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We examine the role of debt in amplifying and propagating recessions. Firms’ debt adjustment makes recessions deeper but makes expansions gradual. In particular, when the aggregate business leverage is ten percentage points above average, the half-life of the recovery doubles.

Unregulated capital flows are likely excessive during a stagflation episode, owing to a macroeconomic externality operating through the economy’s supply side. Inflows raise domestic wages and cause unwelcome upward pressure on firm costs, yet market forces likely generate such inflows. Optimal capital flow management instead requires net outflows.

In a dynamic model with limited commitment, aggregate payout-based compensation induces managers to raise outside equity yet invest too little today. Per-share compensation eliminates the dilution motive and restores efficient investment, but it does so through slower capital accumulation that better protects incumbent shareholder value.

We study economies where firms acquire capital in primary markets then retrade it in secondary markets after information on idiosyncratic productivity arrives. Our secondary markets incorporate bilateral trade with search, bargaining and liquidity frictions.

This paper studies dynamic general equilibrium models where firms trade capital in frictional markets. Gains from trade arise due to ex ante heterogeneity: some firms are better at investment, so they build capital in the primary market; others acquire it in the secondary market.

We study how different types of monetary policy shape the distributional effects of external economic shocks on households’ consumption in a small open economy. Our results present a trade-off between maintaining overall stabilization and controlling consumption inequality.

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.

This paper develops a stress-testing framework in which banks strategically adjust their balance sheets in response to regulatory constraints and market conditions. Applied to Canada’s largest banks, it quantifies the effects of macroprudential policies on lending and identifies systemic vulnerabilities through reverse stress testing.

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.

During downturns, workers get stuck in low-productivity jobs and wages remain stagnant. I build an heterogenous agent incomplete market model with a full job ladder that accounts for these facts. An adverse financial shock calibrated to the US Great Recession replicates the period’s slow recovery and missing disinflation.