We develop an N-regime Markov-switching model in which the latent state variable driving the regime switching is endogenously determined with the model disturbance term. The models structure captures a wide variety of patterns of endogeneity and yields a simple test of the null hypothesis of exogenous switching. We derive an iterative filter that generates objects of interest, including the model likelihood function and estimated regime probabilities. Using simulation experiments, we demonstrate that the maximum likelihood estimator performs well in finite samples and that a likelihood ratio test of exogenous switching has good size and power properties. We provide results from two applications of the endogenous switching model: a three-state model of US business cycle dynamics and a three-state volatility model of US equity returns. In both cases, we find statistically significant evidence in favor of endogenous switching.

We consider a model-averaged forecast-based estimate of the output gap to measure economic slack in 10 industrialized economies. Our measure takes changes in the long-run growth rate into account and, by addressing model uncertainty using equal weights on different forecast-based estimates, is robust to different assumptions about the underlying structure of the economy. For all 10 countries in the sample, we find that the estimated output gap has much larger negative movements during recessions than positive movements in expansions, suggesting business cycle asymmetry is an intrinsic characteristic of industrialized economies. Furthermore, the estimated output gap is always strongly negatively correlated with future output growth and unemployment and positively correlated with capacity utilization. It also implies a convex Phillips Curve in many cases. The model-averaged output gap is reliable in real time in the sense of being subject to relatively small revisions.

We examine the quantitative significance of financial frictions that reduce firms' access to credit in explaining asymmetric business cycles characterized by disproportionately severe downturns. Using rate spread data to calibrate the severity of these frictions, we successfully match several key features of U.S. data. Specifically, although output and consumption are relatively symmetric (with output being slightly more asymmetric), investment and hours worked display significant asymmetry over the business cycle. We also demonstrate that our financial frictions are capable of significantly amplifying adverse shocks during severe downturns. Although the data suggest that these frictions are only active occasionally, our results indicate that they are still a significant source of macroeconomic volatility over the business cycle.