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An Effective Approach to the Repeated Cross‐Sectional Design

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  • Matthew J. Lebo
  • Christopher Weber

Abstract

Repeated cross‐sectional (RCS) designs are distinguishable from true panels and pooled cross‐sectional time series (PCSTS) since cross‐sectional units (e.g., individual survey respondents) appear but once in the data. This poses two serious challenges. First, as with PCSTS, autocorrelation threatens inferences. However, common solutions like differencing and using a lagged dependent variable are not possible with RCS since lags for i cannot be used. Second, although RCS designs contain information that allows both aggregate‐ and individual‐level analyses, available methods—from pooled ordinary least squares to PCSTS to time series—force researchers to choose one level of analysis. The PCSTS tool kit does not provide an appropriate solution, and we offer one here: double filtering with ARFIMA methods to account for autocorrelation in longer RCS followed by the use of multilevel modeling to estimate both aggregate‐ and individual‐level parameters simultaneously. We use Monte Carlo experiments and three applied examples to explore the advantages of our framework.

Suggested Citation

  • Matthew J. Lebo & Christopher Weber, 2015. "An Effective Approach to the Repeated Cross‐Sectional Design," American Journal of Political Science, John Wiley & Sons, vol. 59(1), pages 242-258, January.
    • Handle: RePEc:wly:amposc:v:59:y:2015:i:1:p:242-258
    DOI: 10.1111/ajps.12095
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    Cited by:

    1. Lucrezia Fanti & Dario Guarascio & Matteo Tubiana, 2019. "Skill Gap, Mismatch, and the Dynamics of Italian Companies' Productivity," LEM Papers Series 2019/30, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2. Steven D. Silver & Marko Raseta, 2021. "An ARFIMA multi-level model of dual-component expectations in repeated cross-sectional survey data," Empirical Economics, Springer, vol. 60(2), pages 683-699, February.
    3. Szyszko, Magdalena & Rutkowska, Aleksandra & Kliber, Agata, 2022. "Do words affect expectations? The effect of central banks communication on consumer inflation expectations," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 221-229.
    4. Ben Krishna & Satish Krishnan & M. P. Sebastian, 2023. "Examining the Relationship between National Cybersecurity Commitment, Culture, and Digital Payment Usage: An Institutional Trust Theory Perspective," Information Systems Frontiers, Springer, vol. 25(5), pages 1713-1741, October.

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