This paper incorporates the findings in two distinct branches of literature. The
first branch reviews the effects of currency undervaluation on economic growth,
which has always been a major area of interest for both academics and policy
makers. Most of the early empirical evidence supports the view that real exchange
rate misalignment, when used as a form of price distortion, will have negative
impacts on macroeconomic variables such as imports, exports, industrial structure,
resource allocation, and income distribution. (Edwards 1988; Cottani, Cavallo, and
Kahn 1990). At the same time, there is no difference found between the effects
of currency overvaluation or undervaluation on economic growth in this research.
Razin and Collins (1997) put forward that there might be some nonlinear correlation
between real exchange rate misalignment and economic growth. According to their
results, only very large overvaluations appear to be associated with slower economic
growth. Moderate and high (as opposed to very high) undervaluations appear to be
associated with more rapid economic growth. Specifically, a 10% overvaluation in
the real exchange rate leads to a 0.6 percentage point decrease in the economic growth
rate, while a 10% undervaluation contributes 0.9 percentage points to economic
growth.
There are two traditional approaches in the literature to measuring the
equilibrium real exchange rate. One is to use the fundamental equilibrium exchange
rate (FEER) first proposed by Williamson (1985), who assumed macroeconomic
balance. The other popular measurement is the behavioral equilibrium exchange
rate (BEER), which focuses on the determinants of the exchange rate in the medium
to long run (Baffes, Elbadawi, and O’Connell 1997; Maeso-Fernandez, Osbat, and
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UNDERVALUATION, FINANCIAL DEVELOPMENT, AND ECONOMIC GROWTH 119
Schnatz 2002). Both approaches have pros and cons, but a common challenge is the
availability of data, especially for developing economies.2
To include developing economies in our analysis, we refer to a different
measure used by Rodrik (2008). Our equilibrium value of the real exchange rate
is defined as the predicted real exchange rate based on gross domestic product
(GDP) per worker after controlling for the fixed effects of economy and year. Real
exchange rate misalignment is defined as the difference between the real value and
fitted value, with a positive difference referring to currency undervaluation and a
negative difference to overvaluation. The intuition behind such an approach is to
conceive of the Balassa–Samuelson adjusted rate as the equilibrium. Prices in the
nontradable sector should be lower in poorer economies, which will influence the
real exchange rate through lower overall domestic prices. The advantage of this
approach is to enable the comparison of currency undervaluation both in terms
of cross-section and time series analysis. Moreover, it does not require as many
economy-level macroeconomic variables as the two traditional measures, which
makes it ideal for analyzing long-term panel data containing many developing
economies.
A second branch of literature relates to the role of financial market
development in economic growth. Financial activities have often been seen as
responses to developments in the real economy and therefore the topic previously
did not assume much importance within academia (Robinson 1972, Meier and Seers
1984). A case in point is Lucas (1988), who once commented that the role of finance
on economic growth had been overstressed. As the understanding of incomplete
information and market frictions deepened, a number of people realized the impact
of finance on economic growth, especially on how financial intermediaries help
to overcome the problem of adverse selection and improve the efficiency of credit
allocation (Bagehot 1873, McKinnon 1973, Miller 1998). According to Levine
(2005), there are five channels through which finance can stimulate economic
growth: (i) producing information ex ante about possible investments and the
allocation of capital; (ii) monitoring investments and exerting corporate governance
after providing finance; (iii) facilitating the trading, diversification, and management
of risk; (iv) mobilizing and pooling savings; and (v) easing the exchange of goods
and services. Levine concludes that financial market development can stimulate
economic growth by improving resource allocation and investment returns.
This paper contributes to the literature in three aspects. First, we try to
explain the divergent effects of currency undervaluation on economic growth
between developing and developed economies, which has become a stylized
empirical fact lacking a solid explanation. What we find both theoretically and
empirically is that the level of financial development is important in determining
2For a more detailed methodological comparison of BEERs and FEERs, please refer to Clark and MacDonald
(1999).
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120 ASIAN DEVELOPMENT REVIEW
currency undervaluation’s effect on economic growth. We illustrate that currency
undervaluation can partially compensate for the underdevelopment of financial
markets and such an effect is magnified in less financially developed economies.
Second, by using cross-economy data covering the period 1980–2011, we empirically
quantify the effects of currency undervaluation on economic growth and separately
examine the two channels through which currency undervaluation contributes
to economic growth: (i) raising productivity within the tradable sector, and
(ii) expanding the size of the tradable sector relative to the nontradable sector.
With regard to the policy implications, this paper deepens our understanding
of why some developing economies have a preference for currency undervaluation.
According to our explanation, developing economies with underdeveloped financial
markets can use undervaluation as a remedy for tight financial constraints through
the relaxation of such constraints in the tradable sector, which in turn stimulates
economic growth.
The rest of the paper is organized as follows. Section II introduces our
theoretical model and predictions. Section III describes the data and variables we
have constructed. Section IV presents the benchmark estimates, describes a series
of robustness checks, and explores the two channels through which undervaluation
affects economic growth. Section V concludes.
II. Theoretical Model
In this section, we introduce our theoretical framework for further analysis.
We consider a small, open-economy model in which wage stickiness is assumed in
the short run. There are two sectors in the economy: tradable (T) and nontradable
(N). The price for sector N is denoted as P N
. The tradable sector produces only a
t
single good whose price is denoted as P T
. P T
is determined by the international
t
t
market in our model. Normalizing the world price for the tradable good as 1, we
have
P T
t
= St P T ∗
t
= St
(1)
where P T ∗
and St are the world price and nominal exchange rate, respectively.
t
The exchange rate, St , fluctuates around its equilibrium value, E(St ) = ¯S.
The equilibrium is the expectation value based on all historical information, which
is consistent with the idea that the predicted value is formed using all available
fundamentals.
We assume that wages are sticky in the short run. Following Aghion et al.
(2009), it is assumed the wage rate at t-period is determined by
W T
t
= E
(cid:3)
(cid:2)
P T
t
κ AT
t
= ¯Sκ AT
t
, W N
t
= P N
t
κ AN
t
(2)
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UNDERVALUATION, FINANCIAL DEVELOPMENT, AND ECONOMIC GROWTH 121
t ,AN
which means the real wage in each of the two sectors is equal to sectorial productivity
t ) times κ, where κ < 1 is the reservation utility (the utility gained while not
(AT
working). Since the prices in the tradable sector are also influenced by fluctuation in
the nominal exchange rate, the wage rate is determined by the expected equilibrium
t ) = E(St ) = ¯S. The free mobility of labor will equalize wages
exchange rate, E(P T
(cid:3)= Wt ); such an equation can also be used to determine
in the two sectors (W T
t
the price level of the nontradable sector (P N
= W N
t
t ).
A.
Firm Decision
The wage rate at the beginning of the first period is the function of the
expected equilibrium exchange rate so that a firm’s decision is a two-period problem.
First, based on the known distribution of a liquidity shock, the firm speculates the
probability of achieving a technology upgrade. The labor demand is determined by
maximizing the expected sum of revenues over the two periods. At the end of each
period, the stochastically distributed liquidity shock is realized and only those firms
that succeed in raising sufficient funds can complete the technology upgrade and
realize the associated profit (υt+1). The sectorial productivity is determined by the
proportion of firms succeeding in innovation (ρt ).
Assuming labor is the only input, the production functions in the tradable and
nontradable sectors take the following forms:
yT
t
y N
t
= AT
= AN
t (l T
t (l N
t )αT
t )α N
(3)
To guarantee that profits can be allocated for technological innovations, we
consider the case of decreasing returns to scale. Moreover, it is assumed that the
output elasticity of labor is larger in the nontradable sector:3
1 > α N > αT
(4)
3We discuss more on the validity of assumption 1 > α N > αT here. If the production function takes the
Cobb–Douglas form, then the assumption α N > αT implies that the nontradable sector is more labor intensive
than the tradable sector, which is also a basic assumption in Herrendorf, Rogerson, and Valentinyi (2013). To
measure labor intensity, several major indexes are used. For data at the firm level, these include employer’s
compensation/total assets (Dewenter and Malatesta 2001) and employer’s compensation/sales (Grubaugh 1987).
For data at the industry level, a frequently used index is industrial labor compensation/industrial nominal value-added
output (Acemoglu and Guerrieri 2006). In order to enable summary statistics covering as many economies as possible,
we use industrial labor compensation/value-added output from the World Bank’s World Development Indicators to
proxy for labor intensity. Our sample includes 214 economies covering the period 1960–2014. The mean value of
labor intensity is 0.81 in the manufacturing sector and 1.01 in the service sector. Broken down into subperiods,
the mean values for the manufacturing and service sectors in 1960–1980 are 0.72 and 0.98, respectively. For
1981–2014, the corresponding figures are 0.83 and 1.02, respectively. Therefore, on average, the nontradable (services)
sector is more labor intensive than the tradable (manufacturing) sector, which is compatible with the assumption
α N > αT .
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122 ASIAN DEVELOPMENT REVIEW
The profits at the end of the first period are
π T
t
π N
t
= P T
= P N
t yT
t
t y N
t
− Wtl T
t
− Wtl N
t
= AT
t St (l T
t P N
t )αT − ¯Sκ AT
t )α N − P N
t (l N
t l T
t
κ AN
t
t l N
t
= AN
(5)
We need to assume that wages are sticky in the short run because the wage
level is determined by the expectation formed at the beginning of each period. When
the realized exchange rate value (St ) deviates from ¯S, the wage paid will not change
in the short run. Instead, only the product price and labor demand will be affected.
Only when there is a divergence of the realized value with the equilibrium level can
the profit in the tradable sector be altered, which further impacts the tightness of the
borrowing constraint.
In the maximization problem of the firm, the decision variable is labor demand
(lt ), which affects the firm’s profit at the end of the first period (πt ) and further
determines the upper bound of the borrowing constraint in the presence of a liquidity
shock. All of these factors affect the chance for success of a technology upgrade in
the second period (ρt ) as the firm maximizes the expected sum of revenues over two
periods:
(cid:4)
max
l S
t
π S
t
+ βρ S
t Et υt+1
(cid:5)
, S = T, N
(6)
B.
Technology Upgrading and Borrowing Constraint
In each period, both sectors T and N can upgrade their technology by the
multiplier γ > 1, meaning that in the next period the productivity of firms achieving
innovation will be the following:4
AS
t+1
= γ AS
t
, S = T, N
(7)
Furthermore, we assume the realized value after innovation is proportional to
the nominal productivity in the next period:
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V S
t+1
= υ P S
t+1 AS
t+1
, S = T, N
(8)
υ is assumed to be sufficiently large so that innovation is profitable for firms in
both sectors. That is to say, in the absence of a borrowing constraint, all firms will
choose to make a technology upgrade, which will result in a growth rate of γ > 1
4For simplicity, the rates of technology upgrading are assumed to be equalized across the two sectors. In
cases of the tradable sector having a faster rate (γ T > γ N ), our main conclusions still hold. In fact, the results are
strengthened.
UNDERVALUATION, FINANCIAL DEVELOPMENT, AND ECONOMIC GROWTH 123
for the whole economy. However, firms face a borrowing constraint in our setup: it
is assumed that the funds a firm can borrow should be no more than μ − 1 times
its realized profit (πt ) at the end of period t. Equivalently, the maximum amount of
capital available is μπt . The parameter μ indicates the level of development of the
financial market (or, more explicitly, the tightness of the borrowing constraint). The
smaller μ is, the harder it is for firms to borrow. Contrarily, if μ is sufficiently large,
then all capital demands can be satisfied and there is no borrowing constraint.
Firm i will confront a liquidity shock at the end of period t, (Ct )i , which can
also be seen as the amount of liquidity needed for innovation. Whether or not the
liquidity requirement is satisfied determines the success or failure of innovation.
If the financial market is perfect, then all firms can survive the liquidity shock by
relying on intertemporal borrowing. The probability of firms successfully achieving
a technology upgrade is 1, and the overall growth rate is constant. It is the presence
of a borrowing constraint that leads to only some firms achieving a technology
upgrade. The impact of such a shock is assumed to be proportional to a firm’s
nominal productivity at period t:
(C S
t )i = ci P S
t AS
t
, S = T, N
(9)
where ci is assumed to be independent and identically distributed across all firms
with a cumulative distribution function of F(.).
Consequently, only those firms satisfying μπ S
t
(those firms with
sufficient funds) can survive a liquidity shock and achieve a technology upgrade.
As a result, the probabilities of firms achieving innovation in each of the two sectors
are
≥ C S
t
(cid:6)
ρ S
t
= Pr
ci ≤
μπ S
t
t AS
P S
t
(cid:7)
(cid:6)
= F
(cid:7)
μπ S
t
t AS
P S
t
, S = T, N
C.
Equilibrium Profit
(10)
Plugging the expression ρ S
t into the maximization problem of the firm results
in
(cid:7) 1
1−αT
(cid:6)
αT St
κ ¯S
=
l T
t
(cid:7) 1
1−α N
(cid:6)
α N
κ
, l N
t
=
(11)
Plugging l S
t
into the profit functions of each sector results in
π T
t
= AT
t St
(cid:2)
1 − αT
(cid:3)
(cid:6)
αT St
κ ¯S
(cid:7) αT
1−αT (cid:3)= AT
t St (cid:10) T
(cid:7) αT
1−αT
(cid:6)
St
¯S
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124 ASIAN DEVELOPMENT REVIEW
π N
t
= AN
t P N
t
(cid:2)
1 − α N
(cid:3)
(cid:6)
α N
κ
(cid:7) α N
1−α N (cid:3)= AN
t P N
t
(cid:10) N
(12)
From equation (10), we know the probability of completing the innovation is
⎛
ρ T
t
= F
⎝μ(cid:10) T
(cid:7) αT
1−αT
(cid:6)
St
¯S
⎞
⎠ , ρ N
t
= F
(cid:2)
μ(cid:10) N
(cid:3)
where (cid:10) S = (1 − αs)
(cid:2)
αs
κ
(cid:3) αS
1−αS , S = T, N
(13)
From equation (13), we can see that if the exchange rate remains at its
equilibrium value (St = ¯S), then the probabilities of a technology upgrade in the
tradable and nontradable sectors are time invariant. Instead, they depend only on
the borrowing constraint parameter (μ), the reservation utility (κ), and the labor
intensity parameter (α S, S = T, N ). Producers will adjust their factor demands
at the beginning of each period. For a comparison between sectors, the relative
magnitudes of the technology upgrade probabilities depend only on the parameters
(cid:10) T , (cid:10) S. Since the output elasticity of labor is larger in the nontradable sector
(α N > αT ), it proves that (cid:10) T < (cid:10) N .5 Further, we have ρ T < ρ N . Our conclusions
based on these findings are summarized below.
Conclusion 1: If the exchange rate remains at the equilibrium level and the
borrowing constraint is binding, then the probability of achieving innovation is lower
in the tradable sector than in the nontradable sector.
As we have proved, real currency undervaluation (St > ¯S) will have two
effects on the tradable sector. One is the relative expansion of the tradable sector,
both in terms of employment and output, with the magnitude amplified if measured in
nominal terms. The other effect is the increased probability of a technology upgrade
in this sector when μ is finite. This explains why some developing economies have a
preference for an exchange rate policy based on undervaluation. One possible reason
is that intentional undervaluation relaxes the borrowing constraint in the tradable
sector, which is characterized as having higher productivity than the tradable sector
(Rodrik 2008). However, when μ is sufficiently large, the financing demands of all
→ 1 holds
firms can be satisfied and there is no borrowing constraint. Then ρ T
t
and the effect on ρ T
t due to the increase in St will be very trivial, which implies the
increased probability of a technology upgrade in the tradable sector will be more
significant in economies with a less developed financial market.
, ρ N
t
Conclusion 2: Real exchange rate undervaluation will lead to the expansion
of the tradable sector.
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5To derive (cid:10) T < (cid:10) N from αT < α N , we can define a function (cid:10) (α) = (1 − α) (α/κ)
α
1−α . By calculating the
log of both sides and then calculating the derivative with respect to α, (cid:10) (α) increases in α so that (cid:10) T < (cid:10) N .
UNDERVALUATION, FINANCIAL DEVELOPMENT, AND ECONOMIC GROWTH 125
Conclusion 3: Real exchange rate undervaluation will
increase the
probability of technology upgrading in the tradable sector. Such an effect is magnified
in economies with less developed financial markets.
D.
Economic Growth Rate
Next, we come to evaluate the impact of the real exchange rate on the
economic growth rate. If we assume that the nominal exchange rate at period
t − 1 remains ¯S (equilibrium level), then the real output in each of the two sectors is
yT
t−1
= AT
t−1
(cid:7) αT
1−αT
(cid:6)
αT
κ
, y N
t−1
= AN
t−1
(cid:7) α N
1−α N
(cid:6)
α N
κ
(14)
When there is misalignment in the real exchange rate at period t, which means
the realized value (St ) deviates from S, then the output in each of the two sectors is
yT
t
= [ρ T
t
γ AT
t−1
+
(cid:3)
(cid:2)
1 − ρ T
t
AT
t−1]
(cid:7) αT
1−αT
(cid:6)
αT St
κ ¯S
(cid:2)
1 − ρ T
t
(cid:3)
]
+
(cid:7) αT
1−αT
(cid:6)
St
¯S
y N
t
= [ρ N
t
γ AN
t−1
+
(cid:3)
(cid:2)
1 − ρ N
t
AN
t−1]
(cid:7) α N
1−α N
(cid:6)
α N
κ
= yT
t−1[ρ T
t
γ
= y N
t−1[ρ N
t
(cid:2)
γ +
(cid:3)
]
1 − ρ N
t
(15)
Consequently, the gross growth rate of real output is
gt = yt
yt−1
t
= yT
yT
t−1
(cid:2)
+ y N
t
+ y N
t−1
(cid:2)
(cid:3)
]
vT,t−1 + y N
t
y N
t−1
(cid:12)
= yT
t
yT
t−1
(cid:3) αT
1−αT .vT,t−1 +
St / ¯S
= [ρ T
t
γ +
1 − ρ T
t
(1 − vT,t−1)
γ +
(cid:3)(cid:13)
(cid:2)
1 − ρ N
t
(1 − vT,t−1) (16)
ρ N
t
where vT,t−1 = yT
t − 1.
yT
t−1
t−1
+y N
t−1
, which is the output share of the tradable sector at period
Given equations (11) and (13), we know that neither the probability of a
technology upgrade in the nontradable sector (ρ N
t ) nor the output at different phases
will be changed by nominal exchange rate movement. Instead, the only channel for
nominal exchange rate movement to affect the gross growth rate is through output
change in the tradable sector. It can be seen clearly from equation (16) that, in
the presence of a borrowing constraint, undervaluation affects the growth rate of
real output mainly in two ways: (i) by increasing ρ T
(more firms can achieve a
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126 ASIAN DEVELOPMENT REVIEW
technology upgrade in period t), which leads to an accelerated technology growth
rate in the tradable sector; and (ii) by changing the relative price between sectors
(increase in St / ¯S), which will result in more labor and more output in the tradable
sector (industrial structure change).
If the price factor is taken into consideration, the nominal effect of real
exchange rate undervaluation on the growth rate will be even larger. This is because,
on one side, the relative price in the tradable sector rises as expressed in the increase
of St / ¯S. On the other side, due to the equalization of wages across the two sectors,
the price in the nontradable sector also increases. From equation (2), we know
P N
t
/P N
t−1
= (AT
t
ρ T
t
ρ N
t
=
/AT
γ +
γ +
t−1)/(AN
t
(cid:2)
1 − ρ T
(cid:2)
t
1 − ρ N
t
t−1)
/AN
(cid:3)
(cid:3)
increases while ρ N
t
When there is an undervaluation, ρ T
remains unchanged.
t
Therefore, a technology upgrade in the tradable sector will pull up the price in
the nontradable sector, which is consistent with the spirit of the Balassa–Samuelson
effect. In the case of the nominal growth rate, nominal exchange rate undervaluation,
which is associated with undervaluation, will increase prices in both sectors, making
the nominal increase larger in magnitude than the result measured in real terms.
Conclusion 4: Real exchange rate undervaluation will affect
the real
economic growth rate in two ways: (i) increased productivity within the tradable
sector and (ii) the expansion of the tradable sector since increased relative prices
will attract more resources into the sector. When measured in terms of the nominal
growth rate, the effect of undervaluation on growth is further magnified because of
increased prices in both sectors.
III. Data and Variables
A.
Key Variables
In this section, we test conclusions 2–4 by using cross-economy data. One
conclusion from the model is that real exchange rate undervaluation can promote
economic growth and that such an effect is greater in economies at lower levels
of financial development. To test this hypothesis, we define our key explained
variable—real exchange rate misalignment—as the difference between the realized
value of the real exchange rate and its equilibrium. The accuracy of the “equilibrium
real exchange rate” determines the precision of the explained variable. As discussed
in the introduction, commonly used approaches such as FEER and BEER are more
suitable for time series data for a single economy and panel data for developed
economies. However, the data set we prefer is a sample covering most developed
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UNDERVALUATION, FINANCIAL DEVELOPMENT, AND ECONOMIC GROWTH 127
and developing economies over a longer span. Due to the limitations of the data,
especially for developing economies, we prefer the measure introduced by Rodrik
(2008) for the sake of comparisons between different economies and time spans.
Following Rodrik (2008), we construct the measurement of real exchange
rate undervaluation in three steps. First, we calculate the real exchange rate
ln RERct = ln
(cid:7)
(cid:6)
XRATct
PPPct
where the subscripts c and t denote economy and year, respectively. XRAT
represents the US dollar-denominated value of the domestic currency and PPP is the
relative purchasing power conversion factor. When RERct is less than 1, the nominal
currency value in economy c is lower than the equilibrium level measured in terms
of purchasing power parity. However, it does not necessarily indicate an undervalued
currency in economy c since less developed economies are associated with lower
prices for nontradable goods, which is the essence of the Balassa–Samuelson effect.
To deconstruct the Balassa–Samuelson effect, we then regress the real
exchange rate on GDP per capita (RGDPPCct ) with the time fixed effect controlled:
ln RERct = α + β ln RGDPPCct + ft + uct
where ft is the time fixed effect. The regression result indicates that ˆβ = −0.3 with
an associated t-value of −3.6, which means that given a 10% increase in GDP per
capita, there will be a 3% appreciation in the real exchange rate.
The third step is to define the undervaluation index as the difference between
the realized exchange rate and the predicted value derived from the first two steps.
ln UNDERVALct = ln RERct − ln (cid:14)RERct
ln (cid:14)RERct
is the expected equilibrium value for the exchange rate and ln RERct
is the realized value. When UNDERVALct for economy c is greater than 1, the
domestic currency is undervalued. The real exchange rate misalignment index can
be compared between different economies and periods. Plotting the distribution of
exchange rate misalignment (after taking the logarithm), we observe in Figure 1 that
most of the dots are scattered near zero and the standard deviation is 0.77.
The measurements for financial development are consistent with Levine,
Loayza, and Beck (2000). We use two measures: (i) private credit/GDP and (ii)
M2/GDP. The first index is used for the benchmark result (Figure 2) and the second
is used as a robustness check (Figure 3).
To examine how the correlation between undervaluation and economic growth
varies in economies with different levels of financial development, we divide
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128 ASIAN DEVELOPMENT REVIEW
Figure 1. Distribution of Real Exchange Rate Undervaluation
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Note: The value of real exchange rate undervaluation is in logarithmic form and the 1% outliers have been dropped.
Sources: Authors’ calculations based on World Bank. “World Development Indicators.” http://databank.worldbank.org
/data/reports.aspx?source=world-development-indicators; Penn World Tables 8.0. http://www.rug.nl/research/ggdc
/data/pwt/
Figure 2. Correlation between Undervaluation and Economic Growth
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Notes:
1. Financial development is measured by private credit/gross domestic product (GDP).
2. The economic growth rate is the residual of regressing real GDP per worker on a series of control variables (real
GDP per worker in last period, private credit/GDP, dependency ratio, investment ratio, and government expenditure
ratio).
3. The currency undervaluation is measured based on Rodrik, Dani. 2008. “The Real Exchange Rate and Economic
Growth.” Brookings Papers on Economic Activity 2 (2008): 365–412.
4. The data are averaged over the period 1908–2011.
Sources: Authors’ calculations based on World Bank. “World Development Indicators.” http://databank.worldbank
.org/data/reports.aspx?source=world-development-indicators; Penn World Tables 8.0. http://www.rug.nl/research
/ggdc/data/pwt/
UNDERVALUATION, FINANCIAL DEVELOPMENT, AND ECONOMIC GROWTH 129
Figure 3. Correlation between Undervaluation and Economic Growth
Notes:
1. Financial development is measured by M2/gross domestic product (GDP).
2. The economic growth rate is the residual of regressing real GDP per worker on a series of control variables (real
GDP per worker in last period, private credit/GDP, dependency ratio, investment ratio, and government expenditure
ratio).
3. The currency undervaluation is measured based on Rodrik, Dani. 2008. “The Real Exchange Rate and Economic
Growth.” Brookings Papers on Economic Activity 2 (2008): 365–412.
4. The data are averaged over the sample period.
Sources: Authors’ calculations based on World Bank. “World Development Indicators.” http://databank.worldbank
.org/data/reports.aspx?source=world-development-indicators; Penn World Tables 8.0. http://www.rug.nl/research
/ggdc/data/pwt/
economies into four groups according to their financial development performances
(measured in terms of either private credit/GDP or M2/GDP), and we compare the
economies in the lowest quartile with the ones in the highest quartile. The right
panel of Figure 2 shows that when using private credit/GDP to measure financial
development, there is a significant positive correlation between undervaluation and
economic growth in the lowest quartile.6 However, the left panel of Figure 2 shows
that this correlation disappears in economies whose financial markets rank in the top
quartile. This divergent pattern of correlation holds when we replace the financial
market development index with M2/GDP as shown in Figure 3.
B.
Empirical Analysis
The regression takes the following specification based on Rodrik (2008):
growthct
= α + β. lnyc,t−1
+ γ1. Undervalct + γ2. Undervalct ∗ Fin devtct
+ γ3. Fin devtct + δ. Zc,t−1 + θc + θt + εct
(17)
where growthct is the growth rate of domestic output per worker for economy
c in year t. lnyc,t−1 is real GDP per worker in period t − 1. Undervalct is our
6For economies whose level of financial development falls in the bottom one-third of our sample there is a
consistent positive correlation between undervaluation and economic growth.
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130 ASIAN DEVELOPMENT REVIEW
Table 1. Summary Statistics
Variable
Mean Standard Deviation
9.5
−0.1
0.7
0.6
0.2
0.2
3.7
3.4
Real GDP per worker
Undervaluation
Dependency ratio
Trade openness
Government expenditure share (% of GDP)
Investment share (% of GDP)
M2/GDP
Private credit (% of GDP)
GDP = gross domestic product.
Notes: Real gross domestic product (GDP) per worker, undervaluation, M2/GDP, and
private credit/GDP are in logarithmic form.
Sources: Authors’ calculations based on World Bank. “World Development Indicators.”
http://databank.worldbank.org/data/reports.aspx?source=world-development-indicators;
Penn World Tables 8.0. http://www.rug.nl/research/ggdc/data/pwt/
1.2
0.8
0.2
0.7
0.1
0.1
0.7
1.0
constructed measurement of undervaluation for economy c. Fin devtct indicates the
financial development for economy c. θc and θt are the fixed effects for economy
and year, respectively. Zc,t−1 includes several control variables at the economy
level, including the dependency ratio (ratio of people younger than 15 or older than
64 years of age to the working-age population comprising those aged 15–64 years),
trade openness (sum of exports and imports of goods and services as % of GDP),
government expenditure share (% of GDP), and investment share (gross fixed capital
formation as % of GDP). All control variables except for Undervalct and Fin devtct
are uniformly in lagged form in order to alleviate the concern of reverse causality
or other endogeneity problems.
Our sample covers 156 economies for the period 1980–2011. The summary
statistics are listed in Table 1.
IV. Empirical Results
A.
Effect of Undervaluation on Economic Growth
Based on equation (17), we estimate the overall effect of undervaluation on
the economic growth rate. The results are listed in Table 2. As to the measure of
financial market development, we use private credit (value of credit extended to the
private sector by banks and other financial intermediaries) as a share of GDP, which
is a standard indicator in the related literature. This is superior to other measures of
financial development in that it excludes credit granted to the public sector and funds
provided from central or development banks. For a robustness check, we present
results with financial market development measured as M2/GDP.
The impact of undervaluation on economic growth is generally positive,
though sometimes insignificant. The significantly negative sign of the interactive
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UNDERVALUATION, FINANCIAL DEVELOPMENT, AND ECONOMIC GROWTH 131
(1)
Table 2. Effect of Undervaluation on Economic Growth Rate
Dependent variable: economic growth rate (growthct )
(4)
(2)
fin_devt =
1(private
credit/GDP
> 50th
percentile)
−0.065∗
(−12.30)
fin_devt =
private
credit/GDP
−0.064∗
(−11.68)
fin_devt =
private
credit/GDP
−0.063∗
(−11.56)
0.005
(0.85)
0.002
(0.63)
−0.000
(−1.22)
0.010∗
(3.19)
−0.069∗
(−3.23)
0.041∗∗∗
(1.85)
0.030∗∗∗
(1.95)
0.002
(0.48)
−0.009∗∗∗
(−1.76)
−0.000
(−1.44)
0.010∗
(3.19)
−0.076∗
(−3.50)
0.038∗∗∗
(1.70)
(3)
fin_devt =
1(private
credit/GDP
> 25th
percentile)
−0.063∗
(−12.11)
0.008
(1.41)
−0.014∗
(−3.23)
−0.031∗
(−3.33)
−0.000
(−1.52)
0.010∗
(3.18)
−0.064∗
(−3.16)
0.032
(1.52)
0.015∗∗
(2.29)
−0.006
(−1.44)
−0.032∗
(−3.74)
−0.000∗∗∗
(−1.81)
0.011∗
(3.35)
−0.072∗
(−3.55)
0.029
(1.40)
Real GDP per workert−1
Underval
Fin devt
Underval ∗ fin devt
Dependency ratiot−1
Trade opennesst−1
Govt. expenditure sharet−1
Investment sharet−1
(5)
fin_devt =
1(private
credit/GDP
> 75th
percentile)
−0.065∗
(−12.35)
0.011
(1.43)
0.003
(0.59)
−0.016∗∗∗
(−1.80)
−0.000
(−1.51)
0.010∗
(3.20)
−0.074∗
(−3.59)
0.026
(1.26)
Yes
Yes
4,019
0.086
Yes
Yes
4,019
0.083
Yes
Yes
4,019
0.084
Yes
Yes
4,019
0.084
Yes
Yes
4,019
0.087
Fixed effects
Economy fixed effect
Year fixed effect
Observations
R2
GDP = gross domestic product.
Notes:
1. All observations are annual data for the period 1980–2011.
2. The measure of financial development is private credit as a percentage of GDP.
3. Undervaluation and private credit/GDP are in logarithmic form.
4. All regressions include a constant term and economy and year fixed effects, and control for the main effects
of all three shocks.
5. t-statistics are in parenthesis.
6. ∗∗∗ = 10% level of statistical significance, ∗∗ = 5% level of statistical significance, ∗ = 1% level of statistical
significance.
Sources: Authors’ calculations based on World Bank. “World Development Indicators.” http://databank
.worldbank.org/data/reports.aspx?source=world-development-indicators; Penn World Tables 8.0. http://www
.rug.nl/research/ggdc/data/pwt/
term (underval × fin devt) suggests that the effect of undervaluation is much greater
in economies at lower levels of financial development. In column (1), we find no
significant effect on the economic growth rate. However, when the interactive term
for undervaluation and financial development is added in column (2), we find its
sign is significant and negative, indicating a stronger growth stimulation effect of
undervaluation in economies with less developed financial markets. For instance, in
economies whose financial development lies at the 25th percentile of the distribution,
the mean value of financial development is 2.67. Therefore, a 50% undervaluation
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132 ASIAN DEVELOPMENT REVIEW
can increase the economic growth rate by 0.3 percentage points (50% ∗ [0.03–0.009
∗ 2.67]). Moreover, the coefficient of the interactive term implies that given a
50% undervaluation, there will be an additional 0.045 percentage point increase in
economic growth with every 10% decline in the level of financial development (50%
∗ 0.009 ∗ 10%).
The first two columns are derived using a continuous measurement for
financial development. However, the effect of finance on economic development
may be nonlinear. To deal with this possibility, in columns (3), (4), and (5) we divide
economies into two groups (less developed and more developed) according to their
relative rank of financial development, with thresholds set at the 25th, 50th, and
75th percentiles, respectively. The dummy value is set as 1 for the more developed
group and then this dummy variable is interacted with the undervaluation index.
The coefficients of the interactive term are significantly negative, proving again
the weaker effect of undervaluation on economic growth in economies with more
advanced finance sectors.
In column (3), the coefficient of the interactive term is –0.031, suggesting
that compared with economies whose financial development falls below the 25th
percentile, the effect of a 50% undervaluation on economic growth is 1.5 percentage
points (50% ∗ 0.031) less in those economies with more advanced financial markets.
Similarly, in columns (4) and (5), where the dividing lines are set at the 50th
and 75th percentiles of the financial development distribution, respectively, the
interactive terms remain uniformly negative, reinforcing the idea that economies
with less developed financial markets benefit more from undervaluation in terms of
growth.
The results for other control variables are by and large consistent with
the literature in that higher GDP per worker in the previous period is associated
with a slower growth rate, which is in line with convergence theory (Barro and
Sala-i-Martin 1992). As for the magnitude,
in a related empirical study on
undervaluation, Rodrik (2008) reports the coefficients for lagged real income per
capita for developed and developing economies as –0.055 and –0.065, respectively.
As for the partial derivative of findevt, the relationship between findevt and growth
can be ambiguous. Compared with less developed economies, advanced economies
may perform better in terms of both findevt and growth. On the other hand, advanced
economies with more developed financial markets may grow more slowly than some
emerging economies. The significantly negative role of findevt may be explained by
the faster growth rate of those economies that are catching up, which is the essence
of the convergence theory of economic growth. For the demographic variable, a
higher dependency ratio lowers the economic growth rate (Krugman 1995, Higgins
and Williamson 1997).
Assessing the impact of government expenditure on economic growth is
quite controversial. Barro (1990) proposes the promotion effect of government
expenditure in an endogenous growth model in which public expenditure is seen as
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UNDERVALUATION, FINANCIAL DEVELOPMENT, AND ECONOMIC GROWTH 133
part of the production input. Conversely, many empirical works provide evidence
of the opposite (Landau 1983, Grier and Tullock 1989), which coincides with what
we find in our paper that government expenditure has a negative effect on growth.
Empirically, the magnitude of government spending on economic growth varies
and depends largely on the selection of the sample and the definition of government
spending. Likewise, a possible mechanism for trade openness may be what is stressed
by Young (1991) and Yanikkaya (2003), who note that open trade may hurt an
individual economy even though it is beneficial for economies as a whole.
B.
Robustness Check
In Table 3, we test the robustness of our results in two directions: (i) by altering
the measures of our key variables: financial development and undervaluation and
(ii) by further reporting the results using 5-year-averaged panel and cross-section
data instead of adopting yearly panel data.
First, for an alternative measure of financial development, we refer to M2/GDP
(Levine and Zervos 1996, 1998; Demirg¨uc¸-Kunt and Levine 1996). In column (1),
the results are qualitatively consistent with the benchmark. To be more specific, the
sample mean of financial development is 3.72, implying that the growth effect driven
by a 50% undervaluation is 0.14 percentage points (50% ∗ [0.081–0.021 ∗ 3.72])
on average. Furthermore, given a 50% undervaluation, with every 10% decline in
financial development, the marginal effect on economic growth is amplified by 0.11
percentage points (50% ∗ 10% ∗ 0.021).
Another key variable is undervaluation, which depends on the accuracy of the
real exchange rate. In the benchmark regression, the real exchange rate is constructed
based on Penn World Tables 8.0. For a robustness check, we turn to the counterpart
variable from the International Monetary Fund and the results are listed in column
(2). Compared with the Penn World Tables 8.0, the International Monetary Fund
sample is much smaller, which leads to a sharp decrease in observations from 4,019
to 1,960. However, despite such a drop in the number of observations, the results
are still qualitatively consistent and remain highly significant.
In columns (3) and (4), we report the results using data in 5-year-averaged
panel and cross-sectional forms, respectively. In the cross-sectional regression, all of
the control variables are averaged over the sample year, while real GDP per workert−1
refers to the value at the beginning year. The main conclusion that undervaluation
can promote economic growth still holds. Such an effect is more prominent in less
developed financial markets.
We will now discuss the threshold of findevt that makes the partial effect of
undervaluation positive. According to equation (17), the threshold equals −γ1/γ2.
When findevt is measured as private credit/GDP (in logarithmic form), the threshold
values range from 2.9 to 4.7 (see column [2] of Table 2 and columns [2]–[4]
of Table 3), depending on the data source of the real effective exchange rate
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134 ASIAN DEVELOPMENT REVIEW
Financial development measure M2/GDP
Table 3. Robustness Check
Dependent variable: economic growth rate (growthct )
Private
credit/GDP
PWT 8.0
5-year-averaged
panel
(3)
−0.099∗
(−15.71)
Private
credit/GDP
IMF
PWT 8.0
panel
(1)
−0.060∗
(−10.91)
0.081∗
(3.32)
−0.016∗
(−2.94)
−0.021∗
(−3.09)
−0.000
(−1.60)
0.010∗
(3.18)
−0.065∗
(−3.00)
0.037∗∗∗
(1.65)
panel
(2)
−0.047∗
(−6.66)
0.066∗
(5.81)
−0.011∗
(−2.70)
−0.020∗
(−5.42)
0.000
(1.01)
0.045∗
(5.32)
−0.022
(−0.76)
0.013
(0.43)
0.047∗∗
(2.34)
0.002
(0.60)
−0.010∗∗
(−2.31)
−0.000
(−1.32)
0.014∗∗
(2.26)
−0.054∗∗
(−2.08)
0.037
(1.23)
RER construction source
Data
Real GDP per workert−1
Underval
Fin devt
Underval × fin devt
Dependency ratiot−1
Trade opennesst−1
Govt. expenditure sharet−1
Investment sharet−1
Private
credit/GDP
PWT 8.0
cross-section
(4)
−0.013∗
(−8.15)
0.020∗∗∗
(1.97)
0.001
(0.34)
−0.007∗∗∗
(−1.72)
−0.001∗
(−6.75)
0.006∗∗
(2.49)
−0.029∗∗∗
(−1.83)
0.059∗
(3.23)
127
0.488
Yes
Yes
677
0.388
Yes
Yes
3,682
0.090
Yes
Yes
1,960
0.110
Fixed effects
Economy fixed effect
Year fixed effect
Observations
R2
GDP = gross domestic product, IMF = International Monetary Fund, PWT = Penn World Tables, RER = real
effective exchange rate.
Notes:
1. Observations are annual data for the period 1980–2011.
2. The measures of financial development are the same as indicated in the column headings.
3. Both undervaluation and private credit/GDP are in logarithmic form.
4. Panel regressions in columns (1)–(3) include both economy and year fixed effects. Column (4) reports the
estimates of cross-sectional data where all of the control variables are averaged over the period 1980–2011 and
real GDP per workert−1 refers to the value at the beginning year.
5. t-statistics are in parenthesis.
6. ∗∗∗ = 10% level of statistical significance, ∗∗ = 5% level of statistical significance, ∗ = 1% level of statistical
significance.
Sources: Authors’ calculations based on World Bank. “World Development Indicators.” http://databank
.worldbank.org/data/reports.aspx?source=world-development-indicators; Penn World Tables 8.0. http://www
.rug.nl/research/ggdc/data/pwt/
(International Monetary Fund or Penn World Tables 8.0) and the structure of data
(yearly panel, 5-year-averaged panel, or cross section). In our sample, the threshold
value lies around the 50th percentile of the whole distribution. As an example, the
threshold is close to the financial development level of economies like Mexico and
Peru in 2011, which implies that for economies whose financial markets are less
developed than the threshold level, the adoption of undervaluation may promote
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UNDERVALUATION, FINANCIAL DEVELOPMENT, AND ECONOMIC GROWTH 135
economic growth. Similarly, when findevt is measured as M2/GDP (in logarithmic
form) in column (1) of Table 3, the corresponding threshold value is 3.86, which is
very close to the relative rank suggested by using private credit/GDP.
C.
Endogeneity
The possible endogeneity of an economy’s financial development level leads to
concerns of biased estimates (Arellano and Bond 1991, Blundell and Bond 1998). To
tackle this issue, we adopt a generalized moment method. By taking the differences
of the forward term of explanatory variables together with the lagged explained
variables as instrument variables, we try to alleviate the possible endogeneity of the
dynamic panel data.
Table 4 shows that the results are still very robust with the generalized moment
method estimation: the positive effect of undervaluation on economic growth is again
more prominent for economies with less developed financial markets. Moreover, the
coefficient of the interactive term is close to the results presented in Table 2. To check
the fitness of our specifications, we report the value of AR(2) to test whether there is
autocorrelation of the second order residuals; our result rejects this possibility. The
validity of instrument variable gains is also supported by the results shown in the
last row of Table 4.
D.
Channels Verification
We have thus far examined the overall effect of undervaluation on economic
growth. In this section, we go a step further to verify the two channels implied
in the theoretical model. Equation (16) shows that undervaluation can stimulate
economic growth via two channels: (i) expanding the share of the tradable sector in
the economy, and (ii) increasing productivity within the tradable sector.
The quantified results for the first channel are reported in Table 5. When using
the ratio of industrial output to GDP as a proxy for the tradable sector’s share of
the economy, we find that undervaluation increases this share. This effect is more
prominent at lower levels of financial development. The sample mean of financial
development is 3.38. As shown in column 2, on average, a 50% undervaluation
can increase the ratio of industrial output to GDP by 0.54 percentage points (50%
∗ [0.021–0.003 ∗ 3.38]). Given a 50% undervaluation, an additional 10% drop in
the financial development index has the marginal effect of enlarging the industrial
sector’s share of the economy by 0.015 percentage points (50% ∗ 10% ∗ 0.003). As
the mean value of the ratio of industrial output to GDP is 25% in our sample, the
marginal effect is very significant.
Next, we test the effect of undervaluation on productivity in the tradable sector.
As discussed earlier, when the borrowing constraint is binding, undervaluation can
promote productivity in the tradable sector and this effect is more noticeable in
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136 ASIAN DEVELOPMENT REVIEW
Table 4. Endogeneity
Dependent variable: economic growth rate (growthct )
Difference GMM System GMM
Growthc,t−1
Underval
Fin devt
Underval × fin devt
Dependency ratiot−1
Trade opennesst−1
Govt. expenditure sharet−1
Investment sharet−1
0.018
(0.91)
0.013
(0.36)
0.053∗
(3.90)
−0.003∗
(−0.23)
−0.001∗∗∗
(−1.86)
−0.028∗
(−5.38)
−0.496∗
(−8.98)
0.247∗
(5.60)
0.038∗∗
(2.11)
0.037∗∗
(2.46)
0.004
(1.08)
−0.017∗
(−2.75)
−0.000∗
(−2.67)
−0.009∗
(−4.18)
−0.072∗
(−4.97)
0.085∗
(5.51)
Yes
Yes
3,529
0.101
0.103
Yes
Yes
1,889
0.187
0.201
Fixed effects
Economy fixed effect
Year fixed effect
Observations
AR(2)
Sargan
GMM = generalized moment method.
Notes:
1. t-statistics are in parenthesis.
2. Columns (1) and (2) report the results of difference GMM and system
GMM, respectively.
3. Lagged periods are t-2 and t-3.
4. ∗∗∗ = 10% level of statistical significance, ∗∗ = 5% level of statistical
significance, ∗ = 1% level of statistical significance.
Sources: Authors’ calculations based on World Bank. “World Development
Indicators.” http://databank.worldbank.org/data/reports.aspx?source=world
-development-indicators; Penn World Tables 8.0. http://www.rug.nl
/research/ggdc/data/pwt/
economies with less developed financial markets. One empirical challenge is that
cross-economy data cannot be used to estimate productivity in the tradable sector of
individual economies. Therefore, we turn to the relative productivity of the tradable
and nontradable sectors. In fact, our model tells us undervaluation will only have
an effect on productivity in the tradable sector. Consequently, if we can find a
significant increase in relative productivity between the two sectors (with a more
prominent result in economies with less developed financial markets), we can still
identify the channel through which undervaluation promotes growth by generating
a within-sector productivity increase.
Relative productivity between the two sectors is estimated as follows. First,
relative nominal output is denoted as occurring in period t. Plugging this into
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UNDERVALUATION, FINANCIAL DEVELOPMENT, AND ECONOMIC GROWTH 137
Table 5. Channel I: Effect of Undervaluation on Expanding
the Tradable Sector’s Share of Gross Domestic Product
Dependent variable: Share of industrial output in GDP
Share of industrial output in GDPt−1
Underval
Fin devt
Underval × fin devt
Dependency ratiot−1
Trade opennesst−1
Govt. expenditure sharet−1
Investment sharet−1
(1)
0.795∗
(76.56)
0.013∗
(5.79)
−0.002∗∗∗
(−1.77)
−0.000∗
(−2.92)
0.000
(0.27)
−0.014∗∗∗
(−1.78)
0.021∗∗
(2.53)
(2)
0.795∗
(76.55)
0.021∗
(3.78)
−0.002∗∗∗
(−1.92)
−0.003∗
(−3.61)
−0.000∗
(−3.11)
0.000
(0.31)
−0.017∗∗
(−2.08)
0.020∗∗
(2.41)
Yes
Yes
3,338
0.681
Yes
Yes
3,338
0.682
Fixed effects
Economy fixed effect
Year fixed effect
Observations
R2
GDP = gross domestic product.
Notes:
1. Observations are annual data for the period 1980–2011.
2. Both undervaluation and private credit/GDP are in logarithmic form.
3. t-statistics in parenthesis.
4. ∗∗∗ = 10% level of statistical significance, ∗∗ = 5% level of statistical
significance, ∗ = 1% level of statistical significance.
Sources: Authors’ calculations based on World Bank. “World Development
Indicators.” http://databank.worldbank.org/data/reports.aspx?source=world
-development-indicators; Penn World Tables 8.0. http://www.rug.nl/research
/ggdc/data/pwt/
equation (11) results in
V T N
t
t yT
= P T
t
t y N
P N
t
t AT
= P T
t
t AN
P N
t
(cid:3) αT
1−αT
(cid:2)
αT St /κ ¯S
(cid:2)
α N /κ
(cid:3) α N
1−α N
Taking the log of both sides results in
(cid:7)
(cid:6)
ln
AT
t
AN
t
= ln V T N
t
− ln
−
α N
1 − α N
ln
(cid:7)
(cid:7)
(cid:6)
(cid:6)
P T
t
P N
t
α N
κ
−
αT
1 − αT
ln
(cid:7)
(cid:6)
St
¯S
−
αT
1 − αT
ln
(cid:7)
(cid:6)
αT
κ
(18)
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138 ASIAN DEVELOPMENT REVIEW
t
where both V T N
and St can be observed in the data. The last two terms on the right
side of the equation are constant (allowing for differences across economies). What
remains to be estimated is the relative price (P T
t ) at period t. Following Mao
t
and Yao (2014), we assume the overall domestic price level at each period is the
geometric mean of the price level in two sectors:7
/P N
Pt =
(cid:3)θ (cid:2)
(cid:2)
P T
t
P N
t
(cid:3)1−θ
Based on the definition of purchasing power parity, we have
PPP =
(cid:7)θ (cid:6)
(cid:6)
P T ∗
P T
P N ∗
P N
(cid:7)1−θ
(cid:6)
=
1
St
(cid:7)θ (cid:6)
P N ∗
P N
(cid:7)1−θ
For the simplicity of expression, the subscript t is omitted here. Rearranging
the equation above results in
(cid:7)
(cid:6)
ln
P N ∗
P N
= 1
1 − θ
(ln PPP + θ ln St )
Plugging this into the identity ln
(cid:15)
(cid:16)
(cid:15)
(cid:16)
(cid:15)
P T
P N
= ln
P T
P T ∗
+ ln
(cid:16)
(cid:15)
+ ln
(cid:16)
P N ∗
P N
P T ∗
P N ∗
results in
(cid:7)
(cid:6)
ln
P T
P N
= 1
1 − θ
(ln PPP + ln St ) + ln
(cid:6)
(cid:7)
P T ∗
P N ∗
Since the world relative price P T ∗/P N ∗ between the two sectors is exogenous
for a single economy, it can be absorbed into a time fixed effect. We estimate the
relative price between the two sectors at period t as PT N ,t in the specification below:
ln PT N ,t = γ (ln PPPct + ln Sct ) + δc + δt + εct
Plugging this into equation (18) results in
ln AT N ,ct = ln V T N
t
− (cid:2)
ln V T N
t
where AT N ,ct is the relative productivity between the tradable (T) and nontradable
(N) sectors, which are replaced by the industrial (I) and service sector (S),
7This form can be derived from the utility function Ut =
. The specific function form has a
trivial impact on our estimation results since we only need a specification establishing the relationship between overall
prices and sectorial prices.
cN
t
cT
t
(cid:2)
(cid:3)θ (cid:2)
(cid:3)
1−θ
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UNDERVALUATION, FINANCIAL DEVELOPMENT, AND ECONOMIC GROWTH 139
Table 6. Channel II: Effect of Undervaluation on Increasing
the Relative Productivity of the Tradable Sector
Relative productivity of tradable to
nontradable sector
Relative productivity of tradable to
nontradable sectort−1
Underval
Fin devt
Underval × fin devt
Dependency ratiot−1
Trade opennesst−1
Govt. expenditure sharet−1
Investment sharet−1
(1)
0.792∗
(75.45)
0.081∗
(6.47)
−0.018∗
(−2.69)
−0.001∗∗∗
(−1.72)
0.005
(0.83)
−0.089∗∗
(−2.06)
0.061
(1.34)
(2)
0.791∗
(75.41)
0.159∗
(5.01)
−0.020∗
(−3.00)
−0.028∗
(−2.69)
−0.001∗∗
(−2.08)
0.006
(0.91)
−0.113∗
(−2.58)
0.052
(1.15)
Yes
Yes
3,317
0.666
Yes
Yes
3,317
0.667
Fixed effects
Economy fixed effect
Year fixed effect
Observations
R2
GDP = gross domestic product.
Notes:
1. Observations are annual data for the period 1980–2011.
2. Both undervaluation and private credit/GDP are in logarithmic form.
3. t-statistics are in parenthesis.
4. ∗∗∗ = 10% level of statistical significance, ∗∗ = 5% level of statistical
significance, ∗ = 1% level of statistical significance.
Sources: Authors’ calculations based on World Bank. “World Development
Indicators.” http://databank.worldbank.org/data/reports.aspx?source=world
-development-indicators; Penn World Tables 8.0. http://www.rug.nl/research
/ggdc/data/pwt/
respectively.
(cid:2)
lnV T N
t
is estimated as
ln V T N
t
= δ1 ln PPPct + δ2 ln Sct + δc + δt + εct
The effect of undervaluation on raising the relative productivity of the
tradable sector compared with that of the nontradable sector is shown in Table 6.
Such an effect is significant and is amplified in economies with less developed
financial markets. Quantitatively, column (2) informs us that for economies with
an average level of financial market maturity, a 50% undervaluation can lead to
a relative productivity increase of 3.22 percentage points (50% ∗ [0.159–0.028 ∗
3.38]), which is economically significant. In terms of the interactive effect, given
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140 ASIAN DEVELOPMENT REVIEW
a 50% undervaluation and a 10% decline in financial market development, relative
productivity increases by an additional 0.14 percentage points (50% ∗ 10% ∗
0.028).
V. Conclusion
We have tested our hypothesis using cross-economy data for the period
1980–2011 and the results support our predictions. For economies at the 25th
percentile of financial development distribution, a 50% undervaluation can increase
the economic growth rate by 0.3 percentage points. With a 10% decline in the
financial development level, the stimulating effect of undervaluation is an additional
0.045 percentage points. Verifying the two channels included in our theoretical
discussion, we find that for economies with an average level of financial market
development a 50% undervaluation is associated with a 0.54 percentage point
increase in the tradable sector’s share of GDP. Meanwhile, the relative productivity of
the tradable versus nontradable sector increases by 3.22 percentage points. Given a
10% decline in financial market development, the marginal effects of undervaluation
on expanding the tradable sector’s share of GDP and the relative productivity of the
tradable sector are 0.015 and 0.14 percentage points, respectively.
These findings have substantial policy implications in that they offer a deeper
understanding of why policy makers in many developing economies favor an
undervalued exchange rate and the related export-oriented development strategies.
According to our results, undervaluation will lead to relaxed borrowing constraints
in the tradable sector, which will facilitate increased industrial output (as a %
of GDP) and an accelerating technological growth rate in the tradable sector.
Both of these channels can boost economic growth, with the impacts being
more prominent in economies with less developed financial markets. If we take
the technological spillover effects into consideration, the growth effect is further
magnified. Since developing economies are typically characterized as having
underdeveloped finance sectors and tighter borrowing constraints, their likelihood
of adopting an undervaluation policy will consequently be higher.
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