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Determinants of Intra-Region and Extra-Region Foreign Direct Investment Inflow in ASEAN: A Spatial Econometric Analysis

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A Correction to this article was published on 19 July 2019

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Abstract

In this paper, we explore the dominant forms of foreign direct investment (FDI) (horizontal, vertical, export-platform, and complex vertical) in ASEAN countries. To account for the heterogeneity in FDI forms according to their origins, we examine separately extra-ASEAN and intra-ASEAN FDI in ASEAN countries. Using macro-level annual data covering nine countries over 1999–2011 and spatial econometric models, we find that the significance and the signs of the coefficients for the determinants of FDI and of spatial interactions provide an indirect way to test the dominance of particular forms of FDI over others. Our results suggest that the location of extra-ASEAN FDI is affected by host country characteristics (such as market size, infrastructure quality, political stability, trade costs) and by FDI in neighboring countries. Then, extra-ASEAN FDI inflows seem to be dominated by complex vertical FDI. In contrast, the location of intra-ASEAN FDI is affected by a host country’s political stability and market size, but also by the market potential of neighboring markets, suggesting that intra-ASEAN FDI inflows are dominated by export-platform FDI. The significance of spatial interactions for both origins of flows warrants the acceleration of economic integration between ASEAN countries to continuously attract FDI.

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Change history

  • 19 July 2019

    The original article unfortunately contains an incorrect statement in the Acknowledgments section.

Notes

  1. ASEAN had six members at the time: Brunei, Indonesia, Malaysia, the Philippines, Singapore, and Thailand. Vietnam joined in 1995, Laos and Myanmar in 1997, and Cambodia in 1999.

  2. We thank the reviewer for suggesting this argument.

  3. The theoretical and empirical literature on FDI suggests spatial autocorrelation, and our results show that I-Moran and LM tests rejected the null of no spatial autocorrelation. We then proceeded with the maximum likelihood estimator on SAR- and SEM-type models, which should be preferred to geographically weighted regression models that are based on spatial heterogeneity (random coefficients) with no spatial autocorrelation. We thank the editor for suggesting we include this point.

  4. We used modified models as suggested by the literature on FDI. The theoretical literature on FDI and the bulk of empirical studies suggest that adjusted SAR and SEM, which only include a spatial-lagged explanatory variable, the neighboring market, are more appropriate compared to a spatial Durbin model. The levels of the other explanatory variables in neighboring countries were not expected to directly influence the level of FDI in a destination country. However, the other explanatory variables, controlling for only destination country characteristics that are not spatially lagged, such as trade costs, may also allow the assessment of whether some forms of FDI dominate over others. We thank the referee for suggesting this point.

  5. Myanmar is excluded due to data unavailability. We, however, consider that such a set of nine adjacent countries constitutes an unbroken study area for ASEAN, following Regelink and Elhorst (2015).

  6. http://www.cepii.fr/anglaisgraph/bdd/distances.htm.

  7. We thank the reviewer for suggesting we clarify this point.

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Acknowledgments

This research was funded by the Vietnam National Foundation for Science and Technology Development (NAFOSTED).

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Correspondence to Hong Hiep Hoang.

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I do not have any conflict of interest regarding this paper or anything related to this subject.

Appendices

Appendix 1

Table 4 Data sources

Appendix 2

Table 5 Descriptive statistics

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Hoang, H.H., Goujon, M. Determinants of Intra-Region and Extra-Region Foreign Direct Investment Inflow in ASEAN: A Spatial Econometric Analysis. Appl. Spatial Analysis 12, 965–982 (2019). https://doi.org/10.1007/s12061-018-9280-8

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