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We show that using cross\u2010sectional dependence for estimation is important to obtain an estimator that is more efficient than existing estimators. This new estimator also uses nuisance parameters parsimoniously so that it exhibits good small\u2010 and large\u2010sample properties even when the number of time periods is large. As an empirical application, we estimate the effect of attending private school on student achievement using a value\u2010added model. Copyright \u00a9 2015 John Wiley &amp; Sons, Ltd.<\/jats:p>","DOI":"10.1002\/jae.2486","type":"journal-article","created":{"date-parts":[[2015,9,22]],"date-time":"2015-09-22T10:58:46Z","timestamp":1442919526000},"page":"85-105","source":"Crossref","is-referenced-by-count":10,"title":["Estimation of Dynamic Panel Data Models with Cross\u2010Sectional Dependence: Using Cluster Dependence for Efficiency"],"prefix":"10.1002","volume":"31","author":[{"given":"Valentin","family":"Verdier","sequence":"first","affiliation":[{"name":"Department of Economics University of North Carolina  Chapel Hill NC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2015,9,22]]},"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","unstructured":"AlvarezJ ArellanoM.2004.Robust likelihood estimation of dynamic panel data models. 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