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

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  • KaSaundra M. Tomlin

Abstract

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.

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  • KaSaundra M. Tomlin, 2000. "The Effects of Model Specification on Foreign Direct Investment Models: An Application of Count Data Models," Southern Economic Journal, John Wiley & Sons, vol. 67(2), pages 460-468, October.
    • Handle: RePEc:wly:soecon:v:67:y:2000:i:2:p:460-468
    DOI: 10.1002/j.2325-8012.2000.tb00347.x
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    References listed on IDEAS

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    Cited by:

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