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From |
"Clive Nicholas" <Clive.Nicholas@newcastle.ac.uk> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Simple Question about Fixed Effects |

Date |
Sun, 13 Mar 2005 22:39:09 -0000 (GMT) |

Bob Rijkers wrote: > I am using a fixed effects model to analyze the impact of training on > industrial productivity. When I include both training and a lagged value > of training, however, Stata refuses to execute fixed effects regression. > Why should this be the case? There are a number of ways in which one can run a fixed-effect regression in Stata. Unfortunately, you don't say which one. My preferred option is to use David Roodman's -newey2- routine, downloadable from SSC: this way, you can obtain OLS parameter estimates controlling for both autocorrelation and heteroscedasticity in the residuals. A dynamic panel model option is another of David's user-written routines: -xtabond2-, also available from SSC (however, suitable variables need to be found which can be 'instrumented' with the lagged variable). If the only problem is autocorrelation, use -prais, corc- (which does _not_ produce OLS estimators). > Clearly, including lags of explanatory variables induces autocorrelation > amonths the explanatory variables, but why is this problematic? An unpublished paper by Christopher Achen (2000) makes a number of points that amount to a very strong argument against using lagged dependent variables (LDVs) under _any_ circumstances: (1) including LDVs often bias the coefficients of other key predictor variables toward negligible values that they would not otherwise take were LDVs excluded; (2) because of (1), coefficient values of LDVs are often grossly inflated; (3) conditions (1) and (2) often happen when serial correlation is high and the exogenous variables are heavily trended, as is often the case in panel data; and (4) occasionally, other explanatory variables take on the wrong sign when LDVs are included. A .pdf file of the paper can be downloaded from the link at the bottom of this message. CLIVE NICHOLAS |t: 0(044)7903 397793 Politics |e: clive.nicholas@ncl.ac.uk Newcastle University |http://www.ncl.ac.uk/geps Reference: Achen CH (2000) "Why Lagged Dependent Variables Can Suppress the Explanatory Power of Other Independent Variables", paper presented to the Annual Meeting of the Political Methodology Section of the American Political Science Association, University of California at Los Angeles, July 20-22 (http://polmeth.wustl.edu/workingpapers.php?year=2000). * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: RE: turning low frequency data into high frequency***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**st: Simple Question about Fixed Effects***From:*Bob Rijkers <bob.rijkers@pembroke.oxford.ac.uk>

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