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We analyze the impact of interest rate policy on financial stability in an environment where banks can experience runs on their short-term liabilities, forcing them to sell assets at fire-sale prices.

We document a new empirical finding in the foreign exchange market: currency returns show systematic reversals around the benchmark fixings. Specifically, the US dollar, on average, appreciates in the hours before fixes and depreciates after fixes.

A consumer discloses information to a multi-product seller, which learns about the consumer’s preferences, sets prices, and makes product recommendations. While the consumer benefits from accurate product recommendations, the seller may use the information to price discriminate.

This paper studies the effects of monetary policy shocks on firms’ participation in exporting. We develop a two-country dynamic stochastic general equilibrium model in which heterogeneous firms make forward-looking decisions on whether to participate in the export market and prices are staggered across firms and time.

The current monetary policy framework of the Fed intends to be more ’inclusive’ by running the economy hot for longer during expansions.

This paper studies how unsecured consumer credit impacts the extent to which unemployment insurance (UI) policies smooth aggregate consumption fluctuations over the business cycle. Using a general equilibrium real business cycle model, I find that unsecured credit amplifies the extent to which UI smooths cyclical consumption fluctuations.

We measure systemic risk in the network of financial market infrastructures (FMIs) as the probability that two or more FMIs have a large credit risk exposure to the same FMI participant.

We develop a model in which a financial intermediary’s investment in risky assets—risk taking—is excessive due to limited liability and deposit insurance and characterize the policy tools that implement efficient risk taking.

Using the quantum Monte Carlo algorithm, we study whether quantum computing can improve the run time of economic applications and challenges in doing so. We apply the algorithm to two models: a stress testing bank model and a DSGE model solved with deep learning. We also present innovations in the algorithm and benchmark it to classical Monte Carlo.

Changes in survey mode (e.g., online, offline) may influence the values of survey responses, and may be particularly problematic when comparing repeated cross-sectional surveys.