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The paper adopts the Common Correlated Effects (CCE) approach proposed in the literature and demonstrates that the extension to the estimation of dynamic quantile regression models is feasible under similar conditions to the ones used in the literature. The new quantile regression estimator is shown to be consistent and its asymptotic distribution is derived. Monte Carlo studies are carried out to study the small sample behavior of the proposed approach. The evidence shows that the estimator can significantly improve on the performance of existing estimators as long as the time series dimension of the panel is large. We present an application to the evaluation of Time\u2010of\u2010Use pricing using a large randomized control trial.<\/jats:p>","DOI":"10.1002\/jae.2753","type":"journal-article","created":{"date-parts":[[2020,2,7]],"date-time":"2020-02-07T08:42:39Z","timestamp":1581064959000},"page":"294-314","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":55,"title":["Common correlated effects estimation of heterogeneous dynamic panel quantile regression models"],"prefix":"10.1002","volume":"35","author":[{"given":"Matthew","family":"Harding","sequence":"first","affiliation":[{"name":"Department of Economics University of California at Irvine  Irvine SSPB 3207 United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlos","family":"Lamarche","sequence":"additional","affiliation":[{"name":"Department of Economics University of Kentucky, 223G Gatton College of Business and Economics  Lexington United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M. 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