
Fiona BurligUniversity of Chicago | UC
Fiona Burlig
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19
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Publications
Publications (19)
How do social networks impact technology adoption? Exploiting a natural experiment in the mid‐20th century U.S. Upper Midwest, we find that social network expansions, in the form of mergers between congregations of the American Lutheran Church, led to increased rates of agricultural technology adoption among farmers. In counties that experienced a...
We provide the first at-scale estimate of electric vehicle (EV) home charging. Previous estimates are based on conflicting surveys or are extrapolated from a small, unrepresentative sample of households with dedicated EV meters. We combine billions of hourly electricity meter measurements with address-level EV registration records from California h...
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...
Social science research has undergone a credibility revolution, but these gains are at risk due to problematic research practices. Existing research on transparency has centered around randomized controlled trials, which constitute only a small fraction of research in economics. In this paper, I highlight three scenarios in which study preregistrat...
Social science research has undergone a credibility revolution, but these gains are at risk due to problematic research practices. Existing research on transparency has centered around randomized controlled trials, which constitute only a small fraction of research in economics. In this paper, I discuss three scenarios in which study preregistratio...
How should researchers design experiments to detect treatment effects with panel data? In this paper, we derive analytical expressions for the variance of panel estimators under non-i.i.d. error structures, which inform power calculations in panel data settings. Using Monte Carlo simulation, we demonstrate that, with correlated errors, traditional...
Social science research is increasingly data-driven, rigorous, and policy-relevant, but is at risk of being devalued due to evidence of the prevalence of problematic research practices and norms. This has led to growing interest in transparency practices in the social sciences. At present, the bulk of this work is centered around randomized control...