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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.

We develop a heterogeneous-agent New Keynesian model featuring a frictional labor market with on-the-job search to quantitatively study the positive and normative implications of employer-to-employer transitions for inflation.

An anonymous credential mechanism is a set of protocols that allows users to obtain credentials from an organization and demonstrate ownership of these credentials without compromising users’ privacy. In this work, we construct the first secret-free and quantum-safe credential mechanism.

Investors who trade based on good research are said to be the backbone of stock markets: They conduct research to discover the value of stocks and, through their trading, guide financial prices to reflect true value. What can make their job difficult is that high-speed, short-term traders could use machine learning and other technologies to infer when informed investors are trading.

Economists disagree about the factors driving the substantial increase in residual wage inequality in the United States over the past few decades. To identify changes in the returns to unobserved skills, we make a novel assumption about the dynamics of skills (especially among older workers) rather than about the stability of skill distributions across cohorts, as is standard.

During the COVID-19 pandemic, Canadian financial institutions offered debt-relief programs to help borrowers cope with job losses and economic insecurity. We consider the low take-up rates for these programs and suggest that to be effective, such programs must be visible and easy to use.

We study the effects of financial frictions on firm exit when firms face large liquidity shocks. We develop a simple model of firm cost-minimization that introduces a financial friction that limits firms’ borrowing capacity to smooth temporary shocks to liquidity.

Time-varying capital buffer requirements are a powerful tool that allow bank regulators to avoid severe financial stress without the cost of imposing very high levels of capital. However, this tool is only effective if banks understand how it is used. I present a model that banks and financial market participants can use to anticipate how time-varying capital buffer requirements change over time.

Growth in potential output is expected to drop from 2.3% in 2025 to 1.2% in 2026 given slowing population growth, US tariffs and trade policy uncertainty. It is then estimated to pick up to an average of 1.5% over 2027–29 as strengthening business and government investment supports trend labour productivity (TLP). Gradual adoption of artificial intelligence is also expected to lift TLP growth over the projection horizon.