Role of instability in affecting capital flight magnitude: An ARDL bounds testing approach

Hasnul, Al Gifari and Masih, Mansur (2016): Role of instability in affecting capital flight magnitude: An ARDL bounds testing approach.

Abstract

Capital flight resulting from hot money has been a popular issue recently. The effect of capital flight is unquestionably bad to the domestic economic condition. The current global economic slowdown exposes a bigger risk of capital flight to developing countries. Likewise, the causal relationship of capital flight and political stability as well as exchange rate stability is not clearly observed yet in the literature. This paper aims to analyse this issue and fill the research gap. Our paper extends previous studies by using another measure of political risk index, and also exchange rate stability has not been really examined by previous studies in the case of capital flight. A more focused study on one country may give a direct policy implication to the policymakers of the country, rather than a panel data study. We employed time-series data of Indonesia for 35 years from 1980 to 2015 and use ARDL procedure, which is really suitable for our research objectives and sample used, to analyse the data. We find that political risk plays a significant role in affecting the magnitude of capital flight. Furthermore, the results show that both capital flight and exchange rate stability are endogenous variables, and movement in one variable will affect the movement of another variable. Our main suggestion for the policy makers to prevent capital flight is to maintain political and exchange rate stability in the country. In short, preventing capital flight is all about maintaining domestic stability, either political stability or economic stability.

• Item Type: MPRA Paper
• Language: English
• Keywords: Capital Flight; Political Stability; Exchange Rate Stability; ARDL bounds tests
• Subjects: C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C58 - Financial Econometrics; G - Financial Economics > G1 - General Financial Markets > G15 - International Financial Markets

References

Abdullahi, M. M., Bakar, N. A. B. A., & Hassan, S. B. (2015). Determining the Macroeconomic Factors of External Debt Accumulation in Nigeria: An ARDL Bound Test Approach. Procedia - Social and Behavioral Sciences, 211, 745–752. http://doi.org/10.1016/j.sbspro.2015.11.098

Aizenman, J., Chinn, M. D., & and Ito, H. (2010). "The Emerging Global Financial Architecture: Tracing and Evaluating the New Patterns of the Trilemma's Configurations". Journal of International Money and Finance, Vol. 29, No. 4, 615–641.

Ajayi, S. I. (1997). An analysis of External Debt and Capital Flight in the Severely Indebted Low Income Countries in Sub-Saharan Africa.

Alam, M. I., & Quazi, R. M. (2003). Determinants of Capital Flight: an econometric case study of Bangladesh. International Review of Applied Economics, 17(1), 85. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=9168664&site=ehost-live

Bhagwati, J., Krueger, A., & Wibulswasdi, C. (1974). Capital flight from LDC's: A statistical analysis. In G. Epstein (Ed.), Illegal Transactions in International Trade (pp. 148–154). Amsterdam: North Holland Publishing.

Cavanaugh, C.L., Elliot, G. and Stock, J.H. (1995). Inference in Models with Nearly Integrated Regressors. Econometric Theory. 11: 1131-1147.

Cheung, Y.-W., Steinkamp, S., & Westermann, F. (2015). China’s capital flight: Pre- and post-crisis experiences. Journal of International Money and Finance, -. http://doi.org/http://dx.doi.org/10.1016/j.jimonfin.2015.12.009

Coakley, J., Fuertes, A. M., & Spagnalo, F. (2004). Is the Feldstein-Horioka Puzzle history? The Manchester School, 72, 569-590.

Collier, P., Hoeffler, A., & Pattillo, C. (1999). Flight Capital as a Portfolio Choice. Policy Research Working Paper Series 2066. The World Bank.

Collier, P., Hoeffler, A., & Pattillo, C. (2004). Aid and Capital Flight. Unpublished manuscript. Oxford University, Centre for the Study of African Economies (available at http://users.ox.ac .uk/~ba110144/aid&cf.pdf).Critical values Engle-Granger cointegration test? - ResearchGate. Available from: https://www.researchgate.net/post/Critical_values_Engle-Granger_cointegration_test [accessed May 8, 2016].

Crotty, J. R. (1983). On Keynes and Capital Flight. Journal of Economic Literature, 21(1), 59–65. Retrieved from \nhttp://www.jstor.org/stable/2724749

Cuddington, J. T. (1986). Capital Flight: Estimates, Issues, and Explanations. Princeton Studies in International Finance (Vol. 58).

Duasa, J. (2007). Determinants of Malaysian Trade Balance: An ARDL Bound Testing Approach. Global Economic Review, 36(1), 89–102. http://doi.org/10.1080/12265080701217405

Engle, R. F., & Yoo, B. S. (1987). Forecasting and testing in co-integrated systems. Journal of Econometrics, 35(1), 143–159. http://doi.org/10.1016/0304-4076(87)90085-6

Epstein, G. (2005). Capital Flight and Capital Controls in Developing Countries: An Introduction, 3–14.

Fedderke, J.W. & W. Liu. (2002). Modeling the determinants of capital flows and capital flight: With an application to South African data from 1960 to 1995. Economic Modelling 19: 419–444.

Hutasoit, V. M. (2008). Analisis Faktor-faktor yang Mempengaruhi Capital Flight Di Indonesia.

Istikomah, N. (2003). Analisis Faktor-faktor yang Mempengaruhi “Capital Flight” di Indonesia. Buletin Ekonomi Moneter Dan Perbankan.

Jalil, A., Mahmood, T., & Idrees, M. (2013). Tourism-growth nexus in Pakistan: Evidence from ARDL bounds tests. Economic Modelling, 35, 185–191. http://doi.org/10.1016/j.econmod.2013.06.034

Ketkar, Suhas L., Kusum W. Ketkar. (1989). “Determinants of Capital Flight from Argentina, Brazil, and Mexico,” Contemporary Policy Issues, 3: 11-29

Kiendrebeogo, Y. (2016). Unconventional monetary policy and capital flows. Economic Modelling, 54, 412–424. http://doi.org/10.1016/j.econmod.2016.01.008

Kindleberger, C. P. (1937). International Short-term Capital Movements. Journal of the American Statistical Association, 33(201), 296–298.

Le, Q. V., & Rishi, M. (2006). Corruption and Capital Flight: An Empirical Assessment. International Economic Journal, 20(4), 523–540. http://doi.org/10.1080/10168730601027161

Le, Q. V., & Zak, P. J. (2006). Political risk and capital flight. Journal of International Money and Finance, 25(2), 308–329.http://doi.org/10.1016/j.jimonfin.2005.11.001

Lensink, R., Hermes, N., & Murinde, V. (2000). Capital flight and political risk. Journal of International Money and Finance, 19(1), 73–92. http://doi.org/10.1016/S0261-5606(99)00034-0

MacKinnon, J. G. (1990). Critical Values for Co-Integration Tests. Long-Run Economic Relationships: Readings in Cointegration, (1227), 267–276. http://doi.org/10.1111/1468-0084.61.s1.14

Masih, A. M. M. and Masih, R. (1995). Empirical Tests to Discern the Dynamic Causal Chain in Macroeconomic Activity: New Evidence from Thailand and Malaysia Based on a Multivariate Cointegration/Vector Error- Correction Modeling Approach. Journal of Policy Modeling. 18, 531- 560.

Masih, R. and Masih, A. M. M. (1996). Macroeconomic activity dynamics and Granger causality: New evidence from a small developing economy based on a vector error-correction modelling analysis. Economic Modelling. 13, 407-426.

Maski, G., & Wahyudi, S. T. (2012). Study on the Capital Flight and Its Impact on Economic Growth: A Case Study in Indonesia. 2(7), 7168–7174.

Morgan Guaranty Trust Company. (1986). LDC capital flight. World Financial Markets, March, pp. 13– 15.

Narayan, P. K. (2005). The saving and investment nexus in China: Evidence from cointegration test. Applied Economics, 37(17), 1979-1990

Naylor, R. T. (1987). Hot Money and the Politics of Debt. 1st Edition. (New York, Black Rose Books).

Pesaran, M. H. (1997). The Role of Economic Theory in Modelling the Long- Run. The Economic Journal. 107: 178-191.

Pesaran, M. H. & Pesaran, B. (1997). Microfit 4.0: Interactive Econometric Analysis. Oxford University Press.

Pesaran, M. H. & Shin, Y. (1995). Long-Run Structural Modelling. Unpublished Manuscript. University of Cambridge.

Pesaran, M. H. & Shin, Y. (1999). An autoregressive distributed-lag modelling approach to cointegration analysis. Econometric Society Monographs, 31(7), 371–413. http://doi.org/10.1017/CCOL521633230

Pesaran, M. H., Shin, Y. & Smith, R. J. (1996). Testing for the Existence of a Long-Run Relationship. DAE Working Papers Amalgamated Series, No. 9622, University of Cambridge.

Pesaran, M. H., Shin, Y., & Smith, R. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics, 471-505.

Pradhan, R. P., Norman, N. R., Badir, Y., & Samadhan, B. (2013). Transport Infrastructure, Foreign Direct Investment and Economic Growth Interactions in India: The ARDL Bounds Testing Approach. Procedia - Social and Behavioral Sciences, 104, 914–921. http://doi.org/10.1016/j.sbspro.2013.11.186

Rahnama-Moghadam, M., Samavati, H., & Dilts, D. A. (2002). An Analysis of Capital Flight from East Asian Economies, 11–19.

Schneider, B. (2003). Measuring Capital Flight: Estimates and Interpretations. Working Paper 194 Overseas Development Institute.

Sheets, N. (1996). Capital Flight from the Countries in Transition: Some Theory and Empirical Evidence. Sims, C. (1982). Policy Analysis with Econometric Models. Brookings Papers on Economic Activity 1. 107-152.

Sulaiman, C., & Abdul-Rahim, A. S. (2013). The short- and long-run effects of sustainable forest management practices on trade in Thailand’s forest products. (pp. 103-113)

World Bank. (1985). World Development Report. (New York: Oxford University Press for the World Bank)