02190cam a22002657 4500001000600000003000500006005001700011008004100028100002000069245014400089260006600233490005100299500001500350520100500365530006101370538007201431538003601503690009701539690007701636700002001713710004201733830008601775856003701861856002601898t0323NBER20140822191628.0140822s2006 mau||||fs|||| 000 0 eng d1 aStock, James H.10aHeteroskedasticity-Robust Standard Errors for Fixed Effects Panel Data Regressionh[electronic resource] /cJames H. Stock, Mark W. Watson. aCambridge, Mass.bNational Bureau of Economic Researchc2006.1 aNBER technical working paper seriesvno. t0323 aJune 2006.3 aThe conventional heteroskedasticity-robust (HR) variance matrix estimator for cross-sectional regression (with or without a degrees of freedom adjustment), applied to the fixed effects estimator for panel data with serially uncorrelated errors, is inconsistent if the number of time periods T is fixed (and greater than two) as the number of entities n increases. We provide a bias-adjusted HR estimator that is (nT)1/2 -consistent under any sequences (n, T) in which n and/or T increase to infinity.The conventional heteroskedasticity-robust (HR) variance matrix estimator for cross-sectional regression (with or without a degrees of freedom adjustment), applied to the fixed effects estimator for panel data with serially uncorrelated errors, is inconsistent if the number of time periods T is fixed (and greater than two) as the number of entities n increases. We provide a bias-adjusted HR estimator that is (nT)1/2 -consistent under any sequences (n, T) in which n and/or T increase to infinity. aHardcopy version available to institutional subscribers. aSystem requirements: Adobe [Acrobat] Reader required for PDF files. aMode of access: World Wide Web. 7aC23 - Panel Data Models • Spatio-temporal Models2Journal of Economic Literature class. 7aC12 - Hypothesis Testing: General2Journal of Economic Literature class.1 aWatson, Mark W.2 aNational Bureau of Economic Research. 0aTechnical Working Paper Series (National Bureau of Economic Research)vno. t0323.4 uhttp://www.nber.org/papers/t0323 uurn:doi:10.3386/t0323