Title page for ETD etd-04242003-104034


Type of Document Dissertation
Author Edwards, Jeffrey A
URN etd-04242003-104034
Title A Statistical Approach to Empirical Macroeconomic Modeling with Practical Applications
Degree PhD
Department Economics
Advisory Committee
Advisor Name Title
Cothren, Richard D. Committee Co-Chair
McGuirk, Anya M. Committee Co-Chair
Ball, Sheryl B. Committee Member
Spanos, Aris Committee Member
Yang, Dennis T. Committee Member
Keywords
  • Mundell-Tobin Effect
  • Inflation
  • Growth
  • Misspecification Testing
  • Statistical Specification
Date of Defense 2003-04-23
Availability unrestricted
Abstract
Most of empirical modeling involves the use of Ordinary Least Squares regression where the residuals are assumed normal, independent, and identically distributed. In finite samples, these assumptions becomes critical for accurate estimations, however, in macroeconomics in particular, these assumptions are rarely tested. This study addresses the applications of statistical testing methods and model respecification within the context of applied macroeconomics.

The first application is a statistical comparison of Gregory Mankiw, David Romer and David Weil’s

A Contribution to the Empirics of Economic Growth, and Nazrul Islam’s Growth Empirics: A Panel Data Approach. This analysis shows that the models in both papers are statistically misspecified. When respecified, the functional forms of Mankiw, Romer, and Weil’s models change considerably whereas Islam’s retain the theoretical structure. The second application is a study of the impact of inflation on investment and growth. After instrumenting for inflation with a set of political variables, I find that between approximately 1% and 9% inflation, there is a positive correlation between inflation and investment--the Mundell-Tobin effect may be a valid explanation. I further this analysis

to show that treating investment as an exogenous variable may be problematic in empirical growth

models.

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