Abstract
Thai enterprises and companies have turned their attentions to CLMV countries, since the establishment of ASEAN Economic Community (AEC) in 2015, due to market and production opportunities. This study is conducted with an attempt to provide useful information helping the Thai investors make investment decision. In particular, this study examines the determinants of outward Thailand’s direct investment to the CLMV countries, and later estimates marginal effects. During the analysis, data unavailability in the CLMV and missing values in many available variables become destructive. This study handles this problem by using the bootstrap-based expectation maximization with bootstrapping (EMB). Once a complete data set is obtained, this study then employs the Seemingly Unrelated Regression (SUR) model to analyse the effects of the considered variables on Thailand’s direct investment in the CLMV group. The estimated results show distinct determinants for the countries, which can be useful to investors.
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Acknowledgements
The authors are grateful to Centre of Excellence in Econometrics, Chiang Mai University for the financial support, and also Mr. Woraphon Yamaka who kindly helps ensure that our code is correct. Without their supports, this study could not be completed.
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Jaitang, C., Maneejuk, P., Wiboonpongse, A., Sriboonchitta, S. (2018). Analysis of Thailand’s Foreign Direct Investment in CLMV Countries Using SUR Model with Missing Data. In: Kreinovich, V., Sriboonchitta, S., Chakpitak, N. (eds) Predictive Econometrics and Big Data. TES 2018. Studies in Computational Intelligence, vol 753. Springer, Cham. https://doi.org/10.1007/978-3-319-70942-0_29
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DOI: https://doi.org/10.1007/978-3-319-70942-0_29
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