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The role of foreign direct investment in the host-country firm selection process: firm-level evidence from Slovenian manufacturing

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Abstract

This paper examines the role of inward foreign direct investment (FDI) in firm selection processes in the Slovenian manufacturing sector in the 1994–2003 period. It adopts the firm dynamics framework that allows testing of selection effects directly by assessing the impact of foreign firms’ activity on the probability of exiting of local firms (crowding out). The results show that intra-industry productivity spillover effects offset only a minor part of the competition pressure which results from foreign firm entry, hence incumbent firms experience a drop in their survival probability upon a foreign firm’s entry within a particular industry. This result is driven by foreign firm entry of the greenfield type, as entry through the acquisition of existing firms has no significant effect. The strength of the crowding-out effect decreases with the incumbent firm’s export propensity. There is no significant evidence that inward FDI would stimulate the selection process through backward linkages in the upstream supplying industries, whereas foreign firms’ activity reduces the exit probability of downstream local customers (through forward linkages).

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Notes

  1. These externalities may appear since foreign firms may not be able to fully internalise their technological advantages and therefore their presence would lead to various types of productivity spillovers to domestic firms.

  2. Financial data were obtained from the database of firms’ financial statements collected by the Agency of the Republic of Slovenia for Public Legal Records and Related Services. The data on firms’ formation, legal and organisational forms and termination of operation were obtained from the Business Register of Slovenia. Other data were provided by the Statistical Office of Republic of Slovenia.

  3. The index of productivity, ω, is known to the firm and evolves over time according to an exogenous Markov process. The distribution of ωt conditional on all information known at t is determined by the family of distribution functions Fω = {F(·|ω), ω∈Ω}.

  4. The capital stock at the beginning of the next period is thus determined by k t+1 = (1 − δ)k t  + i t .

  5. Firm’s true age counted from its formation year according to the Business Register is corrected in case the firm has been established before the start of transition (before 1991) since pre-transitional experiences cannot be equalized with post-transition ones with regard to a firm’s learning process. In this case age is counted from the year 1991 onwards.

  6. There is a relationship between a producer's underlying efficiency and the incentive to invest in capital. Essentially, efficient firms generate higher levels of investment and larger capital stocks.

  7. Such specification based on the employment share of foreign firms is used in several studies testing the presence of horizontal spillover effects (among others in Barrios et al. 2005; Keller and Yeaple 2003; Görg and Strobl 2003).

  8. Technical coefficients α jk and δ jk are obtained from the input–output table, more specifically from ‘Use table for the domestic output at basic prices’. As the input–output table for the Slovenian economy is not available for all years in our 1994–2003 sample, the year 2000s I–O table was chosen as a base for the technical (input) coefficient calculation. BackFDI jt and ForFDI jt are constructed at the 2-digit level of NACE which is the most detailed level of the I–O table available.

  9. The impact of vertical FDI is robust to inclusion of controlling variables that measure the general concentration of economic activity in interrelated industries defined as backwardly and forwardly linked industries’ share of total manufacturing employment weighted by technical coefficients α and δ.

  10. I perform instrumental variable probit estimates using the STATA module developed by Gelbach (1999, [http://fmwww.bc.edu/repec/bocode/p/probitiv.ado]).

  11. Marginal effects refer to the marginal probability change at the mean of independent variables or the change in probability for a discrete change in a dummy variable from 0 to 1.

  12. For instance, Damijan et al. (2003) for Czech Republic, Poland and Slovenia, and Smarzynska (2004) for Lithuania.

  13. According to Table 3 one structural point increase in MNEentry variable represents roughly a 100% increase compared to its mean value.

  14. The results of cloglog empirical specification with joint foreign firm entry variable (MNEentry) included are not reported in Table 4. The results can be obtained from the author.

  15. According to Table 3 one tenth of structural point increase in GREENentry variable represents roughly a 33% increase compared to its mean value.

  16. »Rho« is the ratio of the heterogeneity variance to one plus the heterogeneity variance. Chibar2(01) statistics is 0.11 with prob ≥ chibar2 = 0.372.

  17. I test robustness of the results by estimating both, an IV model in which I instrument for foreign ownership without distinguishing between different types of foreign investment, and an IV model in which I instrument for foreign ownership only in case of acquisition-type foreign investments. The IV model results can be obtained from the author upon request.

References

  • Ai, C., & Norton, E. C. (2003). Interaction terms in logit and probit models. Economics Letters, 80(1), 123–129.

    Article  Google Scholar 

  • Barrios, S., Görg, H., & Strobl, E. (2005). Foreign direct investment, competition and industrial development in the host country. European Economic Review, 49(7), 1761–1784.

    Article  Google Scholar 

  • Bernard, A. B., Eaton, J., Jensen, B. J., & Kortum, S. (2003). Plants and productivity in international trade. American Economic Review, 93(4), 1268–1290.

    Article  Google Scholar 

  • Bernard, A. B., & Jensen, B. J. (2002). The deaths of manufacturing plants (Working paper 9026). Cambridge, Mass: National bureau of economic research.

  • Blomström, M., & Kokko, A. (1997). The impact of foreign investment on host countries: A review of the empirical evidence (Policy Research Working Paper 1745). Washington, D.C.: The World Bank.

  • Blomström, M., & Kokko, A. (1998). Multinational corporations and spillovers. Journal of Economic Surveys, 12(3), 247–277.

    Article  Google Scholar 

  • Caves, R. E. (1996). Multinational enterprise and economic analysis. Cambridge: Cambridge University Press.

    Google Scholar 

  • Chamberlain, G. (1984). Panel data. In Z. Griliches & M. D. Intriligator (Eds.), Handbook of econometrics (Vol. 2). Amsterdam: North Holland.

    Google Scholar 

  • Damijan, J. P., Knell, M., Majcen, B., & Rojec, M. (2003). Technology transfer through FDI in top-10 transition countries: How important are direct effects, horizontal and vertical spillovers? (Working paper 549). Ann Arbor, Mich.: William Davidson Institute.

  • De Backer, K., & Sleuwaegen, L. (2003). Does foreign direct investment crowd out domestic entrepreneurship? Review of Industrial Organization, 22(1), 67–84.

    Article  Google Scholar 

  • Djankov, S., & Hoekman, B. (2000). Foreign investment and productivity growth in Czech enterprises. World Bank Economic Review, 14(1), 49–64.

    Google Scholar 

  • Ericson, R., & Pakes, A. (1995). Markov-perfect industry dynamics: A framework for empirical work. Review of Economic Studies, 62(1), 53–82.

    Article  Google Scholar 

  • Evans, D. S. (1987). The relationship between firm growth, size, and age: Estimates for 100 manufacturing industries. Journal of Industrial Economics, 35(4), 567–581.

    Article  Google Scholar 

  • Evenett, S. J., & Voicu, A. (2001). Picking winners or creating them? Revisiting the benefits of FDI in the Czech Republic. Mimeo, Washington: The World Bank.

    Google Scholar 

  • Gelbach, J. B. (1999). Stata module to perform instrumental variables probit. http://fmwww.bc.edu/repec/bocode/p/probitiv.ado. Accessed 19 April 2008.

  • Görg, H., & Strobl, E. (2003). Multinational companies, technology spillovers and plant survival. Scandinavian Journal of Economics, 105(4), 581–595.

    Article  Google Scholar 

  • Hall, B. H. (1987). The relationship between firm size and firm growth in the US manufacturing sector. Journal of Industrial Economics, 35(4), 583–600.

    Article  Google Scholar 

  • Harvey, A. C. (1976). Estimating regression models with multiplicative heteroscedasticity. Econometrica, 44(3), 461–465.

    Article  Google Scholar 

  • Jenkins, S. P. (2004). Survival analysis, Unpublished manuscript, Institute for Social and Economic Research, University of Essex, Colchester, UK. http://www.iser.essex.ac.uk/files/teaching/stephenj/ec968/pdfs/ec968lnotesv6.pdf. Accessed 11 May 2010.

  • Jovanović, B. (1982). Selection and the evolution of industry. Econometrica, 50(3), 649–670.

    Article  Google Scholar 

  • Keller, W., & Yeaple, S. (2003). Multinational enterprises, international trade, and productivity growth: Firm-level evidence from the United States. (GEP Research Paper, No 3). Nottingham: University of Nottingham.

  • Konings, J., & Xavier, A. (2002). Firm growth and survival in a transition country: Micro evidence from Slovenia. (LICOS Discussion paper 11402). Katholieke Universiteit Leuven.

  • Kosová, R. (2006). Do foreign firms crowd out domestic firms? The evidence from the Czech Republic. (Working Paper 0006). Washington: School of Business, The George Washington University.

  • Levinsohn, J. A., & Petrin, A. (2003). Estimating production functions using inputs to control for unobservables. The Review of Economic Studies, 70(2), 317–341.

    Article  Google Scholar 

  • Melitz, M. (2003). The impact of trade on intra-industry reallocations and aggregate industry productivity. Econometrica, 71(6), 1695–1726.

    Article  Google Scholar 

  • Mundlak, Y. (1978). On the pooling of time series and cross section data. Econometrica, 46(1), 69–85.

    Article  Google Scholar 

  • Newey, W. K. (1987). Efficient estimation of limited dependent variable models with endogenous explanatory variables. Journal of Econometrics, 36(3), 231–250.

    Article  Google Scholar 

  • Olley, S., & Pakes, A. (1996). The dynamics of productivity in the telecommunications equipment industry. Econometrica, 64(6), 1263–1297.

    Article  Google Scholar 

  • Pavcnik, N. (2002). Trade liberalization, exit, and productivity improvements: Evidence from Chilean plants. The Review of Economic Studies, 69(238), 245–276.

    Google Scholar 

  • Prentice, R., & Gloeckler, L. (1978). Regression analysis of grouped survival data with application to breast cancer data. Biometrics, 34(1), 57–67.

    Article  Google Scholar 

  • Rivera-Batiz, F., & Rivera-Batiz, L. (1991). The effects of direct foreign direct investment in the presence of increasing returns due to specialization. Journal of Development Economics, 34(1–2), 287–307.

    Google Scholar 

  • Roberts, M. J., & Tybout, J. R. (1996). Industrial evolution in developing countries: Micro patters of turnover, productivity, and market structure. Oxford: Oxford University Press.

    Google Scholar 

  • Smarzynska, J. B. (2004). Does foreign direct investment increase the productivity of domestic firms? In search of Spillovers through backward linkages. American Economic Review, 94(3), 605–627.

    Article  Google Scholar 

  • Tybout, J. R. (2003). Plant- and firm-level evidence on the ‘new’ trade theories. In E. K. Choi & J. Harrigan (Eds.), Handbook of international trade. Oxford: Basil-Blackwell.

    Google Scholar 

  • Wooldridge, J. M. (2002). Econometric analysis of cross section and panel data. Cambridge, Mass: The MIT Press.

    Google Scholar 

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Acknowledgments

I am particularly grateful to M. Motta and A. Kumar for invaluable advice and comments. I would also like to thank referees and editor for helpful comments. Any remaining errors are mine.

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  1. Faculty of Economics, University of Ljubljana, Kardeljeva pl. 17, 1000, Ljubljana, Slovenia

    Katja Zajc Kejžar

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Zajc Kejžar, K. The role of foreign direct investment in the host-country firm selection process: firm-level evidence from Slovenian manufacturing. Rev World Econ 147, 169–193 (2011). https://doi.org/10.1007/s10290-010-0077-3

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