Abstract
Our article has provided new insight into the effect of foreign direct investment inflows and the other macroeconomic factors on financial development. The panel dataset was collected in 31 countries over the 2009–2019 period. The frequentist inference, such as GLS estimation, did not provide evidence of statistical significance of the foreign direct investment. By Bayesian estimation, research findings acknowledged both positive and negative effects of foreign direct investment inflows. Simultaneously, the positive effect of foreign direct investment inflows exceeded its possible negative effect on financial development in some emerging and developing countries. In terms of control variables (such as exchange rate, market capitalization and trade openness), they had prominently positive influences on the financial development by Bayesian estimation. Inflation (inf) was the sole determinant of prevailed negative impact on financial development.
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Notes
- 1.
RUPA DUTTAGUPTA is a division chief in the IMF’s Strategy, Policy, and Review Department, where CEYLA.
- 2.
PAZARBASIOGLU is director.
- 3.
Bangladesh, Bulgaria, Brazil, Colombia, Czech, Chile, China, Hungary, Indonesia, India, Iran, Israel, Korea, Kuwait, Sri lanka, Morocco, Mexico, Mauritius, Malaysia, Nigeria, Pakistan, Peru, Poland, Philippine, Romania, Tunisia, Turkey, Thailand, Ukraine, Vietnam, South Africa.
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Appendices
Appendices
Appendix A: The Detailed Efficiency of the Simulations
The efficiency of simulations | Bayesian estimation | |||||||||
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σ2,\({\upsigma }_{U}^{2}\sim \) igamma prior (100,100) | σ2,\({\upsigma }_{U}^{2}\sim \) igamma prior (200,200) | σ2,\({\upsigma }_{U}^{2}\sim \) igamma prior (300,300) | σ2,\({\upsigma }_{U}^{2}\sim \) igamma prior (400,400) | σ2,\({\upsigma }_{U}^{2}\sim \) igamma prior (500,500) | σ2,\({\upsigma }_{U}^{2}\sim \) igamma prior (600,600) | σ2,\({\upsigma }_{U}^{2}\sim \) igamma prior (700,700) | σ2,\({\upsigma }_{U}^{2}\sim \) igamma prior (800,800) | σ2,\({\upsigma }_{U}^{2}\sim \) igamma prior (900,900) | σ2,\({\upsigma }_{U}^{2}\sim \) igamma prior (1000,1000) | |
θfdi | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 0.9641 | 1.0000 | 1.0000 | 0.9451 | 1.0000 | 1.0000 |
θgdpcap | 1.0000 | 1.0000 | 0.9561 | 1.0000 | 0.8740 | 0.9433 | 0.8951 | 0.8144 | 0.8933 | 0.7906 |
θex | 0.8933 | 0.8276 | 0.8067 | 0.7728 | 0.7055 | 0.6984 | 0.6802 | 0.6451 | 0.5929 | 0.5911 |
θmarket | 0.9701 | 0.8227 | 0.7827 | 0.7427 | 0.7153 | 0.6938 | 0.6367 | 0.6347 | 0.6239 | 0.5617 |
θinf | 0.9550 | 1.0000 | 0.9267 | 0.9455 | 0.8658 | 0.8104 | 0.8280 | 0.8145 | 0.7506 | 0.7826 |
θopen | 0.8483 | 0.9541 | 0.8244 | 0.9455 | 0.7896 | 0.7153 | 0.6779 | 0.6485 | 0.6444 | 0.5815 |
θ_cons | 0.9654 | 0.9646 | 0.8236 | 0.7756 | 0.8350 | 0.7888 | 0.6962 | 0.6940 | 0.6497 | 0.6149 |
σ2 | 0.7865 | 0.6114 | 0.6033 | 0.5496 | 0.5040 | 0.4638 | 0.3901 | 0.3405 | 0.3023 | 0.2515 |
\({\upsigma }_{U}^{2}\) | 0.3239 | 0.3489 | 0.4158 | 0.4172 | 0.4243 | 0.3164 | 0.3318 | 0.2739 | 0.2518 | 0.2253 |
Appendix B: Visual Diagnostics For MCMC Convergence of Bayesian Estimation With σ2, \(\sigma_U^2\) \(\sim \) igammaprior(100,100)
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Kieu, V.T.T., Tien, L.T., Thach, N.N. (2022). The Impact of Foreign Direct Investment on Financial Development: A Bayesian Approach. In: Ngoc Thach, N., Kreinovich, V., Ha, D.T., Trung, N.D. (eds) Financial Econometrics: Bayesian Analysis, Quantum Uncertainty, and Related Topics. ECONVN 2022. Studies in Systems, Decision and Control, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-030-98689-6_50
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