Examining Poverty and Anti-Social Behavior in the Lab (US)

Last registered on August 03, 2015


Trial Information

General Information

Examining Poverty and Anti-Social Behavior in the Lab (US)
Initial registration date
August 03, 2015

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
August 03, 2015, 1:59 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.


Primary Investigator

UC San Diego

Other Primary Investigator(s)

PI Affiliation
Busara Center for Behavioral Economics
PI Affiliation
Princeton University

Additional Trial Information

Start date
End date
Secondary IDs
This paper describes the analysis plan for a randomized experiment examining the effect of poverty on anti-sociality. This study aims to identify the extent to which poverty, through individual cognition and decision making, can influence behavior typically classified as anti-social (dishonesty, aggression, etc.). We simulate poverty in the lab by inducing a priming effect which makes salient psychological states as- sociated with poverty. We observe anti-social behavior with a battery of tasks and questionnaires selected to obtain a broad measure of anti-sociality. We conducted this experiment with a sample of 120 respondents from the city of Trenton, NJ and its sur- rounding communities. This plan outlines our outcomes of interest and econometric approach.
External Link(s)

Registration Citation

Abraham, Justin, Johannes Haushofer and Jeremy Shapiro. 2015. "Examining Poverty and Anti-Social Behavior in the Lab (US)." AEA RCT Registry. August 03. https://doi.org/10.1257/rct.795-1.0
Former Citation
Abraham, Justin, Johannes Haushofer and Jeremy Shapiro. 2015. "Examining Poverty and Anti-Social Behavior in the Lab (US)." AEA RCT Registry. August 03. https://www.socialscienceregistry.org/trials/795/history/4899
Experimental Details


Our study utilizes a methodology developed by Mani et al. (2013) and adapted to our sample to identify the psychological effect of poverty on anti-social behavior in the lab. We presented three hypothetical scenarios to the respondents, which describe a financial problem they might experience. The primes are described in detail in the appendix. Respondents are given 5 minutes per scenario to contemplate about how they might deal with these problems. These scenarios, by touching on financial issues, act as primes that trigger thoughts of the respondent’s own economic situation.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)

Poverty primes (randomly assigned treatment) Cantril Self-Anchoring Ladder
(a) Current life
(b) Life five years from now
Ring Task
Noise Aversion Task
Coin Toss Game
Maudsley Violence Questionnaire
Buss-Perry Aggression Questionnaire (Short) Demographics Questionnaire
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our main specification of interest is the OLS analogue to the analysis conducted in Mani et al. (2013):
yi =β0 +β1Ti +β2Richi +β3(Ti ×Richi)+εi (1)
We collect detailed asset ownership information from our respondents and use this information to construct an objective measure of wealth. We construct a weighted asset index and define the dummy variable Richi = 1 if the respondent is above the median of this index. We construct a weighted asset ownership index following the procedure in Anderson (2008). In addition, we will run a basic treatment effects specification to capture the impact of treatment relative to control:
yi = β0 + β1Ti + εi (2)
where yi is the outcome of interest for respondent i. Ti is a treatment indicator that takes the value 1 for respondents that received the “difficult” financial scenario and 0 for those with the “easy” scenario. εiht is the idiosynratic error term, which we assume is serially uncorrelated. Thus, β1 estimates the treatment effect of the poverty prime on each outcome. We are also interested in the treatment effect as it varies across gender. To examine heterogeneous effects, we estimate the following model:
yi = β0 + β1Ti + β2Femalei + β3(Ti × Femalei) + εi (3) Femalei is an indicator for respondent gender that takes the value 1 for females. Therefore,
β3 estimates the differential effect of the treatment for females compared to males.
Experimental Design Details
Randomization Method
Computerized randomization
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
60 treatment, 60 control
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Princeton University Institutional Review Board
IRB Approval Date
IRB Approval Number
Analysis Plan

Analysis Plan Documents

Analysis Plan


Post Trial Information

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials