{"title":"跨国公司进入模式的选择:我的600万次回归","authors":"Magdalena Ramada-Sarasola","doi":"10.2139/ssrn.1445422","DOIUrl":null,"url":null,"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.","PeriodicalId":165362,"journal":{"name":"ERN: Discrete Regression & Qualitative Choice Models (Single) (Topic)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Determining the Choice of Entry Mode of Multinationals: My 6 Million Regressions\",\"authors\":\"Magdalena Ramada-Sarasola\",\"doi\":\"10.2139/ssrn.1445422\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":165362,\"journal\":{\"name\":\"ERN: Discrete Regression & Qualitative Choice Models (Single) (Topic)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Discrete Regression & Qualitative Choice Models (Single) (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.1445422\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Discrete Regression & Qualitative Choice Models (Single) (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.1445422","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Determining the Choice of Entry Mode of Multinationals: My 6 Million Regressions
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.