As 2017 draws to a close, I am marking the year by posting links to a selection of papers circulated in the past year. These are papers that I read and that I think are especially impressive in moving the methodological frontier forward for people, like myself, who do field experimental and quasi-experimental policy research. I have linked to ungated versions whenever I could:
Foundational Work in Causal Inference
These are papers that challenge conventional wisdom or otherwise newly reveal some basic considerations in causal inference:
- Pei et al. on when placebo tests are preferred to control [pdf].
- Abadie et al. on causal standard errors [arxiv].
- Morgan on permutation vs bootstrap for experimental data [arxiv].
- Young on how IV inference tends to be overconfident [pdf].
- Lenz and Sahn on p hacking through covariate control and why we do indeed want to see the zero order correlations [osf].
- Christian and Barrett on spurious panel IV [pdf].
- Spiess on the importance of statistical unbiasedness in situations where researchers have to persuade skeptics [pdf].
- Savje et al. on when we do and don’t need to worry about interference as a first order problem [arxiv].
- D’amour et al. on a curse of dimensionality for strong ignorability [arxiv].
Generalization, Policy Extrapolation, and Equilibrium Effects
Current program evaluation work is pushing past the old “reduced-form vs. structural” divide and making use of tools from both worlds to address questions of generalization, policy extrapolation, and equilibrium effects. Here are some good recent examples:
- Muralidharan et al. on equilibrium effects of improving access to a cash for work program in India [pdf].
- Banerjee et al. on using an experiment and model to infer an optimal strategy to deter drunk driving [pdf].
- Davis et al on how to design experiments to improve their ability to inform scaled up interventions [nber-gated].
Beautifully Designed Field Studies
Finally, here are papers that I read this year that taught me a lot about framing and designing field experiments. Reading them offers a master class on research design and analysis:
- Benhassine et al. on the low returns from firm formalization [pdf].
- Blattman and Dercon on the drawbacks of factory work [ssrn].
- Munger “bots” experiment to reduce partisan incivility on Twitter [pdf].
- Green et al experiment on how mass media campaigns can reduce intimate partner violence [pdf].
- Matz et al on using psychological profiling to target persuasion [pnas].
- Weigel experiment on how state taxation induces more civic engagement [pdf].
