(Luận văn thạc sĩ) thâm hụt tài khóa và thâm hụt thương mại ở các nền kinh tế mới nổi châu á

BỘ GIÁO DỤC VÀ ĐÀO TẠO T G ĐẠI C I THÂM T T THÂM L Ậ Ă T ỒC Í SĨ I - Ă 2013 C BỘ GIÁO DỤC VÀ ĐÀO TẠO T G ĐẠI C I THÂM T T THÂM C T - 60340201 L Ậ Ă SĨ : PGS.TS S T ỒC Í I - Ă 2013 C L T TÁC GIẢ LUẬ VĂ D I I U L T B ọ T p Ả Gá Đ ồC ạ Đạ ọ T ề Đạ ọ p T T ầ C T Đạ ọ T p ồC ọ p T T ầ – PGS.TS Đ T k X T ọ T ỉ óp ý è ề p ! Tá D L Trang T L p ụ ụ ụ D ụ D ụ D ụ L ý ữ ẽ ắ ị Ầ Lý ọ ề ụ p áp Đ p Ý ĩ B ễ ề ụ 1.1 Cá ý ề ụ ó ụ 1.1.1 Lý ề ụ 1.1.2 Lý ề ụ ó ó thâm hụt 1.1.3 Thâm hụt p ầ 1.2 Cá lý hụt ềm quan h t h â m hụt 1.2.1 Thâm hụt tài khóa tác ó thâm 10 ng n thâm hụ 10 ó Thâm ụ 1.2.2 Thâm hụ có m không uan h 1.2.3 Cá 11 ụ ụ ó 13 1.3 Đá á ề ụ ó ụ 15 21 2.1 21 2.2 p áp 2.2.1 ị 2.2.2 ị 22 ỗ 22 C ữ 27 2.2.3 ị ữ ệ 3.1 T p ữ 3.2 ị 3.3 ị G 29 ế q ả 37 ỉ 41 G ế L 49 í 51 4.1 Cá p 51 4.2 H ý 4.3 ý 4.4 L 31 ị ệ 31 ( Error Correction Mechanism - ECM) 3.4 ự p Ả ó 52 ề 53 54 55 Ý IMF Q ỹ ề GDP Tổ TDGDP B thâm ụ / FDGDP B thâm ụ / LnEX B INF B FDI V ầ ECM Mô h / GDP Ắ ó / GDP á p p ỉ ị PP ị V Ữ p ẩ ADF ODA , A D p p -Fuller test ĩ BẢ B 3.1 T B 3.2 B 3.3 ị ,B Ể ữ 36 37 f p -Perron khơng có ễ2 B 38 ị 3.4 f p - ó ễ2 B 39 ị 3.5 f nh Phillips-Perron không xu ễ2 B 40 ị 3.6 f p - ó ễ2 B 41 3.7 p C ó B 42 3.8 T C B p ầ óp 3.9 ị 45 f p -Perron khơng xu ễ2 B 3.10 45 ị f p - ễ2 B 46 óp B 3.11 ắ C 3.12 47 3.13 (robust) óp G (robust) B 50 óp G 51 ÁC Ồ Đồ ị 3.1 Thâm ụ Ị P ổ C L Á 2012 Đồ 32 ị 3.2 Thâm ụ ó ổi C Á 2012 32 Đồ ị 3.3 Lạ p Đồ ị 3.4 T á ổ C Á ổ C Á 2012 33 33 ễ2 64 2012 ụ ụ 1: ị TDGD ụ ụ 3: ị I ụ ụ 4: ị L ụ ụ 5: ị TDGD ó ễ2 66 ụ ụ 6: ị DGD ó ễ2 67 ụ ụ : ị I ó ụ ụ : ị L X ó ụ ụ :K ị DTDGD ụ ụ 10: ị ễ2 X ễ2 DTDGD ụ ụ 11: 64 65 ễ2 67 ễ2 68 ó ó ễ2 ễ2 C 69 óp 69 ụ ụ 12 T 68 p ầ C 70 ụ ụ 13: ị ụ ụ 14: ị ễ2 ó ễ2 70 71 ụ ụ 15 p ắ C ó 71 ụ ụ 16: Hồ óp Granger ụ ụ 17: Hồ cho DTDGD óp G DGD 71 72 58 Panel Data Approach, Working Papers, WP 24/2009/DE/UECE 33 Freeman, John R., 1983, Granger Causality and the Time Series Analysis of Political Relationships, American Journal of Political Science, 27:327-58 34 Gale, W., G., and Orszag, P., R., 2003, Budget Deficits, National Saving, and Interest Rates, Brookings Institution and Tax Policy Center 35 Granger, C W J., 1969, Investigating Causal Relations by Econometric Models and Cross-spectral Methods, Econometrica, Vol 37, No 3, pp 424-438 36 Granger, C W J and Newbold, P., 1974, Spurious Regressions In Econometrics, Journal of Econometrics 2, pp 111-120 37 Gregory, A.W., Hansen, B.E., 1996a, Residual-based tests for cointegration in modelswith regime shifts, Journal of Econometrics 70, 99–126 38 Gregory, A.W., Hansen, B.E., 1996b, Tests for cointegration in models with regime and trend shifts Oxford Bulletin of Economics and Statistics 58, 555– 560 39 Grier, K., Ye, H., 2009, Twin sons of different mothers: the long and short of the twin deficits debate, Economic Inquiry 47, 625–638 40 Harris, R.D.F and Tzavalis, E., 1999, Inference for unit roots in dynamic panels where the time dimension is fixed, Journal of Econometrics, 91:201–226 41 Hassan, M., 2004, Budget Deficits and the Current Account Balance: New Evidence from Panel Data, Journal of Econimics and Finance; Spring 244; 28, 1, Proquest central, Pg.39 42 Heng, T.K, 1997, Public capital and crowding in, The Singapore Economic review 42 43 Holmes, M.J., 2011, Threshold cointegration and the short-run dynamics of twin deficit behaviour Research in Economics 65, 271–277 44 Hurlin, 2004, Testing Granger causality in heterogeneous panel data models 59 with fixed coefficients, Mimeo, University of Orléans 45 Hurlin and Vernet, 2001, Granger causality tests in panel data models with fixed coefficients, Working Paper Eurisco2001-09, Université Paris IX Dauphine 46 Islam B T D f p Atlantic Economic Journal 26: 121-128 47 James, T and Willem, B., 1980, Fiscal and Monetary Policies, Capital Formation, and Eco- nomic Activity, in von Furstenberg, George M., editor, The Government and Capital Formnation, Cam- bridge: Ballinger 48 Hansen, B.E., 1996, Inference When a Nuisance Parameter Is Not Identied Under the Null Hypothesis, Econometrica Vol 64, pp 413-430 49 Katja F., and Christiance N., 2006, Does fiscal policy matter for the trade account ? 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Robustness Checks and Robustness Tests in Applied Economics, Department of Economics University of California, San Diego 90 Yellen, J.L, 1989, Symposium on the Budget deficit, Journal of Economic Perspective 64 Ụ LỤC ụ ụ 1: ị TDGD ễ2 Fisher-type unit-root test for TDGDP Based on Phillips-Perron tests Ho: All panels contain unit roots Ha: At least one panel is stationary Number of panels = Avg number of periods = 25.00 AR parameter: Panel means: Time trend: Newey-West lags: Asymptotics: T -> Infinity Panel-specific Included Not included lags Inverse chi-squared(12) Inverse normal Inverse logit t(34) Modified inv chi-squared Statistic p-value 12.7965 0.0342 0.3494 0.1626 0.3840 0.5136 0.6355 0.4354 P Z L* Pm P statistic requires number of panels to be finite Other statistics are suitable for finite or infinite number of panels ụ ụ 2: ị FDGDP, không x Fisher-type unit-root test for FDGDP Based on Phillips-Perron tests Ho: All panels contain unit roots Ha: At least one panel is stationary Number of panels = Avg number of periods = 25.00 AR parameter: Panel means: Time trend: Newey-West lags: Asymptotics: T -> Infinity Panel-specific Included Not included lags Inverse chi-squared(12) Inverse normal Inverse logit t(34) Modified inv chi-squared P Z L* Pm Statistic p-value 37.6884 -4.0241 -4.1957 5.2436 0.0002 0.0000 0.0001 0.0000 P statistic requires number of panels to be finite Other statistics are suitable for finite or infinite number of panels ễ2 65 ụ ụ 3: ị I ễ2 Fisher-type unit-root test for INF Based on Phillips-Perron tests Ho: All panels contain unit roots Ha: At least one panel is stationary Number of panels = Avg number of periods = 25.00 AR parameter: Panel-specific Panel means: Included Time trend: Not included Newey-West lags: lags Asymptotics: T -> Infinity Statistic p-value 51.0344 -5.0763 -5.7525 7.9679 0.0000 0.0000 0.0000 0.0000 Inverse chi-squared(12) P Inverse normal Z Inverse logit t(34) L* Modified inv chi-squared Pm P statistic requires number of panels to be finite Other statistics are suitable for finite or infinite number of panels ụ ụ 4: ị L X Fisher-type unit-root test for lnEX Based on Phillips-Perron tests Ho: All panels contain unit roots Ha: At least one panel is stationary Number of panels = Avg number of periods = 25.00 AR parameter: Panel-specific Panel means: Included Time trend: Not included Newey-West lags: lags Asymptotics: T -> Infinity Inverse chi-squared(12) P Inverse normal Z Inverse logit t(19) L* Modified inv chi-squared Pm Statistic p-value 2.1612 1.8145 2.0883 -2.0083 0.9991 0.9652 0.9748 0.9777 P statistic requires number of panels to be finite Other statistics are suitable for finite or infinite number of panels ễ2 66 ụ ụ 5: ị TDGD ó ễ2 Fisher-type unit-root test for TDGDP Based on Phillips-Perron tests Ho: All panels contain unit roots Ha: At least one panel is stationary Number of panels = Avg number of periods = 25.00 AR parameter: Panel means: Time trend: Newey-West lags: Asymptotics: T -> Infinity Panel-specific Included Included lags Inverse chi-squared(12) Inverse normal Inverse logit t(34) Modified inv chi-squared Statistic p-value 6.2880 1.1834 1.1883 -1.1659 0.9009 0.8817 0.8785 0.8782 P Z L* Pm P statistic requires number of panels to be finite Other statistics are suitable for finite or infinite number of panels ụ lụ 6: ị DGD ó Fisher-type unit-root test for FDGDP Based on Phillips-Perron tests Ho: All panels contain unit roots Ha: At least one panel is stationary Number of panels = Avg number of periods = 25.00 AR parameter: Panel means: Time trend: Newey-West lags: Asymptotics: T -> Infinity Panel-specific Included Included lags Inverse chi-squared(12) Inverse normal Inverse logit t(34) Modified inv chi-squared P Z L* Pm Statistic p-value 28.3215 -2.9231 -2.9559 3.3316 0.0050 0.0017 0.0028 0.0004 P statistic requires number of panels to be finite Other statistics are suitable for finite or infinite number of panels ễ2 67 ụ ụ ị : I ó ễ2 Fisher-type unit-root test for INF Based on Phillips-Perron tests Ho: All panels contain unit roots Ha: At least one panel is stationary Number of panels = Avg number of periods = 25.00 AR parameter: Panel means: Time trend: Newey-West lags: Asymptotics: T -> Infinity Panel-specific Included Included lags Inverse chi-squared(12) Inverse normal Inverse logit t(34) Modified inv chi-squared Statistic p-value 45.3166 -4.5929 -5.0518 6.8007 0.0000 0.0000 0.0000 0.0000 P Z L* Pm P statistic requires number of panels to be finite Other statistics are suitable for finite or infinite number of panels ụ ụ ị : L X ó Fisher-type unit-root test for lnEX Based on Phillips-Perron tests Ho: All panels contain unit roots Ha: At least one panel is stationary Number of panels = Avg number of periods = 25.00 AR parameter: Panel means: Time trend: Newey-West lags: Asymptotics: T -> Infinity Panel-specific Included Included lags Inverse chi-squared(12) Inverse normal Inverse logit t(19) Modified inv chi-squared P Z L* Pm Statistic p-value 72.4241 -3.0262 -10.1457 12.3340 0.0000 0.0012 0.0000 0.0000 P statistic requires number of panels to be finite Other statistics are suitable for finite or infinite number of panels ễ2 68 ụ ụ ị : DTDGD ó ễ2 Fisher-type unit-root test for DTDGDP Based on Phillips-Perron tests Ho: All panels contain unit roots Ha: At least one panel is stationary Number of panels = Avg number of periods = 23.83 AR parameter: Panel-specific Panel means: Included Time trend: Not included Newey-West lags: lags Asymptotics: T -> Infinity Inverse chi-squared(12) P Inverse normal Z Inverse logit t(34) L* Modified inv chi-squared Pm Statistic p-value 101.5481 -8.2819 -11.5720 18.2789 0.0000 0.0000 0.0000 0.0000 P statistic requires number of panels to be finite Other statistics are suitable for finite or infinite number of panels ụ ụ 10: ị DTDGD ó Fisher-type unit-root test for DTDGDP Based on Phillips-Perron tests Ho: All panels contain unit roots Ha: At least one panel is stationary Number of panels = Avg number of periods = 23.83 AR parameter: Panel means: Time trend: Newey-West lags: Asymptotics: T -> Infinity Panel-specific Included Included lags Inverse chi-squared(12) Inverse normal Inverse logit t(34) Modified inv chi-squared P Z L* Pm Statistic p-value 90.6994 -7.2642 -10.2371 16.0644 0.0000 0.0000 0.0000 0.0000 P statistic requires number of panels to be finite Other statistics are suitable for finite or infinite number of panels ễ2 69 ụ ụ 11: C óp Fixed-effects (within) regression Group variable: Id Number of obs = Number of groups = 150 R-sq: within = 0.3016 between = 0.0019 overall = 0.0883 Obs per group: = avg = max = 17 25.0 27 corr(u_i, Xb) = -0.2136 F(3,5) Prob > F = = 10.65 0.0130 (Std Err adjusted for clusters in Id) Robust Coef Std Err TDGDP FDGDP INF lnEX _cons sigma_u sigma_e rho -1.329812 0633838 -2.35e-06 -.9047929 2550843 0638189 0000527 8118107 óp Res -5.21 0.99 -0.04 -1.11 P>|t| [95% Conf Interval] 0.003 0.366 0.966 0.316 -1.985528 -.6740973 -.1006679 2274356 -.0001379 0001332 -2.991619 1.182033 6.6022541 4.5765277 67545035 (fraction of variance due to u_i) ụ ụ 12: T Variable t p ầ ạ Mean Std Dev Min Max Observations overall -2.86e-08 7.384262 -14.65421 21.56589 N = 150 between 6.602254 -8.65165 8.339896 n = within 4.451973 -15.3296 13.226 T-bar = 25 C 70 ụ ụ 13: ị ễ2 Fisher-type unit-root test for Res Based on Phillips-Perron tests Ho: All panels contain unit roots Ha: At least one panel is stationary Number of panels = Avg number of periods = 25.00 AR parameter: Panel means: Time trend: Newey-West lags: Asymptotics: T -> Infinity Panel-specific Included Not included lags Inverse chi-squared(12) Inverse normal Inverse logit t(34) Modified inv chi-squared Statistic p-value 38.9590 -3.4345 -4.0084 5.5030 0.0001 0.0003 0.0002 0.0000 P Z L* Pm P statistic requires number of panels to be finite Other statistics are suitable for finite or infinite number of panels ụ ụ 14: ị ó Fisher-type unit-root test for Res Based on Phillips-Perron tests Ho: All panels contain unit roots Ha: At least one panel is stationary Number of panels = Avg number of periods = 25.00 AR parameter: Panel means: Time trend: Newey-West lags: Asymptotics: T -> Infinity Panel-specific Included Included lags Inverse chi-squared(12) Inverse normal Inverse logit t(34) Modified inv chi-squared P Z L* Pm Statistic p-value 27.8517 -1.8774 -2.2592 3.2357 0.0058 0.0302 0.0152 0.0006 P statistic requires number of panels to be finite Other statistics are suitable for finite or infinite number of panels ễ2 71 ụ ụ 15 ắ C óp Fixed-effects (within) regression Group variable: Id Number of obs Number of groups = = 143 R-sq: within = 0.2829 between = 0.0943 overall = 0.1369 Obs per group: = avg = max = 16 23.8 26 corr(u_i, Xb) = -0.7221 F(4,5) Prob > F = = 12.93 0.0076 (Std Err adjusted for clusters in Id) Robust Std Err DTDGDP Coef t P>|t| DFDGDP DINFLA DlnEX LRes _cons -.8726357 0677093 9.66e-06 -.3231909 20862 1944378 0286704 0000441 0774756 0794999 sigma_u sigma_e rho 2.2099128 3.1191434 33420869 (fraction of variance due to u_i) -4.49 2.36 0.22 -4.17 2.62 0.006 0.065 0.835 0.009 0.047 [95% Conf Interval] -1.372454 -.0059904 -.0001037 -.5223482 004259 ụ ụ 16: Hồ -.3728173 1414089 000123 -.1240335 4129809 óp G DTDGD Fixed-effects (within) regression Group variable: Id Number of obs Number of groups = = 136 R-sq: within = 0.1779 between = 0.1352 overall = 0.1744 Obs per group: = avg = max = 15 22.7 25 corr(u_i, Xb) = -0.1377 F(3,5) Prob > F = = 26.29 0.0017 (Std Err adjusted for clusters in Id) Robust Std Err DTDGDP Coef t P>|t| [95% Conf Interval] FDGDP L1 L2 -.699591 5726983 3451381 1433787 2464672 0562303 -4.88 2.32 6.14 0.005 0.068 0.002 -1.068158 -.0608657 2005934 -.3310244 1.206262 4896827 _cons 5114747 3736074 1.37 0.229 -.4489138 1.471863 sigma_u sigma_e rho 40401588 3.3396397 01442407 (fraction of variance due to u_i) 72 ụ ụ 17: Hồ óp G DGD Fixed-effects (within) regression Group variable: Id Number of obs = Number of groups = 129 R-sq: within = 0.0897 between = 0.2901 overall = 0.0487 Obs per group: = avg = max = 14 21.5 24 corr(u_i, Xb) = -0.0480 F(3,5) Prob > F = = 7.80 0.0248 (Std Err adjusted for clusters in Id) FDGDP DTDGDP L1 L2 _cons sigma_u sigma_e rho Robust Coef Std Err -.0548115 0844699 -.1345203 0994474 -.1068991 0509061 t P>|t| -0.65 0.545 -1.35 0.234 -2.10 0.090 -2.056881 0221692 -92.78 0.000 [95% Conf Interval] -.2719484 -.390158 -.2377573 1623253 1211174 0239592 -2.113868 -1.999893 1.5869105 2.1500944 35264216 (fraction of variance due to u_i) ... V ề ụ ề ụ p ầ á Đ L ữ ổ.Q ề ĩ ữ thâm ụ ó ổ á p áp óp ỏ thâm ụ ó àm ý cho sách cho ó ụ ó, ề ó ó ề Cá p ề ụ ụ ó ó ó ? P Đề tài ụ ữ thâm ụ p á ị p p áp á. P cho ề ó , thâm ụ ơ p áp sau: ị p ổ ữ... quan h t h â m hụt 1.2.1 Thâm hụt tài khóa tác ó thâm 10 ng n thâm hụ 10 ó Thâm ụ 1.2.2 Thâm hụ có m khơng uan h 1.2.3 Cá 11 ụ ụ ó 13 1.3 ? ?á á ề ụ ó ụ 15 21 2.1 21 2.2 p áp 2.2.1 ị 2.2.2 ị 22 ỗ... (5) ụ thâm ụ / ó thâm ụ / ĩ p Q thâm ụ G ụ/ ổ ó thâm ụ ép l yế 1.2 T ẽ thâm ụ / ó ó ụ ơ p ị ó thâm thâm ụ / ề mố quan hệ t hâ m h t ý thâm ụ / ý thâm h t p ữ ụ 1.2.1 Thâm h t tài khóa tác đ ng