Archived — Working Paper Number 37: National Political Infrastructure and Foreign Direct Investment

by Steven Globerman, Western Washington University and Daniel Shapiro, Simon Fraser University, December 2002


Introduction

It is widely argued that a country's economic performance over time is determined to a great extent by its political, institutional, and legal environment (OECD, 2001). We refer to these public institutions and policies as the national political infrastructure (NPI) of a country. The NPI thus comprises investments in effective political, economic and legal governance, which in most countries is the exclusive responsibility of the government.1

The national political infrastructure of a country helps to define its investment environment and thus creates favourable conditions for economic growth. Recent empirical evidence does in fact indicate that cross-country differences in growth and productivity are related to differences in political, institutional and legal environments (OECD, 2001; Hall and Jones, 1999; Keefer and Knack, 1997; Knack and Keefer, 1995; Kaufman et al. 1999b). Because the investment environment of a country affects both domestic and foreign investors, and because foreign direct investment (FDI) has been shown to promote host-country efficiency, it is a natural extension of the literature to consider the impact of NPI on cross-country differences in FDI flows. This report therefore focuses on the linkage between measures of national political infrastructure and FDI flows.

Specifically, we test the hypothesis that FDI will be attracted to regions characterized by more favourable NPIs, all other things constant. We also argue that countries with more favourable national political infrastructures will create more domestic multinational enterprises (MNEs), and they will therefore see more capital outflows, so that the net effect on capital flows may be uncertain.

We base our hypotheses on the "eclectic" theory of FDI (Dunning, 1980), which holds that multinational enterprises invest abroad in attractive locations by internalizing firm-specific (ownership) advantages. We suggest that one factor contributing to a location's attractiveness is its national political infrastructure. At the same time, a domestic environment that protects property rights and promotes economic transparency is likely to foster domestic innovation and thus firm-specific advantages which, in turn, result in capital outflows.

There is a relatively extensive empirical literature focusing on the characteristics of locations that seem to either attract or repel foreign investors.2 While it seems plausible that FDI will be attracted to regions characterized by more favourable political infrastructures, all other things constant, most of the relevant literature has focused on economic determinants of FDI inflows, and there is very little discussion of the determinants of capital outflows. It is, of course, true that the international business literature has acknowledged the importance of country-specific political risk (Kobrin, 1976). As a consequence, empirical analyses of FDI now routinely include some kind of variable to control for intercountry differences in the broad political environment (Tuman and Emmert, 1999; Mody and Srinivasan, 1998; Stevens, 2000; Bevan and Estrin, 2000; Morisset, 2000; Altomonte, 2000), albeit with somewhat mixed results (Dawson, 1998).3

It is difficult to generalize about the statistical impact of political governance attributes, in part because these attributes are measured in different ways in different studies. Moreover, although many previous studies adopt measures that are closely related to the notion of national political infrastructure, there has as yet been no systematic attempt to directly relate NPI measures to FDI flows for a wide cross-section of countries. Nor has there been much discussion regarding the specific infrastructure elements that are especially robust determinants of FDI.

In this study, we use newly developed indices to examine the effects of NPI on both FDI inflows and outflows for a broad sample of (at most) 144 developed and developing countries over the period 1995 to 1997. Specifically, we use the six governance indices developed by Kaufman et al. (1999a) to measure national political infrastructure. These six indices, described below, cover a broad range of institutional and policy outcomes and are available for a large sample of countries. In particular, they include factors not commonly found in the FDI literature, notably measures of the rule of law, the regulatory environment, and graft.

National political infrastructure is not the only infrastructure that can contribute to economic well-being and create a favourable climate for FDI. Investments in human capital, physical infrastructure and the environment may also be important. In the context of FDI, the absence of educated and healthy workers can be a significant deterrent to foreign entry. As increasing amounts of FDI becomes skill- and efficiency-seeking, access to an educated and skilled workforce becomes essential.4 There is evidence that a more highly educated populace does in fact attract FDI (Mody and Srinivasan, 1998), but the role of health has not been explored to our knowledge. Similarly, environmental regulation may increase the costs of doing business and thus deter FDI. On the other hand, a clean environment may be associated with a higher quality of life, and thereby attract FDI. To date, there are only a limited number of studies linking environmental policies to FDI (List, 2001; Smarzynska and Wei, 2001; and Wheeler, 2001), with no consistent evidence of a race to the bottom with respect to environmental policies. That is, there is no consistent evidence of a negative relationship between FDI inflows and higher environmental standards.

In this study, we account for aspects of human capital development and the environmental regime using the Human Development Index (HDI) developed by the United Nations, and the Environmental Sustainability Index (ESI) developed jointly at Columbia University, Yale University and the World Economic Forum. The HDI is a composite index created by combining GDP per capita, an education outcome index and a health status index. The ESI measures environmental sustainability using a variety of measures.

The primary purpose of this study is therefore to assess the contribution of national political infrastructure characteristics to the determination of inward and outward FDI flows, and to compare their impact with other measures of non-physical infrastructure such as health, education and the environment. Our report is thus concerned with assessing the importance of "non-traditional" variables in a relatively traditional model of FDI behaviour. Globally, these measures are often associated (directly or indirectly) with the broad notion of a location's quality of life. Policies influencing quality of life in a region are attracting increasing attention from public officials seeking to make their region attractive to foreign investors.5

In order to examine these issues, we employ two sets of FDI data, both covering the period 1995-97. The first set measures total FDI inflows and outflows to/from a sample of 144 developed and developing countries (UNCTAD, 2000). The second set uses U.S. Bureau of Economic Analysis data to measure the inflows of U.S. FDI to these same countries (not all of which were recipients). We refer to the former as the global model, and the latter as the U.S. model.

For the global model, we employ relatively standard techniques to estimate the impact of NPI on the amount of capital inflows and outflows, holding constant other factors, including those discussed above. For the global model, all countries in the sample are FDI recipients. For the U.S. model, however, there are a large number of countries where no positive FDI inflows from the United States were recorded over our sample period. We therefore employ a two-stage estimation procedure to account for the possibility of sample selection bias (Heckman, 1979). We first estimate the likelihood of a country enjoying positive FDI inflows from the United States, and then we estimate the determinants of the magnitude of the positive inflows. In the first stage, the probit method is used to estimate the probability that the United States invests in a particular country. In the second stage, ordinary least squares (OLS) estimates of the determinants of the amount of FDI (given that it is positive) are provided.

For both models, we provide separate estimates of our equations for samples including both developing and developed countries, as well as for developed countries alone. In addition, for the U.S. sample, we investigate the possibility that the determinants of FDI, in particular the importance of NPI, differ across industries. We thus provide separate estimates for U.S. FDI flows in high-technology industries.

For the global model, our results clearly indicate that NPI is an important determinant of both FDI inflows and outflows. The results suggest that investments in governance infrastructure not only attract capital, but also create the conditions under which domestic MNEs emerge and invest abroad. It would appear that investments in governance infrastructure are subject to diminishing returns, so that the benefits, in terms of inflows, are most pronounced for smaller and developing economies. For the U.S. model, the results also point to the importance of NPI, but in a somewhat different way. National political infrastructure is an important determinant of whether a country receives U.S. FDI, but it is less important in determining the amount, given that the country is a recipient.

The study proceeds as follows. In the next section we survey the relevant FDI literature. In the third section we define national political infrastructure, and compare and contrast our definition to other related concepts. In the fourth section, we discuss our measure of NPI, as well as other measures we employ, notably measures of human development and environmental sustainability. Sections where we describe the global FDI model, its estimation technique and results, and then the U.S. FDI model and its estimation and results follow, respectively. A summary and conclusions are provided in the final section.

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