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TR – ăm 2017 TIEU LUAN MOI download : skknchat@gmail.com – 0201 PGS.TS H VI T TI N – ăm 2017 TIEU LUAN MOI download : skknchat@gmail.com TIEU LUAN MOI download : skknchat@gmail.com 10 13 13 15 16 17 22 28 28 29 29 TIEU LUAN MOI download : skknchat@gmail.com 31 32 33 33 39 4.2.1 Ki ng h 4.2.1.1 Gi nh 40 ổi 40 a sai s ữ 4.2.1.2 Gi ầ 40 4.2.1.3 Gi ữ cl ( y hi n ng n) 41 4.2.1.4 Hi ng n i sinh 42 i quy GMM 42 m c a GMM 42 4.2.2.2 Th t n 44 46 ữ 46 ổ ữ 4.3.2.1 Ma tr 50 ặp bi n 50 4.3.2.2 Ki nh hi ổi phầ ữ – Greene (2000) 53 4.3.2.3 Ki nh hi W e( ) ng t e ( ầ ữ – ) 55 56 5: 63 64 64 e 65 66 TIEU LUAN MOI download : skknchat@gmail.com ( e BLUE e Unbiased Estimators) ( CFA ( CPI e ữ FED ổ IFS ( WEG WGI union) e e e) e e e ) (International Monetary Fund) ( MVP WDI e (Gross Domestic Product) e e WB e ) e ( e e GMM IMF e ( EMU GDP ) (W e ) ) (W e e e (W ầ (W ) Outlook) e e e TIEU LUAN MOI download : skknchat@gmail.com ) ổ 23 – 2015 30 W e 1996 – 2015 31 35 B ng 4.2: Th B ng 4.3: Ma tr 46 ữ ặp bi 51 B ng 4.4: K t qu ki m t ng n v 52 B ng 4.5: K t qu ki ổi c 54 B ng 4.6: K t qu ki m tra t 55 B ng 4.7: K t qu h 56 B ng 4.8: K t qu h 59 TIEU LUAN MOI download : skknchat@gmail.com – 2015 28 – 2015 29 – 2015 29 TIEU LUAN MOI download : skknchat@gmail.com Ph l c 3: Ma tr Ph l c : ổi Ph l c : Ki Ph l c : T Ph l c 7: K t qu h i quy Ph l c 8: K t qu h 4.7 TIEU LUAN MOI download : skknchat@gmail.com 1 ặ ổ 11 Trong b i c ng ho ng h i nh p v i n n kinh t th ầ gi i, ữ ặ e ặ ầ ặ e ổ ầ ặ ặ e ( e ặ ) ữ e e ( ) e gia ( ) ặ TIEU LUAN MOI download : skknchat@gmail.com 65 e ( ) e e ( ) ỗ ( e ) ữ ữ ( ) e ữ ầ ổ ( ) ầ ( ) 52 ữ – 2015 gi e e e e u e e n ch TIEU LUAN MOI download : skknchat@gmail.com 66 t qu ặ gi ữ ặ ữ ẹ ữ ữ e ngh e ặ ữ ữ ỗ ữ ữ ặ ữ ẹ ữ e TIEU LUAN MOI download : skknchat@gmail.com m – 2006 cho ho ng qu C i h i hi n T cl n N trang 18-22 m qu c t h c cho Vi t Nam T -39 ữ li u - i h c Kinh t , 2016 ê K li u ph c v ê ứu ch : n d li ứu v th ch m Armas, A., Ize, A and Yeyati, E.L., 2006 Financial Dollarization: An Overview In: Armas, A., Ize, A and Yeyati, E.L., eds 2006 Financial Dollarization: The Policy Agenda Springer, pp.1-12 e Exchange rate regimes and financial dollarization: does flexibility reduce bank currency mismatches? University Of California, Berkeley, California, Center For International And Development Economics Research Broda, C.M, Yeyati, E.L., 2003 Dollarization and the lender of last resort In: Yeyati, E.L., Sturzenegger, F., eds 2003 Dollarization MIT Press, Cambridge, pp.101-130 Broda, C.M., Yeyati, E.L., 2006 Endogenous deposit dollarization Journal of Money, Credit and Banking, 38(4): 963-988 Calvo, G.A., Rodriguez, C.A., 1977 A model of exchange rate determination under currency substitution and rational expectations Journal of Political Economy, 85(3): 617-625 TIEU LUAN MOI download : skknchat@gmail.com e beyond: analytical and policy issues In: Calvo, G.A., ed 1996 Money, Exchange Rates, and Output MIT Press, Cambridge, pp.153-75 Chin, M.D., Ito, H., 2008 A new measure of financial openness Journal of Comparative Policy Analysis, 10(3): 309-322 Cohen, B., 2000 Dollarization: Pros and cons In workshop: Dollars, Democracy and Trade: External Influences on Economic Integration in the Americas Los Angeles, US, May 2000 De la Torre, A., Schmukler, S.L., 2004 Coping with risks through mismatches: domestic and international financial contracts for emerging economies International Finance, 7(3): 349-390 e e deposits: Causes and consequences Journal of Banking & Finance, 29(7): 16971727 Dow, J., 2000 What is Systemic Risk?: moral hazard, initial shocks and propagation Institute for Monetary and Economic Studies, Bank of Japan Greenspan, A., 1995 Remarks Research Conference on Risk measurement and Systemic risk Washington, DC, November 1995 Honig, A., 2009 Dollarization, exchange rate regimes and government quality Journal of International Money and Finance, 28(2): 198-214 Honohan, P., 2008 The retreat of deposit dollarization International Finance, 11(3): 247-268 Ilzetzki, E.O., Reinhart, C.M., Rogoff, K., 2009 Exchange rate arrangements into the 21st century: Will the anchor currency hold? Harvard University, Cambridge and University of Maryland, Colledge Park TIEU LUAN MOI download : skknchat@gmail.com International Monetary Fund, 2017 Wold Economic Outlook (WEO) Available at: [Accessed 10 February 2017] International Monetary Fund, 2017 International Financial Statistics (IFS) Available at: [Accessed 10 February 2017] Ize, A., Yeyati, E.L., 2003 Financial dollarization Journal of International Economics, 59(2): 323-347 Kupiec, P., Nickerson, D., 2004 Assessing systemic risk exposure from banks and GSEs under alternative approaches to capital regulation The Journal of Real Estate Finance and Economics, 28(2): 123-145 Miles, M.A., 1978 Currency substitution, flexible exchange rates, and monetary independence The American Economic Review, 68(3): 428-436 Rennhack, R., Nozaki, M., 2006 Financial Dollarization in Latin America In: Armas, A., Ize, A and Yeyati, E.L., eds 2006 Financial Dollarization: The Policy Agenda Springer, pp.64-96 Romer, D., 2006 Advanced macroeconomics, third ed McGraw-Hill/Irwin Savastano, M.A., 2010 The Pattern of Currency Substitution in Latin American: An Overview A E –Economic Analysis Review, 7(1): 29-72 Schuler, K., 2000 Basics of dollarization In: Schuler, K., 2000 Joint Economic Committee Staff Report US Congress Schwarcz, S.L., 2008 Systemic risk Georgetown Law Journal, 97(1): 193251 Thomas, L.R., 1985 Portfolio theory and currency substitution Journal of Money, Credit and Banking, 17(3): 347-357 TIEU LUAN MOI download : skknchat@gmail.com Vieira, F.A., Holland, M., and Resende, M.F., 2012 Financial dollarization and systemic risks: New empirical evidence Journal of International Money and Finance, 31(6): 1695-1714 Weymouth, S., 2011 Political institutions and property rights: veto players and foreign exchange commitments in 127 countries Comparative Political Studies, 44(2): 211-240 World Bank, 2016 Worldwide Governance Indicators (WGI) Available at: [Accessed 10 February 2017] World Bank, 2017 World Development Indicators (WDI) Available at: [Accessed 29 April 2017] Yeyati, E.L., 2006 Financial dollarization: evaluating the consequences Economic Policy, 21(45): 62-118 Yeyati, E.L., 2010 Dataset: deposit dollarization and dollarization restrictions Available at: [Accessed 10 January 2017] Yeyati, E.L., Ize, A., 2005 Financial De-Dollarization: Is it for Real? IMF Working Paper TIEU LUAN MOI download : skknchat@gmail.com m 27 Belarus Jamaica Nigeria Belize Jordan Peru Bhutan Malaysia Philippines Colombia Maldives Russian Federation Dominica Mauritius Sri Lanka El Salvador Moldova Thailand Georgia Mongolia Uganda Guatemala Morocco Ukraine Indonesia Nepal Vietnam Ph l c 2: Th m Variable Obs Mean dolldep resdoldep inf infvol infacc 540 540 540 540 540 2053041 1.027778 8.717213 1.330886 1.735091 offexc mvp gdp rullaw concorr 540 540 540 540 540 regqua goveff polsta voiacc reaexdummy fo pubdeb size usint Std Dev Min Max 2129596 1.681827 17.43045 2.721653 2.720155 0 -18.10863 -6.850385 -6.44492 8618019 293.6787 15.1456 15.55107 3.734427 7851811 7.652748 -.3204231 -.3480363 2.695173 1.734388 9276857 5686385 5034218 -.3439235 -14.76693 5.330015 -1.522928 -1.388785 9.984956 32.81758 9.651409 1.056625 1.274812 540 540 540 540 540 -.1128969 -.1735083 -.3993416 -.2646469 6.97037 5153951 507325 854299 62377 3.414888 -1.851461 -1.200624 -2.3857 -1.770218 1.123364 1.238739 1.303556 1.109454 15 540 540 540 540 248507 3.785497 23.81344 3.636505 1.418649 6410203 2.033806 2.065995 -1.894798 1.550382 19.28122 1.161394 2.389193 5.579373 28.4333 7.190871 TIEU LUAN MOI download : skknchat@gmail.com Ph l c 3: Ma tr dolldep inf infvol infacc mvp rullaw pubdeb fo gdp reaexdummy size dolldep inf infvol infacc mvp rullaw pubdeb fo 1.0000 0.2169 0.3284 0.3278 0.0002 -0.1271 -0.0320 0.2313 -0.1040 0.2127 -0.0671 1.0000 0.4125 0.4051 0.0142 -0.2463 -0.1107 -0.1739 -0.1334 0.3186 0.0361 1.0000 0.9999 0.0143 -0.3786 0.0395 -0.1053 -0.2642 0.3015 -0.0291 1.0000 0.0143 -0.3783 0.0403 -0.1046 -0.2641 0.3007 -0.0290 1.0000 -0.0097 0.0205 0.0584 0.0282 0.0256 0.0294 1.0000 0.3225 0.0795 0.2946 -0.4069 -0.3683 1.0000 0.0535 -0.1407 -0.2626 -0.4168 1.0000 0.1594 -0.1179 -0.0483 Ph l i Variable VIF 1/VIF infvol infacc rullaw lrullaw pubdeb lpubdeb inf linfacc linf size reaexdummy gdp ldolldep fo lmvp mvp 25339.65 25247.80 41.02 40.42 10.23 9.79 5.93 2.87 2.78 2.32 2.15 1.59 1.33 1.20 1.02 1.01 0.000039 0.000040 0.024376 0.024741 0.097764 0.102144 0.168646 0.348968 0.359886 0.431116 0.465215 0.629842 0.749583 0.834443 0.977779 0.985826 Mean VIF 3169.44 gdp reaexd~y 1.0000 -0.2521 0.2051 1.0000 0.5392 F TIEU LUAN MOI download : skknchat@gmail.com size 1.0000 Ph l c : Ki m i Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (27) = Prob>chi2 = 69022.58 0.0000 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (27) = Prob>chi2 = 66473.32 0.0000 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (27) = Prob>chi2 = 81727.25 0.0000 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (27) = Prob>chi2 = 1.6e+05 0.0000 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (27) = Prob>chi2 = 1.6e+05 0.0000 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (27) = Prob>chi2 = 1.6e+05 0.0000 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (27) = Prob>chi2 = 1.6e+05 0.0000 Modified Wald test for groupwise heteroskedasticity in fixed effect regression model H0: sigma(i)^2 = sigma^2 for all i chi2 (27) = Prob>chi2 = 83527.57 0.0000 TIEU LUAN MOI download : skknchat@gmail.com Ph l c : T Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 26) = 10.629 Prob > F = 0.0031 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 26) = 10.037 Prob > F = 0.0039 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 26) = 9.849 Prob > F = 0.0042 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 26) = 10.496 Prob > F = 0.0033 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 26) = 8.627 Prob > F = 0.0069 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 26) = 9.891 Prob > F = 0.0041 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 26) = 10.055 Prob > F = 0.0039 Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation F( 1, 26) = 10.408 Prob > F = 0.0034 TIEU LUAN MOI download : skknchat@gmail.com Ph l c 7: K t qu h 4.7 Dynamic panel-data estimation, one-step system GMM Group variable: id Time variable : year Number of instruments = 204 Wald chi2(16) = 264.71 Prob > chi2 = 0.000 dolldep Coef ldolldep inf linf infvol infacc linfacc mvp lmvp rullaw lrullaw pubdeb lpubdeb fo gdp reaexdummy size _cons 2724091 0020705 -.0002732 -.7323837 7325428 0055702 -.0019251 -.0027723 -.0007657 -.1422896 -.0327426 -.0065055 0029004 0470266 0053929 -.073216 1.281248 Number of obs Number of groups Obs per group: avg max Robust Std Err .2413522 0011442 0004709 3398275 3397773 002761 0013007 0018627 0700718 0722264 0351484 0350026 0233462 0392317 0039968 0453174 1.018219 z 1.13 1.81 -0.58 -2.16 2.16 2.02 -1.48 -1.49 -0.01 -1.97 -0.93 -0.19 0.12 1.20 1.35 -1.62 1.26 P>|z| 0.259 0.070 0.562 0.031 0.031 0.044 0.139 0.137 0.991 0.049 0.352 0.853 0.901 0.231 0.177 0.106 0.208 = = = = = 513 27 19 19.00 19 [95% Conf Interval] -.2006325 -.000172 -.0011962 -1.398433 0665914 0001587 -.0044745 -.006423 -.1381038 -.2838508 -.1016322 -.0751094 -.0428574 -.0298661 -.0024408 -.1620364 -.7144246 7454507 004313 0006498 -.0663341 1.398494 0109818 0006243 0008784 1365725 -.0007284 0361471 0620983 0486581 1239193 0132266 0156044 3.27692 Instruments for first differences equation Standard D.(lpubdeb linfvol L.gdp D.size linf) GMM-type (missing=0, separate instruments for each period unless collapsed) L(1/4).(lmvp linfacc linf) Instruments for levels equation Standard lpubdeb linfvol L.gdp D.size linf _cons Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = -2.54 -0.18 Pr > z = Pr > z = 0.011 0.857 Prob > chi2 = 0.287 Prob > chi2 = 1.000 Difference-in-Hansen tests of exogeneity of instrument subsets: iv(lpubdeb linfvol L.gdp D.size linf) Hansen test excluding group: chi2(182) = 10.70 Prob > chi2 = Difference (null H = exogenous): chi2(5) = 2.18 Prob > chi2 = 1.000 0.824 Sargan test of (Not robust, Hansen test of (Robust, but overid restrictions: chi2(187) = 197.37 but not weakened by many instruments.) overid restrictions: chi2(187) = 12.88 weakened by many instruments.) TIEU LUAN MOI download : skknchat@gmail.com ( ) Dynamic panel-data estimation, one-step system GMM Group variable: id Time variable : year Number of instruments = 138 Wald chi2(6) = 148.57 Prob > chi2 = 0.000 dolldep Coef ldolldep pubdeb lpubdeb rullaw lrullaw size _cons 2300003 -.0148904 0393938 -.1039987 -.1263411 -.0268393 6311035 Number of obs Number of groups Obs per group: avg max Std Err .073103 024701 0209946 0663847 0699592 0039439 0905688 z 3.15 -0.60 1.88 -1.57 -1.81 -6.81 6.97 P>|z| = = = = = 513 27 19 19.00 19 [95% Conf Interval] 0.002 0.547 0.061 0.117 0.071 0.000 0.000 086721 -.0633035 -.0017549 -.2341104 -.2634587 -.0345692 453592 3732796 0335227 0805425 026113 0107765 -.0191093 808615 Instruments for first differences equation Standard D.(lpubdeb size) GMM-type (missing=0, separate instruments for each period unless collapsed) L(1/4).(lpubdeb size) Instruments for levels equation Standard lpubdeb size _cons Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = -7.06 0.06 Pr > z = Pr > z = 0.000 0.949 Prob > chi2 = 0.131 Difference-in-Sargan tests of exogeneity of instrument subsets: iv(lpubdeb size) Sargan test excluding group: chi2(129) = 126.20 Prob > chi2 = Difference (null H = exogenous): chi2(2) = 23.12 Prob > chi2 = 0.553 0.000 Sargan test of overid restrictions: chi2(131) = 149.32 (Not robust, but not weakened by many instruments.) ( ) Dynamic panel-data estimation, one-step system GMM Group variable: id Time variable : year Number of instruments = 69 Wald chi2(6) = 83.02 Prob > chi2 = 0.000 dolldep Coef ldolldep pubdeb lpubdeb rullaw lrullaw usint _cons 3975228 -.0113864 0571844 -.1766021 -.0219799 0055941 -.1335306 Number of obs Number of groups Obs per group: avg max Std Err .087675 0345326 0327927 0515915 046995 0017861 0712227 z 4.53 -0.33 1.74 -3.42 -0.47 3.13 -1.87 P>|z| 0.000 0.742 0.081 0.001 0.640 0.002 0.061 = = = = = 513 27 19 19.00 19 [95% Conf Interval] 225683 -.079069 -.007088 -.2777196 -.1140885 0020935 -.2731245 5693626 0562962 1214569 -.0754845 0701286 0090947 0060632 Instruments for first differences equation Standard D.(lpubdeb usint D.rullaw) GMM-type (missing=0, separate instruments for each period unless collapsed) L(3/5).(pubdeb usint) Instruments for levels equation Standard lpubdeb usint D.rullaw _cons Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = -7.05 0.67 Pr > z = Pr > z = 0.000 0.502 Prob > chi2 = 0.079 Difference-in-Sargan tests of exogeneity of instrument subsets: iv(lpubdeb usint D.rullaw) Sargan test excluding group: chi2(59) = 68.69 Prob > chi2 = Difference (null H = exogenous): chi2(3) = 9.58 Prob > chi2 = 0.182 0.022 Sargan test of overid restrictions: chi2(62) = 78.28 (Not robust, but not weakened by many instruments.) TIEU LUAN MOI download : skknchat@gmail.com ( ) Dynamic panel-data estimation, one-step system GMM Group variable: id Time variable : year Number of instruments = 69 Wald chi2(6) = 83.49 Prob > chi2 = 0.000 dolldep Coef ldolldep pubdeb lpubdeb concorr lconcorr usint _cons 3911077 -.0265324 0636923 -.1141682 -.1101463 0060764 -.1157554 Number of obs Number of groups Obs per group: avg max Std Err .0899534 0356064 0335943 0426977 0405236 0018133 0622079 z 4.35 -0.75 1.90 -2.67 -2.72 3.35 -1.86 P>|z| 0.000 0.456 0.058 0.007 0.007 0.001 0.063 = = = = = 513 27 19 19.00 19 [95% Conf Interval] 2148023 -.0963196 -.0021514 -.1978541 -.1895712 0025225 -.2376806 5674131 0432548 129536 -.0304823 -.0307214 0096304 0061698 Instruments for first differences equation Standard D.(lpubdeb usint D.concorr) GMM-type (missing=0, separate instruments for each period unless collapsed) L(3/5).(pubdeb usint) Instruments for levels equation Standard lpubdeb usint D.concorr _cons Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = -6.78 0.72 Pr > z = Pr > z = 0.000 0.470 Prob > chi2 = 0.223 Difference-in-Sargan tests of exogeneity of instrument subsets: iv(lpubdeb usint D.concorr) Sargan test excluding group: chi2(59) = 65.75 Prob > chi2 = Difference (null H = exogenous): chi2(3) = 4.41 Prob > chi2 = 0.255 0.220 Sargan test of overid restrictions: chi2(62) = 70.16 (Not robust, but not weakened by many instruments.) ( ) Dynamic panel-data estimation, one-step system GMM Group variable: id Time variable : year Number of instruments = 49 Wald chi2(6) = 102.46 Prob > chi2 = 0.000 dolldep Coef ldolldep pubdeb lpubdeb regqua lregqua usint _cons 2697228 0346116 015491 -.3303948 0022739 009174 -.1098802 Number of obs Number of groups Obs per group: avg max Std Err .1207099 0203935 0174977 0981239 0870561 0020587 0652911 z 2.23 1.70 0.89 -3.37 0.03 4.46 -1.68 P>|z| 0.025 0.090 0.376 0.001 0.979 0.000 0.092 = = = = = 513 27 19 19.00 19 [95% Conf Interval] 0331358 -.0053589 -.018804 -.5227142 -.1683529 0051391 -.2378483 5063099 0745822 0497859 -.1380754 1729006 0132089 0180879 Instruments for first differences equation Standard D.(lpubdeb usint D.pubdeb) GMM-type (missing=0, separate instruments for each period unless collapsed) L(3/5).lpubdeb Instruments for levels equation Standard lpubdeb usint D.pubdeb _cons Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Pr > z = Pr > z = 0.000 0.899 Prob > chi2 = 0.157 Difference-in-Sargan tests of exogeneity of instrument subsets: iv(lpubdeb usint D.pubdeb) Sargan test excluding group: chi2(39) = 31.03 Prob > chi2 = Difference (null H = exogenous): chi2(3) = 20.13 Prob > chi2 = 0.815 0.000 Sargan test of overid restrictions: chi2(42) = 51.16 (Not robust, but not weakened by many instruments.) -4.43 0.13 TIEU LUAN MOI download : skknchat@gmail.com ( ) Dynamic panel-data estimation, one-step system GMM Group variable: id Time variable : year Number of instruments = 49 Wald chi2(6) = 107.13 Prob > chi2 = 0.000 dolldep Coef ldolldep pubdeb lpubdeb goveff lgoveff usint _cons 245019 0552673 008362 -.1623112 -.1920881 0041365 -.1619201 Number of obs Number of groups Obs per group: avg max Std Err .1156193 0217943 0171793 088111 0884197 0017564 0633516 z 2.12 2.54 0.49 -1.84 -2.17 2.36 -2.56 P>|z| = = = = = 513 27 19 19.00 19 [95% Conf Interval] 0.034 0.011 0.626 0.065 0.030 0.019 0.011 0184094 0125512 -.0253088 -.3350055 -.3653875 000694 -.2860871 4716287 0979834 0420329 0103831 -.0187887 007579 -.0377532 Instruments for first differences equation Standard D.(lpubdeb usint D.pubdeb) GMM-type (missing=0, separate instruments for each period unless collapsed) L(3/5).lpubdeb Instruments for levels equation Standard lpubdeb usint D.pubdeb _cons Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = -4.04 0.12 Pr > z = Pr > z = 0.000 0.908 Prob > chi2 = 0.205 Difference-in-Sargan tests of exogeneity of instrument subsets: iv(lpubdeb usint D.pubdeb) Sargan test excluding group: chi2(39) = 33.77 Prob > chi2 = Difference (null H = exogenous): chi2(3) = 15.49 Prob > chi2 = 0.707 0.001 Sargan test of overid restrictions: chi2(42) = 49.26 (Not robust, but not weakened by many instruments.) ( ) Dynamic panel-data estimation, one-step system GMM Group variable: id Time variable : year Number of instruments = 66 Wald chi2(6) = 71.38 Prob > chi2 = 0.000 dolldep Coef ldolldep pubdeb lpubdeb polsta lpolsta usint _cons 5135445 -.0147336 0200994 -.0415123 -.0014469 0055781 0424515 Number of obs Number of groups Obs per group: avg max Std Err .0966381 038535 0332958 0239672 0245822 0019052 0479064 z 5.31 -0.38 0.60 -1.73 -0.06 2.93 0.89 P>|z| 0.000 0.702 0.546 0.083 0.953 0.003 0.376 = = = = = 513 27 19 19.00 19 [95% Conf Interval] 3241373 -.0902607 -.0451591 -.0884871 -.0496272 001844 -.0514433 7029517 0607935 0853579 0054625 0467334 0093121 1363463 Instruments for first differences equation Standard D.(lpubdeb D.polsta usint) GMM-type (missing=0, separate instruments for each period unless collapsed) L(3/5).(lpubdeb usint) Instruments for levels equation Standard lpubdeb D.polsta usint _cons Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Pr > z = Pr > z = 0.000 0.480 Prob > chi2 = 0.445 Difference-in-Sargan tests of exogeneity of instrument subsets: iv(lpubdeb D.polsta usint) Sargan test excluding group: chi2(56) = 39.69 Prob > chi2 = Difference (null H = exogenous): chi2(3) = 20.14 Prob > chi2 = 0.951 0.000 Sargan test of overid restrictions: chi2(59) = 59.83 (Not robust, but not weakened by many instruments.) -6.94 0.71 TIEU LUAN MOI download : skknchat@gmail.com ( ) Dynamic panel-data estimation, one-step system GMM Group variable: id Time variable : year Number of instruments = 138 Wald chi2(6) = 162.38 Prob > chi2 = 0.000 dolldep Coef ldolldep pubdeb lpubdeb voiacc lvoiacc size _cons 1755354 -.0239085 0629356 -.1389524 -.112024 -.0283998 6322019 Number of obs Number of groups Obs per group: avg max Std Err .0740188 0246008 0217488 0547891 0591612 003749 0857893 z 2.37 -0.97 2.89 -2.54 -1.89 -7.58 7.37 P>|z| 0.018 0.331 0.004 0.011 0.058 0.000 0.000 = = = = = 513 27 19 19.00 19 [95% Conf Interval] 0304612 -.0721252 0203087 -.246337 -.2279778 -.0357477 464058 3206097 0243081 1055624 -.0315677 0039297 -.021052 8003458 Instruments for first differences equation Standard D.(lpubdeb size) GMM-type (missing=0, separate instruments for each period unless collapsed) L(1/4).(lpubdeb size) Instruments for levels equation Standard lpubdeb size _cons Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = -6.11 0.32 Pr > z = Pr > z = 0.000 0.747 Prob > chi2 = 0.325 Difference-in-Sargan tests of exogeneity of instrument subsets: iv(lpubdeb size) Sargan test excluding group: chi2(129) = 123.59 Prob > chi2 = Difference (null H = exogenous): chi2(2) = 14.21 Prob > chi2 = 0.618 0.001 Sargan test of overid restrictions: chi2(131) = 137.80 (Not robust, but not weakened by many instruments.) TIEU LUAN MOI download : skknchat@gmail.com ... Arrellano-Bond (1991) ầ e “F e z ( :N w ” ) e ( ) ữ ( ) ầ ữ ầ ầ Dollarized deposits(t) = α0 + α1Dollarized deposits(t-1) + α2Inflation(t) + α3Inflation(t-1) + α4Inflation volatility(t) + α5Inflation... Financial dollarization in Latin Robert Rennhack America Masahiro Nozaki ầ ầ - 2003 Financial dollarization Alain Ize Eduardo Levy Yeyati 2005 e - - tin c y c Dollarization of bank deposits:... 2005 Financial De-Dollarization: Is it Alain Ize for Real Eduardo Levy Yeyati - ữ Comment on Financial DeDollarization: Is it for Real 2006 (Alain Ize and Eduardo Levy Roberto Chang Yeyati)