In: Journal of Business and Economic Statistics, 2019, vol. 37, no. 4, p. 736-748
This article proposes a fully nonparametric kernel method to account for observed covariates in regression discontinuity designs (RDD), which may increase precision of treatment effect estimation. It is shown that conditioning on covariates reduces the asymptotic variance and allows estimating the treatment effect at the rate of one- dimensional nonparametric regression, irrespective of the...
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In: Discussion papers on business and economics, 2017, vol. 2, p. 1-69
In heterogeneous treatment effect models with endogeneity, identification of the LATE typically relies on the availability of an exogenous instrument monotonically related to treatment participation. We demonstrate that a strictly weaker local monotonicity condition identifies the LATEs on compliers and on defiers. We propose simple estimators that are potentially more efficient than 2SLS,...
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In: Economics letters, 2014, vol. 123, no. 2, p. 220-223
The nonparametric identification of the local average treatment effect (LATE) hinges on the satisfaction of three instrumental variable assumptions: (1) Unconfounded assignment of the instrument, (2) no average direct effect of the instrument on the outcome within compliance types (exclusion restric- tion), and (3) weak monotonicity of the treatment in the instrument. While (1) often appears...
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In: Review of economics and statistics, 2015, vol. 97, no. 2, p. 398-411
We derive testable implications of instrument validity in just identified treat- ment effect models with endogeneity and consider several tests. The identifying assump- tions of the local average treatment effect allow us to both point identify and bound the mean potential outcomes (i) of the always takers under treatment and (ii) of the never takers under non-treatment. The point identified...
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In: Labour, 2015, vol. 29, no. 1, p. 1-14
We test the validity of the sibling sex ratio instrument in Angrist and Evans (1998) using the methods proposed by Kitagawa (2008) and Huber and Mellace (2014). The sex ratio of the first two siblings is arguably randomly assigned and influences the probability of having a third child, which makes it a candidate instrument for fertility when estimating the effect of fertility on female labor...
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(Working Papers SES ; 492)
When estimating local average and marginal treatment effects using instrumental variables (IV), multivalued endogenous treatments are frequently binarized based on a specific threshold in treatment support. However, such binarization introduces a violation of the IV exclusion if (i) the IV affects the multivalued treatment within support areas below and/or above the threshold and (ii) such...
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(Working Papers SES ; 489)
This paper proposes a fully nonparametric kernel method to account for observed covariates in regression discontinuity designs (RDD), which may increase precision of treatment effect estimation. It is shown that conditioning on covariates reduces the asymptotic variance and allows estimating the treatment effect at the rate of one-dimensional nonparametric regression, irrespective of the...
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(Working Papers SES ; 480)
Changes in compulsory schooling laws have been proposed as an instrument for the endogenous choice of schooling. It has been argued that raising minimum schooling exogenously increases the educational attainment of a subset of pupils without directly affecting later life outcomes such as income or health. Using the method of Huber and Mellace (2015) and data from the Survey of Health, Ageing and...
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(Working Papers SES ; 479)
This paper provides a review of methodological advancements in the evaluation of heterogeneous treatment effect models based on instrumental variable (IV) methods. We focus on models that achieve identification through a monotonicity assumption on the selection equation and analyze local average and quantile treatment effects for the subpopulation of compliers. We start with a comprehensive...
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