A Berkaert et al Financial Contagion Forbes A A A 2008 A 2008 A 2008 A VAR GARCH ECM Granger Gra

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1 A * Hong A 1 A 2A A 3A Granger Eun & Shim 1989Hamao et al. 1990Koutmos & Booth1995Ng 2000Fratzscher2002Bae et al. 2003Barberis et al. 2005Bodart et al Hong 2001Skintzi & Refenes2006Inagaki2007 * com B YJC Advanced Econometrics Seminar 2010 CES

2 A Berkaert et al Financial Contagion Forbes A A A 2008 A 2008 A 2008 A VAR GARCH ECM Granger Granger Hong et al Hong et al Cross Correlation Function CCF Haugh1976 Koch & Yang1986 Cheung & Ng 1996 Hong Hong et al VaR Hong Hong et al Hong A A A A Granger 1. Granger Granger

3 X Y X X Y X Y Granger Granger Information Spillover Granger Granger Granger PrY t PrY t - I x t - 1 x R k X Y Granger X Y R k k k X I t - 1 t - 1 I x t - 1 t - 1 X I t I x t - 1 t - 1 X Granger X Y Granger Granger 1969 Granger 1986Cheung & Ng 1996Hong 2001 Hong et al I t - 1 = I 1t - 1 I 2t - 1 t - 1 I 1t - 1 = Y 1t - 1 Y 11 I 2t - 1 = Y 2t - 1 Y 21 t EY 1t I 1t - 1 E Y 1t 2 1 Y 2t Y 1t Granger E 3 E Y 1t - μ 0 1t 2 I 1t - 1 VarY 1t E Y 1t - μ 0 1t Y 2t Y 1t Granger Var μ 0 1t Y I t - 1 μ 0 1t = EY 1t H 0 EVarY 1t I 1t - 1 = VarY 1t H 1 EVarY 1t I 1t - 1 VarY 1t H Y 2t Y 1t Granger Y 1t Y 2t Granger 1 2 Y 2 Y 2t Y 1 t E Y 1t - μ 0 1t 2 I t -1 E Y 1t - μ 0 1t 2 I t -1 Y 2t VaR Jorion2000 Hong et al VaR Extreme risk spillover

4 A 4 PY 1t < - V 1t I 1t - 1 PY 1t < - V 1t Granger V t VaR 1 - α 5 PY 1t > V 1t I 1t - 1 PY 1t > V 1t Granger PY t > V t = α V α- 2. CCF Hong2001 Hong et al Hong Hong Hong Hong MontaCarlo Hong Cheung & Ng 1996 Granger1986 Hong CCF Hong ARMA-GARCH u it v it VaR Z it Hong et al u it v it Z it Y it = μ 0 it + ε it i = 1 2 h 0 it = ω 0 i + q ε it = u it h 0 it 1 /2 4 α 0 ijε 2 it - j j = 1 + p β 0 ijh 0 it - j j = 1 u it ~ i. i. d. N0 1 μ 0 it GARCH QMLE ^ε it ^h it ^u it = ^ε1t / ^h it 1 /2 i = ^v it = ^u 2 it - 1 i = v it u it 6 ^v 1t ^v 2t ^ρj = ^Cj/ ^S 1 ^S 2 j = 0± 1 ± T ^S 1 ^S 2 ^v 1 ^v 2 ^Cj 18

5 T -1 T { ^v 1t - α 1 ^v 2t - j - α 2 j 0 t = j +1 ^Cj = T -1 T ^v 1t + j - α 1 ^v 2t - α 2 j < 0 t = - j +1 α 1 α 2 珋 v 1 珋 v 2 H 0 槡 T^ρj ~ N0 1 9 Haugh1976Cheung & Ng 1996 M Hong1996 Hong CCF Hong2001 Hong et al Q 1 Q 1 = { T T -1 k 2 j / M^ρ2 j- C 1T k } Q 2 j = 1 Q 2 = { T T -1 k 2 j / M^ρ2 j- C 2T k } j = 1 - T / { 2D 1T k } 1 /2 / { 2D 2T k } 1 / k Hong Daniel kx= sinπx/ πx M C D C 1T k = T -1 j = j / Tk 2 j / M D 1T k = T -1 j = j / T{ 1 - j + 1/ T} k 4 j / M C 2T k = T j / Tk 2 j / M D 2T k = T j / T{ 1 - j + 1/ T} k 4 j / M j = 1 - T j = 1 - T 12 H 0 Granger A300 HSIS & P500 SPX A A I 396 II 531 A 2 19

6 A A 1 A S & P /07 / /07 / JB 2007 Panel A I 2005 /07 / /04 /04 10 A Panel B II 2007 /04 / /07 /07 1 A % * 100 2% % A 68% A A A 2 GARCH A 0 3 J-B BP BP BP BP BP BP AR- BPmBP 2 m GARCH 2 Box-Pierce p 20

7 3 I A M = 5 M = 10 M = 20 M = 30 AR- GARCH Q * Q Q * * * Q * * * * CCF Hong 2001 Q Hong et al. Q * * * * 5% A Q Q Q % Q Q Q - 1 Q * * * A Q 2 Q 1 A Q - 1 Q - 1 A p * 5% M M 5% VaR α M Q 4 II A A M = 5 M = 10 M = 20 M = 30 Q * * * * ρ- Q * * 1= Q Q * * * A Q Q A 5% Q * * Q Q A 5% Q Q ρ - 1 = Q * * A 3 21

8 A 5% VaR ρ- 4= Q - 1 Q 1 A A Q - 1 M Q 2 Q - 1 Q 2 ρ % Q - 1 A A Q 1 A Q 2 A ρ A 5% Q 1 Q 2 Q - 1 A A Q - 1 A A A A Q Q - 1 M 10 M A 5% Q 1 Q - 1 Q 2 Q 2 A A A + H 50% 2007 A + A - - A A A - A

9 5 I A Q 2 M = 5 M = 10 M = 20 M = 30 Q * * * * Q Q * * % Q * * * * Q Q * * * 5% Q * * * * Q Q % 5% Q Q % Q Q 2 Q 1 A Q - 1 A p * M 5% VaR α 6 II A A M = 5 M = 10 M = 20 M = 30 1 Q * * * * A Q * * * Q * A Q * * * * Q % Q * % A Q * Q Q A 5% Q Q Q Forbes

10 A A A A I II A A A 2005 A A A A A A - A - A Hong 2001 Hong et al Hong A A A A A A A A 24

11 CCF ECM Granger 5 BaeK-H. KarolyiG. A. and StulzR. M A New Approach to Measuring Financial Contagion Review of Financial StudyVol. 16pp BekaertG. HarveyC. R. and NgA Market Integration and Contagion Journal of BusinessVol. 78No. 1pp BodartV. and CandelonB Evidence of Interdependence and Contagion Using a Frequency Domain Framework Emerging Markets ReviewVol. 10pp CheungY. W. and NgL. K A Causality-in-variance Test and Its Application to Financial Market Prices Journal of EconometricsVol. 72pp EunC. S. and ShimS International Transmission of Stock Market Movements Journal of Financial and Quantitative AnalysisVol. 24pp ForbesKristin J. and Rigobon Roberto2001 Measuring ContagionConceptual and Empirical Issues in ClaessensStijnand ForbesKristin J. eds. International Financial Contagion. Kluwer Academic PublishersNorwellMApp ForbesKristen J. and Rigobon Roberto2002 No ContagionOnly InterdependenceMeasuring Stock Market Comovements Journal of FinanceVol. 57pp FratzscherM Financial Market Integration in EuropeOn the Effects of EMU on Stock Markets International Journal of Finance and EconomicsVol. 7pp GrangerC. W. J Investigating Causal Relations by Econometric Models and Cross-spectral Methods EconometricaVol. 37pp GrangerC. W. J Testing for CausalityA Personal View Journal of Economic Dynamics and ControlVol. 2pp GrangerC. RobinsP. P. and EngleR. F Wholesale and Retail Prices Bivariate Time-series Modeling with Forecastable Error Variances InBelsleyD. A. and KuhE. Eds. Model ReliabilityMIT PressCambridgepp HamaoY. MasulisR. W. and NgV. K Correlations in Price Changes and Volatility Across International Stock Markets Review of Financial StudiesVol. 3pp HaughL. D Checking the Independence of Two Covariance-stationary Time SeriesA Univariate Residual Cross-correlation Approach JASAVol. 71pp HongY Testing for Independence Between Two Covariance Stationary Time Series BiometrikaVol. 83pp HongY A Test for Volatility Spillover with Applications to Exchange Rates Journal of EconometricsVol. 103pp HongY. LiuY. and WangS Granger Causality in Risk and Detection of Extreme Risk Spillover Between Financial Markets Journal of EconometricsVol. 150pp InagakiK Testing for Volatility Spillover Between the British Pound and the Euro Research in International Business and FinanceVol. 21pp KochP. D. and YangS. S A Method for Testing the Independence of Two Time Series that Accounts for a Potential Pattern in the Cross-correlation Function JASAVol. 81pp KoutmosG. and BoothG. G Asymmetric Volatility Transmission in International Stock Markets Journal of International Money and FinanceVol. 14pp NgA Volatility Spillover Effects from Japan and the US to the Pacific Basin Journal of International Money and Finance Vol. 19pp SkintziV. D. and RefenesA. N Volatility Spillovers and Dynamic Correlation in the European Bond Markets Journal of International Financial marketsinstitutions and MoneyVol. 16pp

12 Local Government InvestmentAdministrative Monopoly and Economic Growth Evidence from Chinese Provincial Panel Data Zhang Weiguo a Ren Yanyan b and Hua Xiaoan c ashandong Academy of Social SciencesbShandong UniversitycChina Guangfa Bank AbstractThis paper investigates the relationship between local government investmentadministrative monopoly and economic growth based on Chinese provincial panel data from 1994 to The results show that the administrative monopoly has inverse U-shaped effect on local economic growth and current administrative monopoly level promotes local economic growth significantly for most provinces in additionadministrative monopoly has U-shaped effect on local government investment and the relationship between them is still among the descending side. Currentlyboth administrative monopoly and local government investment boost the local economic growth and they have the substitution effect of each other. In the long termhoweveradministrative monopoly is harmful for the countrywide marketed scale effect as a whole. Political rents are in cost of economic efficiency. Key WordsLocal Government InvestmentAdministrative MonopolyEconomic Growth JEL ClassificationE10E22H11 檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵 25 Information Spillover among China s A-shares Market US Stock Market and HK Stock Market Li Hongquan a b Hong Yongmiao b c and Wang Shouyang d aschool of BusinessHunan Normal UniversitybDepartment of EconomicsCornell University cwang Yanan Institute for Studies in Economics WISE Xiamen University dacademy of Mathematics and Systems ScienceChinese Academy of Sciences AbstractThe study of interplay and correlation among stock markets is very valuable to enrich market supervisors knowledge about the cross-country transmission mechanism of information and financial riskmoreoverit also helps gain deep insight into market microstructure as well as informational efficiency in equity markets. Using the unified information spillover testing procedures proposed by Hong we investigate the dynamic linkages among China s A-shares marketthe US stock market and the HK market to obtain the comprehensive picture of the relationships among these three markets. Report shows that 1 The US stock market plays a leading role among those three marketswith significant contagion spread from the US market into the HK market and to China A-shares market. 2A-shares market was not independent of other markets. The shocks from other stock markets will make A-shares market fluctuateand on the other handa-shares market also gains the power to shape other markets behavior. 3 The interplay among those three markets includes mean spillovervolatility spillover and extreme risk spilloverand the relationship can be nonlinear as well as linear. Key WordsFinancial ContagionInformation SpilloverInformational EfficiencySubprime CrisisGranger Casualty in Risk JEL ClassificationG14 G32 C32 37

Alexander & Wyeth Dercon 1995 ECM - Johansen Goodwin 1992 VEC Asche 1999 Gonzalez 2001 ECM Goodwin

Alexander & Wyeth Dercon 1995 ECM - Johansen Goodwin 1992 VEC Asche 1999 Gonzalez 2001 ECM Goodwin 2012 3 * 0. 20 0. 36 0. 05 2006 2010 1. 46 / 2. 14 / 2. 93 / 4. 41 / 1. 27 / 2. 12 / 47% 50% 67% 2006 1 3. 48 / 2010 11 5. 84 / 68% 1 2010 CPI 70% 2006 2006 1 106. 06 2008 6 188. 02 77. 3% 2010 11 173.