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Unformatted text preview: 1. US-GDP The US-GDP data has been downloaded with GDP, M1,M2 and t-bill and these had been declared as time series. The natural logs for all variables except t-bill has been taken, After that the lag values has been calculated. THe data has been detrended for GDP, M1 and T- bill. Aftewr that the line plot of Detrended log values of GDP, M1 and IPI had been created in a single window as shown below. 60 120 180 240 300 360 420 480 Month 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 F G H Y Figure: 1.c Detrended Log(IPI) has been regressed on the Tbill rate. The results are as shown below in the table: TABLE 1.d : OLS Results for Regression Model 1 (standard error) t p-value IPI growth 0.368 (0.034) 15.78 0.00013 Tbill rate 0.0706 (0.076) -2.86 0.0003 R2 = .28 F-stat. p-value = .0003 AIC = 3.223 SIC = .037543 Durbin-Watson d-statistic( 5, 528) = .2127027 (the 5% critical range is 1.44…1.68) Since DW < 1.44, we strongly reject the no serial correlation null hypothesis at the 5% level The residules has been calculated and regressed on the lagged Tbill value: Table 1.e Source SS df MS Model 1373.632 5.332 1536.44269 Residual 4345.40457 99 71.16911937 Number of obs = 527 F( 2, 525) = 3452.54 Prob > F = 4.0000 Adj R-squared = 0.9625 R-squared = 0.9633 The results of the LM statistics are as follows: (Table 1.e) The formula for the LM statistics for tye residuals u at 1 to 6 is as follow: Random Effects Model: v(i,t) = e(i,t) + u(i) Estimates: Var[e] = .361260D-02 Var[u] = .119159D-01 Corr[v(i,t),v(i,s)] = .767356 Lagrange Multiplier Test vs. Model (3) = Lagrange Multiplier Test vs....
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- Fall '08
- Econometrics, Null hypothesis, Statistical hypothesis testing, log likelihood