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How Well Do Structural Demand Models Work? Counterfactual Predictions in School Choice

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  • Parag A. Pathak
  • Peng Shi

Abstract

Discrete choice demand models are widely used for counterfactual policy simulations, yet their out-of-sample performance is rarely assessed. This paper uses a large-scale policy change in Boston to investigate the performance of discrete choice models of school demand. In 2013, Boston Public Schools considered several new choice plans that differ in where applicants can apply. At the request of the mayor and district, we forecast the alternatives' effects by estimating discrete choice models. This work led to the adoption of a plan which significantly altered choice sets for thousands of applicants. Pathak and Shi (2014) update forecasts prior to the policy change and describe prediction targets involving access, travel, and unassigned students. Here, we assess how well these ex ante counterfactual predictions compare to actual outcome under the new choice sets. We find that a simple ad hoc model performs as well as the more complicated structural choice models for one of the two grades we examine. However, the structural models' inconsistent performance is largely due to prediction errors in applicant characteristics, which are auxiliary inputs. Once we condition on the actual applicant characteristics, the structural choice models outperform the ad hoc alternative in predicting both choice patterns and policy relevant outcomes. Moreover, refitting the models using the new choice data does not significantly improve their prediction accuracy, suggesting that the choice models are indeed “structural.” Our findings show that structural demand models can effectively predict counterfactual outcomes, as long there are accurate forecasts about auxiliary input variables.

Suggested Citation

  • Parag A. Pathak & Peng Shi, 2017. "How Well Do Structural Demand Models Work? Counterfactual Predictions in School Choice," NBER Working Papers 24017, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:24017
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    References listed on IDEAS

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    1. James J. Heckman, 2010. "Building Bridges between Structural and Program Evaluation Approaches to Evaluating Policy," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 356-398, June.
    2. Sanjog Misra & Harikesh Nair, 2011. "A structural model of sales-force compensation dynamics: Estimation and field implementation," Quantitative Marketing and Economics (QME), Springer, vol. 9(3), pages 211-257, September.
    3. Michael P. Keane & Kenneth I. Wolpin, 2007. "Exploring The Usefulness Of A Nonrandom Holdout Sample For Model Validation: Welfare Effects On Female Behavior," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1351-1378, November.
    4. Kenneth I. Wolpin & Petra E. Todd, 2006. "Assessing the Impact of a School Subsidy Program in Mexico: Using a Social Experiment to Validate a Dynamic Behavioral Model of Child Schooling and Fertility," American Economic Review, American Economic Association, vol. 96(5), pages 1384-1417, December.
    5. Atila Abdulkadiroğlu & Nikhil Agarwal & Parag A. Pathak, 2015. "The Welfare Effects of Coordinated Assignment: Evidence from the NYC HS Match," NBER Working Papers 21046, National Bureau of Economic Research, Inc.
    6. Simon Burgess & Ellen Greaves & Anna Vignoles & Deborah Wilson, 2015. "What Parents Want: School Preferences and School Choice," Economic Journal, Royal Economic Society, vol. 125(587), pages 1262-1289, September.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    8. Peter C. Fishburn, 1974. "Exceptional Paper--Lexicographic Orders, Utilities and Decision Rules: A Survey," Management Science, INFORMS, vol. 20(11), pages 1442-1471, July.
    9. Nikhil Agarwal & Paulo Somaini, 2018. "Demand Analysis Using Strategic Reports: An Application to a School Choice Mechanism," Econometrica, Econometric Society, vol. 86(2), pages 391-444, March.
    10. Eduardo M. Azevedo & Jacob D. Leshno, 2016. "A Supply and Demand Framework for Two-Sided Matching Markets," Journal of Political Economy, University of Chicago Press, vol. 124(5), pages 1235-1268.
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    Cited by:

    1. Oosterbeek, Hessel & Sóvágó, Sándor & van der Klaauw, Bas, 2019. "Why are schools segregated? Evidence from the secondary-school match in Amsterdam," CEPR Discussion Papers 13462, C.E.P.R. Discussion Papers.

    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • I20 - Health, Education, and Welfare - - Education - - - General

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