gretl version 1.9.1 Current session: 2010-08-22 17:40 # GRETL SCRIPT FOR STATISTICAL COMPUTING ANALYSIS # ? open E:\DSLMHTML\STATCOMP\statcomp.gdt Read datafile E:\DSLMHTML\STATCOMP\statcomp.gdt periodicity: 4, maxobs: 205 observations range: 1959:1-2010:1 Listing 7 variables: 0) const 1) USGDP 2) US3MTBR 3) USIPD 4) USCPI 5) USM1 6) USM2 # ? genr USRM2 = 100*(USM2/USIPD) # Calculate real values by deflating Generated series USRM2 (ID 7) ? genr USRGDP = 100*(USGDP/USIPD) # the series by the GDP deflator. Generated series USRGDP (ID 8) ? genr LUSRM2 = log(USRM2) # Generate logarithms of the Generated series LUSRM2 (ID 9) ? genr LUSRGDP = log(USRGDP) # two series. Generated series LUSRGDP (ID 10) # ? ols LUSRM2 const US3MTBR LUSRGDP # Run the regression Model 1: OLS, using observations 1959:1-2010:1 (T = 205) Dependent variable: LUSRM2 coefficient std. error t-ratio p-value --------------------------------------------------------- const 0.538349 0.0729824 7.376 4.13e-012 *** US3MTBR -0.00252647 0.00135003 -1.871 0.0627 * LUSRGDP 0.873614 0.00812851 107.5 3.22e-180 *** Mean dependent var 8.202252 S.D. dependent var 0.413949 Sum squared resid 0.582969 S.E. of regression 0.053721 R-squared 0.983323 Adjusted R-squared 0.983158 F(2, 202) 5955.177 P-value(F) 2.7e-180 Log-likelihood 310.0372 Akaike criterion -614.0745 Schwarz criterion -604.1054 Hannan-Quinn -610.0422 rho 0.989881 Durbin-Watson 0.036122 Log-likelihood for USRM2 = -1371.42 ? RESIDS = $uhat Generated series RESIDS (ID 11) ? FITTED = $yhat Generated series FITTED (ID 12) # ? modtest --breusch-pagan # test for heteroskedaticity Breusch-Pagan test for heteroskedasticity OLS, using observations 1959:1-2010:1 (T = 205) Dependent variable: scaled uhat^2 coefficient std. error t-ratio p-value -------------------------------------------------------- const -6.45996 1.83383 -3.523 0.0005 *** US3MTBR -0.105153 0.0339221 -3.100 0.0022 *** LUSRGDP 0.911898 0.204245 4.465 1.33e-05 *** Explained sum of squares = 63.2952 Test statistic: LM = 31.647592, with p-value = P(Chi-square(2) > 31.647592) = 0.000000 ? modtest 4 --autocorr # tests for autocorrelation in residuals Breusch-Godfrey test for autocorrelation up to order 4 OLS, using observations 1959:1-2010:1 (T = 205) Dependent variable: uhat coefficient std. error t-ratio p-value ----------------------------------------------------------- const -0.00568243 0.0147688 -0.3848 0.7008 US3MTBR -0.000243492 0.000284676 -0.8553 0.3934 LUSRGDP 0.000831165 0.00165003 0.5037 0.6150 uhat_1 1.30973 0.0709271 18.47 6.23e-045 *** uhat_2 -0.373607 0.116695 -3.202 0.0016 *** uhat_3 0.122629 0.116878 1.049 0.2954 uhat_4 -0.0842327 0.0733981 -1.148 0.2525 Unadjusted R-squared = 0.960049 Test statistic: LMF = 1189.509590, with p-value = P(F(4,198) > 1189.51) = 3.42e-137 Alternative statistic: TR^2 = 196.809991, with p-value = P(Chi-square(4) > 196.81) = 1.82e-041 Ljung-Box Q' = 652.643, with p-value = P(Chi-square(4) > 652.643) = 6.24e-140 # ? matrix Xmat = { const, US3MTBR, LUSRGDP } Generated matrix Xmat ? matrix Yvec = { LUSRM2 } Generated matrix Yvec ? matrix XTXI = inv(Xmat'Xmat) Generated matrix XTXI ? matrix XTY = Xmat'Yvec Generated matrix XTY ? matrix bvec = XTXI*XTY Generated matrix bvec ? bvec bvec (3 x 1) 0.53835 -0.0025265 0.87361 ? matrix fitvec = Xmat*bvec Generated matrix fitvec ? matrix residvec = Yvec-fitvec Generated matrix residvec ? matrix SSE = residvec'residvec Generated matrix SSE ? SSE SSE (1 x 1) 0.58297 ? matrix devyvec = Yvec - mean(Yvec) Generated matrix devyvec ? matrix SST = devyvec'devyvec Generated matrix SST ? SST SST (1 x 1) 34.956 ? matrix SSR = SST - SSE Generated matrix SSR ? SSR SSR (1 x 1) 34.373 ? matrix Rsq = SSR/SST Generated matrix Rsq ? Rsq Rsq (1 x 1) 0.98332 ? matrix df = rows(Xmat)-cols(Xmat) Generated matrix df ? df df (1 x 1) 202 ? matrix sigsq = SSE/df Generated matrix sigsq ? sigsq sigsq (1 x 1) 0.0028860 ? matrix stereg = sqrt(sigsq) Generated matrix stereg ? stereg stereg (1 x 1) 0.053721 ? matrix vcvcoefs = sigsq*XTXI Generated matrix vcvcoefs ? vcvcoefs vcvcoefs (3 x 3) 0.0053264 -2.4718e-005 -0.00058970 -2.4718e-005 1.8226e-006 1.7207e-006 -0.00058970 1.7207e-006 6.6073e-005 ? matrix stdcoefs = sqrt(diag(vcvcoefs)) Generated matrix stdcoefs ? stdcoefs stdcoefs (3 x 1) 0.072982 0.0013500 0.0081285 ? matrix trats = bvec./stdcoefs Generated matrix trats ? trats trats (3 x 1) 7.3764 -1.8714 107.48