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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.

US trade protectionism is making the economic outlook increasingly uncertain. To assess how consumer prices may respond to tariffs, we examine a tariff episode from 2018 using detailed microdata and the synthetic control method.

We propose a model to understand low observed migration rates by considering the interaction between location and wealth decisions. We look at different policies and find that temporary moving vouchers only slightly increase welfare, while lower housing regulations can decrease the welfare gap by lowering house prices nationwide.

Using a two-stage model, we study the determinants of Canadian consumers’ choices of payment method at the point of sale. We estimate consumer preferences and adoption costs for various combinations of payment methods. We analyze how introducing a central bank digital currency would affect the market equilibrium.

Models for macroeconomic forecasts do not usually take into account the risk of a crisis—that is, a sudden large decline in gross domestic product (GDP). However, policy-makers worry about such GDP tail risk because of its large social and economic costs.

This paper addresses an existing gap in the developing literature on conditional skewness. We develop a simple procedure to evaluate parametric conditional skewness models. This procedure is based on regressing the realized skewness measures on model-implied conditional skewness values.

In this paper, the author uses the term structure of nominal interest rates to construct estimates of agents' expectations of inflation over several medium-term forecast horizons. The Expectations Hypothesis is imposed together with the assumption that expected future real interest rates are given by current real rates. Under these maintained assumptions, it is possible to […]

The authors study the macroeconomic consequences of large military buildups using a New Neoclassical Synthesis (NNS) approach that combines nominal rigidities within imperfectly competitive goods and labour markets. They show that the predictions of the NNS framework generally are consistent with the sign, timing, and magnitude of how hours worked, after-tax real wages, and output actually respond to an upsurge in military purchases.

We examine local labor markets in the United States and Canada from 1990 to 2011 using comparable household and business data. Wage levels and inequality rise with city population in both countries, albeit less in Canada.

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.