to be or not to be is QM解答.docx

1.1 (1)Genr-rm1=(m1/cpi)*100Describe: open all as group—stats table/common sample(2)estimation: genr lnrm1=log(rm1)Lnrgdp=log(rgdp) Quick: lnrm1 c lnrgdptbrcpigive an explanation: the sample size is 53 for each series, the mean for cpi is xxxx1.1(b)Dependent Variable: LNRM1Method: Least SquaresDate: 10/27/14 Time: 15:37Sample: 1960 2012Included observations: 53VariableCoefficientStd. Errort-StatisticProb.??C4.3577771.0238494.2562700.0001LNRGDP0.3329430.1292412.5761310.0131TBR-0.0241470.004683-5.1567200.0000CPI-0.0010030.001890-0.5303360.5983R-squared0.809665????Mean dependent var7.120826Adjusted R-squared0.798012????S.D. dependent var0.177041S.E. of regression0.079568????Akaike info criterion-2.151941Sum squared resid0.310221????Schwarz criterion-2.003240Log likelihood61.02643????Hannan-Quinn criter.-2.094757F-statistic69.48031????Durbin-Watson stat0.291136Prob(F-statistic)0.000000 Explanation: the coefficient cpi is insignificant. The cefficient of constant, lnrgdp and tbr is insignificant. Depending on the significant F Statistics, there should exisit the multi-colinearity in cpi with other variable. 1.2the coefficient ocpi is insignificant. The cefficient of constant, lnrgdp and tbr is insignificant. If 1% lnrgdp increase,0.332943% of lnrm1 increase. . If 1 unit of tbr increase, lnrm1decrease by 0.024147%. If 1 unit of CPI increase, lnrm1decrease by 0.003%, but the coefficient is insignificant1.3Adjusted R-squared ==0.798012, it means that how the independent variables can explain the dependent variables. 0.798012 means that 79% of the dependent variables can be explained by the independent variables. Durbin-Watson stat= 0.29 less than the critical value(DL=1.28), so we reject null hypothesis which is non-autocorrelation. So there exist the first-order positive autocorrelation in our model.1.4Report and interpreter the following diagnostics (tests) of the above model:afourth order LM (Breusch-Godfrey) test of residual a