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From | Nick Cox <n.j.cox@durham.ac.uk> |
To | "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu> |
Subject | st: RE: dfuller: why do I get different results? |
Date | Fri, 18 Nov 2011 11:37:24 +0000 |
bysort appt: gen reduct1=reduct_per[_n-1] and gen reduct1 = L1.reduct give identical results only under certain conditions. One is that sorting by -appt- does _not_ itself guarantee that values for each -appt- are sorted in time order. There can be other problems with omitted observations, etc. Use time-series operators after -tsset- to generate lagged variables. Nick n.j.cox@durham.ac.uk -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Yuval Arbel Sent: 18 November 2011 11:30 To: statalist Subject: st: dfuller: why do I get different results? Dear Statalist Participants, when I run: . dfuller reduct_per if appt==2862,noconstant regress I get the following outcome: Dickey-Fuller test for unit root Number of obs = 37 ---------- Interpolated Dickey-Fuller --------- Test 1% Critical 5% Critical 10% Critical Statistic Value Value Value ------------------------------------------------------------------------------ Z(t) -6.026 -2.641 -1.950 -1.605 ------------------------------------------------------------------------------ D.reduct_per | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- reduct_per | L1. | -.5409015 .0897625 -6.03 0.000 -.7229484 -.3588546 ------------------------------------------------------------------------------ Those outcomes imply that the calculated statistic for the unit-root test is -6.03 But when I define: bysort appt: gen reduct1=reduct_per[_n-1] bysort appt: gen dreduct1=reduct_per-reduct_per[_n-1] and I run: regress dreduct1 reduct1 if appt==2862,noconst I get: . regress dreduct1 reduct1 if appt==2862,noconst Source | SS df MS Number of obs = 36 -------------+------------------------------ F( 1, 35) = 0.00 Model | 0 1 0 Prob > F = 1.0000 Residual | 625 35 17.8571429 R-squared = 0.0000 -------------+------------------------------ Adj R-squared = -0.0286 Total | 625 36 17.3611111 Root MSE = 4.2258 ------------------------------------------------------------------------------ dreduct1 | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- reduct1 | 0 .0509647 0.00 1.000 -.1034639 .1034639 ------------------------------------------------------------------------------ . Shouldn't I get exactly the same outcomes in both regressions? * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/