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Do Exporters Respond to Both Tariffs and Nominal Exchange
Rates? Evidence from Chinese Firm-Product Data∗
Zhe Chen† Yoshinori Kurokawa‡
July 25, 2019
Abstract
The Melitz (2003) model with exchange rates and sticky wages predicts that the extensive mar-
gin of exports can respond to both trade liberalization and nominal exchange rates, which might
not, however, be supported by data according to the well-known argument about temporary vs.
permanent shocks. Using Chinese firm-product data from 2000 to 2006, this paper empirically
tests this theoretical prediction and has three main findings. First, though smaller than that of
tariffs charged by trade partners, the coefficient of exporter numbers on nominal exchange rates
is also significant. In fact, as the beta coefficients and overall effects indicate, exchange rates
are much more important than believed. Second, reductions in tariffs and yuan depreciation
increased not only entry but also exit of exporters. Finally, the implied elasticity of aggregate
exports with respect to tariffs is 1.60 and that with respect to nominal exchange rates is 0.20,
which are in line with the estimates in the international real business cycle models.
JEL classification: F12, F14, F31
Keywords: Melitz model, exchange rates, tariffs, extensive margin of exports, trade elasticity,
China
∗We are very grateful to Bo-Young Choi, Gian Luca Clementi, Loretta Fung, Chang Hong, Sewon Hur,Isao Kamata, Tim Kehoe, Matthew Kidder, Bingjing Li, Bernabe Lopez-Martin, Ferdinando Monte, PeterMorrow, Hiroshi Mukunoki, Yang Shen, Nyeong Seon Son, Siqiang Yang, Haishan Yuan, and Yuan Yuan fortheir useful comments and suggestions. We also thank the participants at the Fall 2017 Midwest Macroeco-nomics Meetings, the Fall 2017 Midwest International Trade Conference, the 2018 AMES, the 77th AnnualMeeting of the JSIE, and the 40th Annual Conference of the KIEA. Chen gratefully acknowledges financialsupport from the National Natural Science Foundation of China (Grant Number 71803020), and Kurokawagratefully acknowledges financial support from the JSPS KAKENHI (Grant Number JP19K01644). Thispaper previously circulated under the title “Does Yuan Appreciation Weaken the Increase in Exporters dueto Trade Liberalization? Evidence from Chinese Firm-Product Data.”†School of International Trade and Economics, University of International Business and Economics. 1302
Boxue Building, 10 Huixin Dongjie, Chaoyang District, Beijing 100029, China. E-mail: zhechen@uibe.edu.cn.‡Faculty of Humanities and Social Sciences, University of Tsukuba. 1-1-1 Tennodai, Tsukuba, Ibaraki
305-8571, Japan. E-mail: kurokawa.yoshi.fw@u.tsukuba.ac.jp.
1
1 Introduction
More and more Chinese firms have been entering foreign markets. In addition, China has
recently been conducting the simultaneous trade liberalization and managed floating currency
policy. As Figure 1 shows, China has faced significant changes in both tariffs, charged by
trade partners, and nominal exchange rates. These observations raise a question: Can the
number of exporters—the extensive margin (EM) of exports—respond to both tariffs and
nominal exchange rates?
Theoretically, the answer to this question is yes. The introduction of nominal exchange
rates and sticky wages into the Melitz (2003) model of heterogeneous firm trade predicts that
the EM of exports can respond to not only trade liberalization but also nominal exchange
rates (e.g., Rodrıguez-Lopez, 2011).1 Empirically, however, the answer might be no, according
to the well-known argument by Ruhl (2008) that firms do not change their exporting status
in response to temporary shocks (exchange rates or productivity) while some firms do change
it in response to permanent shocks (tariffs).
We empirically test the aforementioned prediction from the Melitz (2003) model.2 Specif-
ically, we use Chinese firm-product annual data from 2000 to 2006 with 170 trade partners
to test whether the EM of China’s exports responds to both changes in tariffs (charged by
trade partners) and changes in nominal exchange rates.
The benchmark regression results support the theoretical prediction. Though relatively
small compared to that on tariffs, the coefficient of China’s exporter numbers—the EM of
exports—on nominal exchange rates is also significant. In fact, as indicated by the beta
coefficients and overall effects, exchange rates are much more important than believed. This
pattern also holds for the export value/quantity per exporter—the intensive margin (IM) of
exports—at the product level.
When we estimate the coefficients of the entry and exit of China’s exporters, the regression
results suggest that reductions in tariffs, charged by its trade partners, and yuan depreciation
increased not only entry but also exit of exporters. This is in line with Feng et al. (2017), who
1As will be mentioned later, by developing a sticky-wage model of heterogeneous firm trade with exchangerates and endogenous markups, Rodrıguez-Lopez (2011) extends the discussion of the Melitz model to analyzethe response of the EM of trade to nominal exchange rates. Bergin and Lin (2008) also examine the responseto exchange rates, in particular, exchange rate regimes.
2Notably, as mentioned by Baggs et al. (2009), most empirical studies that have examined tariffchanges/trade liberalization include exchange rates as a control variable; however, the analysis is at theindustry level, not at the firm level.
2
also empirically document that the entry and exit of China’s exporters increased following
China’s World Trade Organization (WTO) accession in 2001. Finally, we construct another
measurement of the EM (IM) of exports that is based on export product variety from China’s
exporters. Changes in tariffs affect both the EM and IM of exports while changes in nominal
exchange rate only affect the IM of exports. Thus, while changes in nominal exchange rates
affect the EM of exports in terms of exporter numbers, they do not in terms of export variety
from exporters.
We further perform several robustness checks regarding trade modes (ordinary vs. pro-
cessing trade), export destinations (OECD vs. non-OECD countries; main trade partners),
balanced data, high frequency data (quarterly), real exchange rates, and sectoral and prod-
uct differences. We find that the coefficients on tariffs and exchange rates are significantly
different between processing and ordinary trade firms and that the coefficients are greater if
the export destinations are non-OECD countries. The benchmark results are robust to main
trade partners, balanced data, quarterly data, and real exchange rates. The coefficients of
the EM of exports on tariffs are significant in 8 sectors in China’s top 10 export sectors at
the HS2 level while the coefficients on exchange rates are significant in 9 sectors. We also
find that the coefficients on tariffs and nominal exchange rates are larger for differentiated
goods. Finally, we discuss both firm- and aggregate-level implications from our results. We
particularly want to emphasize that the implied elasticity of aggregate exports with respect
to tariffs is 1.60 and that with respect to nominal exchange rates is 0.20, which are in line
with the estimated (Armington) elasticities in the international real business cycle models.
Our study makes the following contributions to the literature on the EM of trade. Melitz
(2003) focuses on the response of the EM of trade to trade liberalization, and Rodrıguez-
Lopez (2011) focuses on the response of the EM of trade to nominal exchange rates. We
focus on the responses of the EM of trade to these two factors; in particular, we use Chinese
firm-product data to empirically investigate whether the EM of China’s exports responds to
both tariffs (charged by trade partners) and nominal exchange rates.
Of course, there are studies that have empirically investigated the responses of firms or
exporters to trade liberalization vs. exchange rates (e.g., Baggs et al., 2009 ; Fitzgerald and
Hallerz, 2017). They have, however, focused on real exchange rates while we shed light on
the significance of nominal exchange rates. Feenstra (1989) theoretically argues that the
responses of the import price to tariffs and exchange rates are symmetric, and empirically
3
verifies this argument using U.S. import prices of Japanese cars, trucks, and motorcycles.
Motivated by Feenstra (1989), Baggs et al. (2009) (BBF) empirically test, using Canadian
industry-firm annual data, if real exchange rates affect Canadian firm survival/exit, and
they find that the overall effect of the real exchange rate changes is comparable to that of
the Canada-U.S. Free Trade Agreement tariff changes, although the coefficient on the real
exchange rate changes is smaller than that on the tariff changes. Moreover, Fitzgerald and
Hallerz (2017) (FH) empirically test if Irish exporters respond symmetrically to tariffs and
real exchange rates using Irish firm-product annual data, and they find that the coefficient
on tariffs is larger than that on real exchange rates. Differences/similarities between our
paper, BBF, and FH are threefold. First, while FH and BBF both empirically test the
equivalence between tariffs and real exchange rates particularly for developed countries, our
paper compares the responses to tariffs and nominal exchange rates for the developing country
China. Second, our paper and FH both focus on the responses of exporters while BBF look
at all Canadian firms. Third, while our nominal results are in line with the real results by
BBF and FH in that the coefficient on exchange rates is smaller than that on tariffs, our
results based on beta coefficients and overall effects indicate that exchange rates are much
more important than believed. Therefore, these three papers are satisfactory complements.
Our paper also makes contributions to the literature on trade elasticity, in particular, EM
elasticity. Our results imply that the elasticity of exporter numbers with respect to tariffs
is 1.061; that with respect to nominal exchange rates 0.112; and that with respect to real
exchange rates 0.210. On the other hand, the estimated elasticity of exporter numbers with
respect to tariffs by Bas et al. (2017) is 3.83, which is much larger than ours. That with
respect to real exchange rates by Tang and Zhang (2012) is 0.17, which is close to ours. We
note that, while Bas et al. (2017) and Tang and Zhang (2012), respectively, focus on tariffs
and exchange rates, we compare tariffs vs. exchange rates. Our results also imply that the
elasticity of export variety with respect to tariffs is 0.0875; that with respect to nominal
exchange rates 0.00235; and that with respect to real exchange rates 0.0132. The estimated
elasticity of export variety with respect to tariffs by Feenstra and Kee (2007) is about 2,
which is much larger than ours. That with respect to real exchange rates by Colacelli (2010)
is 0.045, which is close to ours in that both are less than 0.1. To our knowledge, however, no
past studies have estimated the elasticity of exporter numbers or export variety with respect
to nominal exchange rates.
4
The rest of this paper is organized as follows. Section 2 provides theoretical motivation for
our empirical question. Section 3 documents the regression specification and data. Section 4
reports the regression results and robustness checks. Section 5 discusses firm- and aggregate-
level implications from our results. Section 6 concludes.
2 Theoretical Motivation
We introduce nominal exchange rates and sticky wages to the Melitz (2003) model of heteroge-
neous firm trade to guide our empirical analysis on the relationship between tariffs/nominal
exchange rates and the EM of exports. Our model is a slightly simplified version of the
Rodrıguez-Lopez (2011) model.3 Note that Melitz (2003) focuses on the response of the EM
of trade to trade liberalization; Rodrıguez-Lopez (2011) the response to nominal exchange
rates; and our paper the responses to both of these two factors.
There are two countries: Home and Foreign. There is a continuum of households in the
interval [0, 1], and each household provides labor to the production of differentiated goods in
each country. There are firms heterogeneous in productivity, and each firm produces a single
variety under monopolistic competition. Home and Foreign markets are segmented. As does
Rodrıguez-Lopez (2011), we introduce the exogenous nominal exchange rates defined as the
price of the Foreign currency in terms of the Home currency (e.g., China’s yuan per U.S.
dollar). We also assume that nominal wages are fixed in the Home currency.
The setup of the preferences and production and the derivation of the equilibrium ex-
porting cutoff productivity level for Home firms are standard and have been relegated to
Appendix A.1. Here, we only state hypotheses, which are derived from the theoretical model
and will be explored empirically.
(a) A decrease in tariffs, charged by partners, causes an increase in exporter numbers (the
EM of exports).
(b) A decrease in nominal exchange rates—appreciation—causes a decrease in exporter
numbers.
3While Rodrıguez-Lopez (2011) analyzes the Melitz (2003) model with nominal exchange rates, stickywages, and translog preferences (endogenous markup) in main text, he also analyzes the Melitz model withnominal exchange rates, sticky wages, and CES preferences (constant markup) in appendix and shows thatthe results are robust. We slightly simplify the latter CES preference (constant markup) model to focus onanalyzing the relationship between tariffs/nominal exchange rates and the EM of exports.
5
(c) In the more differentiated sector, the responses of exporter numbers to tariffs and
nominal exchange rates can be larger.
The intuition for the hypothesis (c) is that, for the same percent change in tariffs or nominal
exchange rates, if the elasticity of substitution is lower, that is, if the markup is higher, then
a change in profits is larger. It leads to a larger change in the exporting cutoff and thus a
larger change in the mass of exporters. Thus, in the more differentiated sector, the elasticity
of the mass of exporters with respect to tariffs/nominal exchange rates can be larger.
3 Regression Specification and Data
3.1 Regression Specification
3.1.1 Exporter Numbers and Export Value/Quantity per Exporter
Guided by the Melitz model with nominal exchange rates presented in the previous section,
we empirically investigate the responses of exporter numbers to tariffs and nominal exchange
rates at the product-country-year level. The benchmark regression is as follows:
ln(Eijt) =α0 + α1 ln(1 + Tariffijt) + α2 ln(NERjt) + Processingijt
+ ρi + θj + ηt + εijt(3.1)
Here, Eijt is the number of exporters of product i from China to country j at time t.4
Tariffijt is the tariff of product i charged by country j at time t. NERjt is the nominal
exchange rate, which is defined as China’s yuan per currency of country j at time t; thus, when
NER increases, China’s yuan depreciates. The trade mode may affect exporters’ behaviors;
thus, we control the processing trade dummy,5 Processingijt. When the product is exported
under the processing trade mode, the dummy is 1; otherwise, it is 0. Finally, we control the
product fixed effect ρi, country fixed effect θj and time fixed effect ηt.
If α1 is negative and α2 is positive, then the implication from the Melitz model with
nominal exchange rates is supported. When tariff decreases, the EM of exports increases.
4Here, the number of exporters within a product is corresponding to the number of exporters within anindustry in the theory. As will be shown in Section 3.2, we define a product at the HS6 level.
5Processing trade refers to importing all or part of the raw and auxiliary materials and re-exporting thefinished products after processing.
6
When China’s yuan appreciates (depreciates), the EM of exports decreases (increases).
We also empirically investigate the responses of export value/quantity per exporter—
the IM of exports—at the product-country-year level. In that case, Eijt is the export
value/quantity per exporter of product i from China to country j at time t.
3.1.2 Entry and Exit of Exporters
A change in exporter numbers could be caused by entry or/and exit of exporters. Thus,
we also investigate the responses of the entry and exit of exporters to tariffs and nominal
exchange rates, respectively. If the export value of a firm is 0 in year t − 1 but positive in
year t, then we consider this firm as a new exporter in year t. If the export value of a firm is
positive in year t−1 but 0 in year t, then we consider this firm as an exit exporter in year t.6
The benchmark regression is as follows:
ln(ENijt) =β0 + β1 ln(1 + Tariffijt) + β2 ln(NERjt) + Processingijt
+ ρi + θj + ηt + µijt(3.2)
Here, the regression specification is similar to equation (3.1). Now ENijt is the number of new
(exit) exporters of product i from China to country j at time t. When ENijt is the number of
new exporters, if α1 is negative and α2 is positive, then a decrease in tariffs causes additional
Chinese firms to enter foreign markets, whereas China’s yuan appreciation (depreciation)
causes less (more) Chinese firms to enter. When ENijt is the number of exit exporters, if
α1 is positive and α2 is negative, then a decrease in tariffs causes less Chinese firms to quit
foreign markets, whereas the appreciation (depreciation) of China’s yuan causes more (less)
Chinese firms to quit.
3.1.3 Export Product Variety
In this section, we construct another measurement of the EM (IM) of exports that is based on
export product variety from exporters. Applying the methodology in Hummels and Klenow
6We also use other definitions of new and exit exporters as robustness checks. If a firm never exportedin previous years and year t is the first year in which this firm exports, then we consider this firm as anew exporter in year t. If a firm quits foreign markets in year t and never returns to foreign markets, thenwe consider this firm as an exit exporter in year t. The results for these new definitions are robust. Note,however, that as shown in Section 3.2, our dataset is from 2000 to 2006 and thus the new definitions are notaccurate for an exporter that actually enters or exits foreign markets beyond this period.
7
(2005), we define the firm-country-product specific export variety at the HS4 level, which
captures the number of HS6 product varieties within each HS4 category that an exporter
exports to a destination country.7
The EM index for exports of HS4 category i from exporter k in China to country j in
year t is defined as follows:
EEVijkt =
∑h∈Iijkt xhkt∑h∈Iikt xhkt
, (3.3)
where Iikt is the set of all HS6 product varieties within HS4 category i that exporter k
exports to the world in year t; Iijkt is the set of HS6 product varieties within HS4 category i
in which exporter k has positive exports to country j in year t; and xhkt is the export value
of HS6 product variety h from exporter k to the world in year t.8 Thus, EEVijkt can be
thought of as a weighted count of varieties that exporter k exports to country j in year t,
relative to all varieties that exporter k exports to the world. If EEVijkt = 1, it means that
exporter k exports the whole set of product varieties within HS4 category i to country j.
If EEVijkt = 0, it means that exporter k does not export any product variety within HS4
category i to country j. When EEVijkt increases, the range of export varieties within HS4
category i from exporter k to country j expands. Thus, EEVijkt can be considered as a
measurement of the EM of exports of HS4 category i from exporter k to country j.
The IM index for exports of HS4 category i from exporter k in China to country j in year
t is defined as follows:
IEVijkt =
∑h∈Iijkt xhjkt∑h∈Iijkt xhkt
, (3.4)
where xhjkt is the export value of HS6 product variety h from exporter k to country j in year
t. Thus, IEVijkt equals exporter k’s exports to country j relative to its exports to the world in
year t, within HS4 category i. If IEVijkt = 1, it means that country j is the only destination
for HS4 category i from exporter k. When IEVijkt increases, the average export value of
HS4 category i from exporter k to country j increases. Thus, IEVijkt can be considered as a
measurement of the IM of exports of HS4 category i from exporter k to country j.
Finally, multiplying IEVijkt by EEVijkt produces the ratio of exporter k’s exports of HS4
7We do not use the number of HS8 product varieties within each HS6 category for two reasons. First, thecode of HS8 is not stable, which changes year by year. Second, the number of HS8 product varieties withineach HS6 category is small.
8While Hummels and Klenow (2005) set the world’s exports to country j as the base, we set exporter k’sexports to the world as the base.
8
category i to country j to its exports of the HS4 category i to the world.
We investigate the responses of these new measurements of the EM and IM of exports to
tariffs and nominal exchange rates, respectively. The benchmark regression is as follows:
ln(EVijkt) =γ0 + γ1 ln(1 + Tariffijt) + γ2 ln(NERjt) + Processingijkt
+ ρi + θj + τk + ηt + νijkt(3.5)
Here, EVijkt is either EEVijkt, the new EM index of exports, or IEVijkt, the new IM index
of exports. The independent variables are the same as equation (3.1). We also control the
exporter fixed effect τk. When EV is EEV , if γ1 is negative and γ2 is positive, then a decrease
in tariffs increases export variety from China’s exporters, whereas China’s yuan appreciation
(depreciation) decreases (increases) it. When EV is IEV , if γ1 is negative and γ2 is positive,
then a decrease in tariffs increases the export value per export variety from China’s exporters,
whereas China’s yuan appreciation (depreciation) decreases (increases) it.
3.2 Data
The nominal exchange rate and Consumer Price Index (CPI) data are from the International
Monetary Fund (IMF) at the annual level.9 The tariff data is from the United Nations
Conference on Trade and Development (UNCTAD)—Trade Analysis Information System
(TRAINS). The tariffs of each HS 6-digit level product charged by each country are at the
annual level. In this study, we use the effectively applied (AHS) tariff which is defined as the
lowest available tariff. In most cases, AHS tariffs are the same as most-favored nation (MFN)
tariffs. But in rare cases AHS tariffs are lower than MFN tariffs, which indicates that China
has a trade agreement with these products. China’s export data is from their customs agency
at the transaction level. We aggregate these transactions to the firm-product-country-year
level. Thus, we have the number of exporters and export value/quantity per exporter for
each HS 6-digit product. The HS code changed in 2002 at the HS6 level. In order to keep
the product category consistent, we firstly aggregate the product to the HS6 level and then
convert all products to HS1996 by using the concordance between HS2002 and HS1996. The
sample period is from 2000 to 2006.
Table 1 presents the data summary, which merges the tariff, exchange rate, and export
9We also present the results with the quarterly data in the robustness checks.
9
datasets. The first part of Table 1 demonstrates that the exporter and destination numbers
increase over time. From 2000 to 2006, the exporter numbers increase by 175 percent and
destination numbers increase by 43 percent. The product numbers are almost constant. The
second part of Table 1 demonstrates that the tariffs, charged by partners, decrease over
time.10 In 2000, the simple average tariffs are 9.6 percent, and in 2006 the tariffs are 8.1
percent. In addition, the simple average tariffs of the OECD11 countries remain stable, and
that of the non-OECD countries decrease by almost 30 percent from 2000 to 2006. Figure 2
shows the average evolution of tariffs charged by China’s selected trade partners. The selected
trade partners are China’s top 21 export destinations minus Hong Kong and Singapore. The
tariffs charged by Hong Kong and Singapore are almost zero, and thus we exclude these two
destinations. Germany, Netherlands, UK, Italy, France, Spain, and Belgium are members
of European Union during the sample period and charge the same tariffs, and thus we use
EU to represent them. The average log deviation of gross tariff from 200012 is stable for
most OECD countries except Mexico. However, this index decreased sharply for non-OECD
countries, in particular India, Thailand and Brazil. The pattern is similar to that of Table 1.
The third part of Table 1 and Figure 1 demonstrate the time trend of China’s nominal
effective exchange rates (NEERs). After China’s WTO accession in 2001, the NEERs de-
crease until 2005—depreciation. On July 21, 2005, the People’s Bank of China announced a
revaluation of the yuan and a reform of the exchange rate regime. After 2005, the NEERs
began to increase—appreciation—and do so until 2015.13
The last part of Table 1 demonstrates the trends of the EM and IM indexes of exports
based on export product variety from China’s exporters. From 2000 to 2006, the average
EM index of exports remains stable for both ordinary and processing trade. This result is
consistent with the pattern in the first part, which demonstrates that the number of products
is stable. During the same period, the average IM index of exports decreases by 6 percent for
ordinary trade and by 17 percent for processing trade. In addition, the EM index is larger
10Table 1 calculates the average of tariffs over the countries included in our merged dataset, while Figure1 calculates the average of tariffs over all the countries included in the original tariff dataset.
11Though Taiwan is not a member of OECD, the GDP per capital of Taiwan is similar to members ofOECD countries. Thus, we attribute Taiwan in the OECD group.
12We use coefficients on year dummies in country-by-country regression of ln(1+Tariff) on HS6 fixed effectsand year dummies.
13Here, an increase (decrease) in the NEERs means China’s yuan appreciation (depreciation), whereas anincrease (decrease) in the independent variable NER—defined as China’s yuan per a foreign currency—meansChina’s yuan depreciation (appreciation).
10
but the IM index is smaller for processing trade, which implies that the scope of product
varieties from China’s exporters is larger for processing trade.
3.2.1 Tariffs and Exchange Rates for Selected Trade Partners
In this section, we present more detailed data for tariffs and nominal exchange rates. Figure
3 shows the time trends of tariffs charged to China and nominal exchange rates for China’s
selected trade partners from 2000 to 2006.14 Here, the tariff data is at the annual level, and
the exchange rate data is at the monthly level.
The figures imply that both tariffs and nominal exchange rates might be crucial factors
that contribute to changes in the EM of China’s exports. In the case of the euro area, for
example, tariffs, charged by the euro area, decreased and the yuan depreciated from 2002 to
2004, implying that both tariff reductions and the yuan’s depreciation might have increased
China’s EM. In the case of Japan, the tariffs charged by Japan decreased and the yuan
first appreciated and then depreciated during the period 2001 to 2005, implying that, while
tariff reductions might have kept increasing it, the yuan’s appreciation and depreciation,
respectively, might have decreased and increased China’s EM.
4 Regression Results
4.1 Exporter Numbers and Export Value/Quantity per Exporter
Column 1 of Table 2 presents the coefficients of equation (3.1), that is, the coefficients of the
EM and IM of exports on tariffs and nominal exchange rates. According to the hypotheses
(a) and (b) in Section 2, a reduction in tariffs charged by trade partners would increase the
number of China’s exporters while the appreciation (depreciation) of China’s yuan would
decrease (increase) it. Our results in Column 1 verify them. If the tariffs decrease by 1
percent, the exporter numbers would increase by 1.061 percent. If China’s yuan appreciates
by 1 percent, the exporter numbers would decrease by 0.112 percent. The coefficient of the
EM of exports on tariffs is larger than that on nominal exchange rates. This result is similar
to the results of BBF and FH, though their focus is on real exchange rates.
14Here, Germany, Netherlands, Italy, France, Spain, and Belgium are labeled as Euro Area.
11
Table 2 also demonstrates that the reductions in tariffs, charged by trade partners, stim-
ulate the IM of exports from China and the appreciation (depreciation) of China’s yuan
decreases (increases) it. If the tariffs decrease by 1 percent, the export value per exporter
would increase by 0.541 percent. If China’s yuan appreciates by 1 percent, the export value
per exporter would decrease by 0.0868 percent. The results are similar for the export quan-
tity per exporter. If the tariffs decrease by 1 percent, the export quantity per exporter would
increase by 0.443 percent. If China’s yuan appreciates by 1 percent, the export quantity per
exporter would decrease by 0.0766 percent. Again, the coefficient on tariffs is larger than that
on nominal exchange rates. In addition, Table 2 demonstrates that the number of exporters
is smaller, but the export value/quantity per exporter is larger in the processing trade mode.
One concern is that the coefficients on tariffs and nominal exchange rates cannot directly
be interpreted as the relative importance of these two factors. Thus, Column 2 reports the
standardized beta coefficients based on the specification in Column 1.15 If the tariff decreases
by 1 standard deviation, the exporter numbers would increase by 0.0663 standard deviation.
If the nominal exchange rate appreciates by 1 standard deviation, the exporter numbers would
decrease by 0.226 standard deviation. Thus, the response of the EM of exports to nominal
exchange rates is even much larger than that to tariffs in terms of standard deviation. For
the IM of exports, we have the similar results.
In order to further interpret the relative importance of tariffs and nominal exchange rates,
we examine the overall effects of these two factors on the EM and IM of exports year by year.
Using the annual changes of tariffs and nominal exchange rates in Table 1, and coefficients in
Column 1, Table 3 presents the results. From 2000 to 2001, the average tariffs (charged by
partners) decreased and China’s yuan appreciated. The overall effects of tariffs and nominal
exchange rates are similar on exporter numbers. But the overall effect of nominal exchange
rates is larger than that of tariffs on the IM of exports. From 2002 to 2005, tariffs decreased
due to China’s entry into WTO and China’s yuan depreciated, both boosting the exports
from China. The overall effect of tariffs dominates that of nominal exchange rates, both on
the EM and IM of exports. From 2005 to 2006, the average tariffs are almost constant, while
China’s yuan appreciated by 2.3 percent. Thus, the overall effect of nominal exchange rates
dominates that of tariffs, both on the EM and IM of exports.
15The beta coefficient standardizes the OLS coefficient to capture the change in standard deviation unitsof the dependent variable in response to a one standard deviation increase in the independent variable.
12
4.2 Entry and Exit of Exporters
In this section, we investigate the exporter dynamics in greater details. Exporter numbers
depend on the entry of new exporters and the exit of incumbent exporters. Exporters’ entry
and exit decisions might have heterogeneous responses to the tariffs and nominal exchange
rates. Thus, we separately examine the responses. Column 1 of Table 4 shows that the
reductions in tariffs, charged by trade partners, increase not only entry but also exit of
exporters. If the tariffs decrease by 1 percent, the new exporter numbers would increase by
0.841 percent and exit exporter numbers would increase by 0.799 percent. The coefficient
of entry is larger than that of exit. Thus, the net response to the tariff reductions is an
increase in the exporter numbers. At first sight, the results for exit might appear odd. In
the Melitz model, a tariff reduction causes the entry of new exporters but does not cause
the exit of incumbent exporters. As Feng et al. (2017) argue, however, an extended Melitz
model can show that a tariff reduction increases both the entry and exit of exporters. This is
because an increase in exporters due to the tariff reduction could increase the competition in
foreign markets, forcing low productivity exporters to exit. Feng et al. (2017) also empirically
document that the entry and exit of China’s exporters increased following China’s WTO
accession in 2001.
The responses to exchange rates are similar to those to tariffs in that depreciation increases
not only entry but also exit of exporters, but the coefficients on exchange rates are smaller
than those on tariffs. If China’s yuan depreciates by 1 percent, new exporter numbers would
increase by 0.0617 percent and exit exporter numbers also would increase by 0.112 percent.
Again, to gauge the relative importance of the two factors, Column 2 reports the stan-
dardized beta coefficients based on the specification in Column 1. If the tariff decreases by 1
standard deviation, new exporter numbers would increase by 0.0557 standard deviation. If
the nominal exchange rate appreciates by 1 standard deviation, the new exporter numbers
would decrease by 0.134 standard deviation. Thus, the response of new exporter numbers to
nominal exchange rates is even much larger than that to tariffs in terms of standard deviation.
For exit exporter numbers, we have the similar results.
13
4.3 Export Product Variety
In this section, we investigate the responses to tariffs and exchange rates from the perspective
of export product variety from China’s exporters. Column 1 of Table 5 shows that the
reductions in tariffs, charged by trade partners, increase not only the EM index but also the
IM index of exports. However, the coefficient of the IM index is much larger. If the tariffs
decrease by 1 percent, the EM index would increase by 0.0875 percent and the IM index
would increase by 0.164 percent. The exchange rate fluctuation only affects the IM index
of exports. If China’s yuan depreciates by 1 percent, the IM index would increase by 0.126
percent. Column 2 reports the standardized beta coefficients based on the specification in
Column 1. If the tariff decreases by 1 standard deviation, the EM index would increase by
0.008 standard deviation and the IM index would increase by 0.006 standard deviation. If
the nominal exchange rate appreciates by 1 standard deviation, the IM index would decrease
by 0.153 standard deviation and the EM index change is not significant.
Thus, the results indicate that changes in tariffs affect the EM of exports in terms of both
the exporter numbers and the export variety from exporters. Changes in nominal exchange
rates, on the other hand, affect it in terms of exporter numbers but do not in terms of export
variety from exporters.
4.4 Robustness Checks
In this section, we examine whether trade modes, export destinations (OECD vs. non-OECD
countries; main trade partners), balanced data, data frequency, real exchange rates, and sec-
toral and product heterogeneity would affect the benchmark results.
Trade Modes
Processing trade refers to the activity of importing all or part of the raw and auxiliary materi-
als from abroad and re-exporting the finished products after processing or assembly by firms
within China. It is possible that the effect of an exchange rate appreciation on the export
price of assembled products is canceled by the effect on the import price of the materials for
assembly. Thus, the response to exchange rate fluctuations on processing trade is likely to
14
be different from that on ordinary trade.16 We thus divide trade into two groups: ordinary
and processing trade. The columns 3 and 4 of Table 2 show that the coefficients of exporter
numbers on tariffs and nominal exchange rates are similar for both trade modes. But the
coefficients of export value/quantity per exporter are larger for processing trade. Thus, in
terms of the IM of exports, firms doing the processing trades are more responsive to the tariff
and nominal exchange rate shocks. In addition, the columns 3 and 4 of Table 4 show that
the coefficients of entry and exit are similar for both trade modes. The columns 3 and 4 of
Table 5 show that the coefficients of the EM index based on export product variety are also
similar but those of the IM index are larger for processing trade. In sum, in terms of the EM
of exports, there are no significant differences between two trade modes. In terms of the IM
of exports, the coefficients for the processing trade are significantly larger.
OECD vs. Non-OECD Countries
After China became a WTO member in 2001, the tariffs charged by trade partners, especially
developing countries, decreased considerably; for example, the comparison among India and
developed countries (Figure 3). Table 1 also presents that the average tariffs charged by
OECD countries decreased by 3.3 percent from 2000 to 2006. During the same period, the
average tariffs charged by non-OECD countries decreased by 29.9 percent. Thus, we divide
the export destinations into two groups: OECD and non-OECD countries. Last two columns
in Tables 2, 4 and 5 show that the results are mixed. In terms of the EM of exports (exporter
numbers, new exporter numbers, and exit exporter numbers), the coefficients for non-OECD
countries are larger than those for OECD countries. In terms of the IM of exports (export
value/quantity per exporter), the coefficients on tariffs are similar between two groups, but
the coefficients on nominal exchange rates are larger for non-OECD countries.
Main Trade Partners
Our data covers about 170 destinations, many of which are small economies. The trade with
these small economies might be significantly affected by unobservable factors other than tar-
iffs and nominal exchange rates, such as political relationship. Thus, we restrict our sample
to the top 50 partners for robustness checks. The export value with these partners is about
16Marquez and Schindler (2007) argue that estimating the response to exchange rates should differentiatethe ordinary and processing trade products.
15
97.5 percent of China’s total export value. The results in Column 1 of Table 6 show that our
main findings are still robust.
Balanced Data
Our data is an unbalanced data at the product-destination level. As Table 1 has shown, the
product number is stable from 2000 to 2006, but the destination number expands quickly
during the same period. Thus, the new export destinations might bias our results. In order
to exclude this concern, we restrict our sample to the product-destination pairs that appear
in the whole period (2000-2006). The export value in the balanced data is about 87 per-
cent of that of the full sample. Column 2 of Table 6 shows the results. For the continuing
product-destination pairs, the coefficient on tariffs is smaller than that for the benchmark,
and the coefficient on nominal exchange rates is larger.
Quarterly Data
The fluctuations of the annual exchange rate data might be small. Naknoi (2015) investigates
the EM of exports using the quarterly U.S. bilateral trade data. Thus, we perform robustness
checks with the quarterly nominal exchange rate data. We conduct a stacked regression as
follows:
ln(Eijt) =α0 + α1 ln(1 + Tariffijt) +3∑
h=0
α2h ln(NERjt−h) + Processingijt
+ ρi + θj + ηt + εijt
(4.1)
Here,∑3
h=0 α2h measures the response to exchange rate fluctuations over the current and last
three quarters. Column 3 of Table 6 demonstrates that the results remain robust. Notably,
however, the coefficients for the quarterly data are smaller than those for the annual data.
This is probably because firms take time to react to the tariff and exchange rate changes.
Real Exchange Rates
The nominal and real exchange rates present very different movements in the United States
from 2000-2006 (Figure A1 in Appendix A.2). Motivated by this observation, we perform
robustness checks with the real exchange rates. Table 7 presents the results with the real
16
exchange rates. Notably, the results remain robust.
Sectoral Differences
The responses of the EM of exports to tariffs and exchange rates might be different across
sectors. In this section, we additionally examine the responses by China’s top 10 export
sectors at the HS2 level. These sectors account for 66 percent of China’s exports. These sec-
tors are Electrical equipment (21.9 percent), Mechanical appliances (18.1 percent), Apparel,
not knitted or crocheted (5.4 percent), Apparel, knitted or crocheted (4.5 percent), Optical
instruments (3.1 percent), Furniture (3 percent), Toys and sports requisites (2.8 percent),
Mineral products (2.5 percent), Footwear (2.5 percent), and Iron or steel (2.4 percent). The
numbers in parentheses are ratios of exports in each sector relative to all exports from China.
Table 8 shows that the coefficient on tariffs is significant in 8 sectors while that on exchange
rates is significant in 9 sectors. Thus, Chinese firms respond more against exchange rates
than against tariff changes.
Differentiated Goods
As implied by Chaney’s (2008) model and the hypothesis (c) in our model, the responses
of the EM of exports to tariffs and nominal exchange rates might also be different across
products.17 In the more differentiated sector, the responses of exporter numbers to tariffs and
nominal exchange rates can be larger. Here, following the classification from Rauch (1999),
we divide products into two groups: homogeneous and differentiated goods. Table 9 presents
the results. Diff Dummy is 1 if the product is a differentiated good; otherwise, it is 0. We find
that the coefficient on nominal exchange rates is larger for differentiated goods. We also find
the similar result for tariffs. These results are in line with some other empirical findings. Yi
and Biesebroeck (2012) showed, using data for China’s imports from 129 countries during the
period 2001–2006, that differentiated goods have the higher elasticity of the EM of exports
to China with respect to China’s tariffs than homogeneous goods. Colacelli (2010) found,
using 136 countries’ bilateral export data during the period 1981–1997, that differentiated
goods have the higher elasticity of the EM of exports with respect to exchange rates, though
real.
17As noted by Yi and Biesebroeck (2012), Chaney (2008) defines the EM of exports as how much newexporters export while almost all the empirical studies testing Chaney (2008) define it as the number offirms/products in exports.
17
5 Discussion
5.1 Firm-level Implications: Temporary vs. Permanent Shocks
Our firm-product level results have shown that the entry and exit of China’s exporters re-
sponded significantly to not only reductions in tariffs but also changes in exchange rates.
At first sight, this result seems to be inconsistent with the well-known argument by Ruhl
(2008) that firms do not change their exporting status in response to temporary shocks while
some firms do change it in response to permanent shocks. This is because if the changes in
exchange rates are considered as temporary shocks, then the coefficients of the entry and exit
of exporters on exchange rates would be insignificant.
However, it should be noted that, besides trade liberalization policy, China was conducting
significant currency policy during the period to be studied in our paper: undervalued currency
policy until 2005 and appreciation policy since 2005. This means that, in China from 2000
to 2006, it might be appropriate to consider changes in both tariffs and exchange rates as
non-temporary shocks. Then it is not odd that our results have shown significant coefficients
of the entry and exit of China’s exporters on both tariffs and exchange rates. In this sense,
our results can be consistent with Ruhl’s (2008) argument.
5.2 Aggregate-level Implications: The Trade Elasticity and the
EM Elasticity
In Section 4, we have demonstrated that China’s exports significantly respond to both tariffs
and exchange rates. This is essentially a problem of the so-called elasticity of trade. Thus, it
is important to know whether the micro results in our paper are consistent with the response
of aggregate exports to these shocks in the existing studies.
We obtain the implied elasticity of aggregate exports by summing the coefficient of ex-
porter numbers and that of export value per exporter, which is averaged over HS6 products.
According to the results in Column 1 of Table 2, the elasticity of aggregate exports with
respect to tariffs is 1.60 and that with respect to nominal exchange rates is 0.20. According
to the results in Column 1 of Table 7, the elasticity of aggregate exports with respect to
real exchange rates is 0.34. According to Ruhl (2008), on the other hand, the estimated
(Armington) elasticities are 0.2-3.5 in the international real business cycle models and 4-15
18
in the applied general equilibrium models. Thus, all of our implied aggregate elasticities are
more close to the former estimates.
It should be, however, noted that our main interest has been particularly in the response
of the EM of exports, not the response of exports overall. Thus, it is also important to
know whether our results are consistent with the response of the EM of exports to tariffs
and exchange rates in the literature, although there are not many studies that estimated the
elasticity of the EM of exports with respect to tariffs and exchange rates. We summarize the
elasticities in our paper and other studies in Table 10.
We obtain the elasticity of the EM of exports by looking at the coefficient of exporter
numbers or export product variety. First, let us focus on exporter numbers as a measurement
of the EM of exports. According to the results in Column 1 of Table 2, the elasticity of
exporter numbers with respect to tariffs is 1.061, and that with respect to nominal exchange
rates is 0.112. According to the results in Column 1 of Table 5, the elasticity of exporter
numbers with respect to real exchange rates is 0.210. On the other hand, the estimated
elasticity of exporter numbers with respect to tariffs by Bas et al. (2017) is 3.83, which is
much larger than ours. That with respect to real exchange rates by Tang and Zhang (2012)
is 0.17, which is close to ours. Note that while our paper and Bas et al. (2017) are at the
product-destination-year level, Tang and Zhang (2012) are at the product-destination-month
level. To our knowledge, however, no past studies have estimated the elasticity of exporter
numbers with respect to nominal exchange rates.
Next, let us consider export variety as a measurement of the EM of exports. According
to the results in Column 1 of Table 8, the elasticity of export variety with respect to tariffs is
0.0875 and that with respect to nominal exchange rates is 0.00235. According to the results
in Column 1 of Table 9, that with respect to real exchange rates is 0.0132. According to the
literature, on the other hand, the estimated elasticity of export variety with respect to tariffs
by Feenstra and Kee (2007) is about 2, which is much larger than ours. That with respect
to real exchange rates by Colacelli (2010) is 0.045, which is larger than ours but close to
ours in that both are less than 0.1. Note that while our paper is at the firm-destination-year
level, Feenstra and Kee (2007) and Colacelli (2010) are at the industry-year level and the
country-destination-year level, respectively. Note also that, to our knowledge, no past studies
have estimated the elasticity of export variety with respect to nominal exchange rates.
19
6 Conclusion
We have empirically tested the implications from the Melitz model with the exchange rates.
Specifically, using China’s firm-product data from 2000 to 2006 with 170 trade partners, we
tested whether the EM of China’s exports respond to both trade liberalization and nominal
exchange rates. Based on regressions, we have three main empirical findings. First, though
relatively small compared to that of tariffs (charged by trade partners), the coefficient of
exporter numbers on nominal exchange rates is also significant. In fact, our results based on
the beta coefficients and overall effects indicate that exchange rates are much more important
than believed. Second, reductions in tariffs and yuan depreciation increased not only entry
but also exit of exporters. Finally, the implied elasticity of aggregate exports with respect to
tariffs is 1.60 and that with respect to nominal exchange rates is 0.20, which are in line with
the estimated (Armington) elasticities in the international real business cycle literature.
The results presented in this paper are valuable, particularly for empirical studies on trade
liberalization and the EM of trade. First, Kehoe and Ruhl (2013), for example, focused on
increases in the EM of trade after trade liberalization or structural changes. Our results,
however, indicate that the observed increases in the EM of trade could be caused by not only
changes in tariffs but also changes in nominal exchange rates. Thus, future studies, in par-
ticular, on China’s EM need to place more importance on exchange rates when investigating
the changes in the EM of trade using firm data. Second, our results provide an important
policy implication. China was a centrally-planned economy and adopted a U.S. dollar pegged
exchange rate policy for a long period. Previous studies paid little attention to the effect
of exchange rates on trade using Chinese data. China, however, allowed a managed float
of its currency in July 2005 and became the largest trader in the world in 2012. It is thus
important to examine the effect of exchange rates. In fact, our results indicate that foreign
currency policy could be an effective tool if Chinese government would like to boost exports.
20
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22
Table 1: Data Summary
Year
Variables 2000 2001 2002 2003 2004 2005 2006
Exporter, Product, and Destination
Exporter Numbers 59,709 65,505 74,882 90,705 114,768 138,881 163,923
Product Numbers 4,789 4,809 4,778 4,816 4,853 4,879 4,894
Destination Numbers 104 134 141 124 125 135 149
Tariffs Charged by Partners (%)
—All Countries
(mean) 9.60 9.54 9.97 8.86 7.89 8.11 8.10
(sd) 16.14 14.87 35.45 15.37 18.86 11.90 12.35
—OECD Countries
(mean) 4.91 5.01 5.12 4.98 3.93 4.63 4.75
(sd) 15.58 15.52 14.29 15.56 13.36 12.37 13.34
—Non-OECD Countries
(mean) 14.86 13.74 14.45 12.43 11.30 10.72 10.42
(sd) 15.12 12.90 46.76 14.28 21.99 10.83 11.04
China’s Nominal Effective Exchange Rate 93.18 98.35 97.92 91.88 87.68 87.26 89.23
Export Product Variety
—EM Index
Ordinary Trade 0.84 0.84 0.84 0.84 0.85 0.84 0.85
Processing Trade 0.92 0.92 0.92 0.93 0.93 0.93 0.93
—IM Index
Ordinary Trade 0.49 0.47 0.46 0.46 0.45 0.44 0.46
Processing Trade 0.36 0.35 0.34 0.33 0.32 0.32 0.30
Note: (a) Taiwan is not a member of OECD. However, the GDP per capital of Taiwan is similar to members of OECDcountries. Thus, we attribute Taiwan in the OECD group. (b) China’s nominal effective exchange rate index for 2010 is 100.
Source: Chinese Customs Export and Import Database, IMF and TRAINS.
23
Table 2: Nominal Exchange Rates, Tariffs, and Exports
(1) (2) (3) (4) (5) (6)
Full Sample Betas Ordinary Processing OECD Non-OECD
ln(Exporter Numbers)
ln(1+Tariff) -1.061*** -0.0663*** -1.041*** -1.220*** -0.341*** -0.662***
(0.0526) (0.00329) (0.0564) (0.0669) (0.0875) (0.0296)
ln(NER) 0.112*** 0.226*** 0.138*** 0.170*** 0.0521*** 0.168***
(0.00778) (0.0157) (0.00910) (0.0120) (0.0124) (0.00842)
Processing Trade -1.202*** -0.405*** -1.253*** -1.209***
(0.0196) (0.00661) (0.0197) (0.0229)
Observations 1,329,035 1,329,035 964,746 364,074 660,819 668,037
R-squared 0.577 0.577 0.633 0.606 0.667 0.531
ln(Export Value per Exporter)
ln(1+Tariff) -0.541*** -0.0223*** -0.410*** -1.057*** -0.337** -0.307***
(0.0627) (0.00259) (0.0597) (0.119) (0.137) (0.0491)
ln(NER) 0.0868*** 0.116*** 0.0631*** 0.256*** -0.0246 0.134***
(0.0138) (0.0183) (0.0141) (0.0286) (0.0245) (0.0151)
Processing Trade 0.591*** 0.132*** 0.654*** 0.426***
(0.0206) (0.00459) (0.0219) (0.0246)
Observations 1,329,035 1,329,035 964,746 364,074 660,819 668,037
R-squared 0.355 0.355 0.362 0.408 0.373 0.359
ln(Export Quantity per Exporter)
ln(1+Tariff) -0.443*** -0.0127*** -0.243*** -1.154*** -0.340** -0.330***
(0.0730) (0.00210) (0.0690) (0.130) (0.152) (0.0557)
ln(NER) 0.0766*** 0.0710*** 0.0609*** 0.259*** -0.0276 0.112***
(0.0149) (0.0138) (0.0158) (0.0305) (0.0268) (0.0165)
Processing Trade 0.432*** 0.0669*** 0.521*** 0.232***
(0.0237) (0.00368) (0.0248) (0.0284)
Observations 1,329,035 1,329,035 964,746 364,074 660,819 668,037
R-squared 0.612 0.612 0.658 0.583 0.605 0.650
Product FE Yes Yes Yes Yes Yes Yes
Time FE Yes Yes Yes Yes Yes Yes
Country FE Yes Yes Yes Yes Yes Yes
Cluster by Product Yes Yes Yes Yes Yes Yes
Note: (a) Since the tariffs charged by Hong Kong are zero, we exclude Hong Kong from the sample. (b)Column 2 reports standardized beta coefficients from Column 1. (c) Taiwan is not a member of OECD.However, the GDP per capital of Taiwan is similar to members of OECD countries. Thus, we attribute Taiwanin the OECD group. (d) *** p < 0.01, ** p < 0.05, * p < 0.1.
Source: Chinese Customs Export and Import Database, IMF and TRAINS.
24
Table 3: The Overall Effects of Tariffs and Nominal Exchange Rates Year by Year
Year
Variables 2000-2001 2001-2002 2002-2003 2003-2004 2004-2005 2005-2006
Exporter Numbers
Tariff 0.663 -4.576 13.292 11.616 -2.958 0.131
NER -0.620 0.049 0.690 0.510 0.020 -0.257
Export Value per Exporter
Tariff 0.338 -2.333 6.778 5.923 -1.508 0.067
NER -0.481 0.038 0.534 0.395 0.016 -0.200
Export Quantity per Exporter
Tariff 0.277 -1.911 5.550 4.850 -1.235 0.054
NER -0.424 0.034 0.472 0.349 0.014 -0.176
Source: Chinese Customs Export and Import Database, IMF and TRAINS.
Table 4: Nominal Exchange Rates, Tariffs, and Exporter Dynamics
(1) (2) (3) (4) (5) (6)
Full Sample Betas Ordinary Processing OECD Non-OECD
ln(New Exporter Numbers)
ln(1+Tariff) -0.841*** -0.0557*** -0.924*** -0.837*** -0.218*** -0.512***
(0.0452) (0.00299) (0.0506) (0.0583) (0.0717) (0.0272)
ln(NER) 0.0617*** 0.134*** 0.0889*** 0.101*** 0.0758*** 0.0918***
(0.00820) (0.0178) (0.00926) (0.0130) (0.0150) (0.00891)
Processing Trade -1.276*** -0.459*** -1.380*** -1.227***
(0.0197) (0.00710) (0.0191) (0.0234)
Observations 1,082,359 1,082,359 825,716 256,341 523,419 558,736
R-squared 0.572 0.572 0.625 0.538 0.664 0.527
ln(Exit Exporter Numbers)
ln(1+Tariff) -0.799*** -0.0546*** -0.877*** -0.781*** -0.107 -0.531***
(0.0499) (0.00341) (0.0570) (0.0595) (0.0730) (0.0301)
ln(NER) 0.112*** 0.254*** 0.144*** 0.133*** 0.0731*** 0.147***
(0.00894) (0.0203) (0.0106) (0.0137) (0.0158) (0.00938)
Processing Trade -1.196*** -0.456*** -1.271*** -1.161***
(0.0187) (0.00712) (0.0185) (0.0223)
Observations 858,707 858,707 649,851 208,504 457,461 401,020
R-squared 0.567 0.567 0.616 0.542 0.649 0.518
Product FE Yes Yes Yes Yes Yes Yes
Time FE Yes Yes Yes Yes Yes Yes
Country FE Yes Yes Yes Yes Yes Yes
Cluster by Product Yes Yes Yes Yes Yes Yes
Note: (a) Since the tariffs charged by Hong Kong are zero, we exclude Hong Kong from the sample. (b)Column 2 reports standardized beta coefficients from Column 1. (c) Taiwan is not a member of OECD.However, the GDP per capital of Taiwan is similar to members of OECD countries. Thus, we attribute Taiwanin the OECD group. (d) *** p < 0.01, ** p < 0.05, * p < 0.1.
Source: Chinese Customs Export and Import Database, IMF and TRAINS.
25
Table 5: Nominal Exchange Rates, Tariffs, and Export Product Variety
(1) (2) (3) (4) (5) (6)
Full Sample Betas Ordinary Processing OECD Non-OECD
ln(EM Index)
ln(1+Tariff) -0.0875*** -0.00800*** -0.0835*** -0.102*** -0.0758** -0.0278*
(0.0253) (0.00231) (0.0265) (0.0268) (0.0320) (0.0163)
ln(NER) -0.00235 -0.00751 -0.00138 0.00245 0.0208*** 0.00943**
(0.00424) (0.0136) (0.00455) (0.00504) (0.00770) (0.00420)
Processing Trade 0.123*** 0.0509*** 0.124*** 0.119***
(0.00631) (0.00261) (0.00662) (0.00758)
Observations 14,310,474 14,310,474 12,380,881 1,919,054 9,361,207 4,924,697
R-squared 0.130 0.130 0.128 0.153 0.130 0.150
ln(IM Index)
ln(1+Tariff) -0.164** -0.00574** -0.129** -0.592** -0.0380 -0.00245
(0.0700) (0.00245) (0.0558) (0.256) (0.137) (0.0413)
ln(NER) 0.126*** 0.153*** 0.120*** 0.238*** 0.167*** 0.0778***
(0.0138) (0.0168) (0.0138) (0.0285) (0.0240) (0.0134)
Processing Trade -0.321*** -0.0509*** -0.204*** -0.699***
(0.0406) (0.00643) (0.0388) (0.0385)
Observations 14,310,474 14,310,474 12,380,881 1,919,054 9,361,207 4,924,697
R-squared 0.362 0.362 0.327 0.524 0.345 0.444
Product FE Yes Yes Yes Yes Yes Yes
Time FE Yes Yes Yes Yes Yes Yes
Country FE Yes Yes Yes Yes Yes Yes
Exporter FE Yes Yes Yes Yes Yes Yes
Cluster by Product Yes Yes Yes Yes Yes Yes
Note: (a) Since the tariffs charged by Hong Kong are zero, we exclude Hong Kong from the sample. (b) Column2 reports standardized beta coefficients from Column 1. (c) Taiwan is not a member of OECD. However, theGDP per capital of Taiwan is similar to members of OECD countries. Thus, we attribute Taiwan in the OECDgroup. (d) *** p < 0.01, ** p < 0.05, * p < 0.1.
Source: Chinese Customs Export and Import Database, IMF and TRAINS.
26
Table 6: Nominal Exchange Rates, Tariffs, and Exports:Robustness Checks
(1) (2) (3)
Main Trade Partners Full Balanced Quarterly
stacked
ln(Exporter Numbers)
ln(1+Tariff) -1.068*** -0.881*** -0.895***
(0.0657) (0.0851) (0.0566)
ln(NER) 0.0996*** 0.221*** 0.0916***
(0.00953) (0.0132) (116.56)
Processing Trade -1.302*** -1.284*** -0.845***
(0.0191) (0.0249) (0.0184)
Observations 985,575 552,956 3,633932
R-squared 0.607 0.613 0.523
ln(Export Value per Exporter)
ln(1+Tariff) -0.655*** -0.304*** -0.365***
(0.0782) (0.0904) (0.0607)
ln(NER) 0.0883*** 0.155*** 0.0384***
(0.0165) (0.0180) (7.8)
Processing Trade 0.651*** 0.925*** 0.568***
(0.0202) (0.0245) (0.0201)
Observations 985,575 552,956 3,633,932
R-squared 0.337 0.467 0.329
ln(Export Quantity per Exporter)
ln(1+Tariff) -0.600*** -0.342*** -0.266***
(0.0882) (0.106) (0.0727)
ln(NER) 0.0860*** 0.0992*** 0.0354**
(0.0183) (0.0193) (5.23)
Processing Trade 0.478*** 0.776*** 0.432***
(0.0231) (0.0271) (0.0236)
Observations 985,575 552,956 3,633,932
R-squared 0.613 0.667 0.599
Product FE Yes Yes Yes
Time FE Yes Yes Yes
Country FE Yes Yes Yes
Cluster by Product Yes Yes Yes
Note: (a) Since the tariffs charged by Hong Kong are zero, we excludeHong Kong from the sample. (b) The export value of the top 50 partnersis about 97.5 percent of China’s total export value. (c) The stacked re-gression in Column 3 measures the responses to exchange rate fluctuationsover the current and last three quarters. (d) *** p < 0.01, ** p < 0.05, * p < 0.1.
Source: Chinese Customs Export and Import Database, IMF and TRAINS.
27
Table 7: Real Exchange Rates, Tariffs, and Exports
(1) (2) (3)
ln(Exporter Numbers) ln(Export Value per Exporter) ln(Export Quantity per Exporter)
ln(1+Tariff) -1.068*** -0.530*** -0.447***
(0.0535) (0.0638) (0.0743)
ln(RER) 0.210*** 0.131*** 0.140***
(0.00943) (0.0165) (0.0184)
Processing Trade -1.198*** 0.606*** 0.448***
(0.0195) (0.0205) (0.0236)
Observations 1,278,015 1,278,015 1,278,015
R-squared 0.577 0.354 0.611
Product FE Yes Yes Yes
Time FE Yes Yes Yes
Country FE Yes Yes Yes
Cluster by Product Yes Yes Yes
(1) (2)
ln(New Exporter Numbers) ln(Exit Exporter Numbers)
ln(1+Tariff) -0.850*** -0.794***
(0.0460) (0.0506)
ln(RER) 0.210*** 0.113***
(0.00959) (0.00970)
Processing Trade -1.274*** -1.194***
(0.0196) (0.0186)
Observations 1,039,128 829,596
R-squared 0.573 0.567
Product FE Yes Yes
Time FE Yes Yes
Country FE Yes Yes
Cluster by Product Yes Yes
(1) (2)
ln(EM Index) ln(IM Index)
ln(1+Tariff) -0.0860*** -0.154**
(0.0251) (0.0713)
ln(RER) 0.0132*** 0.160***
(0.00510) (0.0166)
Processing Trade 0.123*** -0.314***
(0.00633) (0.0406)
Observations 13,871,508 13,871,508
R-squared 0.130 0.361
Product FE Yes Yes
Time FE Yes Yes
Country FE Yes Yes
Exporter FE Yes Yes
Cluster by Product Yes Yes
Note: (a) Since the tariffs charged by Hong Kong are zero, we exclude Hong Kong from the sample. (b) *** p < 0.01, ** p <0.05, * p < 0.1.
Source: Chinese Customs Export and Import Database, IMF and TRAINS.
28
Table 8: Exchange Rates, Tariffs, and Exports by Sectors
(1) (2) (3) (4) (5) (6)
Nominal Exchange Rate Real Exchange Rate
Numbers Value Quantity Numbers Value Quantity
Electrical equipment Tariff -1.054*** -1.189*** -1.162*** -1.022*** -1.148*** -1.127***
(0.153) (0.222) (0.273) (0.156) (0.226) (0.276)
Exchange Rate 0.172*** 0.194*** 0.172*** 0.229*** 0.339*** 0.347***
(0.0201) (0.0457) (0.0495) (0.0249) (0.0507) (0.0613)
Mechanical appliances Tariff -0.831*** -0.484* -0.153 -0.801*** -0.470* -0.150
(0.138) (0.248) (0.307) (0.141) (0.250) (0.310)
Exchange Rate 0.157*** 0.142*** 0.211*** 0.216*** 0.171*** 0.303***
(0.0232) (0.0454) (0.0500) (0.0251) (0.0489) (0.0578)
Apparel, not knitted or crocheted Tariff 0.743*** 0.586*** 0.938*** 0.768*** 0.576*** 0.930***
(0.214) (0.197) (0.265) (0.211) (0.197) (0.260)
Exchange Rate 0.526*** 0.303*** 0.359*** 0.590*** 0.326*** 0.404***
(0.0349) (0.0625) (0.0680) (0.0442) (0.0684) (0.0757)
Apparel, knitted or crocheted Tariff -0.476** -0.0448 0.387 -0.418** -0.0347 0.391
(0.199) (0.313) (0.363) (0.202) (0.310) (0.361)
Exchange Rate 0.310*** 0.0668 0.0897 0.315*** 0.113 0.0663
(0.0394) (0.0552) (0.0708) (0.0492) (0.0774) (0.0896)
Optical instruments Tariff -0.576* -1.187*** -1.522*** -0.556 -1.076** -1.498***
(0.332) (0.413) (0.437) (0.330) (0.412) (0.425)
Exchange Rate 0.407*** 0.326*** 0.234*** 0.729*** 0.621*** 0.571***
(0.0451) (0.0920) (0.0858) (0.0684) (0.122) (0.106)
Furniture Tariff -0.00981 0.00599 0.199 -0.0647 -0.0427 0.130
(0.429) (0.560) (0.587) (0.429) (0.561) (0.593)
Exchange Rate 0.349*** 0.209*** 0.109* 0.507*** 0.291*** 0.223**
(0.0415) (0.0566) (0.0648) (0.0577) (0.0739) (0.0828)
Toys and sports requisites Tariff -0.334 -0.0972 -0.377 -0.316 -0.0625 -0.386
(0.449) (0.429) (0.407) (0.426) (0.408) (0.388)
Exchange Rate 0.170** 0.114 0.0294 0.277*** 0.135 0.0162
(0.0710) (0.0784) (0.0878) (0.0895) (0.0939) (0.0969)
Mineral products Tariff -0.793*** -0.0590 -0.0270 -0.845*** -0.0768 -0.0920
(0.210) (0.323) (0.347) (0.206) (0.322) (0.345)
Exchange Rate 0.209*** 0.272*** 0.197*** 0.335*** 0.234*** 0.214***
(0.0310) (0.0617) (0.0660) (0.0461) (0.0744) (0.0777)
Footwear Tariff -0.601* -0.0748 0.0485 -0.624** -0.0542 0.0580
(0.308) (0.387) (0.422) (0.308) (0.385) (0.416)
Exchange Rate 0.0737** 0.148** 0.182** 0.179*** 0.222** 0.359***
(0.0296) (0.0598) (0.0757) (0.0360) (0.0869) (0.0952)
Iron or steel Tariff -1.938*** -1.943*** -2.147*** -1.998*** -2.036*** -2.278***
(0.211) (0.371) (0.386) (0.218) (0.392) (0.404)
Exchange Rate 0.0690 0.0642 0.0110 0.241*** 0.142* 0.0833
(0.0431) (0.0754) (0.0726) (0.0536) (0.0854) (0.0881)
Note: (a) Since the tariffs charged by Hong Kong are zero, we exclude Hong Kong from the sample. (b) *** p < 0.01, ** p <0.05, * p < 0.1.
Source: Chinese Customs Export and Import Database, IMF and TRAINS.
29
Table 9: Exchange Rates, Tariffs, and Differentiated Products
(1) (2) (3) (4)
Nominal Exchange Rate Real Exchange Rate
ln(Exporter Numbers)
ln(1+Tariff) -1.135*** 0.0483 -1.144*** 0.0730
(0.0542) (0.247) (0.0552) (0.100)
ln(1+Tariff) × Diff Dummy -1.352*** -1.380***
(0.290) (0.111)
ln(Exchange Rate) 0.113*** 0.104*** 0.204*** 0.164***
(0.00809) (0.0334) (0.00978) (0.00942)
ln(Exchange Rate) × Diff Dummy 0.0475*** 0.0496***
(0.00958) (0.00251)
Processing Trade -1.198*** -1.217*** -1.195*** -1.199***
(0.0202) (0.0331) (0.0201) (0.0201)
Observations 1,247,334 1,245,966 1,199,222 1,199,222
R-squared 0.577 0.600 0.577 0.580
ln(Export Value per Exporter)
ln(1+Tariff) -0.583*** 0.290** -0.576*** 0.298**
(0.0673) (0.129) (0.0685) (0.130)
ln(1+Tariff) × Diff Dummy -0.994*** -0.990***
(0.138) (0.139)
ln(Exchange Rate) 0.0879*** 0.0603*** 0.131*** 0.101***
(0.0142) (0.0145) (0.0170) (0.0172)
ln(Exchange Rate) × Diff Dummy 0.0346*** 0.0371***
(0.00389) (0.00403)
Processing Trade 0.584*** 0.581*** 0.599*** 0.596***
(0.0212) (0.0212) (0.0210) (0.0210)
Observations 1,247,334 1,247,334 1,199,222 1,199,222
R-squared 0.354 0.355 0.352 0.353
ln(Export Quantity per Exporter)
ln(1+Tariff) -0.478*** 0.304** -0.486*** 0.299**
(0.0788) (0.138) (0.0803) (0.139)
ln(1+Tariff) × Diff Dummy -0.857*** -0.849***
(0.150) (0.151)
ln(Exchange Rate) 0.0810*** 0.0367** 0.141*** 0.0929***
(0.0154) (0.0158) (0.0190) (0.0192)
ln(Exchange Rate) × Diff Dummy 0.0544*** 0.0583***
(0.00453) (0.00469)
Processing Trade 0.428*** 0.424*** 0.445*** 0.440***
(0.0245) (0.0245) (0.0244) (0.0244)
Observations 1,247,334 1,247,334 1,199,222 1,199,222
R-squared 0.618 0.618 0.617 0.618
Product FE Yes Yes Yes Yes
Country FE Yes Yes Yes Yes
Time FE Yes Yes Yes Yes
Cluster by Product Yes Yes Yes Yes
Note: (a) Since the tariffs charged by Hong Kong are zero, we exclude Hong Kongfrom the sample. (b) Diff Dummy is 1 if the product is a differentiated good according tothe classification from Rauch (1999); otherwise, it is 0. (c) *** p < 0.01, ** p < 0.05, * p < 0.1.
Source: Chinese Customs Export and Import Database, IMF and TRAINS.
30
Table 10: Elasticities in Selected Studies
Paper Country Tariff elasticity Exchange rate elasticity
NER RER
Exporter numbers
Ours China 1.061 0.112 0.210
Bas et al. (2017) China & France 3.83
Tang and Zhang (2012) China 0.17
Export variety
Ours China 0.0875 0.00235 0.0132
Feenstra and Kee (2007) Mexico 2.049
Colacelli (2010) 136 countries 0.045
Note: (a) For exporter numbers, our paper and Bas et al. (2017) are at the product-destination-year level,and Tang and Zhang (2012) are at the product-destination-month level. (b) For export variety, our paperis at the firm-destination-year level; Feenstra and Kee (2007) are at the industry-year level; and Colacelli(2010) is at the country-destination-year level.
31
Figure 1: Average Tariffs Charged by Trade Partners and China’s Nominal Effective Ex-change Rates
9010
011
012
013
0N
EER
89
1011
12Ta
riff
2000 2005 2010 2015Year
Tariff NEER
Note: An increase (decrease) in nominal effective exchange rates means China’s yuan appreciation(depreciation).
Source: IMF and TRAINS.
32
Figure 2: Average Evolution of Tariffs Charged by Selected Trade Partners
-.06
-.04
-.02
0.0
2
avg
log
devi
atio
n of
gro
ss ta
riff f
rom
200
0
2000 2002 2004 2006Year
USA EU JPN
KOR TWN CAN
AUS MEX
OECD
-.2-.1
5-.1
-.05
0
avg
log
devi
atio
n of
gro
ss ta
riff f
rom
200
0
2000 2002 2004 2006Year
IND BRA
THA IDN
MYS
non-OECD
Note: (a) This figure shows coefficients on year dummies in country-by-country regression of ln(1+Tariff)on HS6 fixed effects and year dummies. (b) Taiwan is not a member of OECD. However, the GDP percapital of Taiwan is similar to that of members of OECD countries. Thus, we attribute Taiwan to theOECD group.
Source: TRAINS.
33
Figure 3: Tariffs Charged to China and Nominal Exchange Rates for Selected Trade Partners
7.8
7.9
88.
18.
28.
3Yu
an/U
SD
3.5
3.6
3.7
3.8
3.9
4Ta
riff
2000 2001 2002 2003 2004 2005 2006Year
tariff NER
United States
78
910
11Yu
an/E
uro
4.2
4.4
4.6
4.8
5Ta
riff
2000 2001 2002 2003 2004 2005 2006Year
tariff NER
Euro Area
.06
.065
.07
.075
.08
Yuan
/Yen
1.4
1.6
1.8
2Ta
riff
2000 2001 2002 2003 2004 2005 2006Year
tariff NER
Japan
.006
.006
5.0
07.0
075
.008
.008
5Yu
an/W
on
9.5
1010
.511
11.5
Tarif
f
2000 2001 2002 2003 2004 2005 2006Year
tariff NER
South Korea
1213
1415
16Yu
an/P
ound
4.2
4.4
4.6
4.8
5Ta
riff
2000 2001 2002 2003 2004 2005 2006Year
tariff NER
United Kingdoms
.24
.25
.26
.27
Yuan
/TW
D
4.5
55.
56
6.5
Tarif
f
2000 2001 2002 2003 2004 2005 2006Year
tariff NER
Taiwan
55.
56
6.5
77.
5Yu
an/C
AD
2.6
2.8
33.
23.
4Ta
riff
2000 2001 2002 2003 2004 2005 2006Year
tariff NER
Canada
44.
55
5.5
66.
5Yu
an/A
UD
3.5
44.
55
5.5
Tarif
f
2000 2001 2002 2003 2004 2005 2006Year
tariff NER
Australia
2.14
2.16
2.18
2.2
2.22
Yuan
/MYR
7.8
88.
28.
4Ta
riff
2000 2001 2002 2003 2004 2005 2006Year
tariff NER
Malaysia
.17
.175
.18
.185
.19
Yuan
/INR
1520
2530
35Ta
riff
2000 2001 2002 2003 2004 2005 2006Year
tariff NER
India
.000
7.0
008
.000
9.0
01.0
011
Yuan
/IDR
6.6
6.7
6.8
6.9
7Ta
riff
2000 2001 2002 2003 2004 2005 2006Year
tariff NER
Indonesia
.18
.19
.2.2
1.2
2Yu
an/T
HB
810
1214
16Ta
riff
2000 2001 2002 2003 2004 2005 2006Year
tariff NER
Thailand
.7.7
5.8
.85
.9Yu
an/M
XN
1214
1618
Tarif
f
2000 2001 2002 2003 2004 2005 2006Year
tariff NER
Mexico
23
45
Yuan
/BR
L
1314
1516
17Ta
riff
2000 2001 2002 2003 2004 2005 2006Year
tariff NER
Brazil
Note: A decrease (increase) in nominal exchange rates means China’s yuan appreciation (depreciation).
Source: IMF and TRAINS.
34
A Appendix
A.1 Theory
This appendix introduces nominal exchange rates and sticky wages to the Melitz (2003)
model of heterogeneous firm trade to guide our empirical analysis on the relationship between
tariffs/nominal exchange rates and the EM of exports. Our model is a slightly simplified
version of the Rodrıguez-Lopez (2011) model. There are two countries: Home and Foreign.
There is a continuum of households in the interval [0, 1], and each household provides labor
to the production of differentiated goods in each country. There are firms heterogeneous in
productivity, and each firm produces a single variety under monopolistic competition. Home
and Foreign markets are segmented.
First, we set up the preferences and production and show the equilibrium exporting cutoff
productivity level for Home firms. Then, we derive the proposition regarding the elasticity
of the exporting cutoff/the mass of exporters with respect to tariffs and that with respect to
nominal exchange rates.
Preferences
The representative Home household has the CES preferences for a continuum of differentiated
goods produced in Home and Foreign. The utility function is then given by
U =
(∫i∈∆′
qν−1ν
i
) νν−1
,
where qi is consumption of variety i, ν > 1 is the elasticity of substitution between varieties,
and ∆′= [0, N ] is the set of available varieties at Home.
Solving the utility maximization problem gives the demand for variety i
qi =(piP
)−νQ,
where pi is the price of variety i and P = (∫i∈∆′
p1−νi )
11−ν is the price of the composite good
Q. The total expenditure of this household is I = PQ. Since households are located in the
unit interval, the market demand and the representative household’s demand are equivalent.
35
Production
The production function of a Home firm with productivity φ is given by
y(φ) = φL,
where y(φ) is the output of a Home firm with productivity φ and L is the only factor of
production.18 As in the Melitz model, producers are heterogeneous in productivity, and each
producer knows its productivity, φ, only after entry. The productivity is Pareto distributed
in the interval [φmin,∞), and thus the cumulative distribution function for productivity is
G(φ) = 1− (φmin/φ)κ, where κ > 1 is a parameter of productivity dispersion (the higher κ,
the lower heterogeneity).
As does Rodrıguez-Lopez (2011), we assume that nominal wages are fixed at W in the
Home currency. Then the marginal cost of a Home firm with productivity φ is constant at
W/φ. Foreign production can analogously be defined. The production function of a Foreign
firm with productivity φ is just y∗(φ) = φL∗, where y∗ is the output of a Foreign firm with
productivity φ and L∗ is the Foreign labor. With fixed wages W ∗ in the Foreign currency,
its marginal cost is W ∗/φ.
There is the fixed cost of entry in terms of labor: fE and f ∗E for Home and Foreign firms,
respectively. There is also the fixed cost from selling in each market.19 The fixed cost from
selling in the Home market is fD for Home firms and f ∗X for Foreign firms; the fixed cost
from selling in the Foreign market is fX for Home firms and f ∗D for Foreign firms. Another
exporting cost is an iceberg cost. τ denotes the iceberg cost for Home firms so that a Home
exporter must ship τ > 1 units of the good in order for one unit to reach the Foreign market.
We interpret τ − 1 as tariffs imposed by Foreign. Similarly, τ ∗ denotes the iceberg cost for
Foreign firms, and we interpret τ ∗ − 1 as tariffs imposed by Home.
The profit maximizing domestic price in the Home currency for a Home firm with pro-
ductivity φ is given by
pD(φ) = (1 + µ)W
φ,
18In Rodrıguez-Lopez (2011), the production function of a Home firm with productivity φ is given byy(φ) = ZφL, where Z is an aggregate labor productivity factor. Because Z is not necessary for our purpose,we set Z = 1 for simplification.
19Without fixed costs in this CES model, it is always optimal for firms to produce a positive output foreach market.
36
where µ is the constant markup over marginal cost and equals
µ =1
ν − 1.
As does Rodrıguez-Lopez (2011), let ε be the exogenous nominal exchange rates defined as
the price of the Foreign currency in terms of the Home currency (e.g., China’s yuan per U.S.
dollar). Then the export price in the Foreign currency for a Home firm with productivity φ
is given by
pX(φ) = τ(1 + µ)W
εφ. (A.1)
Equilibrium Exporting Cutoff
Then, we can derive the equilibrium exporting cutoff level for Home firms:
φX = τ
[(fXf ∗D
)1νW
εW ∗
] νν−1
φ∗D, (A.2)
where φ∗D is the cutoff productivity level for Foreign firms selling in the Foreign market and
equals
φ∗D =f∗ 1κ
D
τF ∗ 1κ
[(ττ ∗)κF
κ−(ν−1)ν−1 − 1
τ ∗κFκ−(ν−1)ν−1 − 1
(ρε)κνν−1
(fXf∗D
)κ−(ν−1)ν−1
] 1κ
, (A.3)
where F = (fXf∗X)/(fDf
∗D), ρ = (F ∗/F )
ν−1κν (W ∗/W ), F ∗ = [κ− (ν − 1)]/(κφκmin)(δf ∗E +
f ∗D + f ∗X), F = [κ− (ν − 1)]/(κφκmin)(δfE + fD + fX) and δ is a proportion of existing firms
in each country to exit.20
Elasticity of the Exporting Cutoff and the Mass of Exporters
Then, we obtain the following proposition. Note that while the exporting cutoff part of the
proposition reproduces the results by Melitz (2003) and Rodrıguez-Lopez (2011), the mass
of exporters part was not explicitly derived by them.
Proposition:
20The equilibrium cutoff productivity levels can be derived using the zero-cutoff-profit conditions and thefree-entry conditions.
37
(a) The elasticity of the exporting cutoff with respect to tariffs for Home firms is:
∂ lnφX∂ ln τ
= ζφX ,τ > 1,
and the elasticity of the mass of Home exporters with respect to tariffs is:
∂ lnNX
∂ ln τ= ζNX ,τ < −κ.
(b) The elasticity of the exporting cutoff with respect to nominal exchange rates for Home
firms is:∂ lnφX∂ ln ε
= ζφX,ε < −(1 + µ),
and the elasticity of the mass of Home exporters with respect to nominal exchange rates is:
∂ lnNX
∂ ln ε= ζNX ,ε > κ(1 + µ).
Proof:
(a) ζφX ,τ > 1:
We obtain the elasticity of the exporting cutoff with respect to tariffs τ by taking log of (A.2)
and differentiating it with respect to τ :
ζφX ,τ = 1 + ζφ∗D,τ ,
where ζφ∗D,τ is the elasticity of the domestic cutoff level (φ∗D) with respect to τ for Foreign
firms.
We next show that ζφ∗D,τ > 0. By taking log of (A.3) and differentiating it with respect
to τ , we obtain
ζφ∗D,τ = −1 +1
1− 1
ττ∗κFκ−(ν−1)ν−1
> 0,
where the last inequality is because the second term is greater than 1.
Thus, ζφX ,τ = 1 + ζφ∗D,τ > 1.
ζNX ,τ < −κ:
Given the mass of Home firms at Foreign NX = (φmin/φX)κNP where NP is the pool of Home
38
firms, we have
ζNX ,τ = −κζφX ,τ + ζNp,τ .
Since
NP =κ− (ν − 1)
κ
1
νWφκmin
[(ττ ∗)κF
κ−(ν−1)ν−1
φκDI
fD− φκXεI
∗
fX
(ττ ∗)κFκ−(ν−1)ν−1 − 1
],
we have
ζNp,τ =1
(ττ ∗)κFκ−(ν−1)ν−1
φκDI
fD− φκXεI
∗
fX
[(ττ ∗)κF
κ−(ν−1)ν−1
φκDI
fDκ(1 + ζφD,τ )−
φκXεI∗
fXκζφX ,τ
]
− κ(ττ ∗)κFκ−(ν−1)ν−1
(ττ ∗)κFκ−(ν−1)ν−1 − 1
.
Since
ζφD,τ = ζφX ,τ −τκF
κ−(ν−1)ν−1
τκFκ−(ν−1)ν−1 − (ρε)
κνν−1 (
f∗XfD
)κ−(ν−1)ν−1
,
we have
ζφD,τ + 1 = ζφX ,τ −τκF
κ−(ν−1)ν−1
τκFκ−(ν−1)ν−1 − (ρε)
κνν−1 (
f∗XfD
)κ−(ν−1)ν−1
+ 1
< ζφX ,τ .
Thus,
(ττ ∗)κFκ−(ν−1)ν−1
φκDI
fDκ(1 + ζφD,τ )−
φκXεI∗
fXκζφX ,τ <
[(ττ ∗)κF
κ−(ν−1)ν−1
φκDI
fD− φκXεI
∗
fX
]κζφX ,τ
and
ζNp,τ < κζφX ,τ −κ(ττ ∗)κF
κ−(ν−1)ν−1
(ττ ∗)κFκ−(ν−1)ν−1 − 1
< κζφX ,τ − κ.
Thus,
ζNX ,τ = −κζφX ,τ + ζNp,τ
< −κ.
39
(b) ζφX ,ε < −(1 + µ):
We obtain the elasticity of the exporting cutoff with respect to nominal exchange rates ε by
taking log (A.2) and differentiating it with respect to ε:
ζφX,ε = ζφ∗D,ε −ν
ν − 1,
where ζφ∗D,ε is the elasticity of the domestic cutoff level (φ∗D) with respect to ε for Foreign
firms.
We have ν/(ν − 1) = 1 + µ, and it can be shown that ζφ∗D,ε < 0.
Thus, ζφX ,ε = ζφ∗D,ε −νν−1
< −(1 + µ).
ζNX ,ε > κ(1 + µ):
We have
ζNX ,ε = −κζφX ,ε + ζNp,ε.
Since ζφX ,ε < −(1 + µ), we have −κζφX ,ε > κ(1 + µ).
Since
ζNp,ε =1
(ττ ∗)κFκ−(ν−1)ν−1
φκDI
fD− φκXεI
∗
fX
[(ττ ∗)κF
κ−(ν−1)ν−1
φκDI
fDκζφD,ε −
φκXεI∗
fX(κζφX ,ε + 1)
],
ζφD,ε > 0 and ζφX ,ε < −(1 + µ), we have ζNp,ε > 0.
Thus, ζNX ,ε > κ(1 + µ). �
Proposition (a) argues that a decrease in tariffs, charged by partners, causes a decrease
in the exporting cutoff and an increase in the mass of exporters (the EM of exports). In
particular, the mass of exporters increases by more than κ percent after a 1 percent reduction
in tariffs.
Proposition (b) argues that a decrease in nominal exchange rates—appreciation—causes
an increase in the exporting cutoff and a decrease in the mass of exporters. In particular,
the mass of exporters decreases by more than κ(1 + µ) percent after a 1 percent decrease in
nominal exchange rates (a 1 percent Home-currency appreciation). With the appreciation of
the Home currency and fixed wages, the relative cost of Home to Foreign labor—W/εW ∗—
increases and thus Home firms become less competitive in the Foreign market.
Furthermore, as implied by Chaney’s (2008) model and our model, the elasticity of the
40
mass of exporters with respect to tariffs/nominal exchange rates can be affected by the
elasticity of substitution between varieties ν and thus the markup µ = 1/(ν − 1). The
intuition is that, for the same percent change in tariffs or nominal exchange rates, if the
elasticity of substitution (ν) is lower, that is, if the markup (µ) is higher, then a change in
profits is larger. It leads to a larger change in the exporting cutoff and thus a larger change
in the mass of exporters. Thus, in the more differentiated sector, the elasticity of the mass
of exporters with respect to tariffs/nominal exchange rates can be larger.
A.2 Nominal and Real Exchange Rates
Figure A1 demonstrates the relationship between nominal and real exchange rates for China’s
selected trade partners from 2000/01 to 2006/12. Notably, due to data constraints, to cal-
culate the real exchange rates for the euro area we use producer prices for the euro area’s
CPI.
41
Figure A1: Nominal and Real Exchange Rates for Selected Trade Partners
7.8
88.
28.
48.
68.
8Yu
an/U
SD
2000 2001 2002 2003 2004 2005 2006Year
NER RER
United States
78
910
1112
Yuan
/Eur
o
2000 2001 2002 2003 2004 2005 2006Year
NER RER
Euro Area
.06
.07
.08
.09
.1Yu
an/Y
en
2000 2001 2002 2003 2004 2005 2006Year
NER RER
Japan
.006
.006
5.0
07.0
075
.008
.008
5Yu
an/W
on
2000 2001 2002 2003 2004 2005 2006Year
NER RER
South Korea
1213
1415
16Yu
an/P
ound
2000 2001 2002 2003 2004 2005 2006Year
NER RER
United Kingdoms
.24
.26
.28
.3.3
2Yu
an/T
WD
2000 2001 2002 2003 2004 2005 2006Year
NER RER
Taiwan
56
78
Yuan
/CAD
2000 2001 2002 2003 2004 2005 2006Year
NER RER
Canada
44.
55
5.5
66.
5Yu
an/A
UD
2000 2001 2002 2003 2004 2005 2006Year
NER RER
Australia
2.1
2.15
2.2
2.25
2.3
Yuan
/MYR
2000 2001 2002 2003 2004 2005 2006Year
NER RER
Malaysia
.12
.14
.16
.18
.2Yu
an/IN
R
2000 2001 2002 2003 2004 2005 2006Year
NER RER
India
.000
4.0
006
.000
8.0
01.0
012
Yuan
/IDR
2000 2001 2002 2003 2004 2005 2006Year
NER RER
Indonesia
.17
.18
.19
.2.2
1.2
2Yu
an/T
HB
2000 2001 2002 2003 2004 2005 2006Year
NER RER
Thailand
.65
.7.7
5.8
.85
.9Yu
an/M
XN
2000 2001 2002 2003 2004 2005 2006Year
NER RER
Mexico
12
34
5Yu
an/B
RL
2000 2001 2002 2003 2004 2005 2006Year
NER RER
Brazil
Note: A decrease (increase) in nominal/real exchange rates means China’s appreciation (depreciation).
Source: IMF.
42
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