CHƯƠNG 5 : KẾT LUẬN
5.3 Hướng nghiên cứu mở rộng
Vai trò của nghiên cứu thực nghiệm khu vực châu Á ngày càng đóng vai trị quan trọng, với sự chuyển dịch từ Châu Âu sang Châu Á của kinh tế thế giới. Việc hoàn thiện bài nghiên cứu về mặt dữ liệu cập nhật thêm sau này cũng như hoàn thiện những hạn chế nêu trên là một hướng mở rộng khả thi.
Từ kết quả của mơ hình nghiên cứu tìm thấy các yếu tố tác động đến độ bất ổn định tài chính, một chủ đề nghiên cứu khá mới tại khu vực Châu Á - Thái Bình Dương, dựa trên kết quả này, nên có thêm các nghiên cứu đào sâu thêm về mối liên hệ này tại Việt Nam, đặc biệt trong thời kỳ hội nhập kinh tế, cung cấp thông tin cho các nhà làm chính sách quản trị độ ổn định của thị trường tài chính đạt mục tiêu vĩ mô.
Nguyễn Vỹ Tâm, 2012. Bài giảng kinh tế vĩ mơ số 21- Chương trình giảng dạy Kinh tế Fulbright
Nguyễn Văn Tiến, 2000. Tài Chính Quốc Tế Hiện Đại trong Nền Kinh Tế Mở. Hà Nội: NXB Thống Kê.
Nguyễn Văn Tiến, 2010. Giáo trình tài chính quốc tế .Hà Nội: NXB Thống Kê. Nguyễn Thị Liên Hoa, 2015. Tạp chí Cơng Nghệ Ngân Hàng - S.112
Hoàng T. Phương Anh và Đinh Tấn Danh, 2016. Tạp chí Phát Triển và Hội Nhập - S.26
Nguyễn Minh Sáng và Nguyễn Thiên Kim, 2014. Tạp chí Phát Triển và Hội Nhập - S.19
Trần Ngọc Thơ – Nguyễn Ngọc Định, 2013.Tài chính quốc tế. TP.HCM: Trường Đại học kinh tế TP.HCM.
TÀI LIỆU THAM KHẢO TIẾNG ANH
Michael Batuo Enowbi, Kupukile Mlambo, Simplice Asongu (2016). Linkages between financial development, financial instability, financial liberalisation and economic growth in Africa
Agbloyor, E. K., Abor, J., Adjasi, C. K. D., & Yawson, A., (2013). “Exploring the causality links between financial markets and foreign direct investment in Africa”, Research in International Business and Finance, 28(May, 2013), pp. 118-134. Akerlof, G. (1970) “The Market for Lemon: Quality Uncertainty and the Market Mechanism”. Quarterly Journal of Economics, 84(1970), pp. 488-500.
Ansart, S., & Monvoisin, V.(2016) “ The new monetary and financial initiatives: Finance regaining its position as servant of the economy”, Research in international Business and Finance: Forthcoming.
Arellano, M., & Bond, S., (1991). “Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations”, The Review of Economic Studies, 58(2), pp. 277-297.
Arellano, M., & Bover, O., (1995). “Another look at the instrumental variable estimation of errorcomponents models”, Journal of Econometrics, 68(1), pp. 29-52. Aryeetey, E.(1994), “The global Financial crisis and domestic resources mobilisation in Africa” Working Paper No. 101, African Development Bank,Tunis.
Asongu, S. A. (2013a). “How do financial reforms affect inequality through financial sector competition? Evidence from Africa”, Economics Bulletin, 33(1), pp. 401-414. Asongu, S. A. (2013b). “How has politico-economic liberalization affected financial allocation efficiency? Fresh African Evidence”, Economics Bulletin, 33(1), pp. 663- 676.
Asongu, S. A. (2014). “Financial development dynamic thresholds of financial globalization: evidence from Africa”, Journal of Economic Studies, 41(2), pp. 166- 195.
Asongu, S. A., (2015b). “Liberalisation and Financial Sector Competition: A Critical Contribution to the Empirics with an African Assessment”, South African Journal of Economics, 83(3), pp. 425- 451.
Asongu, S. A. & De Moor, L., (2016). “Financial Globalisation Dynamic Thresholds for Financial Development: Evidence from Africa”, The European Journal of Development Research, DOI: 10.1057/ejdr.2016.10.
Bonfiglioli, A., & Mendicino, C., (2004). “Financial Liberalisation, Banking Crises and Growth: Assessing the links”, SSE/EFI Working Paper No 567, Stockholm. Chortareas, G., Magkonis, G. Moschos, D., & Panagiotidis T., (2015). “Financial Development and Economic Activity in advanced and developing open economies: Evidence from Panel Cointegration”
Daniel, B.C. & Jones J. B., (2007), “Financial Liberalization and Banking Crises in Emerging Economies”, Journal of international Economics, 72(1), 202-221.
Demirguc-Kunt, A. & Levine, R., (1996), “Stock Markets, Corporate Finance and Economic Growth: An Overview”, The World Bank Economic Review, 10(2), pp. 223-40. 22
Demirguc-Kunt, A. and R. Levine (1999), " Bank Based and Market Based Financial System: crosscountry comparisons", the World Bank Policy Research Working Paper No. 2143, Washington.
Donald Mackenzia,(2001), “ The Credit Crisis as a Problem in the Sociology of Knowledge”, American Journal of Sociology, Vol. 116(6), pp.1778-1841
Edison, H. J., Klein, M. W., Ricci, L. A., & Sloek, T., (2002). “Capital account liberalization and Economic Performance: survey and synthesis”, Journal of international Money and Finance 21(6), pp. 749-776
Edwards, S., (2001), “Capital Mobility and Economic Performance: Are Emerging Economies Different?”, NBER Working Paper No. 8076, Cambridge.
Eggoh C., (2008) “Financial Development , Financial Instability and Growth: A Reappraisal” Law, Economics and Management Faculty, University of Orleans.
Bai, J., & Kao, C. (2006).On the estimation and inference of a panel cointegration model with cross-sectional dependence. contributions to Economic Analysis, 274, 3- 30.
Baltagi, B. H., & Hashem Pesaran, M. (2007). Heterogeneity and cross section dependence in panel data models: theory and applications introduction. Journal of Applied Econometrics, 22(2), 229-232.
Baltagi, B. (2008). Econometric analysis of panel data.John Wiley & Sons.
Banerjee, A., Marcellino, M., & Osbat, C. (2005). Testing for PPP: Should we use panel methods?. Empirical Economics, 30(1), 77-91.
Breusch, T. S., & Pagan, A. R. (1980).The Lagrange multiplier test and its applications to model specification in econometrics. The Review of Economic Studies, 47(1), 239-253.
Breitung, J., & Pesaran, M. H. (2008). Unit roots and cointegration in panels(pp. 279- 322). Springer Berlin Heidelberg.
Clements, K. W., & Frenkel, J. A. (1980). Exchange rates, money, and relative prices: the dollar-pound in the 1920s. Journal of International Economics, 10(2), 249-262. Crespo‐Cuaresma, J., Fidrmuc, J., & MacDonald, R. (2005).The monetary approach to exchange rates in the CEECs1. Economics of Transition, 13(2), 395-416.
Dąbrowski, M. A., Papież, M., & Śmiech, S. (2014). Exchange rates and monetary fundamentals in CEE countries: Evidence from a panel approach.Journal of Macroeconomics, 41, 148-159.
Engel, C., Mark, N. C., & West, K. D. (2007). Exchange rate models are not as bad as you think (No. w13318). National Bureau of Economic Research.
Flood, R. P., & Rose, A. K. (1999).Understanding exchange rate volatility without the contrivance of macroeconomics. The Economic Journal, 109(459), 660-672. Frenkel, J. A. (1976). A monetary approach to the exchange rate: doctrinal aspects and empirical evidence. the scandinavian Journal of economics, 200-224.
Groen, J.J.(2000). The monetary exchange rate model as a long-run phenomenon. Journal of International Economics, 52(2), 299-319
Im, K. S., Pesaran, M. H., & Shin, Y. (2003).Testing for unit roots in heterogeneous panels. Journal of econometrics, 115(1), 53-74..
Kao, C., & Chiang, M. H. (1999).On the estimation and inference of a cointegrated regression in panel data. Available at SSRN 1807931.
Krugman, P. (1989). Exchange Rate Instability MIT Press. Cambridge Massachusetts.
Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: asymptotic and finite-sample properties. Journal of econometrics, 108(1), 1-24
MacDonald, R., & Taylor, M. P. (1994). The monetary model of the exchange rate: long-run relationships, short-run dynamics and how to beat a random walk.Journal of international Money and finance, 13(3), 276-290.
Maddala, G. S., & Wu, S. (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and statistics,61(S1), 631- 652
Mark, N. C., & Sul, D. (2001). Nominal exchange rates and monetary fundamentals: evidence from a small post-Bretton Woods panel. Journal of International Economics, 53(1), 29-52.
Mussa, M. (1976).Adaptive and regressive expectations in a rational model of the inflationary process. Journal of Monetary Economics, 1(4), 423-442.
Pedroni, P. (2000). FULLY MODIFIED OLS FOR HETEROGENEOUS COINTEGRATED PANELS.
Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and statistics,61(s 1), 653- 670.
Pesaran, M. H., Shin, Y., & Smith, R. P. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association, 94(446), 621-634.
Pesaran, M. H., Ullah, A., & Yamagata, T. (2008).A bias‐adjusted LM test of error cross‐section independence. The Econometrics Journal, 11(1), 105-127.
Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels.
Perron, P. (1988). Trends and random walks in macroeconomic time series: Further evidence from a new approach. Journal of economic dynamics and control, 12(2), 297-332.
Rapach, D. E., & Wohar, M. E. (2002). Testing the monetary model of exchange rate determination: new evidence from a century of data. Journal of International Economics, 58(2), 359-385.
Sarno, L., Valente, G., & Wohar, M. E. (2004).Monetary fundamentals and exchange rate dynamics under different nominal regimes. Economic Inquiry,42(2), 179-193. Sarno, L., & Taylor, M. P. (2002). The economics of exchange rates. Cambridge University Press
dinterestsp 350 -.1720051 10.37801 -103.7617 143.7133 dinterestr 350 -.1668247 10.71348 -84.55098 135.2955 dm2 350 2.708341 12.17204 -57.8995 172.4046 dm3 350 1.859604 6.753838 -57.28868 26.89999 ddcreditp 350 1.634143 10.23379 -123.3505 34.76884 ddcreditb 350 1.368774 10.83709 -123.4551 34.49695 interestsp 364 5.442853 11.89183 -6.9125 163.5133 interestr 364 6.101477 10.58876 -24.60017 130.7843 m2 364 104.0974 65.62337 3.33 362.8582 m3 364 97.30492 63.54387 11.99 348.75 dcreditb 364 85.92272 47.53706 4.743741 233.211 dcreditp 364 90.9112 52.60816 5.162681 233.211 flib 364 .900133 1.389381 -1.903586 2.374419 ouputgap 364 -1.55e-09 2.921207 -17.61769 10.08724 govexpend 364 23.81161 2.29912 18.33148 27.80868 inflation 364 6.546059 20.61594 -4.009434 268.1505 dtetrade 350 .0820008 6.611387 -18.44154 45.36177 gdppercapita 364 9.430606 1.040143 7.313979 11.30087 gdp 364 4.722934 3.905918 -13.12673 17.29078 fdev 364 -5.87e-10 1.658684 -2.451225 6.105512 finst 350 7.18e-11 1.624062 -18.87852 5.695182 Variable Obs Mean Std. Dev. Min Max
dinterestsp 0.1270 0.6963 -0.0449 0.0403 0.7038 0.0125 0 dinterestr 0.1651 0.6846 -0.0326 0.0007 -0.7090 -0.0169 0 dm2 0.3814 -0.0597 0.6940 0.6074 -0.0006 0.0188 0 dm3 0.4765 -0.0546 0.4107 -0.7744 0.0383 0.0138 0 ddcreditp 0.5362 -0.1391 -0.4327 0.1223 -0.0061 0.7007 0 ddcreditb 0.5446 -0.1435 -0.3991 0.1220 0.0238 -0.7128 0
Variable Comp1 Comp2 Comp3 Comp4 Comp5 Comp6 Unexplained
Principal components (eigenvectors) Comp6 .0396446 . 0.0066 1.0000 Comp5 .157771 .118126 0.0263 0.9934 Comp4 .386889 .229118 0.0645 0.9671 Comp3 .969623 .582734 0.1616 0.9026 Comp2 1.8085 .838873 0.3014 0.7410 Comp1 2.63758 .829082 0.4396 0.4396
Component Eigenvalue Difference Proportion Cumulative
Rotation: (unrotated = principal) Rho = 1.0000 Trace = 6 m3 0.5862 -0.4368 0.6823 0 dcreditp 0.5546 0.8303 0.0550 0 m2 0.5906 -0.3462 -0.7290 0
Variable Comp1 Comp2 Comp3 Unexplained
Principal components (eigenvectors)
Comp3 .02577 . 0.0086 1.0000 Comp2 .222999 .197229 0.0743 0.9914 Comp1 2.75123 2.52823 0.9171 0.9171
Component Eigenvalue Difference Proportion Cumulative
Rotation: (unrotated = principal) Rho = 1.0000 Trace = 3
Number of comp. = 3
fdev 0.1628 -0.1448 0.5556 -0.2311 -0.0595 -0.0429 0.4513 0.2841 1.0000 flib -0.0757 -0.3065 0.5101 -0.0972 0.0245 0.0040 -0.1308 1.0000 govexpend 0.0392 0.0195 0.5274 -0.1992 -0.0623 0.0150 1.0000 ouputgap -0.1050 0.7763 0.0054 -0.1324 0.1152 1.0000 dtetrade -0.0481 0.0600 -0.0455 -0.0091 1.0000 inflation -0.0749 -0.2337 -0.1991 1.0000 gdppercapita 0.0281 -0.1826 1.0000 gdp 0.0061 1.0000
Mean VIF 2.25 dtetrade 1.02 0.977520 inflation 1.23 0.816146 fdev 1.60 0.626099 govexpend 2.16 0.463224 flib 2.34 0.427335 gdppercapita 2.78 0.360298 ouputgap 3.16 0.315969 gdp 3.73 0.268118 Variable VIF 1/VIF . vif . _cons .8765976 1.21865 0.72 0.472 -1.520421 3.273616 fdev .2241705 .0641342 3.50 0.001 .098022 .350319 flib -.1486311 .0940639 -1.58 0.115 -.3336496 .0363873 govexpend -.0848198 .0539439 -1.57 0.117 -.1909246 .0212849 ouputgap -.1417483 .0515719 -2.75 0.006 -.2431873 -.0403093 dtetrade -.0047707 .0129382 -0.37 0.713 -.0302196 .0206781 inflation -.0027581 .0049777 -0.55 0.580 -.012549 .0070329 gdppercapita .0935199 .1360696 0.69 0.492 -.1741215 .3611613 gdp .0857873 .0419992 2.04 0.042 .0031773 .1683974 finst Coef. Std. Err. t P>|t| [95% Conf. Interval] Total 920.514587 349 2.63757761 Root MSE = 1.58 Adj R-squared = 0.0536 Residual 851.21944 341 2.49624469 R-squared = 0.0753 Model 69.2951468 8 8.66189335 Prob > F = 0.0007 F( 8, 341) = 3.47 Source SS df MS Number of obs = 350
Prob>chi2 = 0.0000 chi2 (14) = 1818.36
H0: sigma(i)^2 = sigma^2 for all i in fixed effect regression model
Modified Wald test for groupwise heteroskedasticity . xttest3
.
F test that all u_i=0: F(13, 328) = 1.73 Prob > F = 0.0534 rho .56013118 (fraction of variance due to u_i)
sigma_e 1.5583784 sigma_u 1.758556 _cons 19.93835 10.63493 1.87 0.062 -.9829182 40.85962 fdev .6918 .1827389 3.79 0.000 .3323119 1.051288 flib -.1266868 .174862 -0.72 0.469 -.4706793 .2173058 govexpend -.88141 .8422702 -1.05 0.296 -2.538343 .7755231 ouputgap -.0812544 .0850194 -0.96 0.340 -.2485065 .0859977 dtetrade -.0089292 .0130846 -0.68 0.495 -.0346695 .0168112 inflation -.0072621 .0060595 -1.20 0.232 -.0191825 .0046584 gdppercapita .1102624 1.185211 0.09 0.926 -2.221312 2.441837 gdp .0344928 .083128 0.41 0.678 -.1290384 .198024 finst Coef. Std. Err. t P>|t| [95% Conf. Interval] corr(u_i, Xb) = -0.9406 Prob > F = 0.0008 F(8,328) = 3.45 overall = 0.0087 max = 25 between = 0.0115 avg = 25.0 R-sq: within = 0.0775 Obs per group: min = 25 Group variable: id Number of groups = 14
Prob > F = 0.0001 F( 1, 13) = 29.907 H0: no first order autocorrelation
Difference (null H = exogenous): chi2(3) = 0.80 Prob > chi2 = 0.849 Hansen test excluding group: chi2(318) = 1.79 Prob > chi2 = 1.000 iv(L.gdppercapita L.gdp L.fdev)
Difference (null H = exogenous): chi2(22) = -0.00 Prob > chi2 = 1.000 Hansen test excluding group: chi2(299) = 2.59 Prob > chi2 = 1.000 GMM instruments for levels
Difference-in-Hansen tests of exogeneity of instrument subsets: (Robust, but weakened by many instruments.)
Hansen test of overid. restrictions: chi2(321) = 2.59 Prob > chi2 = 1.000 (Not robust, but not weakened by many instruments.)
Sargan test of overid. restrictions: chi2(321) = 362.12 Prob > chi2 = 0.057 Arellano-Bond test for AR(2) in first differences: z = 0.81 Pr > z = 0.419 Arellano-Bond test for AR(1) in first differences: z = -1.94 Pr > z = 0.052 D.(gdppercapita gdp fdev)
GMM-type (missing=0, separate instruments for each period unless collapsed) _cons
L.gdppercapita L.gdp L.fdev Standard
Instruments for levels equation L(1/25).(gdppercapita gdp fdev)
GMM-type (missing=0, separate instruments for each period unless collapsed) D.(L.gdppercapita L.gdp L.fdev)
Standard
Instruments for first differences equation
_cons .8235071 1.55025 0.53 0.595 -2.214926 3.86194 fdev .1995611 .09176 2.17 0.030 .0197147 .3794075 govexpend -.0420558 .0421444 -1.00 0.318 -.1246572 .0405457 ouputgap -.1741323 .0520595 -3.34 0.001 -.276167 -.0720976 dtetrade -.0055562 .0120888 -0.46 0.646 -.0292497 .0181373 inflation -.0060917 .002788 -2.18 0.029 -.011556 -.0006273 gdppercapita -.0373484 .1126764 -0.33 0.740 -.25819 .1834932 gdp .1181215 .0370665 3.19 0.001 .0454724 .1907706 L1. .0363727 .0645867 0.56 0.573 -.0902149 .1629603 finst finst Coef. Std. Err. z P>|z| [95% Conf. Interval] Robust
Prob > chi2 = 0.000 max = 24 Wald chi2(8) = 33.22 avg = 24.00 Number of instruments = 330 Obs per group: min = 24 Time variable : year Number of groups = 14 Group variable: id Number of obs = 336 Dynamic panel-data estimation, one-step system GMM
Difference (null H = exogenous): chi2(3) = 5.23 Prob > chi2 = 0.156 Hansen test excluding group: chi2(318) = 2.35 Prob > chi2 = 1.000 iv(L.gdppercapita L.gdp L.flib)
Difference (null H = exogenous): chi2(23) = 0.00 Prob > chi2 = 1.000 Hansen test excluding group: chi2(298) = 7.57 Prob > chi2 = 1.000 GMM instruments for levels
Difference-in-Hansen tests of exogeneity of instrument subsets: (Robust, but weakened by many instruments.)
Hansen test of overid. restrictions: chi2(321) = 7.57 Prob > chi2 = 1.000 (Not robust, but not weakened by many instruments.)
Sargan test of overid. restrictions: chi2(321) = 334.82 Prob > chi2 = 0.286 Arellano-Bond test for AR(2) in first differences: z = 0.98 Pr > z = 0.326 Arellano-Bond test for AR(1) in first differences: z = -1.90 Pr > z = 0.057 D.(gdppercapita gdp flib)
GMM-type (missing=0, separate instruments for each period unless collapsed) _cons
L.gdppercapita L.gdp L.flib Standard
Instruments for levels equation L(1/25).(gdppercapita gdp flib)
GMM-type (missing=0, separate instruments for each period unless collapsed) D.(L.gdppercapita L.gdp L.flib)
Standard
Instruments for first differences equation
_cons -.7933231 .5045174 -1.57 0.116 -1.782159 .1955128 flib -.0867959 .1070564 -0.81 0.418 -.2966227 .1230309 govexpend -.0428443 .0401777 -1.07 0.286 -.121591 .0359025 ouputgap -.1477319 .0512433 -2.88 0.004 -.2481669 -.0472968 dtetrade -.0079501 .011416 -0.70 0.486 -.030325 .0144249 inflation -.0090796 .002784 -3.26 0.001 -.0145362 -.003623 gdppercapita .1631475 .1259246 1.30 0.195 -.0836601 .4099551 gdp .0850104 .0381517 2.23 0.026 .0102344 .1597865 L1. .0829939 .0614724 1.35 0.177 -.0374898 .2034776 finst finst Coef. Std. Err. z P>|z| [95% Conf. Interval] Robust
Prob > chi2 = 0.000 max = 24 Wald chi2(8) = 48.04 avg = 24.00
Difference (null H = exogenous): chi2(4) = 0.83 Prob > chi2 = 0.934 Hansen test excluding group: chi2(321) = 1.42 Prob > chi2 = 1.000 iv(L.gdppercapita L.gdp L.fdev L.flib)
Difference (null H = exogenous): chi2(22) = -0.00 Prob > chi2 = 1.000 Hansen test excluding group: chi2(303) = 2.25 Prob > chi2 = 1.000 GMM instruments for levels
Difference-in-Hansen tests of exogeneity of instrument subsets: (Robust, but weakened by many instruments.)
Hansen test of overid. restrictions: chi2(325) = 2.25 Prob > chi2 = 1.000 (Not robust, but not weakened by many instruments.)
Sargan test of overid. restrictions: chi2(325) = 363.00 Prob > chi2 = 0.072 Arellano-Bond test for AR(2) in first differences: z = 0.77 Pr > z = 0.444 Arellano-Bond test for AR(1) in first differences: z = -1.94 Pr > z = 0.052 D.(gdppercapita gdp fdev flib)
GMM-type (missing=0, separate instruments for each period unless collapsed) _cons
L.gdppercapita L.gdp L.fdev L.flib Standard
Instruments for levels equation
L(1/25).(gdppercapita gdp fdev flib)
GMM-type (missing=0, separate instruments for each period unless collapsed) D.(L.gdppercapita L.gdp L.fdev L.flib)
Standard
Instruments for first differences equation
_cons 1.005422 1.436361 0.70 0.484 -1.809793 3.820638 fdev .2111003 .0903073 2.34 0.019 .0341012 .3880993 flib -.1211144 .1301976 -0.93 0.352 -.3762969 .1340682 govexpend -.0788846 .0559075 -1.41 0.158 -.1884613 .0306921 ouputgap -.1521527 .0542738 -2.80 0.005 -.2585274 -.045778