Dissertation Defenses

Doctoral Dissertation Announcement

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Candidate: Lezheng Liu

Degree of: Doctor of Philosophy

Department: Economics

Title: Empirical Essays on Inflation and Economic Growth

Committee:
Dr. C. James Hueng, Chair
Dr. Matthew Higgins
Dr. Joseph W. McKean

Date: Wednesday, July 11, 2007 10:00 a.m.- 12:00 p.m.
5302 Friedmann Hall

Abstract:
This dissertation collects three empirical essays on inflation and economic growth. Chapter 1 examines the impact of inflation uncertainty on the level of inflation. Uncertainty is measured by the conditional variance of inflation, and inflation is modeled as a GARCH-in-mean process with a two-regime Markov-switching coefficient on uncertainty. Using a Bayesian estimator with the Markov Chain Monte Carlo approach, we find that the impacts of uncertainty on inflation are statistically significant and have different signs in different regimes for the U.S. post-war data. The regime switching nature of the inflation process can explain the contradictory theoretical predictions and empirical evidence shown in the existing literature.
In Chapter 2, we develop a time-varying parameter model with survey information to forecast future inflation rates. To capture the inflation dynamics, we first specify quarterly U.S. inflation as an AR (2) process with time-varying unobservable parameters. The model is estimated by the Kalman filter algorithm. We then examine survey data information by combining Survey of Professional Forecasters (SPF) forecasts into the model. Compared to survey data and the classical ARIMA models, the time-varying parameter models significantly reduce out-of-sample prediction errors. We find that the improvement lies in the time-varying feature of the models and that including survey data does not significantly improve predictive ability, indicating that the survey data does not contain too much information beyond realized inflation rates.
Chapter 3 re-examines the convergence hypothesis by using a revised four-step procedure of the panel unit root test suggested by Evans and Karras (1996). We use data on output for 24 OECD countries over 40 years. We incorporate the spatial autoregressive error structure into a fixed-effect panel model to account for spatial dependence that may induce significant size distortion of the conventional panel unit root tests. In contrast to the results obtained from the test that does not consider the spatial error structure, our results indicate that there is no output convergence among the OECD countries.