Staff working papers

Central bankers argue that programmable digital currencies may compromise the uniformity of money. We develop a stylized model to examine this argument and the trade-offs involved in circulating programmable money.

We develop statistical inferences for a non-probability two-phase survey sample when relevant auxiliary information is available from a probability survey sample. The proposed method is assessed by simulation studies and used to analyze a non-probability two phase payment survey.

Our paper employs smartphone data to construct an improved cash access metric by accounting for both spatial agglomeration and households’ travel patterns. We find that incorporating trip-chaining into the travel metric could show that travel costs are from 15 to 25% less than not incorporating trip-chaining and that the biggest decrease is driven by rural residents.

This paper analyzes the optimal quantity of central bank reserves in an economy where reserves and other financial assets provide liquidity benefits. Using a static model, I derive a constrained Friedman rule that characterizes the socially optimal level of reserves, demonstrating that this quantity is neither necessarily large nor small but depends on the marginal benefits of reserves relative to alternative safe assets.

We consider structural vector autoregressions that are identified through stochastic volatility. Our analysis focuses on whether a particular structural shock can be identified through heteroskedasticity without imposing any sign or exclusion restrictions.

In recent years, significant efforts have been made to attract more women into academia and to support their careers, with the goal of increasing their representation.

This paper theoretically and empirically examines the price impacts of liquidations in DeFi and how different liquidation mechanisms affect the price impacts.

Exporters frequently change their market destinations. This paper introduces a new approach to identifying the drivers of these decisions over time. Analysis of customs data from China and the UK shows most changes are driven by demand rather than supply-related shocks.

We propose a novel approach to estimating consumer demand for differentiated products. We eliminate the need for instrumental variables by assuming demand shocks are sparse. Our empirical applications reveal strong evidence of sparsity in real-world datasets.

Can regulators keep pace with banks’ creative regulatory workarounds? Our analysis unpacks the trade-offs between fixed regulations and crisis-triggered rules, showing that the latter are especially prone to circumvention—and can trigger larger, costlier bailouts.