Yunjong Eo

We propose the use of likelihood-ratio-based confidence sets for the timing of structural breaks in parameters from time series regression models. The confidence sets are valid for the broad setting of a system of multivariate linear regression equations under fairly general assumptions about the error and regressors, and allowing for multiple breaks in mean and variance parameters. In our asymptotic analysis, we determine the critical values for a likelihood ratio test of a break date and the e

In this paper, we relax the assumption of constant regime-specific mean growth rates in Hamilton's (1989) two-state Markov-switching model of the business cycle. We introduce a random walk hierarchy prior for each regime-specific mean growth rate and impose a cointegrating relationship between the mean growth rates in recessionary and expansionary periods. By applying the proposed model to postwar U.S. real GDP growth (1947:Q4–2011:Q3), we uncover the evolving nature of the regime-specific mean

Summary We distinguish between the goods and services sectors in an unobserved components model of U.S. inflation. We find that prior to the early 1990s, both sectors contributed to volatility of aggregate trend inflation, while since then, this has been predominantly driven by the services sector, with the trend in goods inflation being essentially flat. We document that the large reduction in the volatility of the trend for goods inflation has been the most important driver of the decline in t

I consider complicated patterns of structural breaks in postwar quarterly US inflation rates based on the CPI and the GDP deflator over the period from 1953:Q1 to 2013:Q4. Bayesian model selection procedures suggest that the two inflation measures had distinct structural changes in different parameters as well as at different dates. CPI inflation experienced a dramatic drop in persistence around the early 1980s, but GDP deflator inflation remains persistent throughout the postwar sample period.

I estimate DSGE models with recurring regime changes in monetary policy (inflation target and reaction coefficients), technology (growth rate and volatil-ity), and/or nominal price rigidities. In the models, agents are assumed to know deep parameter values but make probabilistic inference about prevailing and future regimes based on Bayes ’ rule. I develop an estimation method that takes these probabilistic inferences into account when relating state variables to observed data. In an application

Abstract How and under what circumstances can adjusting the inflation target serve as a stabilization‐policy tool and contribute to welfare improvement? We answer these questions quantitatively with a standard New Keynesian model that includes cost‐push‐type shocks. Our proposed inflation target rule calls for the target to be adjusted in a persistent manner and in the opposite direction to the realization of a cost‐push shock, which is essentially a makeup strategy. The inflation target rule, c