The Effects of Model Specification on Foreign Direct Investment Models: an Application of Count Data Models

Citation data:

Southern Economic Journal, ISSN: 0038-4038, Vol: 67, Issue: 2, Page: 460-468

Publication Year:
2000
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Repository URL:
http://stars.library.ucf.edu/facultybib/4731; http://stars.library.ucf.edu/facultybib2000/2826
DOI:
10.2307/1061481
Author(s):
Ka Saundra M. Tomlin
Publisher(s):
JSTOR
Tags:
Economics, Econometrics and Finance; EXCHANGE-RATES; UNITED-STATES; UNCERTAINTY; ENTRY; FIRMS; Economics
article description
Previous studies have drawn a theoretical and empirical connection between foreign direct investment (FDI) and exchange rates using continuous measures of FDI. However, FDI data are often in discrete count form. I take a representative study of the FDI/exchange rate relationship by Jose M. Campa (1993), and I analyze the sensitivity of the results to specification of the dependent variable. Whereas Campa uses a Tobit specification, I use a count data specification to model counts of FDI occurrences. Using data on FDI in the United States from 1982 to 1993, controlling for the traditional determinants of FDI, I find that the results are sensitive across specifications. Significance levels and the magnitude of the coefficients change when going from a continuous Tobit specification to a zero inflated Poisson (ZIP) model designed for count data. Formal statistical testing finds that the ZIP specification likely models the data most properly. Thus, I indicate that misspecification bias from modeling discrete data with continuous distributions is important.