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We build a network formation game of firms with trade flows to study the adoption and usage of a new digital currency as an alternative to correspondent banking.

Can monetary policy be used to promote financial stability? We answer this question by estimating the impact of a monetary policy shock on private-sector leverage and the likelihood of a financial crisis. Impulse responses obtained from a panel VAR model of 18 advanced countries suggest that the debt-to-GDP ratio rises in the short run following an unexpected tightening in monetary policy.

We provide empirical evidence of effects to the aggregate economy from surprises about financial intermediaries’ net worth based on a high-frequency identification strategy. We estimate that news of a 1% decline in intermediaries’ net worth leads to a 0.2%–0.4% decrease in the market value of nonfinancial firms.

In an economy where production takes place in multiple stages and is subject to financial frictions, how firms finance intermediate inputs matters for aggregate outcomes. This paper focuses on trade credit—the lending and borrowing of input goods between firms—and quantifies its aggregate impacts during the Great Recession.

I study a model of competing data intermediaries (e.g., online platforms and data brokers) that collect personal data from consumers and sell it to downstream firms.

We outline possible system architectures for an online retail central bank digital currency (CBDC) and identify one well-suited for basic payments. We analyze OpenCBDC 2PC, a representative system, finding such designs to be feasible, although some areas require further investigation. Our framing highlights other promising architectures for a retail CBDC.

The prevalence of entrepreneurs, particularly low-productivity non-employers, declines as economies develop. This decline is more pronounced for women. Relative to men, women are more likely to be entrepreneurs in poor economies but less likely in rich economies.

One of the main outcomes of the global financial crisis has been a series of new regulations imposed on the financial system and specifically on banks.

In August 2012, the New York Stock Exchange launched the Retail Liquidity Program (RLP), a trading facility that enables participating organizations to quote dark limit orders executable only by retail traders.

We characterize the bias in cross-sectional Hill estimates caused by common underlying factors and propose two simple-to-implement remedies. To test for the presence, direction and size of the bias, we use monthly US stock returns and annual US Census county population data.