交作业计量经济学-第三次实验诗

2012 12二 Yt=1+2

+YtXtutDependentVariable:YMethod:LeastSquaresDate06/19/15Time14:21Sample:128Includedobservations:Std.t-CXMeandependentAdjustedR-S.D.dependentS.E.ofAkaikeinfoSumsquaredSchwarzLog-Hannan-QuinnF-图示法(回归方程中，Resids按钮） 0 0EE E(-DW检该回归方程R228、一个解释变量的模型、5%DW,dL=1.328,dU=1.476，DW<dL，显然当权重为X（-1）时，DependentVariable:YMethod:LeastSquaresDate:06/19/15Time:16:37Sample(adjusted):228Includedobservations:27afteradjustmentsWeightingseries:X(-1)WhiteHeteroskedasticity-ConsistentStandardErrors&Std.t-CXWeightedMeandependentAdjustedR-S.D.dependentS.E.ofAkaikeinfoSumsquaredSchwarzLog-Hannan-QuinnF-UnweightedMeandependentAdjustedR-S.D.dependentS.E.ofSumsquaredDurbin-Watson当权重为X（-1）2时：DependentVariable:YMethod:LeastSquaresDate:06/19/15Time:16:40Sample(adjusted):228Includedobservations:27afteradjustmentsWeightingseries:X(-1)*X(-1)WhiteHeteroskedasticity-ConsistentStandardErrors&Std.t-CXWeightedMeandependentAdjustedR-S.D.dependentS.E.ofAkaikeinfoSumsquaredSchwarzLog-Hannan-QuinnF-UnweightedMeandependentAdjustedR-S.D.dependentS.E.ofSumsquaredDurbin-Watson权重为X（-1）3DependentVariable:YMethod:LeastSquaresDate:06/19/15Time:16:41Sample(adjusted):228Includedobservations:27afteradjustmentsWeightingseries:X(-1)*X(-1)*X(-1)WhiteHeteroskedasticity-ConsistentStandardErrors&Std.t-CXWeightedMeandependentAdjustedR-S.D.dependentS.E.ofAkaikeinfoSumsquaredSchwarzLog-Hannan-QuinnF-UnweightedMeandependentAdjustedR-S.D.dependentS.E.ofSumsquaredDurbin-WatsonDW=1.702819，使用Cochrane-Orcutt的方法解决自相关问在主菜单选择Quick/GenerateSeries或点击工作文件窗口中的Procs/GenerateSeries，在弹出的框中输入e=resid，点击OK得到残差序列。使用et进行滞后一期的自回归，在EViews命今栏中输入ls DependentVariable:EMethod:LeastSquaresDate:06/19/15Time:14:40Sample(adjusted):228Includedobservations:27after Std. t- E(- MeandependentAdjustedR-S.D.dependentS.E.ofAkaikeinfoSumsquaredSchwarzLog-Hannan-QuinnDurbin-Watsonet=0.7294et-可知ρ=0.7294，DependentVariable:Y-0.7294*Y(-1)Method:LeastSquaresDate:06/19/15Time:14:48Sample(adjusted):228Includedobservations:27afterStd.t-CMeandependentAdjustedR-S.D.dependentS.E.ofAkaikeinfoSumsquaredSchwarz