In recent years a number of school systems have used various schemes to match students with schools. In these mechanisms students rank the schools they would like to attend and then are placed into schools by a process that takes these rankings into account along with the capacities of the schools and any special priorities granted to some students. The resulting matches may be good or bad depending on the behavior of the students (or their parents) in the matching process (i.e., the strategic dissembling they employ.) Theoretical work done to design matching mechanisms that mitigate (or eliminate) such strategic dissembling assumes the matching process occurs once and is not repeated again. As a practical matter, this isn't how school matching markets work. Instead, the matching process is repeated prior to the beginning of each school year. Parents who have participated in prior years may pass along advice to newcomers they know regarding how to behave in these markets. Over time groups of people will develop "traditional wisdom" as to how to behave. If this traditional wisdom leads people to behave optimally then the outcome of the match is likely to be consistent with the intentions of the mechanism designers. If, however, the traditional wisdom reinforces bad behavior, the resulting allocations may be sub-optimal. In the funded research the PI will conduct a series of experiments to examine the impact of intergenerational advice and network structure (who talks with who) on the performance of matching mechanisms. Matching markets occur is a variety of situations from matching students to schools to interns to hospitals. Many share the feature that the market reoccurs at specific intervals with information on "how to play" the game being passed down over time. Understanding how the resulting evolution of traditional wisdom and how the structure of connections among market participants (e.g., which parents talk to who) influences the outcome of matching market is crucial to designing matching mechanisms with desirable properties.

Project Report

In this project I study the properties of two school matching programs used in the US to match students to schools. In these programs parents submit their preferences over schools to an algorithm that then matches them to schools. The main innovation of the research is to take into account the fact that, when parents use these programs in the real world, they typically chat with and seek advice from other parents who are either currently engaging in the program or who have done so in the past. The research studies the impact of such advice. To conduct this research we use experimental laboratory techniques which have the advantage that in the lab we can control and hence know the preferences of our subjects (parents) over the objects (schools) they are seeking to enter. (This information is not available in the real world so naturally occurring field data is less useful.) What we find can be summarized as follows: 1) Chatting has an impact on the preferences subjects submit to the matching programs in that those subjects who chat change their submitted preferences significantly more than those who do not chat. 2) People who chat with others who are of their own type (have similar preferences over schools etc.) change their preferences more often. 3) People who chat with people different from themselves experience a greater increase in welfare than those who chat with others like themselves. This is interesting because we know that subjects who chat with others like themselves change strategies more often so this result suggests that there are instances where chatting is beneficial because it leads people not to change their submitted preferences when they have chosen a good strategy. 4) Chatting leads to an increase in the instance of stable matches between schools and parents. This is important because matching programs that determine unstable matches leave parents being envious of other parents and their matches and this can lead to political turmoil. 5) Parents who are isolated and do not chat with anyone and who also do not have priority for any school (or for a bad local school) would benefit most from being able to get good advice. This has important implications for policy since if one assumes that parents who have priority in admissions to poor quality schools (because they are the local neighborhood school, perhaps) are typically parents of lower incomes. Since poor people tend to live in proximity to each other and have lower educational attainment, it might be that the quality of advice that poor parents receive in the matching program is of lower quality than those parents in richer neighborhoods. This better advice allows them to strategize better when engaging in the match and gives them an advantage. Better educational programs for parents in poor neighborhoods and better advice about the match may lead to more efficient matches. 6) Chatting increases the level of rationality amongst the parents in the sense that fewer of them submit irrational strategies after chatting than before. 7) Finally, when subjects receive advice from others who have engaged in the matching program before them and offer suggestions as to how to behave, the behavior of such subjects can vary dramatically from subjects who gain experience about the matching program by repeatedly engaging in it. In other words, intergenerational advice between generations of subjects engaging in the matching program can lead to a great variety of behavior some of which is beneficial but some detrimental to the welfare of parents. This project has generated two papers which are currently being submitted for publication: Intergenerational Advice and Matching: An Experimental Study (with Tingting Ding) Matching and Chatting: An Experimental Study of the Impact of Network Communication on School-Matching Mechanisms (with Tingting Ding)

Agency
National Science Foundation (NSF)
Institute
Division of Social and Economic Sciences (SES)
Type
Standard Grant (Standard)
Application #
1123045
Program Officer
Donald Hantula
Project Start
Project End
Budget Start
2011-09-15
Budget End
2014-08-31
Support Year
Fiscal Year
2011
Total Cost
$275,241
Indirect Cost
Name
New York University
Department
Type
DUNS #
City
New York
State
NY
Country
United States
Zip Code
10012