In this paper, we develop a Bayesian approach to counterfactual analysis of structural change. Contrary to previous analysis based on classical point estimates, this approach provides a straightforward measure of estimation uncertainty for the counterfactual quantity of interest. We apply the...

In this paper, we present a new approach to trend/cycle decomposition under the assumption that the trend is the permanent component and the cycle is the transitory component of an integrated time series. The permanent component is defined as the steady-state level of the series, a definition...

This paper considers the ability of simulated data from linear and nonlinear time-series models to reproduce features in U.S. real GDP data related to business cycle phases. We focus our analysis on a number of linear ARIMA models and nonlinear Markov-switching models. To determine the timing of...

We investigate the importance of trend inflation and the real-activity gap for explaining observed inflation variation in G7 countries since 1960. Our results are based on a bivariate unobserved-components model of inflation and unemployment in which inflation is decomposed into a stochastic...

In this paper, we develop a Bayesian approach to counterfactual analysis of structural change. Contrary to previous analysis based on classical point estimates, this approach provides a straightforward measure of estimation uncertainty for the counterfactual quantity of interest. We apply the...

The business cycle is a fundamental yet elusive concept in macroeconomics. In this paper, we consider the problem of measuring the business cycle. First, we argue for the output-gap view that the business cycle corresponds to transitory deviations in economic activity away from a permanent, or...

In this paper, we consider the ability of time-series models to generate simulated data that display the same business cycle features found in U.S. real GDP. Our analysis of a range of popular time-series models allows us to investigate the extent to which multivariate information can account...

This paper presents a new nonlinear time series model that captures a post-recession 'bounce-back' in the level of aggregate output. While a number of studies have examined this type of business cycle asymmetry using recession-based dummy variables and threshold models, we relate the...

This paper presents a new approach to trend/cycle decomposition. The trend of an integrated time series is measured as the conditional expectation of the steady-state level of the series, where steady state is determined by simulation from an appropriate forecasting model. By explicitly linking...

This paper presents a new nonlinear time series model that captures a post-recession “bounce-back” in the level of aggregate output. While a number of studies have examined this type of business cycle asymmetry using recession-based dummy variables and threshold models, we relate the...