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Design and Analysis of Cluster-Randomized Field Experiments in Panel Data Settings

Author

Listed:
  • Bharat K. Chandar
  • Ali Hortaçsu
  • John A. List
  • Ian Muir
  • Jeffrey M. Wooldridge

Abstract

Field experiments conducted with the village, city, state, region, or even country as the unit of randomization are becoming commonplace in the social sciences. While convenient, subsequent data analysis may be complicated by the constraint on the number of clusters in treatment and control. Through a battery of Monte Carlo simulations, we examine best practices for estimating unit-level treatment effects in cluster-randomized field experiments, particularly in settings that generate short panel data. In most settings we consider, unit-level estimation with unit fixed effects and cluster-level estimation weighted by the number of units per cluster tend to be robust to potentially problematic features in the data while giving greater statistical power. Using insights from our analysis, we evaluate the effect of a unique field experiment: a nationwide tipping field experiment across markets on the Uber app. Beyond the import of showing how tipping affects aggregate market outcomes, we provide several insights on aspects of generating and analyzing cluster-randomized experimental data when there are constraints on the number of experimental units in treatment and control.

Suggested Citation

  • Bharat K. Chandar & Ali Hortaçsu & John A. List & Ian Muir & Jeffrey M. Wooldridge, 2019. "Design and Analysis of Cluster-Randomized Field Experiments in Panel Data Settings," NBER Working Papers 26389, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:26389
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    References listed on IDEAS

    as
    1. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
    2. Cody Cook & Rebecca Diamond & Jonathan Hall & John List & Paul Oyer, 2018. "The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare Drivers," Natural Field Experiments 00634, The Field Experiments Website.
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    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design

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