{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T21:34:19Z","timestamp":1790199259597,"version":"4.1.0"},"reference-count":43,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2018,5,10]],"date-time":"2018-05-10T00:00:00Z","timestamp":1525910400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Applied Econometrics"],"published-print":{"date-parts":[[2018,9]]},"abstract":"<jats:title>Summary<\/jats:title><jats:p>This paper considers estimation and inference in linear panel regression models with lagged dependent variables and\/or other weakly exogenous regressors when <jats:italic>N<\/jats:italic> (the cross\u2010section dimension) is large relative to <jats:italic>T<\/jats:italic> (the time series dimension). It allows for fixed and time effects (FE\u2010TE) and derives a general formula for the bias of the FE\u2010TE estimator which generalizes the well\u2010known Nickell bias formula derived for the pure autoregressive dynamic panel data models. It shows that in the presence of weakly exogenous regressors inference based on the FE\u2010TE estimator will result in size distortions unless <jats:italic>N<\/jats:italic>\/<jats:italic>T<\/jats:italic> is sufficiently small. To deal with the bias and size distortion of the FE\u2010TE estimator the use of a half\u2010panel jackknife FE\u2010TE estimator is considered and its asymptotic distribution is derived. It is shown that the bias of the half\u2010panel jackknife FE\u2010TE estimator is of order <jats:italic>T<\/jats:italic><jats:sup>\u22122<\/jats:sup>, and for valid inference it is only required that <jats:italic>N<\/jats:italic>\/<jats:italic>T<\/jats:italic><jats:sup>3<\/jats:sup>\u21920, as <jats:italic>N<\/jats:italic>,<jats:italic>T<\/jats:italic>\u2192<jats:italic>\u221e<\/jats:italic> jointly. Extension to unbalanced panel data models is also provided. The theoretical results are illustrated with Monte Carlo evidence. It is shown that the FE\u2010TE estimator can suffer from large size distortions when <jats:italic>N<\/jats:italic>&gt;<jats:italic>T<\/jats:italic>, with the half\u2010panel jackknife FE\u2010TE estimator showing little size distortions. The use of half\u2010panel jackknife FE\u2010TE estimator is illustrated with two empirical applications from the literature.<\/jats:p>","DOI":"10.1002\/jae.2623","type":"journal-article","created":{"date-parts":[[2018,5,10]],"date-time":"2018-05-10T07:54:31Z","timestamp":1525938871000},"page":"816-836","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":57,"title":["Half\u2010panel jackknife fixed\u2010effects estimation of linear panels with weakly exogenous regressors"],"prefix":"10.1002","volume":"33","author":[{"given":"Alexander","family":"Chudik","sequence":"first","affiliation":[{"name":"Federal Reserve Bank of Dallas  Dallas TX USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M. Hashem","family":"Pesaran","sequence":"additional","affiliation":[{"name":"Department of Economics and USC Dornsife INET University of Southern California  Los Angeles CA USA"},{"name":"Trinity College  Cambridge UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jui\u2010Chung","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Economics National Tsing Hua University  Hsinchu City Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2018,5,10]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/0304-4076(94)01641-C"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/1468-0262.00441"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.2307\/2297968"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/0304-4076(94)01642-D"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1080\/07474938.2014.975642"},{"key":"e_1_2_8_7_1","volume-title":"ACTEST: Stata module to perform Cumby\u2013Huizinga general test for autocorrelation in time series (Statistical Software Components S457668)","author":"Baum C. 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