Time Series - Data and Statistical Services - Princeton University
Time Series - Data and Statistical Services - Princeton University
Time Series - Data and Statistical Services - Princeton University
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Run a Cochrane-Orcutt regression using the prais comm<strong>and</strong> (type help prais for more<br />
details)<br />
. prais unemp gdp, corc<br />
Iteration 0: rho = 0.0000<br />
Iteration 1: rho = 0.9556<br />
Iteration 2: rho = 0.9660<br />
Iteration 3: rho = 0.9661<br />
Iteration 4: rho = 0.9661<br />
<strong>Time</strong> <strong>Series</strong>: Correcting for serial correlation<br />
Cochrane-Orcutt AR(1) regression -- iterated estimates<br />
Source SS df MS Number of obs = 191<br />
F( 1, 189) = 2.48<br />
Model .308369041 1 .308369041 Prob > F = 0.1167<br />
Residual 23.4694088 189 .124176766 R-squared = 0.0130<br />
Adj R-squared = 0.0077<br />
Total 23.7777778 190 .125146199 Root MSE = .35239<br />
unemp Coef. Std. Err. t P>|t| [95% Conf. Interval]<br />
gdp -.020264 .0128591 -1.58 0.117 -.0456298 .0051018<br />
_cons 6.105931 .7526023 8.11 0.000 4.621351 7.590511<br />
rho .966115<br />
Durbin-Watson statistic (original) 0.087210<br />
Durbin-Watson statistic (transformed) 0.758116<br />
30<br />
PU/DSS/OTR
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