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In this paper, we define a financial institution’s contribution to financial systemic risk as the increase in financial systemic risk conditional on the crash of the financial institution. The higher the contribution is, the more systemically important is the institution for the system.

In theory, nominal exchange rate movements can lead to “expenditure switching” when they generate changes in the relative prices of goods across countries. This paper explores whether the expenditure-switching role of exchange rates has changed in the current episode of significant global imbalances.

We study the formation of price bubbles on experimental asset markets where cash earns interest. There are two main conclusions.

We develop a discrete-time affine stochastic volatility model with time-varying conditional skewness (SVS). Importantly, we disentangle the dynamics of conditional volatility and conditional skewness in a coherent way.

We assess whether unconventional monetary and fiscal policy implemented in response to the COVID-19 pandemic in the U.S. contribute to the 2021-2023 inflation surge through the lens of several different empirical methodologies and establish a null result.

Consumption volatility relative to output volatility is consistently higher in emerging economies than in developed economies.

The author proposes a test for the parametric specification of each component in the diffusion matrix of a d-dimensional diffusion process. Overall, d (d-1)/2 test statistics are constructed for the off-diagonal components, while d test statistics are constructed for the main diagonal components.

This paper relaxes the Bayesian Nash equilibrium (BNE) assumption commonly imposed in empirical discrete choice games with incomplete information. Instead of assuming that players have unbiased/correct expectations, my model treats a player’s belief about the behavior of other players as an unrestricted unknown function. I study the joint identification of belief and payoff functions.

We build upon new developments in the international trade literature to isolate and quantify the long-run economic impacts of tariff changes on the United States and the global economy.

This paper describes a new test for evaluating conditional density functions that remains valid when the data are time-dependent and that is therefore applicable to forecasting problems. We show that the test statistic is asymptotically distributed standard normal under the null hypothesis, and diverges to infinity when the null hypothesis is false.