Assessing Sampling Error in Pseudo-Panel Models

Khan, Rumman

Abstract

While pseudo-panels are useful when only repeated cross-section data are available, estimates are likely to be attenuated and suffer from sampling error if cell sizes (number of individuals grouped together in a cohort) are too few. However, there is no consensus on how large cell size needs to be, with recommendations ranging from 100 to several thousands. This is due to sampling error being affected by both cell size and three important types of variation in the cohort data (across and within cohorts and over time). We combine these into a single metric, called CAWAR, and demonstrate its relationship to sampling error using Monte Carlo simulations and an empirical application. We produce recommended values for CAWAR beyond which sampling error bias is minimal and from these one can easily calculate the required cell size.

Citation

Khan, R. (2021). Assessing Sampling Error in Pseudo-Panel Models. Oxford Bulletin of Economics and Statistics, 83(3), 742-769. https://doi.org/10.1111/obes.12416

• Journal Article Type: Article
• Acceptance Date: Feb 11, 2020
• Online Publication Date: Jan 10, 2021
• Publication Date: 2021-06
• Deposit Date: May 30, 2023
• Journal: Oxford Bulletin of Economics and Statistics
• Print ISSN: 0305-9049
• Electronic ISSN: 1468-0084
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 83
• Issue: 3
• Pages: 742-769
• DOI: https://doi.org/10.1111/obes.12416
• Keywords: Statistics, Probability and Uncertainty; Economics and Econometrics; Social Sciences (miscellaneous); Statistics and Probability
• Public URL: https://keele-repository.worktribe.com/output/428506
• Publisher URL: https://onlinelibrary.wiley.com/doi/10.1111/obes.12416
• Additional Information: Received: 2020-11-01; Accepted: 2020-11-02; Published: 2021-01-10