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Panel Data and Experimental Design / Fiona Burlig, Louis Preonas, Matt Woerman.
- Format:
- Book
- Author/Creator:
- Burlig, Fiona.
- Series:
- Working Paper Series (National Bureau of Economic Research) no. w26250.
- NBER working paper series no. w26250
- Language:
- English
- Physical Description:
- 1 online resource: illustrations (black and white);
- Place of Publication:
- Cambridge, Mass. National Bureau of Economic Research 2019.
- Summary:
- How should researchers design panel data experiments? We analytically derive the variance of panel estimators, informing power calculations in panel data settings. We generalize Frison and Pocock (1992) to fully arbitrary error structures, thereby extending McKenzie (2012) to allow for non-constant serial correlation. Using Monte Carlo simulations and real world panel data, we demonstrate that failing to account for arbitrary serial correlation ex ante yields experiments that are incorrectly powered under proper inference. By contrast, our "serial-correlation-robust" power calculations achieve correctly powered experiments in both simulated and real data. We discuss the implications of these results, and introduce a new software package to facilitate proper power calculations in practice.
- Notes:
- Print version record
- September 2019.
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