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Identifying Causal Effects of Discrete, Ordered and ContinuousTreatments using Multiple Instrumental Variables

Nadja van 't Hoff

arXiv 29 Nov 2023 · Econometrics

arXiv:2311.17575 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Inferring causal relationships from observational data is often challenging due to endogeneity. This paper provides new identification results for causal effects of discrete, ordered and continuous treatments using multiple binary instruments. The key contribution is the identification of a new causal parameter that has a straightforward interpretation with a positive weighting scheme and is applicable in many settings due to a mild monotonicity assumption. This paper further leverages recent advances in causal machine learning for both estimation and the detection of local violations of the underlying monotonicity assumption. The methodology is applied to estimate the returns to education and assess the impact of having an additional child on female labor market outcomes.

Citation extraction

8
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distinct cited
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main-text words

appendix boundary found by appendix_command · 76% of the source is main text. Read the extracted text to check this.

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
1Angrist, J. D. and Evans, W. N (1998) Children and Their Parents' Labor Supply: Evidence from Exogenous Variation in Family Size0.51121100%
2Card, D (1995) Using Geographic Variation in College Proximity to Estimate the Return to Schooling0.51121100%
3Attanasio, O. P., Maro, V. D., and Vera-Hernández, M (2013) Community Nurseries and the Nutritional Status of Poor Children. Evidence from Colombia0.40511100%
4Cawley, J (2004) The Impact of Obesity on Wages0.40511100%
5Dixon, P., Hollingworth, W., Harrison, S., Davies, N. M., and Smith,… (2020) Mendelian Randomization Analysis of the Causal Effect of Adiposity on Hospital Costs0.40511100%
6Kline, B. and Tobias, J. L (2008) The Wages of BMI: Bayesian Analysis of a Skewed Treatment–Response Model with Nonparametric Endogeneity0.40511100%
7Lindeboom, M., Lundborg, P., and Van Der Klaauw, B (2010) Assessing the Impact of Obesity on Labor Market Outcomes0.40511100%
8Scholder, S. v. H. K., Smith, G. D., Lawlor, D. A., Propper, C., and… (2013) Child Height, Health and Human Capital: Evidence Using Genetic Markers0.40511100%

Showing the top 8 of 8 scored citations.