Identifying the Harm of Manipulable School-Choice Mechanisms

Dur, Umut; Hammond, Robert G.; Morrill, Thayer

doi:10.1257/pol.20160132

Cited by 47 publications

(45 citation statements)

References 18 publications

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“…The objective of our paper is to analyze by means of a laboratory experiment whether behavior is affected and better outcomes are obtained if, instead of submitting rankings to a central authority, subjects make decisions dynamically. Dynamic implementations of matching algorithms are used in college admissions in Brazil (Aygün and Bó [2]) and in Inner Mongolia (Chen and Kesten [7]), and in school choice in the Wake County Public School System (Dur et al [11]). Inspired by these markets, Chen and Pereyra [8] theoretically study a dynamic matching mechanism where at each stage students propose to a school and receive information about the tentative matching.…”

Section: Introductionmentioning

confidence: 99%

Static versus dynamic deferred acceptance in school choice: Theory and experiment

Klijn

Pais

Vorsatz

2019

Games and Economic Behavior

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In the context of school choice, we experimentally study how behavior and outcomes are affected when, instead of submitting rankings in the student proposing or receiving deferred acceptance (DA) mechanism, participants make decisions dynamically, going through the steps of the underlying algorithms. Our main results show that, contrary to theory, (a) in the dynamic student proposing DA mechanism, participants propose to schools respecting the order of their true preferences slightly more often than in its static version while, (b) in the dynamic student receiving DA mechanism, participants react to proposals by always respecting the order and not accepting schools in the tail of their true preferences more often than in the corresponding static version. As a consequence, for most problems we test, no significant differences exist between the two versions of the student proposing DA mechanisms in what stability and average payoffs are concerned, but the dynamic version of the student receiving DA mechanism delivers a clear improvement over its static counterpart in both dimensions. In fact, in the aggregate, the dynamic school proposing DA mechanism is the best performing mechanism.

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Section: Introductionmentioning

confidence: 99%

Static versus dynamic deferred acceptance in school choice: Theory and experiment

Klijn

Pais

Vorsatz

2019

Games and Economic Behavior

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“…These include college admissions in Brazil(Bó and Hakimov, 2016a), Inner Mongolia(Chen and Pereyra, 2015;Gong and Liang, 2016), and Tunisia(Luflade, 2017), and school choice in Wake County(Dur et al, 2018). These implementations differ in various dimensions including the type of information provided to students, the timing, and how students can revise their choices; such differences may very well impact the students' behavior and therefore the outcome.25 Bó and Hakimov (2016a) require that only rejected agents may revise their proposals at each step in order to eliminate possible manipulations that appeared in the mechanism for college admissions in Brazil.26 The impact on students' welfare (which is of major importance) is beyond the scope of this paper, but see, for example, Luflade (2017);Dur et al (2018).27 For a recent definition of a very strong sense of witnessing that the mechanism is run as promised, seeAkbarpour and Li (2017).…”

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confidence: 99%

Stable matching mechanisms are not obviously strategy-proof

Ashlagi

Gonczarowski

2018

Journal of Economic Theory

113

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Many two-sided matching markets, from labor markets to school choice programs, use a clearinghouse based on the applicant-proposing deferred acceptance algorithm, which is well known to be strategy-proof for the applicants. Nonetheless, a growing amount of empirical evidence reveals that applicants misrepresent their preferences when this mechanism is used. This paper shows that no mechanism that implements a stable matching is obviously strategy-proof for any side of the market, a stronger incentive property than strategy-proofness that was introduced by Li (2017). A stable mechanism that is obviously strategy-proof for applicants is introduced for the case in which agents on the other side have acyclical preferences.

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“…Some schools appear to avoid certain types of students, limiting access for the most disadvantaged [28]. Some parents may face uncertainty about their own priorities when submitting preferences, due to the role of the school priorities [29,30].…”

Section: Methodsmentioning

confidence: 99%

Measuring Inequality of Opportunity in Access to Quality Basic Education: A Case Study in Florida, US

Prieto

Flacke

Agüero-Valverde

et al. 2018

IJGI

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Providing all children equal access to essential services, such as primary education, has been set as a priority in the Sustainable Development Goals (SDG)’ agenda during the last two decades. Yet the Global Education Monitoring report in 2016 reveals that wide disparities between the rich and the poor persist in access to education of high quality. This study uses the Human Opportunity Index (HOI) to examine the equality of opportunity in access to basic education of high quality. By using enrollment and admission data from a case study in a large school district in the US in 2015/2016, this research evaluates the capacity of the HOI, in order to reveal disparities in access to school opportunities and examines how much of this inequality is explained by families’ pre-determined circumstances. The way of analyzing equality is by disaggregating applications’ data into circumstance groups, according to gender, geography, race/ethnicity, and other criteria. To capture the contribution of each circumstance to inequality of opportunity, the Shapley decomposition method is used. Findings show that the HOI is capable of systematically monitoring and examining existing admission policies and identifying inequality problems. Furthermore, the analysis of the contribution of each circumstance group can reveal admission criteria that have the potential to harm the educational opportunities for children. This assessment should provide valuable insights into the capability of the indicators to reveal where policy intervention is necessary and supply points of view on how policy can be improved.

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Identifying the Harm of Manipulable School-Choice Mechanisms

Cited by 47 publications

References 18 publications

Static versus dynamic deferred acceptance in school choice: Theory and experiment

Static versus dynamic deferred acceptance in school choice: Theory and experiment

Stable matching mechanisms are not obviously strategy-proof

Measuring Inequality of Opportunity in Access to Quality Basic Education: A Case Study in Florida, US

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