Search

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.

We develop a model with firm heterogeneity in importing and cross-border shopping among consumers. Exchange-rate appreciations lower the cost of imported goods, but also lead to more cross-border shopping; hence, the net impact on aggregate retail prices and sales is ambiguous.

We study the importance of supply constraints in explaining the heterogeneity in house price cycles across geographies in the United States.

This equilibrium model explains the trend in long-term yields and business-cycle movements in short-term yields and yield spreads. The less-frequent inverted yield curves (and less-frequent recessions) after the 1990s are due to recent secular stagnation and procyclical inflation expectations.

Exporters frequently change their market destinations. This paper introduces a new approach to identifying the drivers of these decisions over time. Analysis of customs data from China and the UK shows most changes are driven by demand rather than supply-related shocks.

The Canadian overnight repo market persistently shows signs of latent funding pressure around month-end periods. Both the overnight repo rate and Bank of Canada liquidity provision tend to rise in these windows. This paper proposes three non-mutually exclusive hypotheses to explain this phenomenon.

The Canadian economy continued to expand robustly in 2000 while inflation remained low.

Modeling and estimating persistent discrete data can be challenging. In this paper, we use an autoregressive panel probit model where the autocorrelation in the discrete variable is driven by the autocorrelation in the latent variable. In such a non-linear model, the autocorrelation in an unobserved variable results in an intractable likelihood containing high-dimensional integrals.

We analyze 40 years’ worth of natural disasters using a local projection framework to assess their impact on provincial labour markets in Canada. We find that disasters decrease hours worked within a week and lower wage growth in the medium run. Our study highlights that disasters affect vulnerable workers through the income channel.

The exponential family, relative entropy, and distortion are methods of transforming probability distributions. We establish a link between those methods, focusing on the relation between relative entropy and distortion.