Do Parents Value School Effectiveness?

Abdulkadiroğlu, Atila; Pathak, Parag A.; Schellenberg, Jonathan; Walters, Christopher

doi:10.3386/w23912

Cited by 58 publications

(98 citation statements)

References 43 publications

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“…This model allows us to analyze how candidates combine attributes of alternatives into overall evaluations of the attractiveness of schools (Beggs, Cardel and Haussman, 1981;Hausman and Ruud, 1987;Koop and Poirier, 1994). Previous work that analyzed parental preferences for school characteristics use similar models (Beuermann et al, 2018;Abdulkadiroglu, Pathak and Schellenberg, 2017;Staiger, 2005, 2006).…”

Section: Methodsmentioning

confidence: 99%

Teachers' Preferences for Proximity and the Implications for Staffing Schools: Evidence from Peru

Bertoni¹,

Elacqua²,

Hincapié³

et al. 2019

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Any dispute related to the use of the works of the IDB that cannot be settled amicably shall be submitted to arbitration pursuant to the UNCITRAL rules. The use of the IDB's name for any purpose other than for attribution, and the use of IDB's logo shall be subject to a separate written license agreement between the IDB and the user and is not authorized as part of this CC-IGO license. Following a peer review process, and with previous written consent by the Inter-American Development Bank (IDB), a revised version of this work may also be reproduced in any academic journal, including those indexed by the American Economic Association's EconLit, provided that the IDB is credited and that the author(s) receive no income from the publication. Therefore, the restriction to receive income from such publication shall only extend to the publication's author(s). With regard to such restriction, in case of any inconsistency between the Creative Commons IGO 3.0 Attribution-NonCommercial-NoDerivatives license and these statements, the latter shall prevail. Note that link provided above includes additional terms and conditions of the license.

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Section: Methodsmentioning

confidence: 99%

Teachers' Preferences for Proximity and the Implications for Staffing Schools: Evidence from Peru

Bertoni¹,

Elacqua²,

Hincapié³

et al. 2019

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show abstract

“…MCAS performance levels need not be a measure of school effectiveness. Abdulkadiroglu, Pathak, Schellenberg, and Walters (2017) show that in New York City, applicant preferences are uncorrelated with effectiveness once we control for peer quality. a covariance matrix by taking the inverse of the Hessian of the log likelihood function at the maximum.…”

Section: Multinomial Logit (Mnl) Choice Modelmentioning

confidence: 88%

“…7 The growing literature estimating school demand from similar datasets includes: Abdulkadiroglu, Agarwal, and Pathak (2015), Abdulkadiroglu, Pathak, Schellenberg, and Walters (2017), Agarwal and Somaini (2014), Burgess, Greaves, Vignoles, and Wilson (2015), Calsamiglia, Fu, and Guell (2017), Glazerman and Dotter (2016), Harris and Larsen (2015), Hastings, Kane, and Staiger (2009), He (2012), Hwang (2015), Kapor, Neilson, and Zimmerman (2017), Ruijs and Oosterbeek (2012), and Walters (2014).…”

Section: Introductionmentioning

confidence: 99%

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

Pathak

Shi²

2017

Self Cite

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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.

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“…Even explicit attempts to intervene in the availability and use of information do not reduce the inequality produced by choice as advantaged families benefited more from the intervention than disadvantaged families (Corcoran et al, 2018). Perhaps most troublesome for the theory that the public benefits from private choices because they reveal and reward the most effective schools is new evidence that suggests families select schools based on desired characteristics of a school’s student population rather than on school effectiveness (Abdulkadiroglu et al, 2017).…”

Section: Democratic Engagement and Private Actionmentioning

confidence: 99%

Toward a Framework for Public Accountability in Education Reform

Hutt

Polikoff

2020

Educational Researcher

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Public accountability through information disclosure is a pillar of modern education reform efforts. Despite the ubiquity of this approach, we argue that public accountability in education is undertheorized and often predictably unlikely to achieve its intended policy goals. Drawing on examples from an equity-oriented court case in California and the literatures on democratic engagement and parent use of school performance data, we propose a framework for thinking about the design of public accountability systems in education. The framework could provide guidance for policymakers considering new efforts at improving schools through the production and dissemination of educational data.

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Do Parents Value School Effectiveness?

Cited by 58 publications

References 43 publications

Teachers' Preferences for Proximity and the Implications for Staffing Schools: Evidence from Peru

Teachers' Preferences for Proximity and the Implications for Staffing Schools: Evidence from Peru

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

Toward a Framework for Public Accountability in Education Reform

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