arXiv 9 Sep 2023 · Econometrics · publishedAmerican Economic Review Insights (2025)
arXiv:2309.04793 · PDF · DOI · OpenAlex · Extracted main text
To estimate the causal effects of beliefs on actions, researchers often run information provision experiments. We consider the causal interpretation of two-stage least squares (TSLS) estimators in these experiments. We characterize common TSLS estimators as weighted averages of causal effects, and interpret these weights under general belief updating conditions that nest parametric models from the literature. Our framework accommodates TSLS estimators for both passive and active control designs. Notably, we find that some passive control estimators allow for negative weights, which compromises their causal interpretation. We give practical guidance on such issues, and illustrate our results in two empirical applications.
appendix boundary found by appendix_titled_section at “Appendix” · 52% of the source is main text. Read the extracted text to check this.
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 | Angrist, J. D., Graddy, K., and Imbens, G. W (2000) The interpretation of instrumental variables estimators in simultaneous equations models with an application to the demand for f… | 1.000 | 5 | 4 | 100% |
| 2 | Blandhol, C., Bonney, J., Mogstad, M., and Torgovitsky, A (2022) When is tsls actually late? | 1.000 | 5 | 3 | 100% |
| 3 | Balla-Elliott, D (2023) Identifying causal effects in information provision experiments | 0.956 | 8 | 4 | 88% |
| 4 | Haaland, I., Roth, C., and Wohlfart, J (2023) Designing information provision experiments | 0.920 | 9 | 5 | 78% |
| 5 | Jäger, S., Roth, C., Roussille, N., and Schoefer, B (2024) Worker beliefs about outside options | 0.888 | 20 | 5 | 70% |
| 6 | Kumar, S., Gorodnichenko, Y., and Coibion, O (2023) The effect of macroeconomic uncertainty on firm decisions | 0.874 | 15 | 6 | 67% |
| 7 | Coibion, O., Gorodnichenko, Y., and Weber, M (2022) Monetary policy communications and their effects on household inflation expectations | 0.843 | 4 | 4 | 75% |
| 8 | Deshpande, M. and Dizon-Ross, R (2023) The (lack of) anticipatory effects of the social safety net on human capital investment | 0.843 | 4 | 4 | 75% |
| 9 | Roth, C. and Wohlfart, J (2020) How do expectations about the macroeconomy affect personal expectations and behavior? | 0.843 | 4 | 3 | 75% |
| 10 | Cullen, Z. and Perez-Truglia, R (2022) How much does your boss make? the effects of salary comparisons | 0.843 | 10 | 5 | 60% |
Showing the top 10 of 45 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Identifying Causal Effects in Information Provision Experiments | 0.630 | 8 | 5 |