Journal of International Money and Finance最新文献

We investigate the determinants of emerging markets performance during five U.S. Federal Reserve monetary tightening and easing cycles during 2004–2023. We study how macroeconomic and institutional conditions of an Emerging Market (EM) at the beginning of a cycle explain EM resilience during each cycle. More specifically, our baseline cross-sectional regressions examine how those conditions affect three measures of resilience, namely bilateral exchange rate against the USD, exchange rate market pressure, and country-specific Morgan Stanley Capital International index (MSCI). We then stack the five cross-sections to build a panel database to investigate potential asymmetry between tightening versus easing cycles. Our evidence indicates that macroeconomic and institutional variables are associated with EM performance, determinants of resilience differ during tightening versus easing cycles, and institutions matter more during difficult times. Our specific findings are largely consistent with economic intuition. For instance, we find that current account balance, international reserves, and inflation are all important determinants of EM resilience.

Central banks often buy or sell reserves—so called FX interventions (FXIs)—to dampen sharp exchange rate movements caused by volatile capital flows. At the same time, these interventions may entail unintended side effects. In this paper, we investigate whether FXIs incentivize firms to take on more unhedged FX debt, thereby increasing medium-term corporate vulnerabilities. Using a novel dataset with close to 5,000 nonfinancial firms across 19 emerging markets covering 2002–2017, we find that the firm-level share of FX debt rises following intensive use of FXIs, particularly for non-exporting firms in shallow financial markets with no FX debt to begin with. The magnitude of this effect is economically significant, with one standard deviation increase in the intensity of FXI leading to an average 2 percentage points increase in the FX debt share. For reference, the median share of FX debt in the sample is zero.

I study the effects of labor market outcomes on firms' loan demand and credit intermediation. I first show in partial equilibrium that the presence of frictions in the banking sector lowers the capital factor demand elasticity to changes in real wages. This finding helps to connect the substitutability of labor and capital with credit conditions. Second, I use a new Keynesian banking model with an endogenous financial accelerator mechanism to study the role of lower capital factor demand elasticity in the transmission mechanism of monetary policy. Stabilizing nominal wages is close to the optimal monetary policy because it coincides with stabilizing the credit spread, the net worth gap, and the output gap. Inflation stabilization, in turn, imposes a policy trade-off with high welfare costs.

Financial crises tend to spread across countries, causing equity price crashes that cannot be fully explained by fundamentals. This paper introduces a two-country dynamic general equilibrium model of global financial crises that distinguishes between interdependence and financial contagion. Interdependence arises through trade and capital flows, while contagion occurs through a new channel: confidence spillovers. In the model, contagion is possible due to multiple dynamic and steady-state equilibria, even with fully rational consumers. Self-fulfilling beliefs about equity prices can shift the economy between equilibria, amplifying negative effects and causing contagion. The model has three policy implications. Firstly, monetary policy can offset recessions without causing inflation. Coordinated international policy can potentially improve welfare further. Secondly, capital controls can prevent contagion. Lastly, increased trust in government can mitigate negative confidence shocks. These recommendations emphasize the role of beliefs, where pessimism can spread internationally via the confidence channel, leading to contagion.

We examine how the tail risk of currency returns over the past 20 years were impacted by central bank monetary and liquidity measures across the globe with an original and unique dataset that we make publicly available. Using a standard factor model, we derive theoretical measures of tail risks of currency returns which we then relate to the various policy instruments employed by central banks. We find empirical evidence for the existence of a cross-border transmission channel of central bank policy through the FX market. The tail impact is particularly sizeable for asset purchases and swap lines. The effects last for up to 1 month, and are proportionally higher for joint QE actions. This cross-border source of tail risk is largely undiversifiable, even after controlling for the U.S. dollar dominance and the effects of its own monetary policy stance.

Are nominal exchange rate variations linked to the central bank's balance sheet, in particular to remunerated domestic liabilities? We use two metrics of implied exchange rates based on central bank balance sheet data: one is a traditional metric that includes the monetary base, and the other adds remunerated domestic liabilities. We first estimate a VAR model to investigate the endogenous interactions between central bank balance sheet components for a set of seven Latin American countries for the 2006:01-2019:12 period. Then, we use a pairwise cointegration framework to compare these two metrics of implied exchange rate with the spot (observed) exchange rate. We find that the implied exchange rates and the spot exchange rate are cointegrated for most of the set of Latin American countries. We also find that for a subset of our sample, the spot exchange rate adjusts to the metric that adds remunerated domestic liabilities. We conclude that remunerated domestic liabilities matter for understanding exchange rate dynamics, and explore a simple theoretical setup to better understand the mechanism.

We investigate the effects of rising urban house prices on manufacturing firms’ decisions on outward foreign direct investment (outward FDI) in a home country. By utilizing the panel data of Chinese industrial enterprises in 2005–2013, our estimates suggest that, for every 210 manufacturing firms or 13 listed companies in China, one firm will forgo outward FDI when house prices double. As a result, there could have been 95 percent more manufacturing firms or 70 percent more listed firms conducting outward FDI if house prices remained unchanged during the study period. To address potential endogeneity issues, we exploit a fixed-effects instrumental variable model, a difference-in-differences strategy, and housing discontinuities at provincial borders among neighboring city/county pairs. To elucidate potential mechanisms, we employ the “Olley and Pakes” covariance to assess resource allocation efficiency and observe its negative correlation with house prices. Furthermore, we delve into the impact of house prices and resource allocation efficiency on TFP, and find that house prices and TFP are negatively correlated, while resource allocation efficiency and TFP are positively correlated. Finally, heterogeneity analyses reveal that rising house prices exert a stronger negative influence on outward FDI entry for firms that are less productive, larger, domestically-owned, more closely linked to the real estate industry, labor-intensive, and in industries with higher levels of outward FDI participation. These results underscore the fact that rising house prices could exacerbate resource misallocation, leading to a decline in enterprise TFP and subsequently reducing their outward FDI.

We introduce a novel measure that captures the beta deviation of individual firms from their industry peers within China's stock market. Our analysis reveals that stocks with greater beta deviation generate significantly higher future returns. This predictive power is unaffected by established return predictors and remains robust across alternative peer identification methods, beta estimation techniques, and subsample tests. Our findings suggest a behavioral interpretation, linking positive predictability to mispricing driven by investors' extrapolation biases. Overall, our research highlights the critical role of incorporating peer firms into asset pricing, particularly in emerging markets.

This study analyzes how exchange rates affect corporate investment by scrutinizing firms' global value chain (GVC) networks. A salient feature of our analysis is that we adopt novel GVC datasets and methodologies to construct upstream- and downstream-specific exchange rates. We couple these GVC-integrated real exchange rates with global firm-level data and document that unfavorable exchange rate movements hinder operating performance and, therefore, corporate investment, especially among financially constrained firms. We use two large currency shocks in Brazil and Sweden to provide causal evidence. The results highlight nonnegligible frictions of how GVC-integrated real exchange rates affect corporate investment.

We develop a Bayesian Structural VAR model to study the relationship between different energy shocks and inflation dynamics in Europe. Specifically, we model the endogenous transmission from shocks identified by the global market of crude oil and the European natural gas market to two target macroeconomic variables, i.e. inflation expectations and realized headline inflation rate. Our results demonstrate that, since the post-pandemic recovery, inflation in the Euro area is mostly driven by energy price shocks and aggregate supply factors. In particular, the high peaks of the Eurozone inflation are mostly associated with natural gas supply shocks.