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A large body of work has examined the impact of corporate takeovers on the financial stakeholders (shareholders and bondholders) of the merging firms. Since the late 2000s, empirical research has increasingly highlighted the crucial role played by the non-financial stakeholders (labor, suppliers, customers, government, and communities) in these transactions. It is, therefore, important to understand the interplay between corporate takeovers and the non-financial stakeholders of the firm. Financial economists have long viewed the firm as a nexus of contracts between various stakeholders connected to the firm. Corporate takeovers not only play an important role in redefining the broad boundaries of the firm but also result in major changes to corporate ownership and structure. In the process, takeovers can significantly alter the contractual relationships with non-financial stakeholders. Because the firm’s relationships with these stakeholders are governed by implicit and explicit contracts, circumstances can arise that allow acquiring firms to fully or partially abrogate these contracts and extract rents from non-financial stakeholders after deal completion. In contrast, non-financial stakeholders can also potentially benefit from a takeover if they get to share in any efficiency gains that are generated in the deal. Given this framework, the ex-ante importance of these contractual relationships can have a bearing on the efficacy of takeovers. The ability to alter contractual relationships ex post can affect the propensity of a takeover and merging firms’ shareholders and, in turn, impact non-financial stakeholders. Non-financial stakeholders will be more vested in post-takeover success if they can trust the acquiring firm to not take actions that are detrimental to them. The big picture that emerges from the surveyed literature is that non-financial stakeholder considerations affect takeover decisions and post-takeover outcomes. Moreover, takeovers also have an impact on non-financial stakeholders. The directions of all these effects, however, depend on the economic environment in which the merging firms operate.

The uncovered interest parity (UIP) condition states that the interest rate differential between two currencies is the expected rate of change of their exchange rate. Empirically, however, in the 1976–2018 period, exchange rate changes were approximately unpredictable over short horizons, with a slight tendency for currencies with higher interest rates to appreciate against currencies with lower interest rates. If the UIP condition held exactly, carry trades, in which investors borrow low interest rate currencies and lend high interest rate currencies, would earn zero average profits. The fact that UIP is violated, therefore, is a necessary condition to explain the fact that carry trades earned significantly positive profits in the 1976–2018 period. A large literature has documented the failure of UIP, as well as the profitability of carry trades, and is surveyed here. Additionally, summary evidence is provided here for the G10 currencies. This evidence shows that carry trades have been significantly less profitable since 2007–2008, and that there was an apparent structural break in exchange rate predictability around the same time. A large theoretical literature explores economic explanations of this phenomenon and is briefly surveyed here. Prominent among the theoretical models are ones based on risk aversion, peso problems, rare disasters, biases in investor expectations, information frictions, incomplete financial markets, and financial market segmentation.

The links of international reserves, exchange rates, and monetary policy can be understood through the lens of a modern incarnation of the “impossible trinity” (aka the “trilemma”), based on Mundell and Fleming’s hypothesis that a country may simultaneously choose any two, but not all, of the following three policy goals: monetary independence, exchange rate stability, and financial integration. The original economic trilemma was framed in the 1960s, during the Bretton Woods regime, as a binary choice of two out of the possible three policy goals. However, in the 1990s and 2000s, emerging markets and developing countries found that deeper financial integration comes with growing exposure to financial instability and the increased risk of “sudden stop” of capital inflows and capital flight crises. These crises have been characterized by exchange rate instability triggered by countries’ balance sheet exposure to external hard currency debt—exposures that have propagated banking instabilities and crises. Such events have frequently morphed into deep internal and external debt crises, ending with bailouts of systemic banks and powerful macro players. The resultant domestic debt overhang led to fiscal dominance and a reduction of the scope of monetary policy. With varying lags, these crises induced economic and political changes, in which a growing share of emerging markets and developing countries converged to “in-between” regimes in the trilemma middle range—that is, managed exchange rate flexibility, controlled financial integration, and limited but viable monetary autonomy. Emerging research has validated a modern version of the trilemma: that is, countries face a continuous trilemma trade-off in which a higher trilemma policy goal is “traded off” with a drop in the weighted average of the other two trilemma policy goals. The concerns associated with exposure to financial instability have been addressed by varying configurations of managing public buffers (international reserves, sovereign wealth funds), as well as growing application of macro-prudential measures aimed at inducing systemic players to internalize the impact of their balance sheet exposure on a country’s financial stability. Consequently, the original trilemma has morphed into a quadrilemma, wherein financial stability has been added to the trilemma’s original policy goals. Size does matter, and there is no way for smaller countries to insulate themselves fully from exposure to global cycles and shocks. Yet successful navigation of the open-economy quadrilemma helps in reducing the transmission of external shock to the domestic economy, as well as the costs of domestic shocks. These observations explain the relative resilience of emerging markets—especially in countries with more mature institutions—as they have been buffered by deeper precautionary management of reserves, and greater fiscal and monetary space. We close the discussion noting that the global financial crisis, and the subsequent Eurozone crisis, have shown that no country is immune from exposure to financial instability and from the modern quadrilemma. However, countries with mature institutions, deeper fiscal capabilities, and more fiscal space may substitute the reliance on costly precautionary buffers with bilateral swap lines coordinated among their central banks. While the benefits of such arrangements are clear, they may hinge on the presence and credibility of their fiscal backstop mechanisms, and on curbing the resultant moral hazard. Time will test this credibility, and the degree to which risk-pooling arrangements can be extended to cover the growing share of emerging markets and developing countries.

Macroprudential policy involves using mainly prudential but sometimes also monetary and fiscal tools to reduce systemic risk and achieve financial stability. It is motivated by externalities associated with the buildup of systemic risk over time due to strategic complementarities, fire sales and credit crunches related to a generalized sell-off of assets, and strong cross-institutional interconnectedness. Macroprudential tools apply to both banks and nonbank financial institutions and to different classes of borrowers to the extent that they come with systemic risks. Both advanced economies (AEs) and emerging market economies (EMEs) have steadily increased their use of macroprudential measures since the mid-1990s. Empirical evidence suggests that tighter macroprudential policy has improved banking system resilience and that tools such as lower caps on loan-to-value or debt service ratios have helped reduce housing credit and price growth. Evidence shows that while tightening macroprudential policy is generally effective, relaxing it is less so. By moderating fluctuations in general bank credit, housing/household credit, or house prices, macroprudential policy tends to reduce the severity and likelihood of future crises as well as the volatility of growth, but recent studies also show that it slows output growth. As financial globalization progresses, macroprudential policy may become less effective due to regulatory arbitrage and cross-border leakages, especially in financially more open AEs and EMEs, also given the limited scope for international coordination and the lack of an internationally agreed-upon macroprudential framework. To deal with the associated externally driven risks, many EMEs use foreign exchange (FX)-related macroprudential tools, e.g., FX liability-based reserve requirements, limits on currency mismatch or FX positions, and FX liquidity requirements. In EMEs, FX intervention can also play a macroprudential role. In contrast, AEs rarely use such instruments but use macroprudential capital buffers more actively than EMEs. Recent evidence suggests both positive and negative international spillover effects of these and other macroprudential policies. These and other findings point to the need to build formal models that have a macro-financial stability framework (MFSF) at their core. The framework incorporates the relevant policy tools, their individual effects, and interactions, and captures the channels of financial risk-taking and their implications for global and domestic financial conditions. Such an MFSF includes monetary policy to ensure macroeconomic stability and assist with financial stability, fiscal policy to guarantee fiscal sustainability and limit cyclical economic fluctuations, and macroprudential policy to complement monetary and fiscal policies by strengthening the resilience of the financial system and limiting the buildup of financial imbalances. Research is underway to develop such models, but considerable scope for further work in this area exists.

An overview of research on the microstructure of foreign exchange (FX) markets is presented. We begin by summarizing the institutional features of FX trading and describe how they have evolved since the 1980s. We then explain how these features are represented in microstructure models of FX trading. Next, we describe the links between microstructure and traditional macro exchange-rate models and summarize how these links have been explored in recent empirical research. Finally, we provide a microstructure perspective on two recent areas of interest in exchange-rate economics: the behavior of returns on currency portfolios, and questions of competition and regulation.

Solving dynamic economic models that capture salient real-world heterogeneity and nonlinearity requires the approximation of high-dimensional functions. As their dimensionality increases, compute time and storage requirements grow exponentially. Sparse grids alleviate this curse of dimensionality by substantially reducing the number of interpolation nodes, that is, grid points needed to achieve a desired level of accuracy. The construction principle of sparse grids is to extend univariate interpolation formulae to the multivariate case by choosing linear combinations of tensor products in a way that reduces the number of grid points by orders of magnitude relative to a full tensor-product grid and doing so without substantially increasing interpolation errors. The most popular versions of sparse grids used in economics are (dimension-adaptive) Smolyak sparse grids that use global polynomial basis functions, and (spatially adaptive) sparse grids with local basis functions. The former can economize on the number of interpolation nodes for sufficiently smooth functions, while the latter can also handle non-smooth functions with locally distinct behavior such as kinks. In economics, sparse grids are particularly useful for interpolating the policy and value functions of dynamic models with state spaces between two and several dozen dimensions, depending on the application. In discrete-time models, sparse grid interpolation can be embedded in standard time iteration or value function iteration algorithms. In continuous-time models, sparse grids can be embedded in finite-difference methods for solving partial differential equations like Hamilton-Jacobi-Bellman equations. In both cases, local adaptivity, as well as spatial adaptivity, can add a second layer of sparsity to the fundamental sparse-grid construction. Beyond these salient use-cases in economics, sparse grids can also accelerate other computational tasks that arise in high-dimensional settings, including regression, classification, density estimation, quadrature, and uncertainty quantification.

International transactions are riskier than domestic transactions for several reasons, including, but not limited to, geographical distance, longer shipping times, greater informational frictions, contract enforcement, and dispute resolution problems. Such risks stem, fundamentally, from a timing mismatch between payment and delivery in business transactions. Trade finance plays a critical role in bridging the gap, thereby overcoming greater risks inherent in international trade. It is thus even described as the lifeline of international trade, because more than 90% of international transactions involve some form of credit, insurance, or guarantee. Despite its importance in international trade, however, it was not until the great trade collapse in 2008–2009 that trade finance came to the attention of academic researchers. An emerging literature on trade finance has contributed to providing answers to questions such as: Who is responsible for financing transactions, and, hence, who would need liquidity support most to sustain international trade? This is particularly relevant in developing countries, where the lack of trade finance is often identified as the main hindrance to trade, and in times of financial crisis, when the overall drying up of trade finance could lead to a global collapse in trade.