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2SLS with Multiple Treatments

Manudeep Bhuller, Henrik Sigstad

arXiv 16 May 2022 · Econometrics · publishedJournal of Econometrics (2024) · 21 citations (OpenAlex)

arXiv:2205.07836 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We study what two-stage least squares (2SLS) identifies in models with multiple treatments under treatment effect heterogeneity. Two conditions are shown to be necessary and sufficient for the 2SLS to identify positively weighted sums of agent-specific effects of each treatment: average conditional monotonicity and no cross effects. Our identification analysis allows for any number of treatments, any number of continuous or discrete instruments, and the inclusion of covariates. We provide testable implications and present characterizations of choice behavior implied by our identification conditions.

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60
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175
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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Bhuller, Manudeep, Dahl, Gordon B., Lken, Katrine V., & Mogstad, Magne (2020) Incarceration, Recidivism, and Employment self1.000194100%
2Humphries, John Eric, Ouss, Aurélie, Stevenson, Megan, Stavreva, Kam… (2023) Conviction, Incarceration, and Recidivism: Understanding the Revolving Door1.000123100%
3Heckman, James J, & Vytlacil, Edward J (2007) Econometric evaluation of social programs, part II: Using the marginal treatment effect to organize alternative econometric esti…1.00084100%
4Kline, Patrick, & Walters, Christopher R (2016) Evaluating public programs with close substitutes: The case of Head Start1.00053100%
5Heckman, James J, & Pinto, Rodrigo (2018) Unordered monotonicity0.94613585%
6Lee, Sokbae, & Salanié, Bernard (2018) Identifying effects of multivalued treatments0.92843100%
7Lee, Sokbae, & Salanié, Bernard (2023) Filtered and Unfiltered Treatment Effects with Targeting Instruments0.92843100%
8Kamat, Vishal, Norris, Samuel, & Pecenco, Matthew (2023) Conviction, Incarceration, and Policy Effects in the Criminal Justice System0.8749467%
9Behaghel, Luc, Crepon, Bruno, & Gurgand, Marc (2013) Robustness of the Encouragement Design in a Two-Treatment Randomized Control Trial0.87462100%
10Heinesen, Eskil, Hvid, Christian, Kirkeben, Lars Johannessen, Leuven… (2022) Instrumental Variables with Unordered Treatments: Theory and Evidence from Returns to Fields of Study0.8434375%

Showing the top 10 of 60 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Potential weights and implicit causal designs in linear regression0.794123
2Treatment Effects with Targeting Instruments0.64422
3Contamination Bias in Linear Regressions0.64422
4Interpreting TSLS Estimators in Information Provision Experiments0.51122
5Identification in Multiple Treatment Models under Discrete Variation0.40511
6Dynamic Local Average Treatment Effects0.40511
7Inference for Treatment Effects Conditional on Generalized Principal Strata using Instrumental Variables0.40511
8Sharp Testable Implications of Encouragement Designs0.40511
9Monetary Incentives, Landowner Preferences: Estimating Cross-Elasticities in Farmland Conversion to Renewable Energy0.40511
10The purpose of an estimator is what it does: Misspecification, estimands, and over-identification0.40511