arXiv 21 May 2018 · Econometrics · publishedJournal of Econometrics (2022) · 5 citations (OpenAlex)
arXiv:1805.08275 · PDF · DOI · OpenAlex · Extracted main text
We develop an empirical framework to identify and estimate the effects of treatments on outcomes of interest when the treatments are the result of strategic interaction (e.g., bargaining, oligopolistic entry, peer effects). We consider a model where agents play a discrete game with complete information whose equilibrium actions (i.e., binary treatments) determine a post-game outcome in a nonseparable model with endogeneity. Due to the simultaneity in the first stage, the model as a whole is incomplete and the selection process fails to exhibit the conventional monotonicity. Without imposing parametric restrictions or large support assumptions, this poses challenges in recovering treatment parameters. To address these challenges, we first establish a monotonic pattern of the equilibria in the first-stage game in terms of the number of treatments selected. Based on this finding, we derive bounds on the average treatment effects (ATEs) under nonparametric shape restrictions and the existence of excluded exogenous variables. We show that instrument variation that compensates strategic substitution helps solve the multiple equilibria problem. We apply our method to data on airlines and air pollution in cities in the U.S. We find that (i) the causal effect of each airline on pollution is positive, and (ii) the effect is increasing in the number of firms but at a decreasing rate.
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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 | Ciliberto, F. and E. Tamer (2009) Market structure and multiple equilibria in airline markets | 1.000 | 12 | 3 | 100% |
| 2 | Berry, S. T (1992) Estimation of a Model of Entry in the Airline Industry | 1.000 | 6 | 3 | 100% |
| 3 | Shaikh, A. M. and E. J. Vytlacil (2011) Partial identification in triangular systems of equations with binary dependent variables | 0.928 | 5 | 4 | 80% |
| 4 | Vytlacil, E. and N. Yildiz (2007) Dummy endogenous variables in weakly separable models | 0.928 | 4 | 3 | 100% |
| 5 | Ciliberto, F., C. Murry, and E. Tamer (2018) Market Structure and Competition in Airline Markets | 0.928 | 4 | 3 | 100% |
| 6 | Imbens, G. W. and J. D. Angrist (1994) Identification and Estimation of Local Average Treatment Effects | 0.843 | 3 | 3 | 100% |
| 7 | Lee, S. and B. Salanié (2018) Identifying effects of multivalued treatments | 0.811 | 4 | 2 | 100% |
| 8 | Manski, C. F (2013) Identification of treatment response with social interactions | 0.737 | 3 | 3 | 67% |
| 9 | Manski, C. F. and J. V. Pepper (2000) Monotone instrumental variables: With an application to the returns to schooling | 0.644 | 2 | 2 | 100% |
| 10 | Manski, C. F (1990) Nonparametric bounds on treatment effects | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 40 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Identification in Nonparametric Models for Dynamic Treatment Effects | 0.843 | 3 | 3 |
| 2 | Analysis of Randomized Experiments with Network Interference and Noncompliance | 0.511 | 2 | 1 |