arXiv 21 Oct 2019 · Econometrics · 4 citations (OpenAlex)
arXiv:1910.09502 · PDF · DOI · OpenAlex · Extracted main text
Partial identification approaches are a flexible and robust alternative to standard point-identification approaches in general instrumental variable models. However, this flexibility comes at the cost of a “curse of cardinality”: the number of restrictions on the identified set grows exponentially with the number of points in the support of the endogenous treatment. This article proposes a novel path-sampling approach to this challenge. It is designed for partially identifying causal effects of interest in the most complex models with continuous endogenous treatments. A stochastic process representation allows to seamlessly incorporate assumptions on individual behavior into the model. Some potential applications include dose-response estimation in randomized trials with imperfect compliance, the evaluation of social programs, welfare estimation in demand models, and continuous choice models. As a demonstration, the method provides informative nonparametric bounds on household expenditures under the assumption that expenditure is continuous. The mathematical contribution is an approach to approximately solving infinite dimensional linear programs on path spaces via sampling.
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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 | Imbens \ Newey (2009) `Identification and estimation of triangular simultaneous equations models without additivity', Econometrica 77(5), 1481–1512 | 1.000 | 14 | 3 | 100% |
| 2 | Chesher \ Rosen (2017) `Generalized instrumental variable models', Econometrica 85(3), 959–989 | 1.000 | 10 | 3 | 100% |
| 3 | Kitamura \ Stoye (2018) `Nonparametric analysis of random utility models', Econometrica, forthcoming | 1.000 | 7 | 3 | 100% |
| 4 | Anderson \ Nash (1987) Linear programming in infinite dimensional spaces: Theory and applications, Wiley | 0.928 | 4 | 3 | 100% |
| 5 | Blundell, Chen \ Kristensen (2007) `Semi-nonparametric IV estimation of shape-invariant Engel curves', Econometrica 75(6), 1613–1669 | 0.874 | 9 | 2 | 100% |
| 6 | Russell (2019) `Sharp bounds on functionals of the joint distribution in the analysis of treatment effects', Journal of Business & Economic Sta… | 0.874 | 8 | 2 | 100% |
| 7 | Balke \ Pearl (1994) Counterfactual probabilities: Computational methods, bounds and applications, in `Proceedings of the Tenth international confere… | 0.874 | 7 | 2 | 100% |
| 8 | Balke \ Pearl (1997) `Bounds on treatment effects from studies with imperfect compliance', Journal of the American Statistical Association 92(439), 1… | 0.874 | 7 | 2 | 100% |
| 9 | Pucci de Farias \ Van Roy (2004) `On constraint sampling in the linear programming approach to approximate dynamic programming', Mathematics of Operations Resear… | 0.874 | 6 | 2 | 100% |
| 10 | Beresteanu, Molchanov \ Molinari (2012) `Partial identification using random set theory', Journal of Econometrics 166(1), 17–32 | 0.874 | 5 | 2 | 100% |
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