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I develop a method for Bayesian estimation of globally solved, non-linear macroeconomic models. The method uses a mixture density network to approximate the initial state distribution. The mixture density network results in more reliable posterior inference compared with the case when the initial states are set to their steady-state values.

This paper studies how the outcome of Bayesian persuasion depends on a sender’s information. I study a game in which, prior to the sender’s information disclosure, the designer can restrict the most informative signal that the sender can generate.

We develop and estimate a search model in which identical consumers trade with price-setting firms that differ in productivity. We use the estimated model to characterize the qualitative and quantitative differences in prices and markups across firms. We explore how individual firms respond to changes in cost and demand and how they pass these through to their prices and markup.

We develop a dynamic model to capture key features of decentralized finance lending. We identify a price-liquidity feedback: the market outcome in any given period depends on agents' expectations about lending activities in future periods, with higher future price expectations leading to more lending and higher prices in that period.

This paper studies how the allocation of residual losses affects trading and welfare in a central counterparty. I compare loss sharing under two loss-allocation mechanisms – variation margin haircutting and cash calls – and study the privately and socially optimal degree of loss sharing.

Using highly disaggregated transaction-level trade data, we document the importance of new firm-level trade partner relationships and the addition of new products to existing relationships in driving aggregate trade flows.

Since the creation of Bitcoin in 2009, over 2,000 cryptocurrencies have been issued. We evaluate how well a cryptocurrency functions as a payment system.

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.

Monetary policy in the presence of nominal debt and labour supply heterogeneity creates a policy trade-off: a short-term economic stimulus leads to persistently reduced output over the medium term. Price-level targeting weakens this trade-off and is better able to stabilize inflation and output than inflation targeting.

We introduce a new class of time-varying parameter vector autoregressions (TVP-VARs) where the identified structural innovations are allowed to influence — contemporaneously and with a lag — the dynamics of the intercept and autoregressive coefficients in these models.