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Accepted Manuscript Exchange rate volatility and trade: The role of credit constraints Shu Lin, Kang Shi, Haichun Ye PII: DOI: Reference: S1094-2025(18)30186-8 https://doi.org/10.1016/j.red.2018.05.002 YREDY 871 To appear in: Review of Economic Dynamics Received date: Revised date: 16 August 2016 25 April 2018 Please cite this article in press as: Lin, S., et al Exchange rate volatility and trade: The role of credit constraints Review of Economic Dynamics (2018), https://doi.org/10.1016/j.red.2018.05.002 This is a PDF file of an unedited manuscript that has been accepted for publication As a service to our customers we are providing this early version of the manuscript The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain Highlights • The role of credit constraints play an important role in determining the trade effect of exchange rate volatility • A theoretical model is developed to show how constrained firms and unconstrained firms respond to the changes of exchange rate volatility • Financially more constrained sectors have a more negative exposure of their trade volumes to exchange rate volatility both theoretically and empirically • The estimated trade effects of exchange rate volatility vary substantially across sectors Exchange rate volatility and trade: The role of credit constraints Shu Lin Chinese University of Hong Kong Kang Shi* Chinese University of Hong Kong Haichun Ye Hong Kong Monetary Authority Abstract This study examines the role of credit constraints in determining the trade effect of exchange rate volatility We first develop a small open economy general equilibrium model with credit constraints In our model, constrained firms respond to real depreciations and appreciations in an asymmetric way, and exchange rate volatility reduces their exports on average The effect of exchange rate volatility on unconstrained firms' exports, however, is ambiguous Overall, exchange rate volatility has a more negative impact on constrained firms In a large sector-level bilateral trade dataset, we find robust empirical evidence supporting the predictions of the model We show that financially more constrained sectors have a more negative exposure of their trade volumes to exchange rate volatility Moreover, the estimated trade effects of exchange rate volatility vary substantially across sectors and can be either positive or negative depending on the degree of credit constraints Keywords: exchange rate volatility; trade; credit constraints; sectoral heterogeneity JEL classification: F14, F31, G20 Acknowledgements: The authors would like to thank Editor Matthias Doepke, an associate editor, and two anonymous referees for valuable comments Any views expressed are those of the authors only and should not be attributed to Hong Kong Monetary Authority *Corresponding author Address: Department of Economics, Chinese University of Hong Kong, ELB931, Shatin, N.T., Hong Kong Email: kangshi@cuhk.edu.hk Phone: (852)93272680 Introduction The effect of exchange rate volatility on trade is not only an important academic research topic but also a question of high policy relevance The supposedly beneficial effect on trade flows of limiting exchange rate volatility has been one of the major pro-arguments for currency unions or other types of fixed exchange rate arrangements Numerous studies have empirically examined this issue Early empirical work in the literature (e.g., Hooper and Kohlhagen, 1978; Cushman, 1983; IMF, 1984) often study a small set of rich countries and report no consistent trade effects of exchange rate volatility More recent studies typically apply a gravity model approach to large bilateral trade data to estimate the effect of real exchange rate volatility (e.g., Frankel and Wei, 1993; Dell’Ariccia, 1999; Wei, 1999; Rose, 2000; IMF, 2004) Some studies in this group find a statistically significant but quantitatively small negative effect, but others argue that even this small negative effect is not robust.1 Another group of studies in this literature focus on the unpredictable variation in the real exchange rate and employ ARCH/GARCH type of time-series methods to examine the effects of real exchange rate uncertainty on trade (e.g Baum et al., 2004; Grier and Smallwood, 2007) The results obtained in these studies are also mixed.2 To sum up, despite many efforts, the existing empirical evidence on the trade effect of exchange rate volatility still remains inconclusive, a common conclusion drawn in two comprehensive surveys of the literature, McKenzie (1999) and IMF (2004) For example, in their 2004 study, a group of IMF researchers led by Peter Clark and Shang-Jin Wei reach the following conclusion, See McKenzie (1999) and IMF (2004) for detailed survey of this large literature For example, Grier and Smallwood (2007) show that exchange rate uncertainty has no effect in developed countries but a significantly negative effect in of the emerging countries in their sample " Overall, if exchange rate volatility has a negative effect on trade, this effect would appear to be fairly small and is by no means a robust, universal finding." (IMF 2004, p.6) The mixed empirical findings perhaps should not be surprising as it merely reflects the fact that there are no clear-cut theoretical predictions on the effect of exchange rate volatility on aggregate (bilateral) trade flows Under different assumptions, partial equilibrium models can generate either a negative or a positive effect For example, Clark (1973) and Hooper and Kohlhagen (1978) focus on the role of risk aversion and show that an increase in exchange rate variations causes fluctuations in firms' profits and results in a drop in trade volumes if firms are highly risk averse On the other hand, Pindyck (1982) and Canzoneri et al (1984) consider adjustment costs and show that, given an increase in exchange rate variability, a risk-averse firm may increase output if it is able to adjust factor inputs, and the expected profitability from this adjustment outweighs the aversion to the increased risk More recently, in a general equilibrium framework, Bacchetta and van Wincoop (2000) show that there is no clear relationship between exchange rate volatility and trade either In this study, we argue that a weak and inconclusive average effect of exchange rate volatility on aggregate (bilateral) trade volumes masks a large sectoral heterogeneity More specifically, we combine the exchange rate volatility literature and the recently-emerged credit constraints and trade literature (e.g., Amiti and Weinstein, 2008; Cheney, 2005; Chor and Manova, 2012; Manova, 2013; Manova, Wei, and Zhang, 2015; Minetti and Zhu, 2010) and show both theoretically and empirically that financially more vulnerable sectors have a more negative exposure of their trade volumes to exchange rate volatility Quantitatively, exchange rate volatility has an effect on trade that is negative in some sectors but positive in other sectors depending on the financial vulnerability of the sector We first present a simple small open economy general equilibrium model to examine the role of credit constraints in determining the trade effects of exchange rate volatility In our simple model, households consume, invest, supply labor, and hold foreign assets while firms in non-traded and traded goods sectors produce goods and sell them to domestic and foreign markets, respectively To investigate how credit constraints affect the trade effect of exchange rate volatility, we assume that a fraction of firms in the traded goods sector are subject to credit constraints In an open economy, a real appreciation reduces firms' exports while a real depreciation increases firms' exports Without credit constraints or firm heterogeneity, firms respond to depreciations and appreciations symmetrically Hence, on average, it is difficult to find a clear relationship between exchange rate volatility and trade as these responses cancel each other out However, if credit constraints and firm heterogeneity are considered, the trade effects of exchange rate volatility will be different for constrained and unconstrained firms Constrained firms are directly affected by their own credit constraints When the real exchange rate appreciates, constrained firms reduce exports as the demand for domestic tradable goods declines; however, when the real exchange rate depreciates, constrained firms are not able to increase exports fully since their capacity is limited by credit constraints This implies that appreciations and depreciations will affect constrained firms in an asymmetric way Due to the asymmetric responses, constrained firms' exports decline with exchange rate volatility The effect of exchange rate volatility on unconstrained firms, however, is ambiguous While unconstrained firms are not directly subject to credit constraints, they are indirectly affected in a general equilibrium setting Compared with constrained firms, unconstrained firms can expand or shrink freely in face of exchange rate changes When the real exchange rate depreciates, due to the expenditure switching effect, the demand for domestically produced traded-goods increases Consequently, the export of unconstrained firms will increase Meanwhile, since constrained firms cannot expand fully, unconstrained firms will also benefit from the substitution between goods produced by constrained and unconstrained firms However, when the real exchange rate appreciates, both constrained and unconstrained firms are hurt, and unconstrained firms cannot benefit more from their advantage in credit market Hence, the trade effect of exchange rate volatility on unconstrained firms is ambiguous Overall, our model predicts that exchange rate volatility hurts constrained firms more, and the effect on unconstrained firms’ (and total) exports depends on some key parameters, including the degree of credit constraints, the share of unconstrained firms in the traded goods sector, and the substitutability of goods produced by constrained and unconstrained firms This ambiguity thus can help explain why previous empirical work often finds a small and insignificant effect on aggregate (bilateral) trade We then provide empirical evidence to support the predictions of the model Using a large disaggregate sector-level bilateral trade data of 132 countries for the years 1970-2000 and an augmented gravity model estimation strategy suggested by Anderson and van Wincoop (2003), we find that the estimated interaction effect of exchange rate volatility and sector level financial vulnerability is negative and highly significant Quantitatively, the estimated trade effects of exchange rate volatility vary substantially across sectors and can be either positive or negative depending on the degree of credit constraints The implied overall effect on total bilateral trade is thus ambiguous, which is consistent with the weak effect on aggregate (bilateral) trade documented in previous studies Our empirical results are robust to alternative samples, measures of exchange rate volatility, and model specifications We also make efforts to address the potential endogeneity and zero-trade flows issues Using an instrumental variable (IV) regression approach and a two-stage method developed by Helpman, Melitz, and Rubinstein (2008), we show that controlling for endogeneity and the inclusion of zero-trade flow observations not alter our findings Moreover, in Helpman, Melitz, and Rubinstein's (2008) first-stage Probit estimation, we also detect a significantly negative interaction effect between exchange rate volatility and sectoral financial vulnerability even on the probability of selection into trade partners Our work contributes to the relevant literature in the following ways First, we present a small open economy model to illustrate the role of credit constraints in determining the trade effect of real exchange rate volatility We also provide empirical evidence to confirm the predictions of our model Second, while our result is at disaggregate level, it has important aggregate implications Quantitatively, the sectoral heterogeneity implies an ambiguous average effect on aggregate (bilateral) trade, which helps explain why previous work often find a small and insignificant effect Moreover, our findings also suggest that the sectoral composition of a country's trade is important for its exposure to exchange rate volatility Finally, our study complements nicely with the growing credit constraints and trade literature that documents a crucial role of credit constraints in trade It is also related to the broad literature that explores the heterogeneous effects of exchange rate volatility For example, Broda and Romalis (2011) and Bryne, Darby, and MacDonald (2008) find exchange rate volatility has different effects on homogeneous and differentiated goods Grier and Smallwood (2007) show that exchange rate uncertainty affects developed and emerging countries differently Aghion, Bacchetta, Rancière, and Rogoff (2009) examines how financial constraints influence the effect of exchange rate volatility on productivity growth A recent study by Héricourt and Poncet (2013) finds a similar interaction effect in Chinese firms for the years 2000-2006 Our study differs from theirs in several key aspects First, we present a theoretical model that illustrates how the interaction of credit constraints and exchange rate volatility affects trade Second, our empirical analysis utilizes a comprehensive data of 138 countries for the years 1970-2000, which allows us to draw much more general implications from our results with more confidence The longer sample period also enables us to examine the trade effects of the more relevant long-run volatility measures Further, while the bilateral nominal exchange rates between China and the U.S., and many other countries that peg to the dollar remain strictly fixed till mid-2005, our sample includes countries with various types of exchange rate arrangements and levels of economic and financial development Finally, we also take the zero trade flow and endogeneity issues more seriously and make efforts to address them The remainder of this paper is organized as follows In Section 2, we build a simple small open economy general equilibrium model with credit constraints to provide intuitions for the empirics Section discusses our empirical models and the data Section reports our main empirical results, and Section conducts further sensitivity analyses Concluding remarks are offered in Section A small open economy model with credit constraints In this section, we attempt to provide a theoretical model to demonstrate our main ideas For simplicity, we develop a two-sector small open economy general equilibrium model with credit constraints There are two sectors in the model: non-tradable and tradable sectors Firms in both sectors produce goods using labor and capital, and sell goods to domestic and foreign markets, respectively A key feature of our model is that a fraction of firms in the tradable sector are subject to credit constraints 2.1 Households The representative household has preferences given by ∞ U = E0 ¦ β t [ln(Ct ) − η t =0 L1t +ψ ] +ψ (2.1) where Ct is consumption, and Lt is labor supply Consumption is a Cobb-Douglas aggregation of consumption of non-tradable goods and imported goods, Ct = 1− a Hence, consumer price index is Pt = PNta PFt1− a , with PNt ( PFt ) C Nta C Ft a (1 − a)1−a a defined as time t price of non-tradable (imported) goods Households have access to domestic and international bond markets Trade in international bonds is subject to small portfolio adjustment cost If a household borrows an amount Dt+1, then the portfolio adjustment cost is ψD ( Dt +1 − D) (denominated in the This is a standard assumption in the literature; for example, see Devereux, Lane and Xu (2006) Our qualitative results still hold if we add the domestic tradable goods into household consumption Since our focus is on the impact of exchange rate changes on exports, for simplicity, we make the household side as simple 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Journal of Development Economics 82, 482-508 Uribe, Martin, 2003 “Real exchange rate targeting and macroeconomic instability.” Journal of International Economics 59(1), 137-159 Wei, Shang-Jin, 1999 “Currency hedging and goods trade.” European Economic Review 43, 1371-1394 44 -2 avg FinDep adj.(log) exports Figure Financial vulnerability adjusted exports and exchange rate volatility long-run real exchange rate volatility 1.5 Notes: The vertical axis denotes exporter’s average (log) bilateral exports, adjusted by sector’s external finance dependence, across destinations and sectors in 1995 The horizontal axis denotes exporter’s real exchange rate volatility, weighted by its trade partner’s trade share, in 1995 Only exporter-importer-sector triplets with positive trade are included 45 -.6 -.4 avg FinDep of exports -.2 Figure Average financial vulnerability of exports and exchange rate volatility long-run real exchange rate volatility 1.5 Notes: The vertical axis denotes the average external finance dependence of exports in 1995 The horizontal axis denotes exporter’s real exchange rate volatility, weighted by its trade partner’s trade share, in 1995 46 12 Figure Bilateral exports and sector’s financial vulnerability Argentina Avg (log) bilateral exports 10 11 Denmark -1 -.5 External finance dependence Notes: The vertical axis denotes average (log) bilateral exports per destination by sector The horizontal axis denotes sectors’ external finance dependence The solid line with dots is for Denmark in 1995 (13th percentile by weighted exchange rate volatility, log real GDP=25.66), and the dashed line with circles is for Argentina in 1995 (88th percentile by weighted exchange rate volatility, log real GDP=26.25) 47 Figure The effect of exchange rate volatility on bilateral exports by sector Notes: The vertical axis denotes the effect of one-standard-deviation increase in long-run real exchange rate volatility on bilateral exports by sector The horizontal axis denotes sector's external finance dependence 48 Table Mean of output under high volatility/mean of output under low volatility mean of output under high volatility (σ = 0.5) /mean of output under low volatility (σ = 0.1) Panel A: benchmark φ = 0.2 , κ = 0.5 , tb / y = , λ = 11 , ξ = 0.033 Panel B: initial trade surplus φ = 0.2 , κ = 0.5 , tb / y = 2% , λ = 11 , ξ = 0.033 Panel C: initial trade deficit φ = 0.2 , κ = 0.5 , tb / y = −2% , λ = 11 , ξ = 0.033 Panel D: alternative substitutability φ = 0.2 , κ = 0.5 , tb / y = , λ = , ξ = 0.033 Panel E: alternative sector composition φ = 0.2 , κ = 0.75 , tb / y = , λ = 11 , ξ = 0.033 Panel F: looser credit constraints φ = 0.9 , κ = 0.5 , tb / y = , λ = 11 , ξ = 0.033 Panel G: alternative death rate φ = 0.2 , κ = 0.5 , tb / y = , λ = 11 , ξ = 0.035 constrained subsector 80.54% unconstrained subsector 94.33% overall tradable sector 90.40% constrained subsector 79.68% unconstrained subsector 94.30% overall tradable sector 90.13% constrained subsector 82.72% unconstrained subsector 98.80% overall tradable sector 94.20% constrained subsector 97.12% unconstrained subsector 99.25% overall tradable sector 98.42% constrained subsector 96.59% unconstrained subsector 101.59% overall tradable sector 98.73% constrained subsector 99.77% unconstrained subsector 99.79% overall tradable sector 99.78% constrained subsector 78.12% unconstrained subsector 91.56% overall tradable sector 87.86% 49 Table Benchmark regressions Volatility (1) (2) (2) Level Effect Using Aggregate Bilateral Trade Data Level Effect Using Sector-level Bilateral Trade Data Benchmark Results Using Sector-level Bilateral Trade -0.178 -0.288*** (0.137) (0.088) -0.418*** (0.089) -1.205*** Volatility*Extfin (0.117) Log Distance Same Legal System Common Language Border FTA Colonial Currency Union Islands Landlocked Countries WTO Members Exporter-Year Fixed Effects Importer-Year Fixed Effects Sector Fixed Effects No of Observations R2 -1.218*** -0.886*** -0.886*** (0.028) (0.019) (0.019) 0.309*** 0.244*** 0.244*** (0.041) (0.032) (0.032) 0.264*** 0.156*** 0.156*** (0.051) (0.038) (0.038) 0.325** 0.575*** 0.575*** (0.157) (0.087) (0.087) -0.077 0.477*** 0.478*** (0.214) (0.085) (0.085) 1.045*** 0.627*** 0.627*** (0.110) (0.068) (0.068) 1.854*** 0.549* 0.551* (0.450) (0.307) (0.307) 0.478*** 0.170** 0.170** (0.129) (0.083) (0.083) 0.094 0.365** 0.365** (0.174) (0.164) (0.164) 0.012 0.432*** 0.432*** (0.117) (0.088) (0.088) Y Y N 30,126 0.79 Y Y Y 321,148 0.60 Y Y Y 321,148 0.60 Notes: A constant, exporter-year and importer-year fixed effects are included but not reported in all columns Columns (2) and (3) also includes sector fixed effects Robust standard errors clustered by country pairs are reported in parentheses * p

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