Download The Effect of Exchange Rate Volatility on Productivity of Korean

KIEP Working Paper 16-08
The Effect of Exchange Rate
Volatility on Productivity of Korean
Manufacturing Plants: Market Average
Rate Regime vs Free Floating
CHOI Bo-Young and PYUN Ju Hyun
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Price USD 3
Working Paper 16-08
The Effect of Exchange Rate Volatility
on Productivity of Korean Manufacturing Plants: Market Average Rate
Regime vs Free Floating
CHOI Bo-Young and PYUN Ju Hyun

Executive Summary
This study examines how exchange rate volatility can influence total factor
productivity (TFP) in various dimensions. Using Korean manufacturing
plant-level data for 1990-2007, we first compare and contrast the effects of
exchange rate volatility on TFPs between two different exchange rate regimes―pegged and free floating. We find that the exchange rate volatility
had a negative effect on productivity in both regimes but this negative effect was greater during the period when exchange rate fluctuation was restricted, compared to the period with free floating rate. We also find that
the negative effects of the volatility on productivity were heterogeneous
over TFP quantiles and exhibited an inverted W-shape curve. In particular,
the negative effects were more pronounced for exporting plants that had
the lowest or highest TFPs.
Keywords: Total factor productivity, Korean plant-level data, Exchange
rate volatility, Quantile regression
JEL Classification: F12, F14
Executive Summary
3
Contributors
CHOI Bo-Young
Research Fellow at the Korea Institute for International Economic Policy.
She holds a Ph.D. degree in Economics from the University of CaliforniaDavis. Her fields of research are international trade and industrial organization. Her publication includes “Globalization, Ownership and the Effects of
Trade Liberalization in Chinese Import Prices” with Deborah Swenson, AsiaPacific Journal of Accounting and Economics (2015), “The Impact of Regulatory Measures of CJK on International Trade” The Journal of Northeast Asian
Economic Studies (2016) and others.
PYUN Ju Hyun
Assistant Professor of International Business at Korea University Business
School (KUBS). He serves as an adjunct research fellow at Asiatic Research
Institute (ARI), Korea University. Prior to joining Korea University, he
worked as a research fellow at Korea Institute for International Economic
Policy (KIEP). He received his Ph.D. in Economics from the University of California, Davis.
4 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
Contents
Executive Summary ....................................................................................... 3
1. Introduction ............................................................................................... 7
2. Theoretical Background .......................................................................... 13
3. Data and Methodology ................................................................................ 18
3-1. Data and TFP Estimation ................................................................... 18
3-2. Methodology: Quantile Regression................................................... 21
4. Empirical Results .................................................................................... 23
4-1. Main Results ..................................................................................... 23
4-2. Shape of Quantile Regression Curves: Exporters vs. Non-exporters .... 27
4-3. Robustness: Alternative Volatility Measure ...................................... 28
4-4. Exchange Rate Volatility with Adjacent Major Trading Partners:
China vs. Japan ................................................................................. 28
5. Discussion and Conclusion ...................................................................... 35
References ................................................................................................ 37
Appendix. Production Function Estimation Results ..................................... 40
Contents
5
7
Tables
Table 1. Summary Statistics ................................................................................. 20
Table 2. Main Results: Sub-sample with Different Exchange Rate Regime,
1990-1997 vs 1999-2007 .......................................................................... 25
Table 3. Additional Results: Never-exporters vs. Exporters .................................. 29
Panel A. Market average rate regime ( a la pegged regime) (1990-1997) .. 29
Panel B. Free floating (1999-2007)........................................................... 30
Table 4. Robustness with Real Exchange Rate Volatility, 1990-1997 vs 1999-2007 31
Table 5. Exchange Rate Volatility of China-Korea vs that of Japan-Korea .............. 33
Table A1. Estimates of Production Functions for 18 Manufacturing Industries ....... 40
Figures
Figure 1. Korean Exchange Rate and Its Volatility, 1990-2007 ................................. 8
Figure 2. Productivity Distribution: Exporter vs Non-exporter................................ 16
Figure 3. Theoretical Paradigm for an Inverted W-shape Volatility Effect
Based on Melitz Model (Helpman, 2006)................................................ 17
Figure 4. Quantile Regression Results .................................................................. 24
6 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
The Effect of Exchange Rate Volatility on
Productivity of Korean Manufacturing
Plants: Market Average Rate Regime vs
Free Floating

CHOI Bo-Young and PYUN Ju Hyun
1. Introduction
This study investigates the effects of exchange rate volatility on total
factor productivity (TFP) using plant-level data of Korean manufacturing
industries during 1990-2007. In particular, we shed light on the exchange
rate regime change in Korea from pegged to free floating, and examine
how this regime shift influenced the exchange rate volatility effect on plant
productivity. Our study also utilizes the information on plant-level productivity distribution with a quantile regression approach (Koenker and Hallock 2001). By keeping track of productivity distribution in response to
exchange rate fluctuation, we discuss how differently the exchange rate
volatility shapes plant productivity over productivity quantiles.

We thank Yong Joon Jang and Kyunghun Kim for their helpful comments and suggestions. We also gratefully acknowledge the financial support from KIEP. All remaining
errors are our own.
 Department of Northeast Asian Economies, Korea Institute for International Economic
Policy, 370 Sicheongdaero, Sejong 339-007, Korea; Tel: 82-44-414-1185, Email: [email protected].

Corresponding author: Business School, Korea University, 145 Anam-Ro, Seongbuk-Gu,
Seoul 136-701, Korea; Tel: 82-2-3290-2610, Email: [email protected].
1. Introduction
7
Figure 1. Korean Exchange Rate and Its Volatility, 1990-2007
In Figure 1, we plot the Korean real exchange rate (RER) movements
for the period 1990-2007, which are obtained from OECD and BIS. Before 1997, the real exchange rate had been quite constant and its variation
had been restricted in some range. However, the RERs plummeted about
25 percent in 1998 and started to fluctuate. During 1990-1997, the Korean
government implemented the “market average rate” system. Under this
system, the basic exchange rate of the Korean won against the US dollar
was determined in the market within a specified range around the weighted
average interbank rates of the previous day.1 The range of allowed daily
fluctuations was also limited (mostly 0.4~2.25 percent for whole sample
period), but it steadily widened up to within 10 percent in 1997.2 However,
1
2
An important feature of this system is that it allowed market forces to play a part in determining exchange rates, thereby laying a basis for the market to become more efficient
and moving toward a free-floating regime in the future. See Nam and Kim (1999) for
more detailed discussion.
Exchange rate had been more stable in the 1990s under the market average rate system
8 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
this market average rate was replaced by free floating in December 1997.
Figure 1 also depicts an annual standard deviation of daily Korean
nominal exchange rate against the US dollar and contrasts it between two
periods, before and after 1997. As expected, the exchange rate volatility
had been trivial until 1997. However, during the Asian Financial crisis period (1997-1998), the exchange rate volatility surged. In addition, as the
Korean exchange rate regime was changed from market average rate to
free floating in 1997, the exchange rate fluctuation has increased afterward.
Given the change in the exchange rate regime and the increased exchange rate volatility, this paper empirically investigates whether such
change affected the effect of exchange rate volatility on productivity. Since
not only an exchange rate change but also its volatility can greatly affect a
firm’s decision making―investment, employment, profitability, and/or
productivity,3 it is important to understand the effect of “external” exchange rate shock on firm productivity and the channels through which
exchange rate fluctuation shock is distributed. In particular, this issue is
even more critical for Korea, as it is a small open economy and often vulnerable to external shocks.
We find that exchange rate volatility was negatively associated with
plant productivity, which confirms previous studies such as by Caglayan
and Demir (2014). By comparing and contrasting the two exchange rate
regimes, we find that the negative effect of the volatility on productivity
was greater over all TFP quantiles during the period when exchange rate
variation was restricted before 1997, compared to the period with the free
3
than in the 1980s. At the very beginning, the limit of fluctuation was set at 0.4 percent of
the weighted average of the interbank rates of the previous day in either direction, but it
was expanded to 2.25 percent in December 1995 and to 10 percent in November 1997.
Demir (2013) argue that exchange rate uncertainty is expected to have more depressing
growth effects in developing countries such as Turkey because of i) low levels of financial
market development and the lack of hedging instruments; ii) the presence of original sin
and dollarization with strong balance sheet effects; iii) higher levels of openness, and the
invoicing of exports in hard currencies; and iv) higher levels of capital flow, and growth
volatility.
1. Introduction
9
floating exchange rate regime after 1997. We also show that the volatility
that stemmed from the cross exchange rate between Korea and China had
a greater negative effect than that between Korea and Japan.
In addition, we find that the negative effects of exchange rate volatility
on productivity were heterogeneous over TFP quantiles and exhibited an
inverted W-shape curve. First, the negative effect was greater for not only
the least productive plants but also the most productive plants. Furthermore, around the medium productivity range, this negative effect was
magnified again. We show that these double arches may be driven by two
important attributes―productivity and exposure to the volatility shocks.
While more productive firms are less vulnerable to the exchange rate volatility shock, the productive firms that tend to have a higher exposure to
foreign market are more sensitive to the shock. Our finding is confirmed
by the distinction between exporters and non-exporters. The stronger negative effect in the highest TFP quantiles could be driven by exporting firms
with the uppermost exposure to the volatility shock owing to a large export share. In addition, the greater negative effect of the volatility in medium TFP quantiles could be because of the least productive exporting firms.
Previous studies such as Fung et al. (2011), Ekholm et al. (2012), and
Choi and Pyun (2016) examine the effect of (real) exchange rate change on
firm productivity. These studies recognize various channels that a change
in the “level” of RER affects productivity―scale effect and selection
(competition) effect.4 Thus, the exchange rate effects on productivity are
heterogeneous, depending on whether the scale effect or the selection effect dominates. However, only a few studies examine the second moment
4
Scale effect indicates the reduction of average costs resulting from the expansion of firm
production that serves as an additional source of efficiency gains. Exchange rate depreciation (appreciation) can result in expansion (reduction) of output, which lead to an increase (decrease) in efficiency. Selection effect indicates that a firm’s survival from intense competition increases efficiency. Exchange rate appreciation can result in competitive environment for firm which can increase firm’s efficiency through restructuring or
resource reallocation.
10 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
of exchange rate, “exchange rate volatility,” in determining firm/plant-level
productivity even though uncertain economic environment is detrimental
for a firm’s managerial decision making.
Our work is closely related to previous studies on (exchange rate) volatility and firm growth. Chong and Gradstein (2009) find the adverse effect
of firms’ perceived volatility on its sales growth using the World Business
Environment Survey data for enterprises in 80 countries and find that
weak institutions amplify the negative growth effect of volatility. However,
their volatility measure5 captures the broad economic and financial volatility embedded in economy, not limited to exchange rate. Caglayan and
Demir (2014) and Demir (2013), using Turkish firm-level data, find negative effects of exchange rate volatility on firm output and employment
growth. Caglayan and Demir (2014) show that while output per worker
(labor productivity) is positively related to its credit market access in Turkey, the negative effects of exchange rate volatility on labor productivity
growth turn out not to differ substantially depending on accessibility to
financial markets. However, Demir (2013) shows that having access to foreign capital is found to overcome the negative effect of exchange rate volatility on employment growth.
Nonetheless, our work is distinguished from these works in that we
compare and contrast the marginal effect of exchange rate volatility between the two different exchange rate regimes—pegged and free floating.
As the market belief on exchange rate volatility between the two regimes
could be different, individual firms respond to the same volatility shock
differently according to the regime. Another contribution of this study is
that using the estimated TFP (Levinshon and Petrin 2003) to which many
firm-level studies focus, we try to investigate the heterogeneous effects of
exchange rate volatility on individual plant TFPs with respect to different
5
Their measure is constructed by questionnaires in the survey data, which includes policy
unpredictability and political instability
1. Introduction
11
TFP levels. Our quantile regression shows a common shock of exchange
rate fluctuation that is distributed to firms/plants differently in terms of
their productivity levels.
The remainder of the paper is organized as follows. Section 2 provides
the theoretical background on how the exchange rate volatility affects the
firm/plant productivity. Section 3 describes our data and empirical research design. Section 4 presents the empirical results and robustness
checks, and Section 5 concludes.
12 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
2. Theoretical Background
Previous studies explicitly show that the exchange rate volatility has a
negative effect on investment, employment, and growth (Aghion et al. 2009;
Aizenman and Marion 1999; Chong and Gradstein 2009; Serven 2003).
Some studies also provide channels through which the exchange rate volatility works its effects, particularly for exporting or multinational firms. The
exchange rate volatility affects the future cash flow and profit expectation
of firms operating in foreign markets, leading to changes in their entry and
expansion decisions. According to option-pricing models of Campa (1993),
an increase in the exchange rate volatility hampers firms’ foreign investment and subsequently their growth, as they delay their entry or expansion
decisions to foreign market. Aizenman (2003) theoretically shows that the
macroeconomic volatility in emerging markets decreases foreign firms’
employment as they switch production to less volatile markets.6 Note that
Caglayan and Demir (2014), however, do not find any empirical distinction
in labor productivity changes between foreign and domestic firms in response to exchange rate volatility.
Aghion et al. (2009) theoretically link exchange rate volatility with
productivity growth from a macroeconomic perspective. They show that
exchange rate volatility leads to fluctuations in a firm’s profit because its
revenue fluctuates along with the exchange rate but its cost is fixed under
input (wage) price stickiness in the model. This increase in volatility in
profits in turn lowers investments in innovation, which reduces productivity growth. However, investments in innovation also depend on liquidity
provided from a well-developed financial market. Thus, an increase in volatility decreases aggregate productivity growth, particularly in countries
where the financial market is under-developed (Aghion et al. 2009).
6
Conversely, exchange rate uncertainty may increase foreign firms’ entry and growth as
risk-averse firms substitute foreign production for exports (Cushman 1985; Goldberg
and Kolstad 1995).
2. Theoretical Background
13
Based on previous theoretical works on volatility and productivity, we
can infer that the growth effects of exchange rate volatility would depend
on firm and country characteristics. For instance, the negative shock of
exchange rate volatility on productivity is more pronounced for exporting
firms than domestic firms in that the exchange rate fluctuation does not
directly affect domestic firms’ profit or investment decision. Moreover,
owing to the presence of financing constraints, firms and countries that
have greater access to domestic and/or foreign capital markets can deal
with unexpected exchange rate shocks better than others do (Aghion et al.
2009; Demir 2013). Similarly, the level of import dependence, firm size,
and profitability also determine the nature of firm response to exchange
rate shocks (Klein et al., 2003).
While a few studies have examined the role of firm’s productivity itself
in determining the exchange rate volatility effect on productivity, no study
has focused on the role of exchange rate regime in determining the relationship between exchange rate volatility and productivity. First, we discuss
the effect of a government choice of exchange rate regime on firm’s sensitivity to exchange rate volatility. One may argue that exchange rate volatility and its effect would be more amplified in the free floating regime compared to “pure” fixed exchange rate regime because there is no exchange
rate fluctuation at all under the fixed regime. However, the pure fixed exchange rate regime is often modified by allowing a possible range of exchange rate fluctuation in a practical sense (i.e., a hybrid regime of fixed
and floating, managed float, and/or pegs with a band).
Suppose if there is a same degree of exchange rate volatility shock in
two different exchange rate regimes between a hybrid of fixed and floating
regime and free floating. Then, the volatility in the hybrid regime can be a
more serious concern for firms because firms in this regime recognize that
the exchange rate fluctuation is limited in the market and neglect to respond to exchange rate fluctuation shock that is small. However, under
14 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
free floating, firms would voluntarily prepare hedging tools in response to
exchange rate fluctuation because they cannot expect a possible range of
the fluctuation. For instance, while a 2.25 percent change in exchange rate
under the market average rate regime in Korea represents the maximum
change, the same 2.25 percent change of fluctuation in the free floating
would not be considered as a serious fluctuation. In this regard, the marginal effect of the same degree of exchange rate fluctuation will exert a
different influence on firms according to the regime they are in.
Furthermore, this study focuses on the individual (plant) productivity
level, and how it shapes the relationship between exchange rate volatility
and productivity. While it is evident that the exchange rate volatility shock
mainly affects firms operating in foreign market (i.e., exporting firms), it
could have an indirect effect on domestic firms/plants. First, we discuss
the possible consequences of exchange rate fluctuation on domestic or
non-exporting firms. Owing to the heightened exchange rate volatility,
discouraged exporting firms may substitute its exporting with domestic
operation, which leads to intense competition in the domestic market.
Thus, “market stealing effect” driven by discouraged exporters has a negative influence on domestic firm’s market share. Furthermore, this indirect
negative effect of volatility would be more distinct for rival domestic firms
(over a certain productivity level) against the exporters.
The exchange rate volatility shock has a direct effect on exporters. As
only exporters are exposed to the volatility shock, the shock would have a
greater negative effect on exporters than on domestic firms. However, one
may argue that exporting firms would be less sensitive to the external
shock than non-exporters because productivity is positively related to a
firm’s exporting status. Bernard et al. (2007), using the US manufacturing
firm-level data, find that exporters are systematically more productive than
non-exporters. Jang et al. (2015) also show that Korean firms that are more
productive are engaged in exporting activity more and vice versa. Using data
2. Theoretical Background
15
Figure 2. Productivity Distribution: Exporter vs Non-exporter
of Korean manufacturing plants, in Figure 2, we plot the normalized
productivity at the industry mean productivity separately for exporters and
non-exporters. Certainly, exporters’ productivity distribution in green is
located on the right-hand side of non-exporters’ distribution.
Among exporters, if they face exactly the same degree of exchange rate
volatility shock, less productive firms are more sensitive to the shock because they would not be able to adjust the shock due to their limited resources. However, more productive firms tend to be exposed to a greater
exchange rate volatility shock because they tend to have a larger share of
foreign sales out of total sales. Because productivity and the exposure to
the shock act as independent attributes to determine the relationship between exchange rate volatility and productivity, the volatility effect on
productivity would not be linear. The negative effect of exchange rate volatility on productivity would be more pronounced for not only the least
productive exporting firms (owing to lower productivity) but also the most
16 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
productive exporting firms (owing to higher exposure to the shock). Figure
3, using Helpman’s (2006) exposition on Melitz framework, summarizes
our theoretical argument on the exchange rate volatility effect on productivity separately for exporters and non-exporters.
Figure 3. Theoretical Paradigm for an Inverted W-shape Volatility Effect
Based on Melitz Model (Helpman, 2006)
2. Theoretical Background
17
3. Data and Methodology
3-1. Data and TFP Estimation
We use plant-level data of South Korean manufacturing industries for
the period 1990–2007.7 The unpublished plant-level data are from the
Annual Report on Mining and Manufacturing Survey in Statistics Korea.
Statistics Korea has originally done a complete enumeration survey of all
plants in Korea and compiled the survey data at the plant level. The data
cover all plants with 10 or more employees in 461 manufacturing industries at 5-digit KSIC (Korean Standard Industrial Classification). The unbalanced panel data are for about 51,000 to 93,000 firms for each year during the 1990–2007 period. For each year, production structures and export
statuses are available. Note that Statistics Korea permits credential users to
access this database only through their online Microdata Integration Service.
Our baseline measurement for exchange rate volatility is constructed
using daily Korean exchange rate against the US dollar. We compute an
annual standard deviation using these daily rates. Choi and Pyun (2016)
utilize the “industry”-level real exchange rate data collected from the Research Institute of Economy, Trade and Industry (RIETI). However, owing to the limited data availability of this industry rate, we use a countrylevel exchange rate to compute the exchange rate volatility. For the robustness of the results, we use the monthly real exchange rate data from
the OECD statistics. Annual standard deviations of monthly real exchange
rates are calculated as an alternative measurement of exchange rate volatility.
We estimate the plant-level productivity by industry following Levinsohn and Petrin (2003) (hereafter LP) to control for the endogeneity of
input choices influenced by productivity shocks. For instance, plants ex-
7
We exclude data in year 2000 because of firm id error in the data.
18 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
pand their output and consequently increase their inputs in response to a
positive productivity shock. Here, without addressing the simultaneity issue, the input estimates of the production function would be biased upward. LP propose a novel approach to address the simultaneity problem by
using intermediate inputs as a proxy for an unobserved time-varying
productivity shock.8 We specify the production function for each industry
in equation (1) and estimate the plant-level productivity as follows:
vit   0  l lit   k kit  it  it
(1)
,
where 𝑣𝑖𝑡 is the logarithm of manufacturing plant i’s output measured as
value added; 𝑙𝑖𝑡 is the logarithm of freely variable labor input; and 𝑘𝑖𝑡 is
the logarithm of real capital, which is a state variable. Here, value added is
calculated as revenue less cost and deflated with the producer price index;
labor input is measured with the number of workers; and real capital is
defined as fixed assets deflated by the capital equipment price index. The
deflators are from the Bank of Korea. The error term can be decomposed
with the transmitted productivity component given as i ,t and an i.i.d.
component i ,t .
The plant-level TFPs are not comparable across industries, so there is a
caveat when pooling TFP measures across industries. In addition, our
quantile regression approach evaluates the heterogeneous marginal effects
of exchange rate volatility on productivity at different levels of TFP quantiles. In equation (2), we standardize the estimated TFPs for each industry
by differencing TFPs from the industry mean and scaling it at the mean.
Then, we pool the rescaled TFPs across industries as follows:
8
Olley and Pakes (1996) use investment as a proxy for an unobserved time-varying
productivity shock, it is valid only when investments respond smoothly to productivity
shocks and sample observations report positive investment.
3. Data and Methodology
19
STFPijt 
ln TFPijt  ln TFPjt
ln TFPjt
,
(2)
where ln TFPijt is log of estimated TFP for plant i in industry j at t, and
ln TFPjt is the mean of log TFP in industry j.
Table 1 provides the descriptive statistics of the key variables for analysis
according to the exchange rate regime chosen by the Korean government.
We add the number of employment as a proxy for plant size. The Herfindahl index (HHI) is calculated as
 s , where sit is the market share of
i j
2
it
plant i in industry j at time t. This is a proxy for the degree of industry concentration capturing the information on each plant’s market share. This is
ranged from 0 (perfect competition) to 1 (monopolistic producer). The
measures for internationalization are exporting dummy coded as 1 if plants
have export volume greater than zero at year t. One concern about our
analysis is that the data include the Asian financial crisis period (1997-1998).
Table 1. Summary Statistics
20 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
To avoid any structural shock during this period, we use the sub-sample
analysis before 1997 and after 1998 as the Korean exchange rate regime
was changed in 1997.
3-2. Methodology: Quantile Regression
The standard linear regression is a useful tool for summarizing the average relationship between an outcome and a set of regressors, based on
the conditional mean function E(y|x). However, the relationship between
outcome y and regressor x could be more complex at different points in
the conditional distribution of y. The advantage of quantile regression is
that it is more robust for the sample having outliers than mean regression
(Koenker and Hallock 2001). This quantile regression also allows a richer
understanding of the data. In particular, it is more suitable for examining a
heteroskedastic data set. We specify our econometric model for the plantlevel productivity as follows:
𝑆𝑇𝐹𝑃𝑖𝑗𝑡 = 𝐸𝑋𝑅_𝑉𝑜𝑙𝑡−1 𝛽𝜃 + 𝑋𝑖𝑗𝑡−1 𝛾𝑖𝑗𝜃 + 𝛼𝑖 + 𝜖𝜃,𝑖𝑗𝑡
with QuantileƟ(𝑆𝑇𝐹𝑃𝑖𝑗𝑡 |𝐸𝑋𝑅_𝑉𝑜𝑙𝑡−1)= 𝛽𝜃 ,
(3)
where STFPijt is the standardized (log of) TFP for plant i in industry j at t ;
𝐸𝑋𝑅_𝑉𝑜𝑙𝑡−1 is a lagged value of exchange rate volatility; and 𝑋𝑖𝑗𝑡−1 is a
vector of other controls that affect plant-level TFPs, which includes firm
size, exporter dummy, and HHI. We also use a lagged value for these variables to reduce any endogeneity; 𝛼𝑖 represents plant fixed effects. Because we consider how the exchange rate volatility shapes plant-level TFPs
differently with respect to the TFP level, controlling for individual plantlevel unobserved (time-invariant) factors is important to avoid any omitted
variable bias. Hence, we include plant fixed effects in our specification. To
3. Data and Methodology
21
estimate the quantile regression with plant fixed effects, we follow Canay’s
(2011) two-step approach. 𝜖𝜃,𝑖𝑗𝑡 is an error term across quantiles.
Our main question is how different exchange rate regimes (policy
choices) lead to different 𝛽𝜃 . Therefore, we estimate the above quantile
regression using sub-samples according to the regime shift that occurred in
1997.
22 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
4. Empirical Results
4-1. Main Results
We begin by using the quantile regression to estimate the coefficients in
equation (3) separately before 1997 and after 1998. As noted, we exclude
the Asian financial crisis period (1997-1998) to avoid any abnormal shock
on plant TFPs and other macroeconomic fundamentals. We estimate the
model at each quantile (or decile) of the conditional productivity distribution (i.e., the 10th, 25th,..., 90th percentiles). Figure 4 shows our main results
on the exchange rate volatility effect on plant standardized TFP at each
TFP quantile. The x-axis reports the TFP quantile at which the regression
model was estimated. The y-axis shows the marginal effect of the volatility
on TFPs.
First, in each panel, we plot the average OLS estimates on exchange
rate volatility (horizontal navy line) and its 95 percent confidence intervals
(horizontal dash and dot lines). In two sub-samples of different exchange
rate regimes, the exchange rate volatility shows negative effects on plant
TFP; this implies that a higher volatility might lead to a decrease in firm
efficiency. More interestingly, the negative effects of exchange rate volatility are about 10 times greater in the market average rate regime than in the
free floating period. This requires more discussion but a possible explanation is as follows: a firm’s responses to an exchange rate fluctuation under
different exchange rate regimes would have different consequences on
productivity.
During the hybrid regime when the government restricted the exchange
rate fluctuation, firms and other economic agents would expect a possible
limit of changes in exchange rate. It is likely that firms do not prepare
much to avoid the loss from exchange rate fluctuation, rather than making
4. Empirical Results
23
an effort to hedge against exchange rate fluctuation. Thus, the marginal
effect of exchange rate volatility would be greater in the hybrid regime than
in the free floating regime.
Furthermore, in Figure 4, the marginal effects of exchange rate volatility on productivity vary over TFP quantiles. The red bold line represents
the marginal effect of exchange rate volatility on plant TFP at each TFP
quantile, and the dotted lines indicate the 95 percent confidence intervals.
Whenever the quantile coefficients and their confidence intervals deviate
from the OLS results, it means that there are significant differences in the
effects of the volatility across quantiles. For instance, the results in Panel A
of Figure 4 show that the coefficient on exchange rate volatility from the
OLS estimate is −1.94, which imply that a 10 percent increase in exchange
rate volatility from its mean (=0.114) is associated with a decrease of roughly
Figure 4. Quantile Regression Results
A. Market average rate regime: 1990-1997
B. Free floating:1999-2007
Note: The x-axis reports the TFP quantile at which regression the model was estimated. The y-axis shows
the marginal effect of exchange rate volatility on manufacturing plant TFPs. The average OLS estimate is depicted as the horizontal black line and its 95% confidence intervals as the horizontal
dash and dot lines. The marginal effect of the volatility on TFP at each TFP quantile are shown as a
red bold line, and the dotted lines indicate the 95% confidence intervals.
24 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
Table 2. Main Results: Sub-sample with Different Exchange Rate Regime, 1990-1997 vs 1999-2007
Note: Bootstrapped standard errors are reported in parentheses. *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively.
Source: Author’s Calculation.
10 percent in productivity from its mean (=−0.229). However, the coefficients on the volatility vary over TFP quantiles. While the coefficient on
exchange rate volatility is −2.07 at the 90th percentile of the productivity
distribution, such coefficients on the volatility at the 10th and 25th percentiles are −1.49 and −1.25, respectively. Table 2 presents the coefficient
estimates on the exchange rate volatility for two sub-samples at the 10th,
25th, 50th, 75th, and 90th conditional percentiles.
We find that both results before 1997 and after 1998 exhibit inverted
W-shape quantile regression curves. The common in both shapes is that
the negative effect of exchange rate fluctuation becomes greater at both
tails of productivity quantiles. The result also suggests that the plants with
a medium range of productivity also lost much from the exchange rate
volatility. As discussed in section 2, it is evident that the least productive
firms (regardless of whether they are exporters) were more sensitive to the
external shock. Among exporters, the least productive exporters (could be
in the medium range of productivity quantiles) were also vulnerable to the
exchange rate volatility shock. However, the greater negative effect for
most productive firms also makes sense in that a firm’s orientation of foreign market via exporting or FDI is positively associated with productivity,
and firms with higher TFPs tend to have a greater volatility shock. In sum,
our results suggest that while the least productive plants were likely to focus on domestic market and might not respond sensitively to exchange rate
volatility, most productive plants are often operating in foreign market and
more sensitive to exchange rate volatility. Our findings are also in line with
those of the previous study by Caglayan and Demir (2014) in that they also
find that export-oriented firms are hurt more from volatility.
The inverted W-shape quantile curve just shifted upward as the exchange rate regime was changed from market average exchange rate regime
to free floating, which is consistent with the OLS estimates that we discussed above.
26 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
4-2. Shape of Quantile Regression Curves: Exporters vs.
Non-exporters
As discussed, the greater negative effects of exchange rate volatility on
productivity for plants with medium and highest TFP levels need to be
investigated thoroughly in that productivity is compounded by many other
firm characteristics, particularly exporting status and export share. For robustness of results, we repeat our analysis for exporters and non-exporters
and compare the effects of exchange rate volatility on their productivities.
Exporters are defined as those plants that are now exporting or have past
experience of exporting, and otherwise non-exporters. For two subsamples of exchange rate regime, we divide each into sub-samples of exporters and non-exporters and examine the exchange rate volatility effect
on productivity. Note that the importing firms are also influenced by exchange rate volatility. However, owing to the data limitation of firm import
share, we focus more on the consequences of exporting firms. Moreover,
Choi and Pyun (2016) also show that exporting firms are highly correlated
with importing firms using another Korean manufacturing firm dataset;
their correlation is about 0.5.
The results are reported in Panels A and B of Table 3. The results in
Panel A for market average rate regime show that the negative effects of
exchange rate volatility become larger for more productive non-exporters
(a downward sloping quantile regression curve). Here, the indirect competition effect may dominate the productivity effect, which buffers the negative shock. However, for exporters, the negative marginal effect exhibits an
inverted U-shape along the TFP quantiles, which may correspond to the
right arch in our main results in Figure 4A.
Panel B shows the results for the free floating regime. For nonexporters, the marginal effect depicts an inverted U-shape, which could
match the left arch in our main result in Figure 4B. For exporters, the re-
4. Empirical Results
27
sult is interesting in that the marginal effect again exhibits an inverted Wshape. This requires another detailed investigation among exporters: The
complex shape of the curve may be due to the fact that a significant share
of the exporters group is consisted with multinationals while multinationals
tend to have higher productivity than others.
4-3. Robustness: Alternative Volatility Measure
To strengthen the robustness of the results, we introduce the alternative measurement of exchange rate volatility using monthly “real” exchange rate data collected from the OECD statistics. Real effective exchange rate index is constructed by a basket that consists of multiple currencies and corresponding constant trade weights. Therefore, this index
captures not only the exchange rate volatility between Korea and the United States but also other important trading partners. The results in Table 4
are consistent with our main findings in Table 2.
4-4. Exchange Rate Volatility with Adjacent Major Trading
Partners: China vs. Japan
Here, we introduce the bilateral exchange rate with Korea’s major trading partners, such as China and Japan. We examine the linkage between
their volatility and Korean plants’ productivity. In particular, two major
trading partners, China and Japan, have different exchange rate practice:
Japan has implemented free floating since the collapse of Bretton Woods
system in 1971, while China has used almost fixed exchange rate over the
sample period (China introduced managed float in 2005). Thus, the two
cross-exchange rates of the Korean won against the Japanese yen and the
Chinese yuan via the US dollar would have different implications on the
28 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
Table 3. Additional Results: Never-exporters vs. Exporters
Panel A. Market average rate regime (a la pegged regime) (1990-1997)
Table 3. Continued
Panel B. Free floating (1999-2007)
Note: Bootstrapped standard errors are reported in parentheses. *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively.
Source: Author’s Calculation.
Table 4. Robustness with Real Exchange Rate Volatility, 1990-1997 vs 1999-2007
Note: Bootstrapped standard errors are reported in parentheses. *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively.
Source: Author’s Calculation.
exchange rate volatility effect on productivity.
Table 5 shows the quantile regression results on the exchange rate volatility effect on plant standardized TFP at each TFP quantile, using ChinaKorea cross exchange rate and Japan-Korea cross exchange rate. The results for Korea’s cross exchange rate volatility between China and Japan
turn out to be different. First, we discuss the results for the free floating
regime. The Korean won exchange rate volatility against the Chinese yuan
had a significantly negative effect on Korean plant productivity over all
TFP quantiles and this negative effect was pronounced for the most productive plants in this free floating regime. However, the Korean exchange
rate volatility against the Japanese yen had rather greater negative influence
on the least productive Korean plants compared to that against the Chinese yuan. Moreover, the significant negative effects of volatility against
both currencies are observed for the plants with medium productivity levels.
This finding can be explained by several factors among these three
countries. First, China has became Korea’s number one trading partner
since 2002. This increasing share of Korea’s trade to China would explain
why most productive Korean (exporting) firms/plants were more sensitive
to the exchange rate fluctuation against the Chinese yuan compared to the
Japanese yen. In addition, the currency liquidity and/or vehicle currency
use for invoicing in international trade between the Chinese yuan and Japanese yen may influence the exchange rate volatility effect on Korean
plant-level productivity. The Japanese yen is considered as one of the key
currencies, as well as more frequently used as a vehicle currency (after the
US dollar) compared to the Chinese yuan during our sample period (see
Goldberg and Tille 2008).9 In this regard, the less negative effect of the
Japanese yen’s volatility compared to the Chinese yuan observed for the plants
9
Note that many recently discuss a possibility of using Chinese Yuan as a vehicle currency
in international transactions vividly.
32 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
Table 5. Exchange Rate Volatility of China-Korea vs that of Japan-Korea
Note: Bootstrapped standard errors are reported in parentheses. *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively.
Source: Author’s Calculation.
over 50th percentiles (maybe exporting firms) can be consistent with previous studies. That is, more developed financial (currency) market might
moderate the exchange rate volatility effect on productivity (Aghion et al.
2009).
In the period with market average exchange rate regime, the results for
the volatility against the Chinese yuan are consistent with our main results
in Table 2. Overall, the negative effect of the volatility on productivity in
this period is about 10 times greater than in the next period with free floating. However, the coefficients on exchange rate volatility of the Japanese
yen are puzzling. They exhibit significant and positive signs, meaning that
the exchange rate volatility against the Japanese yen had a positive effect
on Korean manufacturing plant productivity before 1997. Thus, this puzzling finding requires detailed investigation.
34 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
5. Discussion and Conclusion
Using Korean manufacturing plant-level data for 1990-2007, we find
that the negative effect of volatility on productivity was more pronounced
during the period when the exchange rate variation was restricted, compared to the period with the free floating exchange rate regime. This finding implies that firms/plants seem to be more ready to hedge the exchange
rate fluctuation allowed in the free floating regime, whereas they might
rely on the government intervention in the forex market under the hybrid
regime. However, this does not mean that free floating is better than the
hybrid regime to moderate the negative effect of exchange rate volatility
because the source of negative shock is still exchange rate fluctuation.
Thus, the government may help firms by providing detailed information
on how exporting firms can hedge exchange rate fluctuation using various
hedging tools, such as financial derivatives or foreign debts. In addition,
the government may also help firms by promoting the financial derivative
market.
Another interesting finding from this study is that the negative effects
of exchange rate volatility on productivity exhibit an inverted W-shape.
The exchange rate volatility was negatively associated with productivity and
this effect was particularly more pronounced for the plants with the lowest,
median, and highest productivities over productivity quantiles. We also
show that these double arches may be driven by the distinction between
exporters and non-exporters. While the intense negative effect of the volatility in medium TFP quantiles could be because of the least productive
exporting firms or rival domestic firms against exporters, the magnified
negative effect in the highest TFP quantile may be driven by the most productive exporting firms with the uppermost exposure to the volatility
shock owing to its large export share. This finding shows that not only
exchange rate level but also its fluctuation greatly influences the exporting
5. Discussion and Conclusion
35
firm/plant-level efficiency. Thus, the government needs to consider how
to reduce unexpected exchange rate volatility.
36 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
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Appendix. Production Function Estimation Results
Table A1. Estimates of Production Functions for 18 Manufacturing
Industries
Note: The table reports a two-sided test. For one side of the test for IRS, the p-value can be obtained by
dividing the reported p-value in half.
40 The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants
List of KIEP Working Papers (2012-2016. 10)
 2016
 2015
16-08
The Effect of Exchange Rate Volatility on Productivity of Korean Manufacturing Plants: Market Average Rate Regime vs
Free Floating
CHOI Bo-Young and PYUN Ju Hyun
16-07
To Whom does Outward FDI Give Jobs?
KANG Youngho and WHANG Unjung
16-06
Labor Market Flexibility and FDI: Evidence From OECD Countries
CHO Hyelin
16-05
International Transmission of U.S.Monetary Policy Suprises
KIM Kyunghun, and KANG Eunjung
16-04
The Impact of Chinese Economic Structural Changes on Korea's Export to China
CHOI Bo-Young and SHIN Kotbee
16-03
A Predictive System for International Trade Growth
CHON Sora
16-02
A Short-term Export Forecasting Model using Input-Output
Tables
PYO Hak K. and OH Soo Hyun
16-01
Access to Credit and Quality of Education in Vietnam
HUR Yoon Sun
15-03
Estimating Regional Matching Efficiencies in the Indian Labor Market: State-level Panel Data for 1999-2011
LEE Woong
15-02
The Distribution of Optimal Liquidity for Economic Growth
and Stability
PYO Hak K. and SONG Saerang
A List of all KIEP publications is available at: http://www.kiep.go.kr
References
41
15-01
Income Distribution and Growth under A Synthesis Model of Endogenous and Neoclassical Growth
KIM Se-Jik
14-05
Regional Financial Arrangement in East Asia: Policy Proposal
for Strengthening the Chiang Mai Initiative Multilateralization
Pravin Krishna, Jiyoung Choi, and Tae-Hoon Lim
14-04
Labor Market Flexibility and Different Job-Matching Technologies across Regions in India: An Analysis of State-Level Disaggregate Matching Functions
Woong Lee
14-03
Rising Income Inequality and Competition: Evidence
Minsoo Han
14-02
Inequality and Fiscal Policy Effectiveness
Ju Hyun Pyun and Dong-Eun Rhee
14-01
Inequality and Growth: Nonlinear Evidence from Heterogeneous Panel Data
Dooyeon Cho, Bo Min Kim, and Dong-Eun Rhee
13-09
Gains from Trade Liberalization: CUSFTA
Soohyun Oh and Gihoon Hong
13-08
Determinants of International Labor Migration to Korea
Yoon Ah Oh and Jione Jung
13-07
European Affiliations or National Interests? Analyses of Voting
Patterns on Trade Policy in European Parliament
Yoo-Duk Kang
13-06
The Causal Relationship between Trade and FDI: Implication
for India and East Asian Countries
Choongjae Cho
13-05
Nonlinear Effects of Government Debt on Private Consumption in OECD Countries
Dooyeon Cho and Dong-Eun Rhee
 2014
 2013
 2012
13-04
Anti-Dumping Duty and Firm Heterogeneity: Evidence from
Korea
Seungrae Lee and Joo Yeon Sun
13-03
Regional Borders and Trade in Asia
Woong Lee and Chankwon Bae
13-02
Joining Pre-existing Production Networks: An Implication for
South-East Asian Eco-nomic Integration
Jeongmeen Suh and Jong Duk Kim
13-01
Measurement and Determinants of Trade in Value Added
Nakgyoon Choi
12-07
An Assessment of Inflation Targeting in a Quantitative Monetary Business Cycle Framework
Dooyeon Cho and Dong-Eun Rhee
12-06
Real Frictions and Real Exchange Rate Dynamics: The Roles
of Distribution Service and Transaction Cost
In Huh and Inkoo Lee
12-05
Korea’s Monetary Policy Responses to the Global Financial
Crisis
In Huh
12-04
Election Cycles and Stock Market Reaction: International Evidence
Jiyoun An and Cheolbeom Park
12-03
A Theory of Economic Sanctions
12-02
Multilateral Engagement in North Korea’s Economic Rehabilitation
and Possible Establishment of Trust Funds
Jong-Woon Lee and Hyoungsoo Zang
12-01
Comparative Advantage, Outward Foreign Direct Investment
and Average Industry Productivity: Theory and Evidence
Yong Joon Jang and Hea-Jung Hyun
Baran Han
국문요약
본 연구는 1990년부터 2007년까지 제조업 사업체 데이터를 사용하여 환율변동
성이 사업체의 생산성에 미치는 효과를 실증적으로 분석하였다. 특히 1997년을
기점으로 우리나라의 환율제도가 시장평균환율제도에서 자유변동환율제도로 전
환됨에 따라 이 두 체제가 사업체의 생산성에 미치는 효과를 비교해보았다. 분석
결과 환율변동성은 사업체의 생산성에 부정적인 영향을 끼치며 그 부정적인 효
과는 환율변동성의 폭이 상대적으로 작았던 시장평균환율제도 하에서 더 컸음이
드러났다. 또한 본 연구는 기업의 생산성 분위별로 이러한 부정적인 효과가 다르
다는 사실을 보였다. 환율변동성의 부정적인 효과는 생산성이 가장 낮거나 생산
성이 가장 큰 사업체에 가장 두드러지는 것으로 나타났다.
핵심용어: 총요소생산성, 한국 사업체 데이터, 환율변동성, 분위회귀분석
최보영(崔輔榮)
미국 University of California, Davis 경제학 박사
대외경제정책연구원 동북아경제본부 협력정책팀 부연구위원 (現, E-mail: [email protected])
저서 및 논문
『주요국의 중소기업 해외진출지원전략과 시사점』(공저, 2014)
『한·중·일의 비관세장벽 완화를 위한 3국 협력방안: 규제적 조치를 중심으로』(공저, 2015) 외
편주현(片周弦)
고려대학교 경제학과 졸업
고려대학교 경제학과 석사
미국 University of California, Davis 경제학 박사
고려대학교 국제경영학과 교수(現, E-Mail: [email protected])
저서 및 논문
『글로벌 금융위기 이후 주요국 거시금융 정책의 평가와 시사점』(공저, 2012)
『금융통합이 금융위기에 미치는 영향』(공저, 2013) 외
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KIEP Working Paper 16-08
The Effect of Exchange Rate Volatility on Productivity of Korean
Manufacturing Plants: Market Average Rate Regime vs Free Floating
CHOI Bo-Young and PYUN Ju Hyun
This study examines how exchange rate volatility can influence total factor productivity (TFP) in various dimensions.
Using Korean manufacturing plant-level data for 1990-2007, we first compare and contrast the effects of exchange
rate volatility on TFPs between two different exchange rate regimes—pegged and free floating. We find that the
exchange rate volatility had a negative effect on productivity in both regimes but this negative effect was greater
during the period when exchange rate fluctuation was restricted, compared to the period with free floating rate.
We also find that the negative effects of the volatility on productivity were heterogeneous over TFP quantiles and
exhibited an inverted W-shape curve. In particular, the negative effects were more pronounced for exporting plants
that had the lowest or highest TFPs.
Building C, Sejong National Research Complex, 370, Sicheong-daero, Sejong-si, Korea
Tel. 82-44-414-1114 Fax. 82-44-414-1001
www.kiep.go.kr
ISBN 978-89-322-4259-0
978-89-322-4026-8(set)
Price USD 3