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Public Goods, Private Goods, and Families’ School Preferences
Initial registration date
June 10, 2020
June 11, 2020 8:55 AM EDT
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Other Primary Investigator(s)
Additional Trial Information
Public education generates benefits that accrue both to the individual and to the community as a whole. By preparing students to compete for jobs and social positions, education acts as a private good with benefits that are enjoyed individually. By producing citizens and workers who strengthen our democracy and economy, education also acts a public good with benefits enjoyed by everyone in a society. This study asks how the framing of these benefits—education as a private good, a public good, or a combination of both—affect individuals' preferences for various school characteristics. If people think of education primarily as a private good, will they be willing to travel further for a school with higher academic performance? If people think of education primarily as a public good, will they place greater weight on racial/ethnic and economic diversity? How does thinking of education as a mixed public and private good affect school choices? We explore these questions by conducting a survey experiment using the Harvard Digital Lab for the Social Sciences (DLABSS). In the survey, participants are randomly assigned statements that depict education as a public, private, or mixed good. They then select their preferred schools from a series of head-to-head conjoint experiments in which the schools’ characteristics vary randomly. This research design allows us to identify the effects of these priming statements on participants’ school selections and the school characteristics that they prefer.
We use three different primes, each of which describes the primary purpose of education differently. One conceptualization characterizes the purpose of education as being about maintaining and strengthening democracy. Another sees the purpose of education as being about social mobility, and the third describes the purpose of education as being for the creation of productive workers that can grow our economy. Our intervention is to prime respondents with one or multiple of these conceptualizations to see if it impacts the factors they value when choosing a school.
Intervention Start Date
Intervention End Date
Primary Outcomes (end points)
Our outcomes are the elementary school characteristics that participants choose. The information for these outcomes is gathered via a conjoint experiment. We are interested in seeing if the intervention influences what school characteristics respondents choose in head-to-head school selection match-ups.
Primary Outcomes (explanation)
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
We prime respondents with one of three statements about the purpose of education. One articulates a democratic equality purpose, another lays out a social mobility purpose, and the third lays out a social efficiency purpose. Which prime respondents receive will be randomized. Respondents will then receive information about two different hypothetical schools and be asked to choose one. This is the conjoint experiment. The attributes of the schools, like its test scores, distance, racial composition, and wealth, will be randomized, and will be displayed to look like the kind of information parents see on websites like GreatSchools.com. Respondents will have to choose a school three times (they will view three head-to-head match-ups). Then, they will again receive the same prime as before, but this time, some respondents will also receive a second prime. For example, respondents receiving the democratic equality prime the first time would receive both the democratic equality and social mobility primes the second time. Respondents will then be asked to select a school from three head-to-head match-ups where the attributes are randomized. The first conjoint will allow us to see if the individual primes impact the schools selected by respondents. The second conjoint will allow us to see if the combination of primes makes a difference in school selection.
Experimental Design Details
Randomization done by qualtrics survey software.
Was the treatment clustered?
Sample size: planned number of clusters
Sample size: planned number of observations
approximately 1,500 participants
Sample size (or number of clusters) by treatment arms
Our experiment will consist of four randomly assigned groups of approximately 375 participants per group.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Minimum Detectable Effect Size for Main Outcomes: Under conservative assumptions, we will be able to detect effect sizes of 0.2 standard deviations at 80% power (alpha = 0.05).
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Approval Date
IRB Approval Number