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This paper examines the business cycle linkages that propagate industry-specific business cycle shocks throughout the economy in a way that (sometimes) generates aggregated cycles. The transmission of sectoral business cycles is modelled through a multivariate Markov-switching model, which is estimated by Gibbs sampling.

Macroeconomists have traditionally ignored the behavior of temporary price markdowns (“sales”) by retailers. Although sales are common in the micro price data, they are assumed to be unrelated to macroeconomic phenomena and generally filtered out.

This paper provides a framework for the early assessment of current U.S. nominal GDP growth, which has been considered a potential new monetary policy target. The nowcasts are computed using the exact amount of information that policy-makers have available at the time predictions are made. However, real-time information arrives at different frequencies and asynchronously, which poses challenges of mixed frequencies, missing data and ragged edges.

This paper proposes a Markov-switching framework to endogenously identify the following: (1) regimes where economies synchronously enter recessionary and expansionary phases; and (2) regimes where economies are unsynchronized, essentially following independent business cycles.

We build an otherwise-standard business cycle model with housework, calibrated consistently with data on time use, in order to discipline consumption-hours complementarity and relate its strength to the size of fiscal multipliers.

This paper studies the effects of a monetary policy expansion in the United States during times of high financial stress. The analysis is carried out by introducing a smooth transition factor model where the transition between states (“normal” and high financial stress) depends on a financial conditions index.

Forecasts of the price of crude oil play a significant role in the conduct of monetary policy, especially for commodity producers such as Canada. This article presents a range of recently developed forecasting models that, when pooled together, can generate, on average, more accurate forecasts of the price of oil than the oil futures curve. It also illustrates how policy-makers can evaluate the risks associated with the baseline oil price forecast and how they can determine the causes of past oil price fluctuations.

We incorporate a participation decision in a standard New Keynesian model with matching frictions and show that treating the labor force as constant leads to incorrect evaluation of alternative policies.

We construct a small-open-economy, New Keynesian dynamic stochastic general-equilibrium model with real-financial linkages to analyze the effects of financial shocks and macroprudential policies on the Canadian economy. Our model has four key features.

We provide evidence regarding the dynamic behaviour of net labour flows across U.S. states in response to a positive technology shock. Technology shocks are identified as disturbances that increase relative state productivity in the long run for 226 state pairs, encompassing 80 per cent of labour flows across U.S. states in the 1976 - 2008 period.