Does Yuan Appreciation Weaken the Increase in Exporters due to Trade Liberalization? Evidence from Chinese Firm-Product Data

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1 Does Yuan Appreciation Weaken the Increase in Exporters due to Trade Liberalization? Evidence from Chinese Firm-Product Data Zhe Chen Yoshinori Kurokawa February 5, 2018 Abstract Using Chinese firm-product data from to, this paper empirically tests whether the appreciation (depreciation) of China s yuan weakens (strengthens) the effect of trade liberalization on the extensive margin of China s exports to 170 countries. Based on regressions, we have four main empirical findings. First, reductions in tariffs, charged by China s trade partners, increased China s exporter numbers and export value/quantity per exporter at the product level, whereas the appreciation (depreciation) of China s yuan caused a decrease (increase) the effect of exchange rates is larger than that of tariffs in all cases. Second, reductions in tariffs, charged by trade partners, increased the entry and exit of China s exporters, and yuan appreciation (depreciation) decreased (increased) them. Third, the effects of tariffs and exchange rates are significantly d- ifferent between processing and ordinary trade firms. Fourth, the significance of the effects is greater if the export destinations are non-oecd countries. JEL classification: F12, F14, F31 Keywords: Melitz model, exchange rates, tariffs, extensive margin, exports, China We are very grateful to Gian Luca Clementi, Chang Hong, Sewon Hur, Isao Kamata, Tim Kehoe, Bernabe Lopez-Martin, Ferdinando Monte, Peter Morrow, Siqiang Yang, and Yuan Yuan for their useful comments and suggestions. We also thank the participants at the Fall 2017 Midwest Macroeconomics Meetings and the Fall 2017 Midwest International Trade Conference. School of International Trade and Economics, University of International Business and Economics Boxue Building, 10 Huixin Dongjie, Chaoyang District, Beijing , China. zhechen@uibe.edu.cn. Corresponding author. Faculty of Humanities and Social Sciences, University of Tsukuba Tennodai, Tsukuba, Ibaraki , Japan. kurokawa.yoshi.fw@u.tsukuba.ac.jp. 1

2 1 Introduction One of the most notable works in the recent history of international trade is the Melitz () model of heterogeneous firm trade. The model theoretically shows that a reduction in trade costs (i.e., a decrease in export price) decreases the export cutoff productivity level, increasing the number of exporters the extensive margin (EM) of exports. Rodríguez-López (2011) extends the discussion of the Melitz model to analyze the effect of nominal exchange rates. 1 The model with exchange rates theoretically shows that the appreciation of the home currency (i.e., an increase in export price in the foreign currency) makes home exporters less competitive in the foreign market, thus increasing the export cutoff productivity level and decreasing the number of home exporters the EM of home exports. By contrast, the depreciation of the home currency (i.e., a decrease in export price in the foreign currency) makes home exporters more competitive in the foreign market, thus decreasing the export cutoff productivity level and increasing the EM of home exports. 2 These two theoretical predictions by Melitz () and Rodríguez-López (2011) suggest that trade liberalization and nominal exchange rates can affect the EM of exports. Therefore, although it has been empirically documented that the EM increases after trade liberalization (e.g., Kehoe and Ruhl, 2013), the observed changes in EM after trade liberalization might have been results weakened or strengthened by changes in nominal exchange rates. 3 In other words, they might have been stronger or weaker without changes in nominal exchange rates. This possibility is crucial, particularly for empirical studies on trade liberalization and the EM because they might have under- or overestimated the pure effect of trade liberalization on the EM. To the best of our knowledge, however, no previous studies have empirically tested the aforementioned implications from the Melitz model. We now fill this void. Notably, as mentioned by Baggs et al. (2009), most empirical studies that have examined tariff changes/trade liberalization include exchange rates as a control variable; however, the analysis is at the industry level, not at the firm level. 1 As will be mentioned later, Bergin and Lin (2008) also examine the effect of exchange rates, in particular, exchange rate regimes on the EM of trade. 2 Rodríguez-López (2011) develops a sticky-wage model of heterogeneous firm trade with exchange rates and endogenous markups. 3 Feenstra (1989) theoretically argues that the effects of tariffs and exchange rates on the price of imports are symmetric and empirically tests whether their effects on U.S. prices of Japanese cars, trucks, and motorcycles are symmetric. 2

3 We use Chinese firm-product annual data from to to test whether the appreciation (depreciation) of China s yuan weakens (strengthens) the effect of trade liberalization on the EM of China s exports to 170 countries. The benchmark regression results suggest that reductions in tariffs charged by China s trade partners increased China s exporter numbers at the product level, whereas the appreciation (depreciation) of China s yuan decreased (increased) them. The results support the theoretical implication that an increase in the EM of exports because of trade liberalization can be weakened or strengthened by currency appreciation or depreciation, respectively. The regression results are similar for the export value and quantity per exporter the intensive margin (IM) of exports at the product level. In all cases, the impact of nominal exchange rates is larger than that of tariffs. When we investigate the effects on the entry and exit of China s exporters, the regression results suggest that reductions in tariffs, charged by its trade partners, increased the entry and exit of exporters and that yuan appreciation (depreciation) decreased (increased) them. This is because reductions in tariffs could encourage additional Chinese firms to enter. It 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 Chinese exporters increased following China s World Trade Organization (WTO) accession in. We also perform several robustness checks regarding trade modes (ordinary vs. processing trade), export destinations (OECD vs. non-oecd countries), real exchange rates, and high frequency data (quarterly). The benchmark results remain robust. Our study makes the following contributions to the literature on the EM of trade. One set of studies (e.g., Melitz, ) that focus on the effect of trade liberalization on the EM of trade, and another set of studies (e.g., Rodríguez-López, 2011 ; Bergin and Lin, 2008) that focus on the effect of exchange rates on the EM of trade. We focus on the effects of these two factors on the EM of trade; in particular, we use Chinese firm-product data to empirically investigate whether the effect of trade liberalization on the EM of China s exports is weakened (strengthened) by China s yuan appreciation (depreciation). Baggs et al. (2009) (BBF) also examine trade liberalization and exchange rates, but they empirically test, using Canadian industry-firm annual data, if tariffs and real (not nominal) exchange rates symmetrically affect Canadian firm survival/exit (not the EM of exports). Moreover, Fitzgerald and Hallerz (2017) (FH) empirically test if tariffs and 3

4 real exchange rates symmetrically affect Irish exporters using Irish firm-product annual data. FH are similar to BBF, in that both empirically test the equivalence between tariffs and real exchange rates. FH are also similar to our paper, in that both focus on the effects on exporters. Thus, FH are somewhere in between BBF and our paper. There are four major differences among our paper, BBF, and FH. First, BBF, and FH focus on real exchange rates, whereas our paper focuses on nominal exchange rates; however, we also perform robustness checks with real exchange rates. Second, BBF use industry-firm data, whereas our paper and FH use more detailed data, that is, firm-product data. Third, BBF, and FH, respectively, cover the United States and 30 countries as trade partners, whereas our paper covers 170 countries a much greater number. Fourth, all three studies present different results: the effect of exchange rates is larger than that of tariffs in China (our paper), whereas it is similar in Canada (BBF) and smaller in Ireland (FH). Therefore, these three papers are satisfactory complements. The rest of this paper is organized as follows. Section 2 documents the regression specification and data. Section 3 reports the regression results. Section 4 concludes. 2 Regression Specification and Data 2.1 Regression Specification Exporter Numbers and Export Value/Quantity per Exporter The Melitz model with exchange rates implies that an increase in the EM of exports caused by trade liberalization can be weakened or strengthened by currency appreciation or depreciation, respectively. Guided by this theoretical implication, we empirically investigate the impact of tariffs and nominal exchange rates on exporter numbers at the product level. The benchmark regression is as follows: ln(e ijt ) = α 0 + α 1 ln(t ariff ijt ) + α 2 ln( jt ) + Other Controls + ɛ ijt (2.1) Here, E ijt is the number of exporters of product i from China to country j at time t. T ariff ijt is the tariff of product i charged by country j at time t. jt is the nominal exchange rate, which is defined as China s yuan per currency of country j at time t; thus, when 4

5 increases, China s yuan depreciates. Because the reduction of China s import tariffs could decrease the costs of China s firms, thus helping more non-exporting firms enter foreign markets, we control China s import tariffs within the same industry (HS 2-digit level). 4 The trade mode may also affect exporters behaviors; thus, we control the processing trade dummy. 5 When the product is exported under the processing trade mode, the dummy is 1; otherwise, it is 0. Finally, we also control the product, country, and time fixed effects. If α 1 is negative and α 2 is positive, then the implication from the Melitz model is supported. When T arif f decreases, the EM of exports increases. When China s yuan appreciates (depreciates), the EM of exports decreases (increases), that is, the increase in EM of exports caused by tariff reductions is weakened or strengthened by currency appreciation or depreciation, respectively. We also empirically investigate the effect on export value/quantity per exporter the IM of exports at the product level. In that case, E ijt is the export value/quantity per exporter of product i from China to country j at time t Entry and Exit of Exporters In the previous section, we observe a change in exporter numbers caused by entry and exit. Thus, we also investigate the impacts of tariffs and nominal exchange rates on the entry and exit of exporters. The benchmark regression is as follows: ln(en ijt ) = β 0 + β 1 ln(t ariff ijt ) + β 2 ln( jt ) + Other Controls + η ijt (2.2) Here, EN ijt is the number of new (exit) exporters of product i from China to country j at time t. We also control China s import tariffs within the same industry (HS 2-digit level), the processing trade dummy, and the product, country, and time fixed effects. When EN is the number of new exporters, if β 1 is negative and β 2 is positive, then a decrease in T ariff causes additional Chinese firms to enter foreign markets, whereas China s yuan appreciation (depreciation) causes less (more) Chinese firms to enter. When EN is the number of exit exporters, if β 1 is positive and β 2 is negative, then a decrease in T ariff causes less of China s firms to quit foreign markets, whereas the appreciation (depreciation) of China s yuan causes 4 The input-output table is based on the industry level, while our regressions are at the firm-product level. Thus, we do not use the input-output table to obtain the import tariffs. 5 Processing trade refers to importing all or part of the raw and auxiliary materials and re-exporting the finished products after processing. 5

6 more (less) Chinese firms to quit. 2.2 Data The exchange rate and Consumer Price Index (CPI) data are from the International Monetary Fund at the annual level. 6 The tariff 7 data is from the United Nations Conference on Trade and Development Trade Analysis Information System (TRAINS). The import tariffs of each HS 6-digit level product for each country are at the annual level. China s export data is from their customs agency at the transaction level. We aggregate these transactions to the firm-product-year level. Thus, we have the number of exporters and export value/quantity per exporter for each HS 6-digit product. The sample period is from to. The data summary is presented in Table 1 and Figure 1. The first part of Table 1 demonstrates that the exporter and destination numbers increase over time. From to, the exporter numbers increase by 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. In, the simple average tariffs are 9.6 percent, and in the tariffs are 8.1 percent. In addition, the simple average tariffs of the OECD countries remain robust, and that of the non-oecd countries decrease by almost 30 percent from to. The third part of Table 1 shows that China s import tariffs also decrease from to. Especially, when China became a WTO member in, China s average import tariffs decrease by about 27 percent in that year. The last part of Table 1 and Figure 1 demonstrate the time trend of China s nominal effective exchange rates (NEERs). After entering the WTO in, the NEERs decrease until depreciation. On July 21,, the People s Bank of China announced a revaluation of the yuan and a reform of the exchange rate regime. After, the NEERs began to increase appreciation and do so until Notably, here, an increase (decrease) in the NEERs means China s yuan appreciation (depreciation), whereas an increase (decrease) in the independent variable N ER defined as China s yuan per a foreign currency means China s yuan depreciation (appreciation). 6 We also present the results with the quarterly data in the robustness checks. 7 The tariff is the effectively applied tariff (AHS) which is defined as the lowest available tariff. 6

7 2.3 and Exchange Rates In this section, we present more detailed data for tariffs and nominal exchange rates: the time trends of tariffs and nominal exchange rates for China s top 10 trade partners from to (Figures 2 and 3). The top 10 partners are the euro area, the United States, Hong Kong, Japan, South Korea, the United Kingdom, Singapore, Taiwan, Canada, and India. Here, the tariff data is at the annual level, and the exchange rate data is at the monthly level. The figures imply that tariffs and nominal exchange rates might be crucial factors that contribute to changes in the EM of China s exports. They also imply that the increase in EM because of tariff reductions might be weakened by currency appreciation or strengthened by currency depreciation. In the case of the euro area, for example, tariffs, charged by the euro area, decreased and the yuan depreciated from to, implying that the yuan s depreciation might have strengthened the increase in China s EM because of tariff reductions. In the case of Japan, the tariffs charged by Japan decreased and the yuan first appreciated and then depreciated during the period to, implying that the yuan s appreciation and depreciation, respectively, might have weakened and strengthened the increase in China s EM because of tariff reductions. 3 Regression Results 3.1 Exporter Numbers and Export Value/Quantity per Exporter The first part of Table 2 presents the EM effects of tariffs and the nominal exchange rates. According to the Melitz model, a reduction in tariffs charged by foreign countries would increase the number of China s exporters while the appreciation (depreciation) of China s yuan would decrease (increase) it. Our results verify this hypothesis. If the tariffs decrease by 1 percent, the exporter numbers would increase by percent. If China s yuan appreciates by 1 percent, the exporter numbers would decrease by percent. The effect of the nominal exchange rates is larger than that of the tariffs. 8 From to, the tariffs decreased 8 Although their primary interest is in estimating the effects of imported inputs on export values, Feng et al. (2016) also observe a similar pattern using China s data. They control real exchange rates and tariffs and observe that the former effect on export values is larger than the latter. 7

8 and China s yuan depreciated; thus, the two effects could stimulate the EM of exports. After, however, China s yuan began to appreciate, which could weaken the effect of tariffs reductions. The second and third parts of Table 2 demonstrate that the reductions in tariffs, charged by foreign countries, stimulate the IM of exports from China and the appreciation (depreciation) of China s yuan would weaken (strengthen) this effect. If the tariffs decrease by 1 percent, the export value per exporter would increase by percent. Although the impact of tariff reduction is significant, the size is small. By contrast, the impact of the exchange rate fluctuations on the export value per exporter is larger. If China s yuan appreciates by 1 percent, the export value per exporter would decrease by percent. The effects are similar for export quantity per exporter. If the tariffs decrease by 1 percent, the export quantity per exporter would increase by percent. If China s yuan appreciates by 1 percent, the export quantity per exporter would decrease by percent. 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. In column 2, we additionally control the import tariffs charged by China. The effects of tariff reductions and exchange rate fluctuations remain robust. We also observe that the import tariff reductions stimulate exports from China, at both the IM and EM. The reductions of import tariffs could decrease the input costs of China s firms, which improves their competitiveness in foreign markets. In sum, from to, the reductions of tariffs charged by partners, China s yuan depreciation, and China s import tariff reductions could all stimulate China s exports, at both the IM and EM. However, after, China s yuan appreciation could weaken the benefits from trade liberalization. 3.2 Entry and Exit of Exporters In this section, we investigate the exporter dynamics in greater detail. Exporter numbers depend on the entry and exit of exporters. The tariffs and nominal exchange rates might have heterogeneous effects on exporters entry and exit decisions. Thus, we separately examine the impacts. Column 1 of Table 3 shows that the reductions in tariffs, charged by foreign countries, increase the entry and exit of exporters. If the tariffs decrease by 1 percent, the new exporter numbers would increase by percent and exit exporter numbers would 8

9 increase by percent. The effect on entry is larger than that of exit. Thus, the overall effect of tariff reduction is to increase the exporter numbers. At first sight, the results for exit might appear odd. As Feng et al. (2017) argue, however, it is possible 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. The effect of exchange rate fluctuation is similar but larger. If China s yuan depreciates by 1 percent, new exporter numbers would increase by percent and exit exporter numbers also would increase by percent. In column 2, we additionally control China s import tariffs, and the aforementioned pattern remains robust. 3.3 Robustness Checks In this section, we examine whether trade modes, export destinations, real exchange rates, and data frequency would affect the benchmark results. Trade Modes: Processing trade refers to the activity of importing all or part of the raw and auxiliary materials from abroad and re-exporting the finished products after processing or assembly by firms within the mainland. 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 effect of exchange rate fluctuations on processing trade is likely to be different from that on ordinary trade. Marquez and Schindler (2007) argue that estimating exchange rate effects should differentiate the ordinary and processing trade products. We thus divide firms into two groups: ordinary and processing trade firms. The columns 3 and 4 of Table 2 show that the effects on exporter numbers and export value/quantity per exporter of tariffs and nominal exchange rates are larger for processing trade firms. However, the columns 3 and 4 of Table 3 show that effects on entry and exit are smaller for processing trade firms. Export Destinations: After China became a WTO member in, the tariffs charged by foreign countries, especially developing countries, decreased considerably; for example, the comparison among India and developed countries (Figures 2 and 3). Thus, we divide the export destinations into two groups: OECD and non-oecd countries. Columns 5 and 6 in 9

10 Tables 2 and 3 demonstrate that the effects are more significant for non-oecd countries. Real Exchange Rates: The nominal and real exchange rates present very different movements in the United States from - (Figure A1 in Appendix A.1). Motivated by this observation, we perform robustness checks with the real exchange rates. Tables 4 and 5 present the results with the real exchange rates. Notably, the results remain robust. Although our main focus is on nominal exchange rates, we want to emphasize that the effect of real exchange rates is larger than that of tariffs in China, whereas it is similar in Canada (Baggs et al., 2009) and smaller in Ireland (Fitzgerald and Hallerz, 2017). 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. Tables 6 and 7 demonstrate that the results remain robust. Notably, however, the effects of the quarterly data are smaller than that of the annual data. This is probably because firms take time to react to the tariff and exchange rate changes. 4 Conclusion We have empirically tested the implications from the Melitz model with the exchange rates. Specifically, using China s firm-product data from to with 170 trade partners, we tested whether the effect of trade liberalization on the EM of China s exports is weakened (strengthened) by China s yuan appreciation (depreciation). Based on regressions, we have four main empirical findings. First, reductions in tariffs, charged by China s trade partners, increased China s exporter numbers and export value/quantity per exporter at the product level, whereas the appreciation (depreciation) of China s yuan decreased (increased) them the latter effect is larger than the former in all cases. Second, reductions in tariffs, charged by trade partners, increased the entry and exit of China s exporters, and the yuan s appreciation (depreciation) decreased (increased) them. Third, the effects of tariffs and exchange rates are significantly different between processing and ordinary trade firms. Fourth, the effects are more significant if export destinations are non-oecd countries. The results presented in this paper are valuable, particularly for empirical studies on trade liberalization and the EM of trade. Because the results indicate that the observed increases 10

11 in EM after trade liberalization could be the results weakened by currency appreciation or strengthened by currency depreciation, past studies might have under- or overestimated the pure effect of trade liberalization on the EM. Thus, future studies must more carefully control exchange rates when investigating the changes in EM using firm data. Finally, our empirical results demonstrate that the effect of exchange rates is larger than that of tariffs, which might, however, appear to be inconsistent with the argument that a tariff change is permanent, whereas an exchange rate change is temporary (e.g., Ruhl, 2008). Thus, this phenomenon poses a challenge to theorists developing models to explain why the effect of exchange rates on China s exporters is larger than that of tariffs; for example, one possible direction is highlighting the effect of exchange rates on export fixed costs. The Melitz () model with exchange rates implies that with fixed wages the depreciation of the home currency decreases the relative export fixed costs of home to foreign exporters, thereby making home exporters more competitive in the foreign market. This change in the relative export fixed costs, even if not permanent, could have a large impact on exporter s behavior. We leave this direction of research to future work. 11

12 References Baggs, Jen, Eugene Beaulieu, and Loretta Fung (2009) Firm survival, performance, and the exchange rate. Canadian Journal of Economics 42(2), Bergin, Paul R., and Ching-Yi Lin (2008) Exchange rate regimes and the extensive margin of trade. NBER Working Paper Feenstra, Robert C. (1989) Symmetric pass-through of tariffs and exchange rates under imperfect competition: An empirical test. Journal of International Economics 27(1), Feng, Ling, Zhiyuan Li, and Deborah L. Swenson (2016) The connection between imported intermediate inputs and exports: Evidence from Chinese firms. Journal of International Economics 101(1), (2017) Trade policy uncertainty and exports: Evidence from China s WTO accession. Journal of International Economics 106(1), Fitzgerald, Doireann, and Stefanie Hallerz (2017) Exporters and shocks. Federal Reserve Bank of Minneapolis Staff Report 549 Kehoe, Timothy, and Kim Ruhl (2013) How important is the new goods margin in international trade? Journal of Political Economy 121(2), Marquez, Jaime, and John Schindler (2007) Exchange-rate effects on China s trade. Review of International Economics 15(5), Melitz, Marc J. () The impact of trade on aggregate industry productivity and intraindustry reallocation. Econometrica 71(6), Naknoi, Kanda (2015) Exchange rate volatility and fluctuations in the extensive margin of trade. Journal of Economic Dynamics & Control 52, Rodríguez-López, José A. (2011) Prices and exchange rates: A theory of disconnect. Review of Economic Studies 78,

13 Ruhl, Kim (2008) The international elasticity puzzle. Working Paper, University of Texas at Austin 13

14 Table 1: Data Summary Year Variables Exporter, Product, and Destination Exporter Numbers 59,709 65,505 74,882 90, , , ,923 Product Numbers 4,789 4,809 4,778 4,816 4,853 4,879 4,894 Destination Numbers Charged by Partners All Countries (mean) (sd) OECD Countries (mean) (sd) Non-OECD Countries (mean) (sd) China s Import (mean) (sd) China s Nominal Effective Exchange Rate

15 Table 2: Nominal Exchange Rates,, and Exports (Annual) Full Sample Ordinary Trade Processing Trade OECD Non-OECD ln(exporter Numbers) ln(tariff) *** *** *** *** *** (0.0138) (0.0138) (0.0136) (0.0180) (0.0250) (0.0161) ln() *** *** *** 0.135*** *** (0.0269) (0.0268) (0.0310) (0.0261) (0.115) (0.0376) Processing Trade *** *** *** *** (0.0315) (0.0315) (0.0432) (0.0462) ln(china s Import Tariff) *** *** *** *** *** ( ) ( ) (0.0149) ( ) (0.0103) Observations 1,464,519 1,464,519 1,068, , , ,793 R-squared ln(export Value per Exporter) ln(tariff) *** *** ** *** (0.0125) (0.0125) (0.0110) (0.0220) (0.0211) (0.0172) ln() ** ** *** ** (0.0350) (0.0349) (0.0366) (0.0493) (0.0686) (0.0426) Processing Trade 0.603*** 0.603*** 0.666*** 0.442*** (0.0586) (0.0586) (0.0848) (0.0622) ln(china s Import Tariff) *** *** *** *** *** (0.0128) (0.0125) (0.0264) (0.0159) (0.0218) Observations 1,464,518 1,464,518 1,068, , , ,793 R-squared ln(export Quantity per Exporter) ln(tariff) *** *** ** *** * (0.0145) (0.0145) (0.0126) (0.0225) (0.0247) (0.0172) ln() ** ** *** * (0.0329) (0.0329) (0.0330) (0.0545) (0.0830) (0.0410) Processing Trade 0.455*** 0.455*** 0.548*** 0.263*** (0.0529) (0.0529) (0.0704) (0.0520) ln(china s Import Tariff) *** *** *** *** (0.0143) (0.0135) (0.0290) (0.0155) (0.0218) Observations 1,462,916 1,462,916 1,067, , , ,169 R-squared Product FE Yes Yes Yes Yes Yes Yes Country FE Yes Yes Yes Yes Yes Yes Time FE Yes Yes Yes Yes Yes Yes Cluster by Country Yes Yes Yes Yes Yes Yes Notes: (1) Since the tariffs charged by Hong Kong are zero, we exclude Hong Kong from the sample. (2) *** p < 0.01, ** p < 0.05, * p <

16 Table 3: Nominal Exchange Rates,, and Exporter Dynamics (Annual) Full Sample Ordinary Trade Processing Trade OECD Non-OECD ln(new Exporter Numbers) ln(tariff) *** *** *** ** (0.0105) (0.0105) (0.0107) (0.0140) (0.0206) (0.0118) ln() ** ** *** *** *** (0.0213) (0.0213) (0.0264) (0.0233) (0.128) (0.0237) Processing Trade *** *** *** *** (0.0340) (0.0340) (0.0471) (0.0462) ln(china s Import Tariff) *** *** *** *** ( ) ( ) (0.0112) ( ) ( ) Observations 1,313,190 1,313, , , , ,591 R-squared ln(exit Exporter Numbers) ln(tariff) * * ** e (0.0119) (0.0119) (0.0118) (0.0163) (0.0221) (0.0140) ln() *** *** 0.125*** *** *** (0.0255) (0.0254) (0.0290) (0.0207) (0.0758) (0.0299) Processing Trade *** *** *** *** (0.0347) (0.0347) (0.0472) (0.0490) ln(china s Import Tariff) *** *** *** *** ( ) ( ) ( ) ( ) ( ) Observations 1,079,900 1,079, , , , ,607 R-squared Product FE Yes Yes Yes Yes Yes Yes Country FE Yes Yes Yes Yes Yes Yes Time FE Yes Yes Yes Yes Yes Yes Cluster by Country Yes Yes Yes Yes Yes Yes Notes: (1) Since the tariffs charged by Hong Kong are zero, we exclude Hong Kong from the sample. (2) *** p < 0.01, ** p < 0.05, * p <

17 Table 4: Real Exchange Rates,, and Exports (Annual) Full Sample Ordinary Trade Processing Trade OECD Non-OECD ln(exporter Numbers) ln(tariff) *** *** *** *** *** (0.0143) (0.0143) (0.0142) (0.0185) (0.0262) (0.0168) ln() 0.181*** 0.181*** 0.180*** 0.230*** 0.295** 0.167** (0.0565) (0.0564) (0.0665) (0.0432) (0.117) (0.0751) Processing Trade *** *** *** *** (0.0324) (0.0324) (0.0441) (0.0479) ln(china s Import Tariff) *** *** *** *** *** ( ) ( ) (0.0152) ( ) (0.0110) Observations 1,400,260 1,400,260 1,018, , , ,749 R-squared ln(export Value per Exporter) ln(tariff) *** *** * *** (0.0130) (0.0130) (0.0115) (0.0227) (0.0218) (0.0181) ln() 0.129** 0.130** 0.104* 0.301*** ** (0.0529) (0.0531) (0.0590) (0.0694) (0.0820) (0.0641) Processing Trade 0.622*** 0.622*** 0.682*** 0.459*** (0.0588) (0.0588) (0.0840) (0.0635) ln(china s Import Tariff) *** *** *** *** ** (0.0133) (0.0130) (0.0270) (0.0161) (0.0226) Observations 1,400,259 1,400,259 1,018, , , ,749 R-squared ln(export Quantity per Exporter) ln(tariff) *** *** ** *** (0.0150) (0.0150) (0.0132) (0.0233) (0.0258) (0.0178) ln() 0.138*** 0.138*** 0.107* 0.329*** ** (0.0504) (0.0505) (0.0558) (0.0761) (0.114) (0.0573) Processing Trade 0.474*** 0.474*** 0.564*** 0.277*** (0.0528) (0.0528) (0.0688) (0.0532) ln(china s Import Tariff) ** *** *** *** (0.0148) (0.0139) (0.0297) (0.0157) (0.0226) Observations 1,398,707 1,398,707 1,017, , , ,164 R-squared Product FE Yes Yes Yes Yes Yes Yes Country FE Yes Yes Yes Yes Yes Yes Time FE Yes Yes Yes Yes Yes Yes Cluster by Country Yes Yes Yes Yes Yes Yes Notes: (1) Since the tariffs charged by Hong Kong are zero, we exclude Hong Kong from the sample. (2) *** p < 0.01, ** p < 0.05, * p <

18 Table 5: Real Exchange Rates,, and Exporter Dynamics (Annual) Full Sample Ordinary Trade Processing Trade OECD Non-OECD ln(new Exporter Numbers) ln(tariff) *** *** *** * ** (0.0109) (0.0109) (0.0111) (0.0143) (0.0215) (0.0123) ln() 0.151*** 0.151*** 0.156** 0.150*** 0.271** 0.126** (0.0539) (0.0539) (0.0618) (0.0403) (0.122) (0.0563) Processing Trade *** *** *** *** (0.0350) (0.0350) (0.0484) (0.0478) ln(china s Import Tariff) *** *** *** *** ( ) ( ) (0.0113) ( ) ( ) Observations 1,255,604 1,255, , , , ,105 R-squared ln(exit Exporter Numbers) ln(tariff) * * ** * (0.0122) (0.0122) (0.0123) (0.0166) (0.0229) (0.0146) ln() ** ** 0.111** ** * (0.0397) (0.0397) (0.0492) (0.0328) (0.0894) (0.0462) Processing Trade *** *** *** *** (0.0356) (0.0356) (0.0485) (0.0503) ln(china s Import Tariff) *** *** *** *** ( ) ( ) (0.0103) ( ) ( ) Observations 1,038,351 1,038, , , , ,407 R-squared Product FE Yes Yes Yes Yes Yes Yes Country FE Yes Yes Yes Yes Yes Yes Time FE Yes Yes Yes Yes Yes Yes Cluster by Country Yes Yes Yes Yes Yes Yes Notes: (1) Since the tariffs charged by Hong Kong are zero, we exclude Hong Kong from the sample. (2) *** p < 0.01, ** p < 0.05, * p <

19 Table 6: Nominal Exchange Rates,, and Exports (Quarterly) Full Sample Ordinary Trade Processing Trade OECD Non-OECD ln(exporter Numbers) ln(tariff) *** *** *** ** ** (0.0132) (0.0132) (0.0127) (0.0197) (0.0241) (0.0145) ln() *** *** 0.101*** 0.117*** *** (0.0220) (0.0219) (0.0279) (0.0201) (0.0791) (0.0325) Processing Trade *** *** *** *** (0.0271) (0.0271) (0.0378) (0.0407) ln(china s Import Tariff) *** *** *** *** *** ( ) ( ) (0.0148) ( ) ( ) Observations 4,116,652 4,116,652 3,033,655 1,082,827 2,100,039 2,016,485 R-squared ln(export Value per Exporter) ln(tariff) *** *** *** (0.0117) (0.0117) ( ) (0.0211) (0.0187) (0.0165) ln() * * *** *** (0.0301) (0.0301) (0.0326) (0.0386) (0.0481) (0.0364) Processing Trade 0.574*** 0.574*** 0.603*** 0.451*** (0.0583) (0.0583) (0.0807) (0.0640) ln(china s Import Tariff) *** *** *** *** * (0.0115) (0.0108) (0.0230) (0.0131) (0.0218) Observations 4,116,651 4,116,651 3,033,654 1,082,827 2,100,038 2,016,485 R-squared ln(export Quantity per Exporter) ln(tariff) *** *** * *** * (0.0139) (0.0139) (0.0118) (0.0217) (0.0231) (0.0161) ln() *** ** (0.0294) (0.0294) (0.0300) (0.0452) (0.0701) (0.0379) Processing Trade 0.445*** 0.445*** 0.504*** 0.284*** (0.0509) (0.0509) (0.0639) (0.0526) ln(china s Import Tariff) *** *** *** (0.0128) (0.0121) (0.0256) (0.0136) (0.0221) Observations 4,111,533 4,111,533 3,030,198 1,081,165 2,096,888 2,014,517 R-squared Product FE Yes Yes Yes Yes Yes Yes Country FE Yes Yes Yes Yes Yes Yes Time FE Yes Yes Yes Yes Yes Yes Cluster by Country Yes Yes Yes Yes Yes Yes Notes: (1) Since the tariffs charged by Hong Kong are zero, we exclude Hong Kong from the sample. (2) *** p < 0.01, ** p < 0.05, * p <

20 Table 7: Nominal Exchange Rates,, and Exporter Dynamics (Quarterly) Full Sample Ordinary Trade Processing Trade OECD Non-OECD ln(new Exporter Numbers) ln(tariff) ** ** *** * ( ) ( ) ( ) (0.0143) (0.0165) ( ) ln() *** *** *** *** *** (0.0155) (0.0155) (0.0209) (0.0127) (0.0547) (0.0185) Processing Trade *** *** *** *** (0.0302) (0.0302) (0.0417) (0.0377) ln(china s Import Tariff) ** *** *** *** ( ) ( ) ( ) ( ) ( ) Observations 4,116,652 4,116,652 3,033,655 1,082,827 2,100,039 2,016,485 R-squared ln(exit Exporter Numbers) ln(tariff) ** (0.0107) (0.0107) ( ) (0.0175) (0.0194) (0.0114) ln() *** *** *** *** *** (0.0167) (0.0167) (0.0186) (0.0160) (0.0359) (0.0209) Processing Trade *** *** *** *** (0.0320) (0.0320) (0.0430) (0.0416) ln(china s Import Tariff) *** *** *** *** ( ) ( ) ( ) ( ) ( ) Observations 3,084,725 3,084,725 2,234, ,858 1,694,961 1,389,610 R-squared Product FE Yes Yes Yes Yes Yes Yes Country FE Yes Yes Yes Yes Yes Yes Time FE Yes Yes Yes Yes Yes Yes Cluster by Country Yes Yes Yes Yes Yes Yes Notes: (1) Since the tariffs charged by Hong Kong are zero, we exclude Hong Kong from the sample. (2) *** p < 0.01, ** p < 0.05, * p <

21 NEER Figure 1: Nominal Effective Exchange Rates 130 China's NEER Note: An increase (decrease) in nominal effective exchange rates means China s yuan appreciation (depreciation). 21

22 Figure 2: and Nominal Exchange Rates by Euro Area and Yuan/Euro by USA and Yuan/USD by HKG and Yuan/HKD 5.5 by JPN and Yuan/Yen by KOR and Yuan/Won by GBR and Yuan/Pound Note: A decrease (increase) in nominal exchange rates means China s yuan appreciation (depreciation). 22

23 Figure 3: and Nominal Exchange Rates (Continued) by SGP and Yuan/SGD by TWN and Yuan/TWD by CAN and Yuan/CAD by IND and Yuan/INR Note: A decrease (increase) in nominal exchange rates means China s yuan appreciation (depreciation). 23

24 A Appendix A.1 Nominal and Real Exchange Rates Figures A1-A2 demonstrate the relationship between nominal and real exchange rates for China s top 10 trade partners from /01 to /12. Notably, due to data constraints, to calculate the real exchange rates for the euro area we use producer prices for the euro area s CPI. 24

25 Figure A1: Nominal and Real Exchange Rates China and Euro Area: (Yuan/Euro) and 12 China and USA: (Yuan/USD) and China and HKG: (Yuan/HKD) and 1.08 China and JPN: (Yuan/Yen) and China and KOR: (Yuan/Won) and China and GBR: (Yuan/Pound) and Note: A decrease (increase) in nominal/real exchange rates means China s appreciation (depreciation). 25

26 Figure A2: Nominal and Real Exchange Rates (Continued) China and SGP: (Yuan/SGD) and China and TWN: (Yuan/TWD) and China and CAN: (Yuan/CAD) and China and IND: (Yuan/INR) and Note: A decrease (increase) in nominal/real exchange rates means China s appreciation (depreciation). 26