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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
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    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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    Bibliographic Info

    Article provided by Southern Economic Association in its journal Southern Economic Journal.

    Volume (Year): 67 (2000)
    Issue (Month): 2 (July)
    Pages: 460-468

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    Handle: RePEc:sej:ancoec:v:67:2:y:2000:p:460-468

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    Cited by:
    1. Gregory Price, 2008. "NEA Presidential Address: Black Economists of the World You Cite!!," The Review of Black Political Economy, Springer, Springer, vol. 35(1), pages 1-12, March.
    2. Russ, Katheryn Niles, 2007. "The endogeneity of the exchange rate as a determinant of FDI: A model of entry and multinational firms," Journal of International Economics, Elsevier, Elsevier, vol. 71(2), pages 344-372, April.
    3. Bruce Blonigen, 2005. "A Review of the Empirical Literature on FDI Determinants," Atlantic Economic Journal, International Atlantic Economic Society, International Atlantic Economic Society, vol. 33(4), pages 383-403, December.
    4. Fujita, Yasunori, 2007. "Toward a new modeling of international economics: An attempt to reformulate an international trade model based on real option theory," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 383(2), pages 507-512.
    5. Katheryn Russ, 2012. "Exchange rate volatility and first-time entry by multinational firms," Review of World Economics (Weltwirtschaftliches Archiv), Springer, Springer, vol. 148(2), pages 269-295, June.
    6. Wang, Peiming & Alba, Joseph D., 2006. "A zero-inflated negative binomial regression model with hidden Markov chain," Economics Letters, Elsevier, Elsevier, vol. 92(2), pages 209-213, August.
    7. Phillips, Shauna & Ahmadi-Esfahani, Fredoun Z., . "Exchange Rates and Foreign Direct Investment: Theoretical Models and Empirical Evidence," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, Australian Agricultural and Resource Economics Society.
    8. George Dikos & Dimitrios Thomakos, 2012. "Econometric testing of the real option hypothesis: evidence from investment in oil tankers," Empirical Economics, Springer, Springer, vol. 42(1), pages 121-145, February.
    9. Chin-Tsai Lin & Cheng-Ru Wu, 2004. "Decision for the Optimal Location -- Waiting Timing Relationship in A Real Options Model," Annals of Economics and Finance, Society for AEF, vol. 5(2), pages 271-282, November.

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