Determining the Choice of Entry Mode of Multinationals: My 6 Million Regressions

59 Pages Posted: 9 Aug 2009

See all articles by Magdalena Ramada-Sarasola

Magdalena Ramada-Sarasola

Towers Watson; Innovation & Research Multiplier; ORT University - Uruguay

Date Written: August 7, 2009

Abstract

Motivated by the findings of Ramada-Sarasola (2009) and the lack of robustness of the previous literature’s results on foreign entry mode choice to model specification in this paper I perform an Extreme Bounds Analysis to determine which of almost 60 explanatory variables used in the literature are robust to different model specifications. I do so by following the methodology introduced in Sala-i-Martin (1997b) in a multinomial logit framework, based on 640 entries into foreign countries done by the largest 22 financial MNCs in the last 15 years. I suggest additional hypothesis to capture host-country level determinants and I improve the operationalization of industry level variables in a multi home-country and host-country setting. Amongst other results I find that an MNC’s size and its international experience increase the likelihood of greenfields as opposed to M&A or any type of entry mode involving a partner, and that more cultural distance between home and host country, a better developed local financial sector (or local credit market), a more regulated environment for obtaining licenses and more macroeconomic sustainability increase the chances of GI, while a worse local infrastructure, higher ITC costs and more difficulties in registering property and employing workers decrease its odds.

Keywords: Offshoring, foreign establishment mode, M&A, Greenfield investment, Extreme Bounds Analysis

JEL Classification: F23, R30, L10, G34, M13

Suggested Citation

Ramada-Sarasola, Magdalena, Determining the Choice of Entry Mode of Multinationals: My 6 Million Regressions (August 7, 2009). Towers Watson Technical Paper No. 1445422, Available at SSRN: https://ssrn.com/abstract=1445422 or http://dx.doi.org/10.2139/ssrn.1445422

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