{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T14:33:39Z","timestamp":1793370819136,"version":"4.5.0"},"reference-count":29,"publisher":"Cambridge University Press (CUP)","issue":"1","license":[{"start":{"date-parts":[[2009,2,11]],"date-time":"2009-02-11T00:00:00Z","timestamp":1234310400000},"content-version":"unspecified","delay-in-days":6922,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Econom. Theory"],"published-print":{"date-parts":[[1990,3]]},"abstract":"<jats:p>This paper develops a general approach to robust, regression-based specification tests for (possibly) dynamic econometric models. A useful feature of the proposed tests is that, in addition to estimation under the null hypothesis, computation requires only a matrix linear least-squares regression and then an ordinary least-squares regression similar to those employed in popular nonrobust tests. For the leading cases of conditional mean and\/or conditional variance tests, the proposed statistics are robust to departures from distributional assumptions that are not being tested, while maintaining asymptotic efficiency under ideal conditions. Moreover, the statistics can be computed using any \u221a<jats:italic>T<\/jats:italic>-consistent estimator, resulting in significant simplifications in some otherwise difficult contexts. Among the examples covered are conditional mean tests for models estimated by weighted nonlinear least squares under misspecification of the conditional variance, tests of jointly parameterized conditional means and variances estimated by quasi-maximum likelihood under nonnormality, and some robust specification tests for a dynamic linear model estimated by two-stage least squares.<\/jats:p>","DOI":"10.1017\/s0266466600004898","type":"journal-article","created":{"date-parts":[[2009,3,10]],"date-time":"2009-03-10T15:48:17Z","timestamp":1236700097000},"page":"17-43","source":"Crossref","is-referenced-by-count":220,"title":["A Unified Approach to Robust, Regression-Based Specification Tests"],"prefix":"10.1017","volume":"6","author":[{"given":"Jeffrey M.","family":"Wooldridge","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2009,2,11]]},"reference":[{"key":"S0266466600004898_ref029","unstructured":"29. Wooldridge J.M. A C(\u03b1) Version of the Newey-Tauchen-White Test. Manuscript, MIT Department of Economics, 1989."},{"key":"S0266466600004898_ref016","volume-title":"Efficient estimation of semiparametric models via moment restrictions","author":"Newey"},{"key":"S0266466600004898_ref025","first-page":"1","volume-title":"Advances in Econometrics-Fifth World Congress","volume":"I","author":"White","year":"1987"},{"key":"S0266466600004898_ref013","unstructured":"13. Kennan J. & Neuman G.R. . Why does the information matrix test reject too often? University of Iowa Department of Economics Working Paper No. 88\u20134, 1988."},{"key":"S0266466600004898_ref024","volume-title":"Asymptotic Theory for econometricians","author":"White","year":"1984"},{"key":"S0266466600004898_ref023","doi-asserted-by":"publisher","DOI":"10.2307\/1912526"},{"key":"S0266466600004898_ref022","doi-asserted-by":"publisher","DOI":"10.2307\/1913132"},{"key":"S0266466600004898_ref008","doi-asserted-by":"crossref","first-page":"775","DOI":"10.1016\/S1573-4412(84)02005-5","volume-title":"Handbook of Econometrics","volume":"II","author":"Engle","year":"1984"},{"key":"S0266466600004898_ref028","unstructured":"28. Wooldridge J.M. Specification testing and quasi-maximum likelihood estimation. 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Wooldridge J.M. Asymptotic properties of econometric estimators. UCSD Ph.D. dissertation, 1986."},{"key":"S0266466600004898_ref001","unstructured":"1. Bollerslev T. & Wooldridge J.M. . Quasi-maximum likelihood estimation of dynamic models with time-varying covariances. MIT Department of Economics Working Paper No. 505, 1988."},{"key":"S0266466600004898_ref006","doi-asserted-by":"publisher","DOI":"10.1016\/0304-4076(82)90102-6"},{"key":"S0266466600004898_ref018","doi-asserted-by":"publisher","DOI":"10.1080\/07311768308800039"},{"key":"S0266466600004898_ref027","unstructured":"27. Wooldridge J.M. A regression-based Lagrange Multiplier statistic that is robust in the presence of heteroskedasticity. 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