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Using our central limit theorem (CLT), we establish the asymptotic properties of parameter estimates of a general class of models based on a combination of cross-sectional and time-series data, recognizing the interdependence between the two data sources in the presence of aggregate shocks. Despite the complicated nature of the analysis required to formulate the joint CLT, it is straightforward to implement the resulting parameter limiting distributions due to a formal similarity of our approximations with Murphy and Topel\u2019s (1985,<jats:italic>Journal of Business and Economic Statistics<\/jats:italic>3, 370\u2013379) formula.<\/jats:p>","DOI":"10.1017\/s0266466622000391","type":"journal-article","created":{"date-parts":[[2022,9,19]],"date-time":"2022-09-19T10:29:58Z","timestamp":1663583398000},"page":"162-212","source":"Crossref","is-referenced-by-count":3,"title":["CENTRAL LIMIT THEORY FOR COMBINED CROSS SECTION AND TIME SERIES WITH AN APPLICATION TO AGGREGATE PRODUCTIVITY 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