Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging Nikolaos Antonakakis and Gabriele Tondl VIENNA UNIVERSITY OF ECONOMICS AND BUSINESS INSTITUTE FOR INTERNATIONAL ECONOMICS
Motivation Literature Review Data & Methodology Empirical Results Conclusion Outline Motivation 1 Surge of FDI into developing countries since mid 1990s Literature Review 2 Insufficient guidance for selecting proper FDI determinants Data & Methodology 3 Description of data BMA analysis Empirical Results 4 Heterogenous patterns of FDI in developing regions Conclusion 5 Further discussion & future prospects Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 2 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Surge of OECD FDI into developing countries Since the mid 1990s OECD countries started to place an increasing share of their FDI into developing countries in ECA, ESA, MENA, SSA, LAC. Major 4 OECD investors’ (US, Germany, France and Netherland) presence varied substantially in these regions in terms of value and time. Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 3 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Figure 1: OECD FDI per capita position (US$) by region of destination 120 120 113.41 108.77 100 100 80 80 69.19 US US 59.08 60 60 GER GER FRA FRA NED NED 39.66 40 40 37.68 35.94 34.99 34.60 30.20 27.64 27.04 23.23 22.54 20.72 19.15 20 17.58 20 15.52 8.88 8.88 8.32 7.38 7.01 6.82 6.33 5.77 3.97 4.33 3.29 1.65 1.65 1.88 1.42 1.30 1.92 0.88 0.77 0.74 1.15 0.40 0 0 ECA ESA MENA SSA LAC ECA ESA MENA SSA LAC (1995) (2008) Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 4 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Important questions raised These facts raise several important questions: What determines FDI from high income countries to different developing 1 regions? Which are indeed the most crucial ones? 2 Are they homogenous among distinct regions? 3 Answers to such questions are of great importance for the design of appropriate policies to attract FDI in specific regions. Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 5 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Theoretical & Empirical Literature Theoretical and Empirical Survey of Faeth (2009) presents 9 theoretical models explaining FDI: no single theory of FDI, but a variety of theoretical models. Thus, analysis of FDI determinants should be explained more broadly by a combination of factors from a variety of theoretical models. No sufficient guidance for selecting the proper empirical model = > the issue of model uncertainty arises. So far the empirical literature has not attempted to evaluate the robustness of FDI determinants. Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 6 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Determinants of FDI Annual data for 129 developing countries classified into 5 developing regions (ECA, ESA, MENA, SSA & LAC based on WB classification) for the 1995–2008 period. Dependent variable: Bilateral FDI stocks per capita from major 4 OECD investors (US, GER, FRA & NED), FDIpc . Explanatory Variables: Market size & Market Potential: GDP , GDPpc , GROWTH . Labor cost & Productivity: WAGE & LPROD . Resources: OIL , GAS & MINORES . Host Country’s Openness, Bilateral Trade Experience & Common Policy Framework: OPEN , BTRADE & FTA . Human Capital Development: NETP & NETS . Macroeconomic Factors: EXC , STDEXC , INF , STDINF & DEBT Geographical & Cultural proximity: DIST , LANG & COLON . Institutional Factors: ACC , CORR , GOV , LAW , POL & REG . Double Taxation Treaties & Bilateral Investment Treaties: DTT & BIT . Infrastructure & Corporate Tax: MOBFIX , INT & TAX . Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 7 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Methodology: Bayesian Model Averaging Alternative models M j , with j = 1 , ..., J defined by a subset of k j included from K . i β j + ε i y i = a i ι T + X j (1) If θ j = β j , σ, α i is the quantity of interest, then its posterior distribution given the data, y , is: 2 K p ( θ j | y i ) = � p ( θ j | y i , M j ) p ( M j | y i ) (2) j = 1 This is an average of the posterior distributions under each of the models considered, weighted by their PMPs: Have to compute PMPs = > choose prior distribution over the space M of all 2 K . We allocate equal prior model probability to each model: p ( M j ) = 2 − K (3) Yields uninform distribution; implies prob. of including a regressor is 0.5, independent of the combination of regressors included in the model. Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 8 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Methodology: BMA continued... With this prior model probability we get the following expression for the PMPs: p ( y i | M j ) p ( M j | y i ) = (4) � 2 K i = 1 p ( y i | M j ) where p ( y i | M j ) is the marginal likelihood of Model M j given by: � p ( y i | α i , β j , σ, M j ) p ( α i , σ ) p ( β j | α i , σ, M j ) d α i d β j d σ p ( y i | M j ) = (5) with p ( y i | α i , β j , σ, M j ) the model corresponding to eq. (1), and p ( α i , σ ) , and p ( β j | α i , σ, M j ) , the parameter priors defined in the next slide. Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 9 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Methodology: BMA continued... Challenging to compute the relevant distributions: No. of estimated models increases with the No. of regressors exponentially, 2 K . Integrals may not exist in closed form. We approximate the posterior distribution by applying MC 3 (Madigan and York, 1995). MC 3 based on Random Walk Metropolis-Hastings algorithm. Choice of Priors influences results. Thus, non-informative priors preferable. The prior for p ( α i , σ ) has a g-prior structure; resembles the one suggested by the risk inflation criterion of Foster and George (1994) and has a good small sample performance (FLS, 2001b). We adopt a uniform prior for the scale parameter common to all models which implies equal prior weight. Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 10 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Table 4: Determinants of FDI to developing countries Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 11 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Table 5: Determinants of FDI to developing countries (Restricted) Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 12 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Table 6: Determinants of FDI to ECA by OECD investor Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 13 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Table 7: Determinants of FDI to ESA by OECD investor Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 14 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Table 8: Determinants of FDI to MENA by OECD investor Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 15 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Table 9: Determinants of FDI to SSA by OECD investor Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 16 / 22
Motivation Literature Review Data & Methodology Empirical Results Conclusion Table 10: Determinants of FDI to LAC by OECD investor Do Determinants of FDI to Developing Countries differ among US and European Investors? Insights from Bayesian Model Averaging 17 / 22
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