arXiv 25 Nov 2024 · Econometrics · publishedEconometrics Journal (2025) · 1 citations (OpenAlex)
arXiv:2411.16906 · PDF · DOI · OpenAlex · Extracted main text
In an empirical study of persuasion, researchers often use a binary instrument to encourage individuals to consume information and take some action. We show that, with a binary Imbens-Angrist instrumental variable model and the monotone treatment response assumption, it is possible to identify the joint distribution of potential outcomes among compliers. This is necessary to identify the percentage of mobilised voters and their statistical characteristic defined by the moments of the joint distribution of treatment and covariates. Specifically, we develop a method that enables researchers to identify the statistical characteristic of persuasion types: always-voters, never-voters, and mobilised voters among compliers. These findings extend the kappa weighting results in Abadie (2003). We also provide a sharp test for the two sets of identification assumptions. The test boils down to testing whether there exists a nonnegative solution to a possibly under-determined system of linear equations with known coefficients. An application based on Green et al. (2003) is provided.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Green, D. P., A. S. Gerber, and D. W. Nickerson (2003) Getting out the vote in local elections: Results from six door-to-door canvassing experiments | 1.000 | 16 | 4 | 100% |
| 2 | Gerber, A. S., D. P. Green, and R. Shachar (2003) Voting may be habit-forming: evidence from a randomized field experiment | 0.928 | 4 | 3 | 100% |
| 3 | Abadie, A (2003) Semiparametric instrumental variable estimation of treatment response models | 0.874 | 12 | 4 | 67% |
| 4 | Bai, Y., A. Santos, and A. M. Shaikh (2022) On testing systems of linear inequalities with known coefficients | 0.874 | 6 | 2 | 100% |
| 5 | DellaVigna, S. and M. Gentzkow (2010) Persuasion: empirical evidence | 0.811 | 4 | 2 | 100% |
| 6 | Jun, S. J. and S. Lee (2023) Identifying the effect of persuasion | 0.806 | 21 | 6 | 52% |
| 7 | Imbens, G. W. and D. B. Rubin (1997) Estimating outcome distributions for compliers in instrumental variables models | 0.794 | 6 | 3 | 50% |
| 8 | Balke, A. and J. Pearl (1997) Bounds on treatment effects from studies with imperfect compliance | 0.644 | 3 | 2 | 67% |
| 9 | Heckman, J. J., J. Smith, and N. Clements (1997) Making the most out of programme evaluations and social experiments: Accounting for heterogeneity in programme impacts | 0.644 | 2 | 2 | 100% |
| 10 | Manski, C (1997) Monotone treatment response | 0.511 | 3 | 2 | 33% |
Showing the top 10 of 33 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | 2503.06046 | 0.737 | 3 | 3 |
| 2 | 2212.14105 | 0.644 | 4 | 1 |
| 3 | 2410.14871 | 0.405 | 1 | 1 |
| 4 | 2509.26517 | 0.405 | 1 | 1 |