Journal of International Money and Finance最新文献

This paper examines the stabilization role of flexible exchange rates for emerging economies within the Latin America and Asia regions. Based on a structural VAR model, we utilize zero, sign and exchange rate pass-through restrictions to identify structural macroeconomic shocks. Overall, we find that exogenous exchange rate shocks drive around half of total exchange rate fluctuations in emerging economies. Despite this predominant role, we find evidence that exchange rates do not act as a source of shocks to the real economy, but they instead absorb and reduce output growth and inflation volatilities. Based on counterfactual analyses, we further find that this shock-insulation property is highly shock-dependent, where the benefits of flexible exchange rates are sizable for demand and global monetary policy shocks, but are overall small in the face of supply shocks. Results also differ across time horizons, where the shock stabilization benefits are mainly limited to the short run for output, but also extend to the medium term for inflation. We also find that the net benefits of flexible exchange rates as a shock absorber are in general larger for emerging economies in Latin America than in Asia, particularly during crises periods. Finally, while we find that the stabilization role of exchange rates hinges upon the nature of underlying structural shocks, there is also a positive association with structural determinants such as a country's degree of exchange rate flexibility and trade openness.

The Eurosystem purchased €178 billion of corporate bonds between June 2016 and December 2018 under the Corporate Sector Purchase Programme (CSPP). Did these purchases lead to a deterioration of liquidity conditions in the corporate bond market, thus raising concerns about unintended consequences of large-scale asset purchases? To answer this question, we combine the Bundesbank's detailed CSPP purchase records with a range of liquidity indicators. We find that while the flow of purchases initially supported secondary market liquidity by providing a predictable source of demand, liquidity conditions deteriorated in the long-run as the Bundesbank reduced the stock of corporate bonds available for trading in the secondary market.

We characterise the probability distributions of various types of gross capital flows conditional on information contained in financial asset prices in a panel of emerging market economies, with a focus on ‘tail’ events. Our framework, based on the quantile regression methodology, allows for a separate role of push- and pull-type factors. We find that both push and pull factors have heterogeneous effects across the distributions of gross capital flows, which are most marked in the left tails. We then explore the role of the pre-existing stance of macroprudential and capital flow management policy in shaping probability distributions of capital flows. Macroprudential and capital flow management measures can both be stabilising, leading to less volatile flows and in particular to lower chances of large portfolio outflows. A tighter macroprudential stance can also reduce the sensitivity of portfolio flows to global financial shocks.

We investigate preferential trade agreement (PTA) formation when risk averse countries face demand uncertainty and, hence, have an insurance motive for pursuing trade integration. In this environment, when deciding which type of PTA − if any − they wish to form, countries seek to maximise their net welfare; that is, their expected utility less a risk premium. The desire for insurance influences, not just whether a particular PTA forms, but also the preferred depth of integration. We analyze the insurance implications of free trade agreements (FTAs), customs unions (CUs), and countries choosing to stand alone. We further distinguish between shallow CUs and deep CUs; in the former, members maximise the sum of their individual net welfares, while in the latter they maximise the net value of the sum of their individual expected welfares. We show that differences in country risk attitudes and the levels of risk they face, as well as the degree to which these risks are correlated with each other, each, and together, influence the formation and design of TAs. When countries’ demands are uncorrelated, they form a deep CU if their levels of risk aversion are sufficiently different. If, however, their risk attitudes are similar, countries opt for shallower trade integration − either a shallow CU or a FTA − if they face low levels of uncertainty, and choose to stand alone if one country faces a sufficiently high level of uncertainty. When countries’ demands are correlated, they tend to form a deep CU if their demands are strongly negatively correlated, a FTA if their demands are strongly positively correlated and a shallow CU when their demands are weakly correlated. Intuitively, differences in country risk attitudes (i.e., their degree of risk aversion) act as an additional source of comparative advantage. Deeper integration − particularly via a CU − permits less risk averse members to essentially export their relative partiality for risk to more risk averse partners, thereby effectively providing the latter with insurance.

This paper constructs a global anomaly index based on the long-short portfolio returns of 153 anomalies across 33 stock markets. We find that global anomaly index is a strong negative predictor of aggregate stock returns in international markets, both in-sample and out-of-sample. The index delivers considerable economic value for a mean–variance investor. Moreover, it captures global common changes in overpricing, and is not subsumed by extant return predictors. Its predictive power arises from global asymmetric mispricing correction persistence, and partly from the ability to forecast sentiment-changes. Furthermore, we demonstrate significant transfer learning from the U.S. market to other markets in terms of time series predictions.

We examine the reactions of US-based multinationals and subsequent financial market reactions to Russia’s invasion of Ukraine in February 2022. The multinationals’ firm-level decisions range from clean exits from the Russian market, all the way to ‘digging in’ as if the war never happened. Findings show that, in the short-term, markets favour ‘middle ground’ decisions which balance shareholder interests with regulatory and ethical concerns. This is manifest through those firms taking extreme decisions, on either end of the spectrum, experiencing more negative returns. In the longer term, however, investor ethical concerns and other considerations dominate such that firms announcing clean breaks incur lower losses compared to their peers. In other words, sitting on the fence and playing both sides does not pay off for long. We also show interesting differences in investor reactions between two major non-US markets: China − a Russia-leaning country − vs India − a neutral country. While Indian investors behave largely similar to US investors, Chinese investors do not significantly punish firms that stay put in Russia. We re-examine the situation one year into the war and show that markets reward a Russia-opposing corporate position in the longer term.

This paper investigates the relationship between the views expressed in the minutes of the meetings of the Central Bank of Brazil's Monetary Policy Committee (COPOM) and the real economy. It applies various linguistic machine learning algorithms to construct different measures of the uncertainty contained in the minutes of the COPOM. To achieve this, we first infer the content of the paragraphs of the minutes with Latent Dirichlet Allocation (LDA). Secondly, we build an uncertainty index for the minutes with Word Embedding and K-Means. Thirdly, we create two topic-uncertainty indices. The first topic-uncertainty index is constructed from paragraphs with a higher probability of topics related to general economic conditions. The second topic-uncertainty index is built from paragraphs with a higher probability of topics related to inflation and the monetary policy decision. Then, via a Structural VAR, we explore the lasting effects of these uncertainty indices on some Brazilian macroeconomic variables. Our results show that an unexpected increase in the minutes' uncertainty leads to a depreciation of the exchange rate and a decline in industrial production and retail trade. Moreover, we show that a positive shock to the general economic conditions topic-uncertainty index leads to higher inflation, whereas a positive shock to the inflation and monetary policy decision topic-uncertainty index leads to lower inflation.

This paper measures systemic risk in eight Asian foreign exchange markets between 2015 and 2021. We define systemic risk as the risk of significant devaluation in a large number of currencies. Our measures, derived using a time-varying factor copula model, can take into account heterogeneous and dynamic dependencies among markets. Our empirical findings reveal that (1) systemic risk spiked during the US-China trade conflict and the COVID-19 pandemic; (2) Among the currencies studied, the Japanese yen contributes most to systemic risk, while it is the least vulnerable to systemic shocks; (3) Higher levels of regional trade and financial integration increase a currency's vulnerability to systemic risk in the Asian foreign exchange markets.

We study the impact of US presidential election TV debates on the cross section of intraday exchange rate returns of 96 currencies from 1996 to 2016. The performance of the candidates in the debate is an exogenous shock to the election probability. We find that currencies of countries with high levels of bilateral foreign trade with the US depreciate if the election probability of the protectionist candidate increases during the debate, while no significant impact is detected for countries with bilateral US exports to GDP below 2 percent. Expectations about protectionist measures are the main transmission channel of debate outcomes, while the candidates' stance towards military and immigration play a minor role.

This paper uses time-varying Bayesian models to assess the impact of the shifting, and progressively more volatile (especially since the EU Referendum vote in 2016) macroeconomic landscape on Foreign Direct Investment (FDI) inflows to the UK. FDI inflows are depressed in response to higher UK-specific economic and geopolitical uncertainty. A stronger real exchange rate and a higher interest rate also have a negative effect. It benefits from lower UK corporate tax rates and higher US uncertainty, the latter creating investment opportunities in the UK. Rising economic policy uncertainty since the EU Referendum, has led to FDI losses of up to 0.5% of GDP.