MONEY AND INFLATION IN CHINA TABLE 2 Multivariate Cointegration Regression Rest Coefficient on lag of P M Constant 0433(0.611) 0.363(7.53) 0.043(0.159) 0.345°(-3.84 0011(0.0752) 0.997 -4.91 ADF(I) 5.51 ADF(2) Notes. Figures in the parentheses undemeath the coefficients are the i-ratios, Dw and Se are the Durbin-Watson statistic and the standard error of the regression, respectively. The regressions als include a time trend and an intercept dummy for 1979. Significant at the 1% level b Significant at the 5% level Results of Johansens maximum eigenvalue test indicate that there exist at least one cointegrating relationship in the six-variate VAR system, since r=0 clearly rejected in favor of r= I by the 95% critical value. The trace test, on the other hand, suggests that there are two cointegrating vectors in the model since r s I is clearly rejected in favor of r=2; but r s 2 cannot be rejected by the 95% critical values. Since there is growing evidence in favor of the robustness of the trace statistic compared to the maximal eigenvalue statistic Cheung and Lai, 1993; Kasa, 1992, Luintel and Paudyal, 1998), we accept the race test results that tend to suggest there are at least two stationary relationships between price, money stock, wage, output gap, agricultural and industrial pro- ductivity variables. Given that there are (n-r) common trends within the system, we can conclude that there exist at most four common trends within the vector such that current price is moving into alignment with the trend values of explanatory variables in Eq (4) The finding of cointegration among these macroeconomic variables eral implications. First, consistent with economic theory, it indicates that money, wages, and prices have a long-run equilibrium relationship that may be exploited by the monetary authorities in the formulation of monetary policy. Second, theResults of Johansen’s maximum eigenvalue test indicate that there exist at least one cointegrating relationship in the six-variate VAR system, since r 5 0 is clearly rejected in favor of r 5 1 by the 95% critical value. The trace test, on the other hand, suggests that there are two cointegrating vectors in the model since r # 1 is clearly rejected in favor of r 5 2; but r # 2 cannot be rejected by the 95% critical values. Since there is growing evidence in favor of the robustness of the trace statistic compared to the maximal eigenvalue statistic (Cheung and Lai, 1993; Kasa, 1992; Luintel and Paudyal, 1998), we accept the trace test results that tend to suggest there are at least two stationary relationships between price, money stock, wage, output gap, agricultural and industrial pro￾ductivity variables. Given that there are (n 2 r) common trends within the system, we can conclude that there exist at most four common trends within the vector such that current price is moving into alignment with the trend values of explanatory variables in Eq. (4). The finding of cointegration among these macroeconomic variables has sev￾eral implications. First, consistent with economic theory, it indicates that money, wages, and prices have a long-run equilibrium relationship that may be exploited by the monetary authorities in the formulation of monetary policy. Second, the TABLE 2 Multivariate Cointegration Regression Results Coefficient on lag of Dependent variable P M Constant 0.433 (0.611) 3.78b (2.38) P 1.38a (6.43) M 0.363a (7.53) W 0.527a (5.85) 0.043 (0.159) g 20.345a (23.84) 1.23a (6.63) AP 0.011 (0.0752) 20.653b (22.16) IP 20.133b (22.00) 20.254 (21.61) R2 0.995 0.997 DW 1.59 1.76 SE 0.038 0.076 Cointegration test DF 24.91b 26.20a ADF(1) 25.51a 25.06b ADF(2) 25.28b 23.96 Notes. Figures in the parentheses underneath the coefficients are the t-ratios; DW and SE are the Durbin–Watson statistic and the standard error of the regression, respectively. The regressions also include a time trend and an intercept dummy for 1979. a Significant at the 1% level. b Significant at the 5% level. MONEY AND INFLATION IN CHINA 677