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Dynamic general-equilibrium models (DGEMs) are being increasingly used in macroeconomic research. In this article, the author describes the main features of these models and outlines their contribution to economic research performed at the Bank of Canada. He notes that the basic principle of DGEMs is that the modelling of economic activity, even on a scale as large as the economy of a country, should start with a series of microeconomic problems (at the scale of individuals), which, once resolved, are aggregated to represent the macroeconomic reality described by the model.

We demonstrate the usefulness of payment systems data and machine learning models for macroeconomic predictions and provide a set of econometric tools to overcome associated challenges.

This paper studies the relationship between bank holding company affiliation and the individual and systemic risk of banks. Using the 2005 hurricane season in the US as an exogenous shock to bank balance sheets, we show that banks that are part of a holding parent company are more resilient than independent banks.

We ask whether a weaker contribution of information and communication technologies (ICT) to productivity growth could account for the productivity slowdown observed in Canada since the early 2000s. To answer this question, we consider several methods capturing channels through which ICT could affect aggregate productivity growth.

When China joined the World Trade Organization in December 2001, it marked a watershed for the world economy. Ten years from now, the opening of China’s capital account and the financial integration that will unfold will be viewed as a milestone of similar importance.

I develop a population-based Markov chain Monte Carlo algorithm known as parallel tempering to estimate dynamic stochastic general equilibrium models. Parallel tempering approximates the posterior distribution of interest using a family of Markov chains with tempered posteriors.

This paper studies the effects of financial development, taking into account both formal and informal financing. Using cross-country firm-level data, we document that informal financing is utilized more by rich countries than poor countries.

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.

We use graphic processing unit computing to compare Bayesian and sample theory semiparametric binary response models. Our findings show that optimal bandwidth does not outperform regular bandwidth in binary semiparametric models.

The degree to which financial constraint is binding is often not directly observable in commonly used business data sets (e.g., Compustat). In this paper, we measure and estimate the likelihood of a firm being constrained by external financing using a data set of small- and medium-sized Canadian firms.