scholarly journals Size of foreign direct investment and firm characteristics

2018 ◽  
Author(s):  
Hecht Veronika ◽  
Moritz Michael ◽  
Noska Patricia ◽  
Schäffler Johannes
Keyword(s):  
Foreign Direct Investment ◽  
Czech Republic ◽  
Direct Investment ◽  
Multinational Firms ◽  
Sample Selection ◽  
Indirect Measurement ◽  
Empirical Literature ◽  
Firm Level ◽  
Data Set ◽  
The Czech Republic

This paper focuses on the role of classifying types of foreign direct investment (FDI) for analysing the determinants of cross-border investment relationships. We base our investigation on a newly established firm-level data set of German multinational firms and their affiliates in the Czech Republic that allows various categorisations into vertical foreign direct investment (VFDI) and horizontal foreign direct investment (HFDI). Apart from data for conventional approaches to classifying FDI types, the surveyed information contained herein also includes a detailed self-assessment of the firms with respect to investment motives, and specifications on intra-firm trade and the flow of intermediate inputs. In order to correct for sample selection, we apply a two-step Heckman procedure by comparing multinational firms that have an affiliate in the Czech Republic to companies without investment abroad. The results for the direct measures of FDI types confirm theoretical expectations and previous empirical literature and stand in marked contrast to the outcome for indirect measurement concepts. Our finding leads us to the conclusion that one should be more cautious in interpreting differences between vertical and horizontal FDI when using approximative classification concepts.

scholarly journals Size of foreign direct investment and firm characteristics

2018 ◽  
Author(s):  
Hecht Veronika ◽  
Moritz Michael ◽  
Noska Patricia ◽  
Schäffler Johannes
Keyword(s):  
Foreign Direct Investment ◽  
Czech Republic ◽  
Direct Investment ◽  
Multinational Firms ◽  
Sample Selection ◽  
Indirect Measurement ◽  
Empirical Literature ◽  
Firm Level ◽  
Data Set ◽  
The Czech Republic

This paper focuses on the role of classifying types of foreign direct investment (FDI) for analysing the determinants of cross-border investment relationships. We base our investigation on a newly established firm-level data set of German multinational firms and their affiliates in the Czech Republic that allows various categorisations into vertical foreign direct investment (VFDI) and horizontal foreign direct investment (HFDI). Apart from data for conventional approaches to classifying FDI types, the surveyed information contained herein also includes a detailed self-assessment of the firms with respect to investment motives, and specifications on intra-firm trade and the flow of intermediate inputs. In order to correct for sample selection, we apply a two-step Heckman procedure by comparing multinational firms that have an affiliate in the Czech Republic to companies without investment abroad. The results for the direct measures of FDI types confirm theoretical expectations and previous empirical literature and stand in marked contrast to the outcome for indirect measurement concepts. Our finding leads us to the conclusion that one should be more cautious in interpreting differences between vertical and horizontal FDI when using approximative classification concepts.

scholarly journals The political determinants of foreign direct investment: a firm-level analysis

2018 ◽  
Author(s):  
Vincent Arel-Bundock
Keyword(s):  
Foreign Direct Investment ◽  
Political Institutions ◽  
Direct Investment ◽  
Multinational Firms ◽  
Statistical Significance ◽  
Machine Learning Techniques ◽  
The Political ◽  
Firm Level ◽  
Data Set ◽  
Political Determinants

Many large-N cross-national studies claim to show that political institutions and phenomena determine where foreign direct investment (FDI) flows. In this article, I argue that these studies tend to overemphasize statistical significance and often neglect to assess the explanatory or predictive power of their theories. To illustrate the problem, I estimate variations of a statistical model published in an influential article on “Political Risk, Institutions, and FDI.” I find that none of the political variables that the authors consider accounts for much of the variation in aggregate FDI inflows. To ensure that this underwhelming result is not driven by misspecification or measurement error, I leverage a large firm-level data set on the investment location decisions of thousands of multinational firms. Using nonparametric machine-learning techniques and out-of-sample tests, I show that gravity variables can help us develop very accurate expectations about firm behavior but that none of the 31 “political determinants” of FDI that I consider can do much to improve our expectations. These findings have important implications because they suggest that governments retain some room to move in the face of economic globalization.

Does Social Capital Matter in the Location Decision of Foreign Direct Investment? Evidence from Korea

2016 ◽  
Vol 15 (2) ◽  
pp. 71-102 ◽  
Author(s):  
Jong-Il Choe ◽  
Ki-Dong Lee
Keyword(s):  
Social Capital ◽  
Foreign Direct Investment ◽  
Direct Investment ◽  
Multinational Firms ◽  
Location Factors ◽  
Firm Level ◽  
Data Set ◽  
Agglomeration Externalities ◽  
Knowledge Based ◽  
High Level

Social capital refers to the stock of social relationships such as network, norms, and trust that facilitate both coordination and cooperation. Utilizing an extensive firm-level data set for 2006–10, this paper investigates the importance of social capital in conjunction with the conventional location factors that are known to influence the location decisions of multinational firms within Korea. Our nested logit estimates show that the “Trust and Norms” component of social capital has a stronger influence on locational decisions than does the “Social Network” component. That is, regions in Korea characterized by a high level of “Trust and Norms” attract more knowledge-based foreign direct investment (FDI) firms than those with lower levels of trust and norms. In addition, positive agglomeration externalities are more powerful in regions with a higher level of trust and norms. Another important result of our analysis is the discovery that the regions with high unemployment levels and union activities are less attractive to foreign investors. On the basis of the results we conclude that measures that strengthen the trust and norms component of social capital should be fostered along with traditional cost-saving policies, which are used to attract FDI in Korea.

Investment Attractiveness of Visegrad Group Countries

2014 ◽  
pp. 740-775 ◽  
Author(s):  
Tomasz Dorożyński ◽  
Anetta Kuna-Marszałek
Keyword(s):  
Foreign Direct Investment ◽  
Czech Republic ◽  
Direct Investment ◽  
Economic Transformation ◽  
Geographic Proximity ◽  
The Czech Republic ◽  
Shared Experiences ◽  
Main Determinants ◽  
Political Economic ◽  
Visegrad Group

The aims of this chapter are to evaluate the main determinants of the inflow of FDI into selected countries of CEE and to examine the volume, dynamics, and structure of FDI inflow into these countries. Due to certain similarities, the authors focus the analysis on four countries: Poland, the Czech Republic, Hungary, and Slovakia. The reasons are geographic proximity, political, economic, and cultural similarities, as well as shared experiences of economic transformation. This chapter focuses on matters pertaining to foreign direct investment, mostly on the reasons motivating FDI inflow in light of selected studies and theories. The authors also provide characteristics of the dynamics and structure of FDI inflow into the V4 countries. The final part of the chapter compares investment attractiveness, the system of incentives, and identifies barriers facing investors in the analyzed countries.

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