ï»¿ WPS5989
Policy Research Working Paper 5989
Spillover Effects of Exchange Rates
A Study of the Renminbi
Aaditya Mattoo
Prachi Mishra
Arvind Subramanian
The World Bank
Development Research Group
Trade and Integration Team
March 2012
Policy Research Working Paper 5989
Abstract
This paper estimates how changes in Chinaâ€™s exchange spillover effect that is statistically and quantitatively
rates would affect exports from competitor countries in significant. Their estimates suggest that a 10-percent
third-country marketsâ€”in other words, the â€œspillover appreciation of Chinaâ€™s real exchange rate boosts a
effect.â€? The authors use recent theory to develop an developing countryâ€™s exports of a typical four-digit
identification strategy, with a key role for the competition Harmonized System product category to third markets
between China and its developing country competitors by about 1.5 to 2 percent on average. The magnitude
in specific products and export destinations. Using of the spillover effect varies systematically with the
disaggregated trade data, they estimate the spillover effect characteristics of products, such as the extent to which
by exploiting the variation across different exporters, they are differentiated.
importers, products, and time periods. They find a
This paper is a product of the Trade and Integration Team, Development Research Group. It is part of a larger effort by
the World Bank to provide open access to its research and make a contribution to development policy discussions around
the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be
contacted at amattoo@worldbank.org, pmishra@imf.org, and asubramanian@piie.com.
The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development
issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the
names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those
of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and
its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.
Produced by the Research Support Team
â€
Spillover Effects of Exchange Rates: A Study of the Renminbi
Aaditya Mattoo (Development Research Group, World Bank),
Prachi Mishra (Research Department, International Monetary Fund), and
Arvind Subramanian
(Peterson Institute for International Economics and Center for Global Development)
Keywords: exchange rates, exports, China, spillover
JEL codes: F13, F14, O53
â€
Authorsâ€™ contact: amattoo@worldbank.org, pmishra@imf.org, asubramanian@piie.com. The views expressed in
this paper are those of the authors and do not necessarily represent those of the International Monetary Fund (IMF)
or World Bank (WB) or their policies. We are grateful to George Akerlof, Olivier Blanchard, Andy Berg, Elhanan
Helpman, Gita Gopinath, Amit Khandelwal, Maurice Obstfeld, Hui Tong, and Shang-Jin Wei as well as seminar
participants at the American Economic Association Meetings (Chicago), Georgetown University, IMF, Peterson
Institute for International Economics, and World Bank for helpful comments and discussions. We are particularly
grateful to Rob Feenstra for very detailed suggestions and advice. Martin Kessler and Ujjal Basu Roy provided
excellent research assistance. All remaining errors are our own.
I. Introduction
Studying the effects of exchange rates is a hardy perennial of international macroeconomics. But
nearly all the empirical research is focused on the impact of exchange rate changes on the
country experiencing or undertaking them. 1 There is less evidence quantifying the effect of
exchange rate movements on the exports of competitor countries, a classic case of spillover that
in its adverse manifestation is dubbed the â€•beggar-thy-neighborâ€– effect.
This paper examines the spillover effect of movements in Chinaâ€™s exchange rate on exports of
other developing countries in third country markets. The Chinese currency provides a suitable
opportunity to study the spillover dimension for three reasons. First, China, by virtue of being the
worldâ€™s largest exporter of goods, is likely to have quantitatively more significant competitive
consequences for other countries than nearly any other exporter. Second, China is also a highly
diversified exporter so that it potentially competes with a broad range of countries and across the
product spectrum. Finally, reflecting Chinaâ€™s dominant size and encompassing scope, its
exchange rate policy has been one of the most controversial aspects of international
macroeconomics during the 2000s. More recently, it has been in the spotlight because of the
consequences of a possibly undervalued renminbi on demand and output in industrial countries
experiencing high unemployment and excess capacity.
The spillover effect is estimated with the help of highly disaggregated trade data which facilitates
the use of a novel methodology to exploit the variation across exporters, importers, products, and
time. We use disaggregated trade data at the 6-digit level spanning 124 developing country
exporters and 57 large importers over the period 2000-2008. Our empirical approach is
motivated by an analytical framework that we develop based on Feenstra, Obstfeld, and Russ
1
This is generally true of the older, voluminous literature on the trade consequences of exchange rates (Goldstein
and Khan (1985) provides a survey and other contributions include Hooper, Johnson and Marquez (2000); Thursby
and Thursby (1987)). It is also true of the more recent micro-literature on trade and exchange rates (Dekle and Ryoo
(2007); Das, Roberts and Tybout (2001); Forbes (2002); Berman, Martin and Mayer (2012)). It is also a
characteristic of the recent literature on the growth consequences of exchange rates (Dooley et. al. (2003); Rodrik
(2008); and Johnson et. al. (2010)).
2
(2011). The framework suggests an identification strategy that relies on the following reasoning:
the more a country competes with China in a third market, the more a given depreciation of the
renminbi is likely to hurt its exports in that market. We develop indices of competition between
China and its competing exporting countries at the exporter-importer-product level to implement
this strategy. The empirical specification, with a battery of very general fixed effects that control
for all observable and unobservable importer-exporter-product, importer-exporter-time, exporter-
product-time and importer-product-time varying characteristics, helps us overcome to a large
extent the problems of omitted variables that plague estimation of trade-exchange rate equations
using aggregated data. Moreover, our estimates are less susceptible to reverse causality concerns
as exports, measured at a disaggregated level, are unlikely to affect a macroeconomic variable
like the exchange rate, more so when the latter is the exchange rate of another country, China.2
We find robust evidence for the existence of a statistically and economically significant spillover
effect. In particular, exports to third markets of countries with a greater degree of competition
with China tend to rise/fall significantly more as the renminbi appreciates/depreciates. Our
estimates suggest that a 10 percent appreciation of the renminbi increases a developing countryâ€™s
exports at the product-level on average by about 1.5-2 percent. For high indices of competition,
the increase could be as large as 6 percent. The results imply that, going forward, an appreciation
of the renminbi could provide a substantial boost to developing country exports. Our spillover
estimates are robust to a variety of statistical tests, to alternative measures of exchange rates, to
alternative disaggregation of the trade data, and also across exporting and importing regions.
They are also robust to incorporating the effect of competition from countries (other than China)
whose currencies move with the renminbi.
We also find that the magnitude of the spillover effect is consistent with the predictions from the
analytical framework. For example, as implied by theory, the spillover effect is greater for
homogenous products with greater substitution possibilities than differentiated products. Further,
the spillover effect is attenuated for products that rely more on foreign inputs (and hence have a
lower degree of Chinese domestic value added).
2
See Engel (2009), for a discussion of how hard it is econometrically to separate out the effect of exchange rates on
trade.
3
A few recent studies examine the effects of Chinaâ€™s export performance on other Asian countries
but do not focus on exchange rates (Hanson and Robertson (2008), Eichengreen, Rhee and Tong
(2004) and Ahearne et. al. (2003); the latter two use an augmented gravity framework and find
some evidence of Chinese exports crowding out other Asian exports). A few other papers
examine the impact of exchange rate changes but on variables other than trade.3 For example,
Eichengreen and Tong (2011) have recently estimated the effect of renminbi revaluation on stock
market valuations of foreign firms. 4 There is no study so far on the effect of exchange rate
changes on exports of other countries, even though this has been a central international concern
going back to Robinson (1947) and the experience of the competitive devaluations prior to and
during the Great Depression.
The rest of the paper is organized as follows. In Section II, we set out the analytical framework.
Section III elaborates the estimation strategy and Section IV describes the data. The results are
presented and validated in Section V and Section VI concludes.
II. Analytical Framework
In order to develop an analytical framework for our empirical exercise, we use the model in
Feenstra, Obstfeld and Russ (2011). The setting is as follows. There are countries, different
goods. Each country produces a range of distinct varieties of each good. There is a constant
elasticity of substitution ( ) consumption index for the representative consumer in country .
Goods are differentiated not only by their characteristics, also by their country of origin
(Armington assumption), with a constant elasticity of substitution between domestically
produced and foreign varieties of good ( ), and a constant elasticity of substitution between
different varieties of good originating in different exporters ( ). The same elasticity applies to
different varieties of good produced domestically.
3
Yet another strand in the China-related literature has been to explain the determinants of Chinaâ€™s real exchange
rate (Wei and Zhang, 2011).
4
Eichengreen and Tong (2011) find that renminbi appreciation has a positive effect on stock prices of firms in
sectors competing with China, which is consistent with the findings in this paper.
4
Feenstra, Obstfeld and Russ (2011) show that we can express country â€™s imports from country
(equivalent to exports of country i to country j) of a particular good , defined at the HS 6-digit
level, , as follows (equation 11 in their paper).
(1)
That is, the proportion import demand ( ) of total consumption in , depends on three sets
of components: 5
ï‚· the preference weight consumers in attach to imports of good g from country , ; the
price of g imports by from , , relative to the price index of all imports, ; and
the elasticity of substitution between imported varieties of , ;
ï‚· the preference weight consumers in j attach to domestically produced units of good , ;
the price index of all imports by , , relative to the domestic price of good , ;
and the elasticity of substitution between the home and foreign varieties of good , ;
ï‚· the preference weight consumers in attach to consumption of the good, ; the price
index of the good, , relative to the price index of all goods in , ; and the
elasticity of substitution between different goods, .
We first establish the effect of a change in Chinaâ€™s exchange rate changes vis-a-vis country ,
, on country â€™s imports of a particular good from country , -- what we define as the
â€•spillover effectâ€–. We can express this as a chain effect, consisting of the effects of: the change
5
Note that we use imports and exports interchangeably throughout this paper, based on the simple identity that
imports of a country A from another country say B are exactly the exports of B to A. In the empirical section, we
use data reported by importing countries, which is generally regarded as more reliable than export data.
5
in the Chinese exchange rate on the price of the Chinese good, the change in the price of the
Chinese good on the foreign price index, and the change in the foreign price index on demand for
good from country :
(2)
Now consider each term in the chain starting from the third term. Taking logs of Equation (1)
and differentiating with respect to under the assumption that a change in has a negligible
effect on the aggregate price index for good in country , we get:6
(3)
This implies that the elasticity of demand for imports of good from country with respect to
the foreign price index is simply the difference between the elasticity of substitution between
imported varieties of , , and the elasticity of substitution between home and foreign
varieties, .
From Feenstra, Obstfeld and Russ (2011), we have the price index for imported goods, ,
(their equation 5):
(4)
Taking logs, differentiating with respect to the price of the Chinese good in the market,
and simplifying, we get:
6
This is an innocuous assumption from the empirical perspective because any additional termsâ€”for example
aggregate destination-specific prices â€” will be absorbed in the very general fixed effects.
6
(5)
This implies that the elasticity of the foreign price index for good with respect to the price of
the Chinese good is equal to the expenditure on the Chinese good as a share of expenditure on
all imports of , .
We assume that the price of the Chinese good in the market, , depends on the price in
China, , the exchange rate, (defined in renminbi/importer currency), and an exponent
which captures the extent of product-specific exchange rate pass-through from prices in China to
, .
(6)
Differentiating with respect to the exchange rate, , we have:
(7)
Substituting from Equations (3), (5) and (7) in Equation (2), we get:
(8)
Equation (8) implies that a change in the Chinese exchange rate will have a non-zero effect on
import demand for good only if (i) the elasticity of substitution across imported varieties is
7
different from that between imported and domestic varieties, (ii) Chinese share in total imports
of that good is strictly positive, and (iii) the exchange rate pass-through is non-zero. 7
Given our assumption regarding the symmetric elasticity of substitution between imported
varieties, , the effect of a change in Chinaâ€™s exchange rate changes vis-Ã -vis country , ,
on country â€™s imports of a good from country , , does not depend on any exporter
attribute. This makes Equation (8) less amenable to empirical analysis. For example, if in order
to test the prediction in Equation (8), we were to regress the import demand at the exporter-
importer-product level on the Chinese exchange rate vis-Ã -vis the importing country, we would
not be able to include destination country fixed effects. We could, of course, strive to include all
the relevant destination country attributes explicitly, but the effect of the exchange rate would
not be estimated precisely because we would inevitably fail to control for certain unobserved
sources of variation at the destination country (or destination-year) level.
One way to have such more general controls is to introduce more variationâ€”for example, across
exportersâ€”in the right hand side of Equation (8). This would allow importer demand at the
exporter-importer-product level to be regressed on a term that had all three sources of variation,
which in turn would allow the inclusion of general fixed effects in the regression. To find such
variation across exporters, we consider country â€™s imports, , from country of a particular
bundle of goods , defined at a higher level of aggregation. In our empirical analysis, we use
trade data at the Harmonized System (HS) 6-digit. Therefore is defined at the HS 6-digit level.
Country â€™s imports of (at say the HS 4-digit level) can be expressed as:
(9)
7
Note that in Broda and Weinstein (2006), , i.e. the elasticities of substitution between imported varieties
equals the elasticity of substitution between home and foreign varieties. In our framework, if , in response
to a renminbi depreciation, consumers in country reduce their demand for varieties of good produced at home
and hence there is no spillover effect.
8
G denotes the number of HS 6-digit lines in the product category p. Taking logs and
differentiating with respect to the exchange rate, and simplifying we get8
(10)
This equation is intuitive because it captures the interplay between two ingredients that together
determine the spillover effect of Chinaâ€™s exchange rate: the first is the relative importance of
China as a source of imports of a good in the importing country, ; the second is the relative
importance of that good ( ) in the exports of the competitor country. More formally, the
elasticity of say Brazil's exports to at the HS 4-digit category with respect to Chinaâ€™s exchange
rate vis-Ã -vis is related to the weighted average of China's share in total imports in each
constituent 6-digit category which Brazil exports, where the weights are Brazilâ€™s exports in the
corresponding 6-digit category as a share of its total exports in the 4-digit category.
Further, we also assume that the elasticities of substitution and the pass-through are constant for
all 6-digit lines within the relevant 4-digit category. i.e. ï? g ï€½ ï? Cj , ï?³ g ï€ ï?·g ï€½ ï?³ p ï€ ï?· p . Then
Cj
p
Equation (10) can be rewritten to give us an expression for the spillover effect, ,
(11) I ijp * [ï€ï? Cj * (ï?³ p ï€ ï?· p )]
V
p
G Vgij
where I ijp ï€½ ïƒ¥[(
V
ij
) * sg ] is what we call the â€•value-based index of competitionâ€– (VBI) with
Cj
g ï€½1 V p
China for good g exported from i to j . For example, if the HS 4-digit category, shirts,
consisted of only two items, cotton shirts and non-cotton shirts, then our measure is simply the
share of China in country j â€™s imports of each type of shirt, weighted by the importance of each
8
See the Appendix for the intermediate steps in deriving Equation (10).
9
type of shirt in country i â€™s shirt exports to j . Equation (11) suggests that the elasticity of
exports of a typical product to the importing country depends on: the index of competition; the
two elasticities of substitution, and Ï‰; and the extent of passthrough, .
Under some additional symmetry assumptions, we can also compute an alternative index of
competition where we rely on the overlap between Chinaâ€™s exports and those of country , at the
extensive margin. We first assume that for each 6-digit category that exports to within a 4-
digit category, it exports the same amount. If exports N ij 6-digit categories in the relevant 4
p
digit category to , then the first term in Equation (10) simplifies to 1 / N ij . Next assume that in
p
each 6-digit category within the relevant 4-digit category where exports to , China exports
either a fixed share, s Cj or nothing. s g ï€½ s Cj for N ij,Ch lines or zero otherwise. Then summing
p
Cj
p p
the second ratio over the relevant 6-digit lines gives us s Cj * N ij,Ch . As above, we also assume
p p
that the elasticities of substitution and the pass-through are constant for all 6-digit lines within
the relevant 4-digit category. i.e. ï? g ï€½ ï? Cj , ï?³ g ï€ ï?·g ï€½ ï?³ p ï€ ï?· p .
Cj
p
So that in this special case, Equation (11) can be written as:
[ï€s Cj * ï? Cj * (ï?³ p ï€ ï?· p )]
C
(12) I ijp p p
N ij,Ch
where I C
ijp ï€½ pij is what we call the â€•count-based indexâ€– (CBI) of competition. The notion of
Np
competition in the CBI is based on whether or not China and its competitor commonly export a
particular good (the extensive margin), and unlike the VBI, ignores the magnitudes of exports.
III. Estimation Strategy
Equations (11) and (12) motivate the estimation of the spillover effect. They imply two key
predictions which we can take to the data: (i) spillover effect is less than or equal to zero and (ii)
10
the magnitude of this effect depends on the index of competition between China and its
competing exporters. Higher is the degree of competition, larger is the magnitude of the spillover
effect.
Our identification strategy relies on the following intuition. Take two countries, Malawi and
Brazil. Assume that Brazil faces a greater degree of competition with China in the US market for
a particular product. When the renminbi depreciates vis-Ã -vis the US$, exports from Brazil to the
US for that product will fall more than exports from Malawi to the US (Figure 1).
Figure1. Identification Strategy
Renminbi/$
China Z (US)
Exports
Exports
X (Malawi)
Exports
Y (Brazil)
This identification strategy yields the following estimating equation:
11
(13)
where is the value of exports of HS 4-digit product from country to country . is the
Chinese exchange rate vis-Ã -vis measured in renminbi per unit of â€™s currency. is an index
of competition between Chinese exports and those of its competitors as described in the
analytical section. Note that the index does not have a time sub-script which we explain below.
The interaction term combines the exchange rate between China and the importing country (say
the renminbi-dollar exchange rate) and the index of competition between the exporter and China
in the importing country.
Econometrically, an advantage of the formulation in equation (13) is that we can control for a
wide range of omitted variables through a set of very general fixed effects. In fact, in our core
estimations, we employ all three-way combinations of importer, exporter, product and time fixed
effects. The term captures any importer, product and time varying characteristics: one
example would be fiscal support for the car industry in the United States. Similarly, the term
captures any exporter, product, and time-varying characteristics; for example, a productivity
shock in Bangladesh that helped textile exports. Note that these fixed effects also encompass all
country-time shocks both on the importer and exporter side such as the business cycle in each
country. The term captures any bilateral time-varying determinants of exports: for example,
currency unions, and exchange rate pegs against particular currencies. The term captures
bilateral product-specific characteristics: for example, all pre-existing preferential trade
agreements that have product-specific tariffs and other barriers. The only factors that are not
controlled for are policies of the importing country that vary by source country and product and
time (for example, changes over time in product-specific preferential tariffs).9 Finally, it is worth
noting that our estimation strategy also controls for any possible effect on competitor countries
stemming from productivity or other developments in China, whether exogenous or induced by
exchange rates: if these are time-varying and product-specific, they will be absorbed in the
and fixed effects.
9
The lack of a comprehensive database on trade policies at the importer-exporter-product-time level makes it
difficult to control for such effects.
12
Furthermore, our estimating equation is less susceptible to reverse causality from exports to
exchange rates for two reasons: our dependent variable, disaggregated exports, is less likely to
affect a macroeconomic variable like the exchange rate; moreover, the latter is the exchange rate
of another country. What about reverse causality from the exports to the index of competition?
Our count-based index, while derived from theory under symmetry assumptions, has the
empirical virtue of being based on the extensive margin and not being measured in value terms;
hence being less related to the left hand side variable and less afflicted by reverse causality
problem. Our value based index is potentially more vulnerable to the reverse causality problem
because it is expressed in values, like the dependent variable. To minimize such endogeneity
concerns we compute both indices for the initial period of the sample (i.e. for the year 2000).
IV. Data
We focus on the period 2000-2008, during which concerns about Chinaâ€™s exchange rate policy
have been most debated. For this period, we compile disaggregated data on bilateral exports
from the UN Comtrade database. We collect data reported by the importing countries, which is
generally regarded as more reliable than data on exports (i.e. exports from i to j are measured by
imports of j from i). The data are for roughly 6000 non-oil HS 6-digit lines covering 900 4-digit
products. We cover the 57 major importing countries (making sure that we include all countries
that together accounted for over 95 percent of total exports of developing countries) and 124
developing country exporters which are potentially in competition with China (summary
statistics are provided in Appendix Table A1 and the list of importing and exporting countries
covered in Appendix Table A2). 10 The list of developing countries is based on World Bank
country classification, and is comprised of all low and middle income countries (2010 GNI per
capita of $12,275 or less).
10
In principle, we could include all exporting countries in our sample. We choose to restrict the analysis to
developing country exporters, largely due to computational constraints. However, this restricted choice also stems
from the fact that developing countries compete more with China than industrial countries do: the average index of
competition between the former set and China is about 0.4 and 0.9, respectively for the value based and count based
indices of competition. The corresponding numbers for industrial countries are 0.1 and 0.7, respectively.
13
The trade data are reported in current US dollars, and are deflated by the US CPI. We recognize
that ideally we would use bilateral price indices to deflate trade between different country pairs
but such bilateral deflators are not available. However, the presence of the very general fixed
effects has the consequence also of implicitly deflating the trade data. The data are implicitly
deflated by prices that vary by importer, product and time; by importer, product and exporter;
and by exporter, product and time. They are, however, not deflated by prices that vary along all
four dimensions (importer, exporter, product, and time).
Exchange rate data are from the IMFâ€™s International Financial Statistics (IFS) database. In the
theoretical framework, the key price that determines the transmission mechanism of exchange
rate changes is the price in the importing market charged by Chinese exporters. Equation (6)
suggests that this price is determined by the domestic price of the good in China, the China-
importer bilateral exchange rate and the passthrough. Since we parameterize the passthrough, the
relevant changes to focus on are those stemming from changes in domestic prices in China and
the exchange rate. Hence, our bilateral exchange rate is deflated by Chinaâ€™s CPI.
Before we present the econometric results, it is worth looking at some basic data. Figure 2 plots
Chinaâ€™s average index of competition (where the average is over all exporters and products). The
index is measured in two ways consistent with the discussion in the analytical section. Both the
VBI and the CBI rise over time, consistent with China becoming a bigger and more diverse
exporter. The CBI shows in particular that by 2008, on average, China occupies nearly all the
product space of other developing country exporters. Figures 3a and 3b plot the same indices but
disaggregated by region. These charts show that Chinaâ€™s overlap with all regions has risen
steadily over time, with the level of the overlap greatest with other exporters in Asia (over 95
percent in 2008 for the CBI) and least with Europe and Central Asia.
14
V. Results
Main findings and robustness
All results are presented for both variations of our competition index. In Table 1, we present the
baseline results. Our core sample has nearly 3.6 million observations. Columns [1]-[4] use the
value-based index (VBI) while columns [5]-[8] use the count-based index (CBI). In both cases,
the number of fixed effects progressively increase across the specifications, with a
comprehensive set of fixed effects in columns [4] and [8], making the specification a very
demanding one. These will constitute our core specifications. All regressions are clustered at the
importer-exporter-product level.
We find that the coefficient on the interaction term between the Chinese exchange rate and the
index of competition is consistently negative and significant at the 1 percent confidence level. In
other words, a depreciation of the Chinese exchange rate vis-Ã -vis say the dollar is associated
with a greater reduction in a developing countryâ€™s exports of a particular product to the United
States, the more that country is in competition with China in that product in the United States.
We subject this core specification to a series of robustness checks in Tables 2-6. In Table 2,
column [1], we drop outliers, defined as the top and bottom 1 percentile of observations. The
key coefficient is negative and statistically significant with the magnitudes close to those for the
larger, core sample. In columns [2]-[4], we cluster the standard errors at the exporter-importer-
year, exporter-product-year and importer-product year levels, and the statistical significance of
the coefficients remains unchanged.11
11
Clustering the standard errors at a higher level of aggregation (importer-exporter, importer-product, or exporter-
product) also does not alter the significance of our findings.
15
Our core specification uses annual data. To test whether the results hold for the medium run, we
use a long difference approach suggested by Acemoglu and Johnson (2007). Thus, in column [5],
we use observations only for 2000 and 2008 and find that the results remain similar to the
baseline, with the magnitude of the interaction coefficient increasing by a little. In columns [6]
and [7], to make sure that the results are not driven by the choice of year for measuring the index
of competition, we measure the index for the years 2001 and 2002, respectively. In column [8],
we use an alternative measure of competitionâ€”the export similarity index due to Finger and
Kreinin (1979).12 Thus, for a wide range of robustness tests, the core results remain unaltered,
both in the sense that the coefficients are stable and consistently significant at the 1 percent
confidence level.
In Table 3, we test for robustness to alternative measures of the exchange rate variable. In our
analytical framework, we assumed that the price of Chinese goods in the importing country
market is determined by a simple relationship between domestic prices in China and exchange
rate pass-through. Based on the framework, in our core specifications, we deflate the nominal
bilateral exchange rate (between China and the importing country) by Chinese prices. The
X ijgt X Cjgt
12
The Finger-Kreinin index can be expressed as: FK ijpt ï€½ ïƒ¥ min [ , ] where
g
ïƒ¥
g
X ijgt ïƒ¥
g
X Cjgt
X ijgt
ï€½ Share of product g in total exports from i to j at the 4 - digit level
ïƒ¥g
X ijgt
X Cjgt
ï€½ Share of product g in total exports from China to j at the 4 - digit level.
ïƒ¥g
X Cjgt
The results are also robust to using the alternative formulation of the Finger-Kreinin Index defined as
and the weighted Finger-Krenin Index defined as
.
16
implicit assumption here is that Chinese producers take account of changes in the bilateral
exchange rate and average domestic inflation to determine export prices. However, there could
be alternative ways Chinese producers and exporters determine their destination-specific export
prices. Chinese producers could be influenced just by the nominal bilateral exchange rate ( ) or
by the real bilateral exchange rate ( ), with and denoting prices in importing
country and China respectively. The specifications corresponding to these two ways of
measuring the exchange rate are in columns [1] and [2] (for the VBI) and columns [6] and [7]
(for the CBI). In both cases, the results are robust, although the magnitudes decline relative to the
core specification.
Yet other models of pricing behavior could involve Chinese producers looking at changes in
their multilateral competitiveness in determining destination-specific export prices. In this case,
the relevant exchange rate is not destination specific but a multilateral one that is identical across
all importers ( ) where stands for Chinaâ€™s multilateral exchange rate and hence without a
13
subscript). We re-estimate the core regression to cater to these possibilities by using the
IMFâ€™s effective exchange rate as the relevant measure with the nominal rate in columns [3] and
[8], and the real rate in columns [4] and [9]. Again, the coefficients are correctly signed and
significant at the 1 percent confidence level. Interestingly, these coefficients are substantially
greater than for the core specification.
In all these specifications, exchange rates are measured as the relative price of two different
currencies. An alternative way of measuring real exchange ratesâ€”sometimes called the internal
real exchange rateâ€”is as the relative price of tradables to nontradables within a country. This
exchange rate is available from the Penn World Tables from the series that measures the price
level of GDP.14 In columns [5] and [10], we use this measure of Chinaâ€™s real exchange rate.
13
Note that in this case, the exchange rate varies across time and the index varies across importer, exporter, and
product so that the interaction term exploits the variation across all four dimensions.
14
A higher price level is associated with a higher price of non-tradables and hence signifies an appreciation of the
real exchange rate (see Rogoff, 1996). This exchange rate variable, like the IMFâ€™s nominal and effective exchange
rate series, is a multilateral variable, and hence varies only by time and not across importers.
17
Again, we find that the coefficient on the interaction term is significant at the 1 percent level, and
is greater in magnitude than in the core specification.15
One potential omitted variable issue arises in regard to our core specification. Our finding that
the typical developing countryâ€™s exports are adversely affected when Chinaâ€™s currency
depreciates has not yet addressed an important question: What if other countries respond to
Chinaâ€™s depreciation by devaluing their own currencies? In Table 4, we control for this
possibility. Among the developing countries which are the top exporters, we identify those
whose currencies are most closely correlated with that of China (in real terms) during the period
2000-08.16 We interact the exchange rates of each of these countries with the respective index of
competition of each with the exporting country, where the index is defined analogous to that of
China in equations (11) and (12).
In columns [1] and [4], we include countries whose exchange rates have a correlation coefficient
relative to the renminbi that is greater than 0.7. So we add two additional regressors to the core
specification. In each case, the regressor is the interaction between the countryâ€™s exchange rate
and that countryâ€™s index of competition. In columns [2] and [5], we repeat this procedure to
include countries whose correlation coefficients with the renminbi are more than 0.4. In columns
[3] and [6], the threshold correlation coefficient is 0.3. For presentational reasons, we only show
the impact on the main coefficient of interest, namely that relating to China. This coefficient
remains significant at the 1 percent confidence level, although it is slightly reduced in magnitude.
Overall, these results suggest that our main finding related to the spillover effect of the Chinese
exchange rate remains strong and robust to inclusion of possible omitted variables. Thus,
exporters competing with China suffer because of a renminbi depreciation and not (or not just)
15
Note that an increase in all the effective exchange rate measures in columns [3]-[5], and [8]-[10] denotes an
appreciation (unlike in columns [1]-[2], and [6]-[7], and our baseline exchange rate measures in Tables 1 and 2).
Hence, a positive coefficient on the interaction terms in these columns is consistent with our main findings.
16
We include the top 10 exporters (after China) based on total exports between 2000 and 2008. Developing
countriesâ€™ index of competition with other non-significant exporters is likely to be much smaller, and hence
exchange rate movements in these countries is less likely to displace exports of other developing countries.
18
because they are adversely affected by the depreciation of currencies that closely track the
renminbi.
An interesting related finding is that we do find statistically significant and negative coefficients
on the interaction terms for the other countries (not shown). Therefore, the spillover effect we
estimate is not specific to China, and is more general. Unsurprisingly, the indices of competition
are much lower for all the other countries. Therefore, the magnitude of the spillover effect which
is given by the coefficient multiplied by the index is much smaller for the other countries than
for China.17
In Table 5, we test for robustness across exporters, defined in geographic terms. We split the
sample into four regions and find that the results hold across all. The coefficients on the China
spillover effect are greater for Asia than for Sub-Saharan Africa but it is difficult to say whether
these differences are due to the fact of supply conditions in the exporting region or due to
differences in the product composition of their exports and/or their geographic destination.18
In Table 6, we check if the results are robust to the degree of product disaggregation. In the core
specification, the data are at the HS 4-digit level. In Table 6, we use data at the HS 2-digit level.
The indices of competition are measured by aggregating across 6-digit lines within the 2-digit
category. The sample size shrinks from over 3.6 million to about 860,000 observations. But the
interaction term remains negative and significant.
17
See Section V for detailed discussion on the magnitudes of the coefficients.
18
The differences are also statistically significant (based on a estimating a stacked specification with triple
interaction terms with regional dummies). We find some suggestive evidence that the differences between Asia and
sub-Saharan Africa, for example, may be due to the fact that the lattersâ€™ exports tend to be less homogenous than
those of Asia. We also tested for robustness across importers, defined in terms of advanced and other countries, and
the results hold for each category of importers.
19
Overall, the results in Tables 1-6 confirm the predictions from the analytical framework. The
elasticity of developing country exports with respect to Chinese exchange rate is consistently and
robustly negative. Further, this elasticity depends on the index of competition: a given
depreciation of the renminbi is associated with a bigger reduction in developing country exports
the higher this index.
Spillover Effect and Product Characteristics
Equations [11] and [12] suggest that the spillover effect should vary according to two product
attributes: elasticity of substitution ( ï?³ p ) between different imported varieties and exchange rate
pass through ( . Higher the values of ï?³ p and , the larger should be the spillover effect.
First, we analyze how the spillover effect varies by the degree of substitution between products.
We partition the data into homogenous (i.e. those with a greater degree of substitutability) and
differentiated products based on Rauchâ€™s (1999) classification.19 As shown in Table 7, columns
[1], [2], [4] and [5], we find that the coefficients on the interaction between the index of
competition and exchange rates are higher in magnitude for homogenous products vis-Ã -vis
differentiated ones. Columns [3] and [6] confirm that the differences between the coefficients for
the two types of goods are statistically significant. The differences are substantial: for the count-
based and value-based indices, the coefficients on homogenous goods are about 20 and 40
percent greater, respectively than for differentiated goods.
Second, we explore how the spillover effect is related to a likely determinant of Chinese
exchange rate pass-through â€“ the imported intermediate content of Chinese exports. One of the
key features of Chinese manufacturing exports has been the extent to which they have relied on
19
Note that Rauchâ€™s classification is available at the SITC 4-digit; we concord it to HS 6-digit level using standard
concordance tables, and then partition the data into homogenous and differentiated using Rauchâ€™s liberal
classification (reference priced goods are included in the homogenous category). We then aggregate the data to the
HS 4-digit level.
20
foreign intermediate inputs. The greater the reliance on foreign inputs (lower the domestic value
added), the more an exchange rate depreciation will increase input costs and hence dampen the
competitive advantage from a depreciation. In other words, a greater reliance on foreign inputs is
analytically analogous to a lower passthrough which theory predicts will dampen the spillover
effect. We test this proposition in the data. We use the classification in Koopman, Wang and Wei
(forthcoming) to divide our data into two samples: those characterized by a high degree of
foreign inputs and those with a low degree.20
In Table 8 we estimate our core specification for each of these samples. We find that, consistent
with theory, our spillover effect is in fact dampened for products with a high degree of foreign
inputs (compare columns [2] versus [1] and [5] versus [4]). Columns [3] and [6] confirm that the
differences between the two samples are statistically different: the coefficient on the core
interaction term is about 13 percent greater (in absolute value) for the sample with the lower
degree of foreign intermediate inputs in the case of the value based index and 10 percent greater
for the count-based index.21
Discussion of Magnitudes
Recall that the spillover effect we estimate in equation (13) is given by:
Our estimations identify which we can multiply by the relevant value of the index of
competition to obtain the average spillover effect. The range of estimates for different
combinations of the two indices of competition and estimates of are shown in Table 9. For the
baseline estimate of our elasticity (columns [4] and [8] in Table 1) and for the median index of
competition, we get a total spillover effect of -0.14 and -0.20 for the value and count-based
20
The classification of sectors by domestic value added is restricted to manufacturing, and is based on ISIC data
which we concorded with HS 4-digit data.
21
The same result holds for an alternative classification by share of processing exports (with high domestic value
added products being those with low share of processing) due to Koopman et. al. (forthcoming).
21
indices respectively. The estimates imply that a 10 percent depreciation/appreciation of the
renminbi is associated with a reduction/increase in developing country exports at the product
level to a third market of about 1.5-2 percent.
For countries that are in the 90th percentile in terms of competition with China, the range of
baseline estimates increases to 2-3 percent for the two indices. If we use the higher values of
corresponding to e.g. multilateral measure of exchange rates (column 5 in Table 3), the
magnitude of the estimates increases substantially. For the indices of competition in the 90th
percentile, the spillover effect could be as high as 6 percent for a 10 percent change in the
renminbi.22
How do our empirical estimates compare with those suggested by the analytical framework?
Equations (11) and (12) yield theoretical magnitudes for the spillover effect. From the existing
literature, we can obtain estimated values for each of the parameters. Of course, there is wide
variation in each of these, but some ball-park estimates are the following: ï?³ ï€½ 3 , ï?· ï€½ 1 , ï? ï€½ 0.4
and s ï€½ 0.4 . The estimates of ï?³ (the elasticity of substitution between imported goods, or the
micro-Armington elasticity) and ï?· (the elasticity of substitution between domestic and imported
goods, or the macro-Armington elasticity) are based on Feenstra, Obstfeld and Russ (2011). The
pass-through coefficient ( ï? ) is an average of the estimates from Campa and Goldberg (2005) for
industrial countries and the estimates of Gopinath, Itskhoki and Rigobon (2011) for the United
States. 23 The average share of China, s , in the markets of each of the importing countries is
obtained from our data.
22
Note that even using the estimates from Table 4, where we control for movements in other currencies, the
spillover effect of Chinaâ€™s exchange rate movements is in the range of 1-2 percent. We also conduct another exercise
where we assume that a movement in the renminbi is followed by movements in other correlated currencies. Based
on our estimates from Table 4, the overall spillover effect of movements in all these currencies is also in the range of
1-2 percent. This is due to the fact that spillover effect of other currencies is much smaller in magnitude than
Chinaâ€™s. Although the coefficients on the interaction terms are similar, the indices of competition are much smaller
for the other countries. These results are available upon request.
23
Goldberg and Knetter (1997) and Goldberg and Hellerstein (2008) also provide evidence on pass-through and its
decline over time. Xing (2010) looks specifically at pass-through of Chinese exchange rates to import prices in US
and Japan, and estimates pass-through coefficients of 0.23 and 0.56 for the US and Japan respectively.
22
Combining these estimates with the average value of the index of competition for the value
( and count-based ( indices from our data (of 0.4 and 0.9, respectively), yield a
magnitude of the third-market effect of -0.32 for the value-based index and -0.29 for the count-
based index. Therefore, theory appears to predict a spillover effect of about 0.3. For the count-
based index, the theoretical and our baseline empirical estimates (-0.2) are not far apart. For the
value-based index, our baseline empirical estimates are below those derived from theory (0.14
versus 0.32). There are two possible explanations. Residual measurement errors would impart a
natural attenuation bias to the econometric estimates. Second, the values of the elasticity of
substitution that we use to derive the theoretical prediction are based on Feenstra et. al. (2011),
who estimate the elasticity for goods at a level of disaggregation close to the HS 10-digit level.
Our data on the other hand are at HS 4-digit so that the relevant elasticity for our purpose could
be well below the value of 3 that we use here.24 Such a lower value would bring our empirical
estimates closer to those based on theory.
Overall, the baseline estimates in this paper suggest that a 10 percent depreciation/appreciation in
the renminbi exchange rate vis-Ã -vis an importing country decreases/increases on average
developing country exports by about 1.5-2 percent. Given the 30 percent appreciation of Chinaâ€™s
real exchange rate vis-Ã -vis the US dollar over 2000-2008, our findings suggest that this could
have been associated with about a 4.5-6 percent increase in the typical developing countryâ€™s
exports to the US, with much greater effects for countries in closer competition with China.
VI. Conclusion
To our knowledge, this paper is the first attempt to quantify the effect of exchange rate changes
on the exports of competitor countries to third marketsâ€”the spillover effectâ€”that both exploits
24
Broda and Weinstein (2006) argue that with more disaggregated data, one is likely to find higher estimates of the
elasticity of substitution.
23
the rich variation afforded by disaggregated trade data and does so in a manner that is motivated
by and consistent with theory. We study the case of China and find that its exchange rate changes
can have significant and robust spillover effects.
These findings may have important policy implications for developing countries and for the
multilateral system if exchange rate movements (or the lack thereof) stem from policy actions.
Since we have found that the resulting spillover effects are significant, one countryâ€™s policies can
then potentially have substantial export implications for other countries.
Importantly, we would emphasize that this paper identifies precisely and in a robust way a very
specific mechanism of influence from exchange rates to trade (the â€•spillover effectâ€– of Chinese
exchange rate movements on exports of competitor countries to third markets). There could be
other beneficial effects on developing country exports to China which we do not measure. For
example, a depreciation of the renminbi could increase developing country exports of raw
materials and intermediate goods to China to be used in the production of Chinaâ€™s exports to
third countries. Similarly, if Chinaâ€™s depreciation boosts its own growth, that could increase its
demand for all goods and services, which could also lead to greater developing country exports.
Thus, the effect of Chinaâ€™s exchange rate on overall exports of other countries remains an open
question. Finally, we have not directly estimated any effects of Chinaâ€™s exchange rate
movements on its own exports. Further research is needed to precisely identify all these other
effects.
24
References
Acemoglu, Daron and Simon Johnson, 2007. "Disease and Development: The Effect of Life
Expectancy on Economic Growth," Journal of Political Economy, vol. 115(6), pages 925-985.
Ahearne, Alan, John Fernald, Prakash Lougani, and John Schindler, 2003. â€•China and Emerging
Asia: Comrades or Competitors?â€– International Finance Discussion Paper No. 789, (Washington,
D.C.: Federal Reserve Board)
Berman, Nicolas, Philippe Martin and Thierry Mayer, 2012. "How do different exporters react to
exchange rate changes? Theory, empirics and aggregate implications," Quarterly Journal of
Economics, 127(1): pp. 437-492.
Broda, Christian and David E. Weinstein. 2006. "Globalization and the Gains from Variety,"
Quarterly Journal of Economics 121(2): 541-585.
Campa, Jose Manuel, and Linda S. Goldberg, 2005. "Exchange Rate Pass-Through into Import
Prices," The Review of Economics and Statistics, vol. 87(4), pages 679-690, December
Das, S., Roberts, M., and J. Tybout, 2001. "Market Entry costs, Producer Heterogeneity, and
Export Dynamics." NBER Working Paper No. 8629
Dekle, Robert and Heajin H. Ryoo, 2007. â€•Exchange rate fluctuations, financing constraints,
hedging, and exports: Evidence from firm level data.â€– Journal of International Financial
Markets, Institutions and Money 17, 437â€“451
Dooley, Michael P., David Folkerts-Landau, and Peter Garber, 2003. â€•An Essay on the Revived
Bretton Woods System.â€– NBER Working Paper No. 9971
Eichengreen, B., Y. Rhee and H. Tong (2004). â€•The Impact of China on the Exports of Other
Asian Countries,â€– NBER Working Paper no.10768
Eichengreen, Barry and Hui Tong, 2011. â€•The External Impact of China's Exchange Rate Policy:
Evidence from Firm Level Data.â€– IMF Working Paper, 155
Engel, Charles, 2009. â€•Exchange Rate Policies.â€– Federal Reserve Bank of Dallas Staff Paper.
Feenstra, Robert C., Maurice Obstfeld, and Katheryn N. Russ, 2011. â€•In Search of the
Armington Elasticity,â€– mimeo, UC Berkeley and UC Davis.
Finger, J. Michael, and Mordechai E. Kreinin. 1979. "A Measure of 'Export Similarity' and Its
Possible Uses," Economic Journal, 89, (December) pp. 905-912.
Forbes, K., 2002. "How Do Large Depreciations Affect Firm Performance", NBER Working
Paper No. 9095
25
Goldberg, P and M. Knetter, 1997, â€•Goods Prices and Exchange Rates: What Have We Learned?
Journal of Economic Literature, pp. 1243-72.
Goldberg, P. and R. Helllerstein, 2008, â€•A Structural Approach to Explaining Incomplete
Exchange Rate Pass-through and Pricing-To-Market,â€– American Economic Review, pp. 423-29.
Goldstein, Morris and M. S. Khan, 1985. "Income and Price Effects in Foreign Trade",
Handbook of International Economics, vol. 2. R.W. Jones and P.B. Kenen, eds. Amsterdam:
North-Holland.
Gopinath, Gita, Oleg Itskhoki, and Roberto Rigobon. 2011. â€•Currency Choice and Exchange
Rate Pass-Through.â€– American Economic Review, vol. 100(1), pages 304-36
Hooper, P., K. Johnson, and J. Marquez, 2000. "Trade Elasticities for G-7 Countriesâ€–, Princeton
Studies in International Economics No. 87.
Hanson, Gordon H., and Raymond Robertson, 2008. â€•China and the Manufacturing Exports of
Other Developing Countries.â€– NBER Working Paper No. 14497.
Johnson, Simon H., Jonathan Ostry, and Arvind Subramanian, 2010. "Prospects for Sustained
Growth in Africa: Benchmarking the Constraints," IMF Staff Papers, vol. 57(1), pages 119-171,
April
Koopman, Robert, Zhi Wang, and Shang-Jin Wei, forthcoming, â€•Estimating domestic content in
exports when processing trade is pervasiveâ€–, Journal of Development Economics.
Michael Peneder, 2011. â€•Intangible Investment and Human Resources.â€– The New WIFO
Taxonomy of Manufacturing Industries," WIFO Working Papers 114, WIFO
Rauch, J.E., 1999. â€•Networks versus Markets in International Trade.â€– Journal of International
Economics 48, 7â€“35
Robinson, Joan. 1947. Essays in the Theory of Employment, 2nd edition, Oxford: Basil
Blackwell. First published in 1937.
Rodrik, Dani, 2008. â€•The Real Exchange Rate and Economic Growth,â€– Brookings Papers on
Economic Activity, 2, pp. 365â€“412.
Rogoff, K., 1996. â€•The Purchasing Power Parity Puzzle,â€– Journal of Economic Literature 34,
647â€“668.
Thursby J.G., and M.C. Thursby, 1987. â€•Bilateral Trade Flows, the Linder Hypothesis, and
Exchange Risk,â€– Review of Economics and Statistics 69, 488-495
Wei, Shang-Jin and Xiaobo Zhang, 2011, â€•The Competitive Savings Motive: Evidence from
Rising Sex ratios and Savings Rates in China,â€– Journal of Political Economy, 119 (3), 511-564.
26
Xing, Yuqing, 2010. â€•The Yuan's Exchange Rates and Pass-through Effects on the Prices of
Japanese and the US Imports.â€– Comparative Economic Studies, 52, 531â€“548.
27
Notes. The figure shows averages over time for the value and count-based indices of competition. The
indices are measured at the exporter-importer-HS 4-digit product-time level. The value-based index is
defined as the summation over all 6-digit products within the 4-digit category of the following: share of
China in overall imports of a 6-digit product multiplied by the share of the 6-digit product in total 4-digit
exports from the exporter to the importer. The count-based index of competition with China is defined at
the 4-digit product level, and is equal to the share of 6-digit products within a 4-digit category that i
exports to j, that China also exports to j.
28
29
Table 1. Exports from Developing Countries and Chinese Exchange Rates: Baseline Specification
Dependent variable = log(exports) at (exporter,importer,4-digit product, year) level
Value-based index of competition Count-based index of competition
[1] [2] [3] [4] [5] [6] [7] [8]
Index of competition with China*log(exchange rate of importer
with respect to China) -0.178*** -0.227*** -0.128*** -0.352*** -0.250*** -0.234*** -0.158*** -0.222***
[0.002] [0.001] [0.001] [0.004] [0.001] [0.001] [0.001] [0.002]
N 3,586,936 3,586,936 3,586,936 3,586,936 3,586,936 3,586,936 3,586,936 3,586,936
Fixed effects
exporter*importer*product N N N Y N N N Y
exporter*importer*time N N Y Y N N Y Y
exporter*product*time N Y Y Y N Y Y Y
importer*product*time N Y Y Y N Y Y Y
Notes. Exchange rate of importer wrt China is measured as renminbi/importer currency, deflated by the Chinese CPI. The index of competition in columns [1]-[4] is defined
as the summation over all 6-digit products within the 4-digit category of the following: share of China in overall imports of a 6 digit product multiplied by the share of the 6-
digit product in total 4-digit exports from the exporter to the importer. The index of competition with China in columns [5]-[8], is defined at the 4-digit product level, and is
equal to the share of 6-digit products within a 4-digit category that i exports to j, that China also exports to j. The index of competition in all the columns is measured in the
year 2000. The regression sample includes years from 2000-2008. Standard errors denoted in parentheses are clustered at the importer*exporter*product level. ***, ** and *
denote statistical significance at the 1, 5 and 10 percent respectively.
30
Table 2. Robustness
Dependent variable = log(exports) at (exporter,importer, 4-digit product, year) level
[1] [2] [3] [4] [5] [6] [7] [8]
long-
cluster cluster difference index of index of Finger-
drop cluster exp*prod* imp*prod* (2000, competition competition -- Krenin
outliers exp*imp*year year year 2008) -- 2001 2002 Index
Value-based index of competition
Index of competition with China*log(exchange rate of importer
with respect to China) -0.370*** -0.352*** -0.352*** -0.352*** -0.416*** -0.326*** -0.311*** -0.385***
[0.005] [0.001] [0.003] [0.003] [0.038] [0.004] [0.004] [0.003]
Count-based index of competition
Index of competition with China*log(exchange rate of importer
with respect to China) -0.192*** -0.222*** -0.222*** -0.222*** -0.208*** -0.387*** -0.417***
[0.002] [0.001] [0.001] [0.001] [0.017] [0.002] [0.003]
N 3,479,214 3,586,936 3,586,936 3,586,936 788,775 3,586,936 3,586,936 3,586,936
Notes. See notes to Table 1 for definitions of the value-based and count-based index of competition. Exchange rate of importer wrt China is measured as renminbi/importer
currency, deflated by the Chinese CPI. In column [1], the top and bottom fifth percentile of the observations are dropped. In columns [2]-[4], we make alternative
assumptions on clustering the standard errors. In column [5], we retsrict the sample to two years -- 2000 and 2008. In columns [6] and [7], the index of competition is
measured in 2001 and 2002 respectively. In Column [8], we use the Finger-Krenin index of export similarity. The index of competition except in columns [6] and [7] is
measured in the year 2000. The regression sample (except column [5]) includes years from 2000-2008. All regressions include exporter*importer*time,
exporter*product*time, importer*product time, and exporter*importer*product fixed effects. Standard errors denoted in parentheses are clustered at the
importer*exporter*product level (except in columns [3]-[5]) . ***, ** and * denote statistical significance at the 1, 5 and 10 percent respectively.
31
Table 3. Robustness to Alternative Exchange Rate Measures
Dependent variable = log(exports) at (exporter,importer, 4-digit product, year) level
Value-based index of competition Count-based index of competition
[1] [2] [3] [4] [5] [6] [7] [8] [9] [10]
Real
exchange
Real exchange Nominal Real Real rate Nominal Real Real
Nominal rate (deflated effective effective effective Nominal (deflated by effective effective effective
exchange by relative exchange exchange exchange exchange relative exchange exchange exchange
rate prices) rate rate rate (PWT) rate prices) rate rate rate (PWT)
Index of competition with China*log(exchange rate of importer
with respect to China) -0.150*** -0.245*** 0.576*** 0.545*** 0.681*** -0.133*** -0.214*** 0.346*** 0.356*** 0.398***
[0.009] [0.009] [0.006] [0.006] [0.007] [0.004] [0.004] [0.003] [0.002] [0.003]
N 3,586,936 3,586,936 3,602,228 3,602,228 3,602,228 3,586,936 3,586,936 3,602,228 3,602,228 3,602,228
Notes. See notes to Table 1 for definitions of the value-based and count-based index of competition. In columns [1] and [5], nominal exchange rate of importer wrt China is measured as
renminbi/importer currency. In columns [2] and [6], real exchange rate of importer wrt China is measured as renminbi/importer currency, deflated by the Chinese CPI relative to importer CPI. In
columns [3] and [7], nominal effective exchange rate of China (2005=100) from the IMF is used. In columns [4] and [8], real effective exchange rate of China (2005=100) from the IMF is used. Note that an
increase in the real and nominal effective exchange rates denotes an appreciation. In columns [5] and [10], the measure of the real exchange rate is the price level of GDP (series p) from the Penn World
Tables (version 7), which is the ratio of GDP at market exchange rates to GDP at purchasing power parity exchange rates. The price level is expressed relative to that of the United States. An increase in
the price level denotes an appreciation of the real exchange rate. The regression sample in all regressions includes years from 2000-2008. All regressions include exporter*importer*time,
exporter*product*time, importer*product time, and exporter*importer*product fixed effects. Standard errors denoted in parentheses are clustered at the importer*exporter*product level. ***, ** and
* denote statistical significance at the 1, 5 and 10 percent respectively.
32
Table 4. Robustness to Omitted Variables
Dependent variable = log(exports) at (exporter,importer,4-digit product, year) level
Value-based index of competition Count-based index of competition
[1] [2] [3] [4] [5] [6]
Index of competition with China*log(exchange rate of importer
with respect to China) -0.253*** -0.211*** -0.172*** -0.163*** -0.224*** -0.242***
[0.005] [0.006] [0.008] [0.005] [0.006] [0.008]
N 3,141,707 2,697,281 2,248,111 3,141,707 2,697,281 2,248,111
Controls
Index of competition with other country*log(exchange rate of
importer wrt that country)
Malaysia, Poland (correlation >= 0.7) Y Y Y Y Y Y
Mexico, Thailand (correlation>=0.4) N Y Y N Y Y
Brazil, India (correlation>=0.3) N N Y N N Y
Fixed effects
exporter*importer*product Y Y Y Y Y Y Y
exporter*importer*time Y Y Y Y Y Y Y
exporter*product*time Y Y Y Y Y Y Y
importer*product*time Y Y Y Y Y Y Y
Notes. The control countries are among the top ten exporters in the world, whose real effective exchange rates are highly correlated with the Chinese. Exchange rate of
importer wrt e.g. China is measured as renminbi/importer currency, deflated by the Chinese CPI. The exchange rate of importer wrt other countries is also measured in a
similar way.The index of competition in columns [1]-[3] is defined as the summation over all 6-digit products within the 4-digit category of the following: share of
China/Malaysia/South Africa, etc. in overall imports of a 6 digit product multiplied by the share of the 6-digit product in total 4-digit exports from the exporter to the importer.
The index of competition with China/Malaysia/South Africa, etc. in columns [4]-[6], is defined at the 4-digit product level, and is equal to the share of 6-digit products within a
4-digit category that i exports to j, that China/Malaysia/South Africa also exports to j. The index of competition in all the columns is measured in the year 2000. The regression
sample includes years from 2000-2008. Standard errors denoted in parentheses are clustered at the importer*exporter*product level. ***, ** and * denote statistical
significance at the 1, 5 and 10 percent respectively.
33
Table 5. Robustness By Region of Exporter
Dependent variable = log(exports) at (exporter,importer,4-digit product, year) level
Value-based index Count-based index
Asia Europe LAC MENA+SSA Asia Europe LAC MENA+SSA
Index of competition with China*log(exchange rate of importer
with respect to China) -0.467*** -0.433*** -0.297*** -0.116*** -0.288*** -0.258*** -0.192*** -0.139***
[0.008] [0.011] [0.012] [0.015] [0.004] [0.005] [0.005] [0.007]
N 1,234,019 997,174 750,565 436,403 1,234,019 997,174 750,565 436,403
Notes. The region of the exporter is defined based on the World Bank country classification. See notes to Table 1 for definitions of the valuey-based and count-based
index of competition. Exchange rate of importer wrt China is measured as renminbi/importer currency, deflated by the Chinese CPI. The index of competition in all
the columns is measured in the year 2000. The regression sample includes years from 2000-2008. LAC denotes Latin America and the Caribbean; MENA denotes the
Middle East and North Africa; SSA denotes Sub-Saharan Africa. All regressions include exporter*importer*time, exporter*product*time, importer*product time, and
exporter*importer*product fixed effects. Standard errors denoted in parentheses are clustered at the importer*exporter*product level. ***, ** and * denote
statistical significance at the 1, 5 and 10 percent respectively.
34
Table 6. Robustness to Degree of Product Aggregation (HS 2-Digit Level)
Dependent variable = log(exports) at (exporter,importer,2-digit product, year) level
Value-based index Value-based index
[1] [3] [4] [5] [1] [3] [4] [5]
Index of competition with China*log(exchange rate of importer
with respect to China) -0.131*** -0.084*** -0.009*** -0.306*** -0.293*** -0.206*** -0.113*** -0.268***
[0.002] [0.002] [0.002] [0.006] [0.001] [0.001] [0.001] [0.003]
N 861,487 861,487 861,487 861,487 861,487 861,487 861,487 861,487
Fixed effects
exporter*importer*product N N N Y N N N Y
exporter*importer*time N N Y Y N N Y Y
exporter*product*time N Y Y Y N Y Y Y
importer*product*time N Y Y Y N Y Y Y
Notes. Exchange rate of importer wrt China is measured as renminbi/importer currency, deflated by the Chinese CPI. The index of competition in columns [1]-[4] is
defined as the summation over all 6-digit products within the 2-digit category of the following: share of China in overall imports of a 6 digit product multiplied by the
share of the 6-digit product in total 2-digit exports from the exporter to the importer. The index of competition with China in columns [5]-[8], is defined at the 2-digit
product level, and is equal to the share of 6-digit products within a 2-digit category that i exports to j, that China also exports to j. The index of competition in all the
columns is measured in the year 2000. The regression sample includes years from 2000-2008. Standard errors denoted in parentheses are clustered at the
importer*exporter*product level. ***, ** and * denote statistical significance at the 1, 5 and 10 percent respectively.
35
Table 7. Products Distinguished by Degree of Differentiation
Dependent variable = log(exports) at (exporter,importer, 4-digit product, year) level
Value-based index Count-based index
Homogenous Differentiated Interaction Homogenous Differentiated Interaction
[1] [2] [3] [4] [5] [6]
Index of competition with China*log(exchange rate of importer
with respect to China) -0.339*** -0.312*** -0.101*** -0.240*** -0.205*** -0.176***
[0.010] [0.004] [0.002] [0.004] [0.002] [0.001]
Index of competition with China*log(exchange rate of importer
with respect to China)*Dummy for homogenous -0.040*** -0.046***
[0.003] [0.002]
N 981,310 2,679,680 1,326,035 981,310 2,679,680 1,326,035
Notes. Goods are classified into homogeneous or differentiated according to Rauch's liberal classification at 6-digit level. Exchange rate of importer wrt
China is measured as renminbi/importer currency, deflated by the Chinese CPI. The index of competition in all the columns is measured in the year 2000.
The regression sample includes years from 2000-2008. All regressions include exporter*importer*time, exporter*product*time, importer*product time,
and exporter*importer*product fixed effects. Standard errors denoted in parentheses are clustered at the importer*exporter*product level. ***, ** and *
denote statistical significance at the 1, 5 and 10 percent respectively.
36
Table 8. Products Distinguished by Domestic Value Added
Dependent variable = log(exports) at (exporter,importer, 4-digit product, year) level
Value-based index Count-based index
High
domestic Low domestic High domestic Low domestic
value added value added Interaction value added value added Interaction
[1] [2] [3] [5] [6] [7]
Index of competition with China*log(exchange rate of importer
with respect to China) -0.329*** -0.285*** -0.283*** -0.236*** -0.191*** -0.170***
[0.005] [0.005] [0.007] [0.002] [0.003] [0.004]
Index of competition with China*log(exchange rate of importer
with respect to China)*Dummy for high domestic value added -0.125*** -0.100***
[0.013] [0.006]
N 1,511,450 1,830,310 3,341,760 1,738,687 1,848,249 3,341,760
Notes. Regressions are restricted to manufacturing only. The data on share of domestic value added for products in the manufacturing sector is from Koopman,
Wang and Wei (forthcoming). Goods are classified into high and low-value added based on values above and below the median. See notes to Table 1 for
definitions of the value-based and count-based index of competition. Exchange rate of importer wrt China is measured as renminbi/importer currency, deflated
by the Chinese CPI. The index of competition in all the columns is measured in the year 2000. The regression sample includes years from 2000-2008. All regressions
include exporter*importer*time, exporter*product*time, importer*product time, and exporter*importer*product fixed effects. Standard errors denoted in
parentheses are clustered at the importer*exporter*product level. ***, ** and * denote statistical significance at the 1, 5 and 10 percent respectively.
37
Table 9. Range of Estimated Spillover Effect of a 10 percent Depreciation of Chinese Exchange Rate
Value-based index Count-based index
Beta coefficients Baseline Minimum Maximum Baseline Minimum Maximum
Percentile of the index of
competition
10 -0.01 0.00 -0.01 0.00 0.00 0.00
50 -1.30 -0.47 -2.52 -1.99 -1.39 -3.74
90 -3.12 -1.13 -6.03 -2.22 -1.55 -4.17
Notes. For the value-based index, the baseline, minimum and maximum values of the estimated coefficients correspond to column
[4], Table 1; column [3], Table 1; and column [5], Table 3 respectively. For the count-based index, the baseline, minimum and
maximum values of the estimated coefficients correspond to column [8], Table 1; column [4], Table 4; and column [7], Table 2
respectively.
38
Appendix: Steps in the Derivation of Equation (10)
From Equation (9),
Applying the formula:
Applying the identity:
Further, applying the formula:
Substituting for from Equation (8)
This is Equation (10) in the paper.
39
Table A1. Summary Statistics
Standard
Variable Observations Mean Deviation Minimum Maximum
Nominal Exports ('000 USD) 3,586,936 2009.797 39531.450 0.001 1.590E+07
Log (real exports, deflated by US CPI) 3,586,936 -1.485 3.134 -11.611 12.100
Index of competition with China (structural
measure) 3,586,936 0.408 0.325 0.000 1.000
Index of competition with China (count-
based measure) 3,586,936 0.898 0.282 0.000 1.000
Nominal exchange rate (renminbi / importer
currency) 3,586,936 2.614 3.332 0.000 15.222
Log (renminbi/importer currency exchange
rate, deflated by Chinese CPI) 3,586,936 -5.892 2.426 -13.247 -2.632
40
Table A2. List of countries
Exporting countries Importing countries
Afghanistan Macedonia, FYR Algeria
Albania Madagascar Argentina
American Samoa Malawi Australia
Argentina Malaysia Austria
Armenia Maldives Belarus
Bangladesh Mali Belgium
Belarus Marshall Islands Brazil
Belize Mauritania Canada
Benin Mauritius Chile
Bhutan Mexico Colombia
Bolivia Micronesia, Fed. Sts. Czech Republic
Bosnia and Herzegovina Moldova Denmark
Botswana Mongolia Egypt, Arab Rep.
Brazil Montenegro Finland
Bulgaria Morocco France
Burkina Faso Mozambique Germany
Burundi Myanmar Greece
Cambodia Namibia Hong Kong SAR, China
Cameroon Nepal Hungary
Cape Verde Nicaragua India
Central African Republic Niger Indonesia
Chile Pakistan Ireland
Colombia Palau Israel
Comoros Panama Italy
Congo, Dem. Rep. Papua New Guinea Japan
Costa Rica Paraguay Kazakhstan
Cote d'Ivoire Peru Korea, Rep.
Cuba Philippines Malaysia
Djibouti Poland Mexico
Dominica Romania Morocco
Dominican Republic Russian Federation Netherlands
Ecuador Rwanda New Zealand
Egypt, Arab Rep. Samoa Nigeria
El Salvador Sao Tome and Principe Norway
Eritrea Senegal Pakistan
Ethiopia(excludes Eritrea) Seychelles Philippines
Fiji Sierra Leone Poland
Gabon Solomon Islands Portugal
Gambia, The Somalia Qatar
Georgia South Africa Romania
Ghana Sri Lanka Russian Federation
Grenada St. Kitts and Nevis Saudi Arabia
Guatemala St. Lucia Singapore
Guinea St. Vincent and the Grenadines Slovak Republic
Guinea-Bissau Suriname South Africa
Guyana Swaziland Spain
Haiti Syrian Arab Republic Sweden
Honduras Tajikistan Switzerland
India Tanzania Taiwan, China
Indonesia Thailand Thailand
Jamaica Togo Turkey
Jordan Tonga Ukraine
Kazakhstan Tunisia United Arab Emirates
Kenya Turkey United Kingdom
Kiribati Uganda United States
Kyrgyz Republic Ukraine Venezuela
Lao PDR Uruguay Vietnam
Latvia Uzbekistan
Lebanon Vanuatu
Lesotho Vietnam
Liberia Zambia
Lithuania Zimbabwe
41