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Estimating Welfare Effects in a Nonparametric Choice Model: The Case of School Vouchers

Vishal Kamat, Samuel Norris

arXiv 31 Jan 2020 · General Economics · publishedThe Review of Economic Studies (2025) · 1 citations (OpenAlex)

arXiv:2002.00103 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We develop new robust discrete choice tools to learn about the average willingness to pay for a price subsidy and its effects on demand given exogenous, discrete variation in prices. Our starting point is a nonparametric, nonseparable model of choice. We exploit the insight that our welfare parameters in this model can be expressed as functions of demand for the different alternatives. However, while the variation in the data reveals the value of demand at the observed prices, the parameters generally depend on its values beyond these prices. We show how to sharply characterize what we can learn when demand is specified to be entirely nonparametric or to be parameterized in a flexible manner, both of which imply that the parameters are not necessarily point identified. We use our tools to analyze the welfare effects of price subsidies provided by school vouchers in the DC Opportunity Scholarship Program. We find that the provision of the status quo voucher and a wide range of counterfactual vouchers of different amounts can have positive and potentially large benefits net of costs. The positive effect can be explained by the popularity of low-tuition schools in the program; removing them from the program can result in a negative net benefit. We also find that various standard logit specifications, in comparison, limit attention to demand functions with low demand for the voucher, which do not capture the large magnitudes of benefits credibly consistent with the data.

Citation extraction

49
references
71
in-text mentions
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distinct cited
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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
1Bhattacharya, D (2018) Empirical welfare analysis for discrete choice: Some general results0.92843100%
2Wolf, P., Gutmann, B., Puma, M., Kisida, B., Rizzo, L., Eissa, N., C… (2010) Evaluation of the dc opportunity scholarship program: Final report0.87452100%
3Mogstad, M., Santos, A. and Torgovitsky, A (2018) Using instrumental variables for inference about policy relevant treatment parameters0.84333100%
4Bhattacharya, D (2015) Nonparametric welfare analysis for discrete choice0.81142100%
5Epple, D., Romano, R. E. and Urquiola, M (2017) School vouchers: A survey of the economics literature0.73732100%
6Tebaldi, P., Torgovitsky, A. and Yang, H (2021) Nonparametric estimates of demand in the california health insurance exchange0.73732100%
7Arcidiacono, P., Muralidharan, K., Shim, E.-y. and Singleton, J. D (2021) Experimentally validating welfare evaluation of school vouchers: Part i0.64422100%
8Barseghyan, L., Coughlin, M., Molinari, F. and Teitelbaum, J. C (2021) Heterogeneous choice sets and preferences0.64422100%
9Bhattacharya, D (2021) The empirical content of binary choice models0.64422100%
10Carneiro, P. M., Das, J. and Reis, H (2019) The value of private schools: Evidence from pakistan0.64422100%

Showing the top 10 of 49 scored citations.

Cited by, within the corpus

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1Identification in Multiple Treatment Models under Discrete Variation0.40511