Poverty and Social Capital

Last registered on August 16, 2015

Pre-Trial

Trial Information

General Information

Title
Poverty and Social Capital
RCT ID
AEARCTR-0000813
Initial registration date
August 15, 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 15, 2015, 9:34 AM EDT

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

Last updated
August 16, 2015, 10:37 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation
University of Warwick

Other Primary Investigator(s)

PI Affiliation
Princeton University
PI Affiliation
University of Oxford

Additional Trial Information

Status
Completed
Start date
2015-08-15
End date
2015-08-16
Secondary IDs
Abstract
This document describes the analysis plan for a randomized experiment examining the psychological effects of poverty on cooperation, trust, negative reciprocity and altruistic punishment. We will recruit respondents from Amazon Mechanical Turk. We will run two separate experiments in which we expose our treatment group to a prime that triggers feelings of poverty Mani et al. (2013). In each experiment we recruit 972 participants. In the first experiment we examine the effect of poverty primes on behavior in a public goods game and the behavior of a first mover in a trust game. In the second experiment we explore the consequences of feeling poor on the behavior of the second mover in a ultimatum game and on the behavior of the punisher in a third-party punishment game. This plan outlines the design of the experiments, the outcomes of interest, the econometric approach and the dimensions of heterogeneity we intend to explore.
External Link(s)

Registration Citation

Citation
Grigorieff, Alexis, Johannes Haushofer and Christopher Roth. 2015. "Poverty and Social Capital." AEA RCT Registry. August 16. https://doi.org/10.1257/rct.813-2.0
Former Citation
Grigorieff, Alexis, Johannes Haushofer and Christopher Roth. 2015. "Poverty and Social Capital." AEA RCT Registry. August 16. https://www.socialscienceregistry.org/trials/813/history/5006
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2015-08-15
Intervention End Date
2015-08-16

Primary Outcomes

Primary Outcomes (end points)

Public Goods Game: Each respondent will play a game with three other MTurkers. All players will start with $50 each. Then, every player will have the possibility of contributing some of their $50 to a project, without knowing the contributions of the other players. The sum of the contributions made by the four players will then be multiplied by two, and all of the money will then be split equally among all four players. Thus, a player's total payoff consists of two parts: 1) The part of the $50 that the player did not contribute to the project, 2) plus the payoff the player receives from the project, which is equal to 0.5 x (the sum of the contributions made by all four players).Therefore, each player's total payoff is:($50 - the player's contribution to the project) + 0.5 x (the sum of the contributions made by all four players to the project). Once everyone has completed the survey, we will randomly form groups of four MTurkers. We will choose one group at random, and implement the choices made by the four players in that group.
Mechanisms Public Goods game: Directly after specifying their contribution in the public goods game, our participants will be asked various questions ecliciting beliefs about others' likely contributions, their fairness concerns and their understanding: How much money do you think the other players will contribute to the project on average? (Players are told that they receive 5 cents of they guess the other player's contributions correctly)
Imagine that each of the other three players contributed $25 to the project. How much money would you contribute to the project in that case?
Imagine that, of the other three players, one contributes $0, one contributes $25 and one contributes $50. How much money would you contribute to the project in that case? Please click on the slider to choose the amount.
Imagine that you wanted to earn as much money as possible from this game. How much money should you then contribute to the project? If you give the correct answer, you will receive an extra 5 cents.

Trust: We will ask our respondents to complete a game in which there are two players, whom we shall refer to as person A and person B. All of our respondent's (except for one) will play the role of person A. Person A and person B start with $50 each. Then, person A can choose to send some money to person B. Person B will receive 3 times the amount sent by person A. Then person B will have to choose how much money to send back to person A. Once everyone has completed the survey, we will randomly choose one participant in our survey who played the role of A to get their choice implemented and we will randomly choose one participant to play the role of B and get their choice implemented.
Mechanisms Trust Game: After completing the trust game:

Our respondent's will be asked the following question:
"What amount do you think will Person B send back to you?"

Third Party Punishment:
There are three players in this game: Player A, Player B and Player C. Our respondents will play the role of player C. All three players start with $100 each. This game has two stages. Stage 1: In this stage, Player A is the only one who has a decision to make. At the beginning of this stage, Player A receives an extra $100, which he or she can share with Player B. In particular, Player A can give either $0, $10, $20, $30, $40 or $50 to Player B. Stage 2: In this stage, Player C is the only one who has a decision to make. At the beginning of this stage, Player C receives an extra $50.
Player C can use this extra $50 to reduce Player A's payoff, based on how much money Player A gave to Player B. For every $1 that Player C spends, Player A's payoff goes down by $2. We then ask our respondents how much money they want to spend to reduce Player A's payoff, for all of Player A's possible choices.
Mechanisms Third Party Punishment Game:
Costless punishment: We ask our respondents to consider again case where Person A doesn't give any money to Person B. But this time, imagine that Person C does not need to give up some of their $50 in order to reduce Person A's payoff.
Fairness concerns: Moreover, we shed light on our respondents' fairness concerns by asking them the following question: In order to be fair, how much money should Person A give to Person B? Please click on the slider to choose the appropriate offer?


Negative Reciprocity: We ask our respondents to complete a game in which there are two players, whom we shall refer to as person 1 and person 2. All of our respondent's (except for one) will play the role of person 2. At the beginning of this game, person 1 receives \$100, while person 2 receives nothing. Then, person 1 has to make an offer to person 2 on how to split the $100. Person 2 chooses either to accept the offer made by person 1, or to refuse it. If person 2 refuses the offer, both players receive nothing. If person 2 accepts the offer, each player receives the amount specified in the offer. Then our respondents specify the minimum amount that person 1 would have to offer them, in order for them to accept their offer? Once everyone has completed the survey, we will randomly choose one participant in our survey who played the role of person 2 to get their choice implemented and we will randomly choose one participant to play the role of person 1 and get their choice implemented.
Mechanism Negative Reciprocity: After completing the ultimatum game, we ask the second mover the following question:
In order to be fair, what offer should person 1 make to person 2?
Cognitive Function: Raven’s Progressive Matrices: This task measures fluid intelligence. Each trial consists of a 3x3 matrix of figures, with the bottom right figure missing.
Respondents are asked to choose the correct figure, from a set of 8 candidate figures, which best completes the overall pattern of the matrix. Respondents must complete five matrices without any time limits. They receive a payoff of 5 cents for each correct answer. In this task, we measure the number of correct answers and reaction time. Risk-preferences: In addition, we include a standard risk-preference measure in which individuals choose one out of six lotteries with different levels of risk Eckel and Grossman (2003)


Financial worries scale: This 3-item questionnaire provides an addition manipulation check for our poverty primes. We ask respondents to self-report on a Likert scale how worried they are about their financial situation.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design

We have adapted the poverty primes by Mani et al. (2013) to the MTurk environment. As in \cite{mani2013}, we present our respondents with hypothetical scenarios, each of which describes a financial problem. We randomly assign our respondents to either a hard or an easy financial scenario.

In the first financial scenario they need to explain how they would deal with an income decrease of 20% (5%) in the hard (easy) financial scenario. We then ask them a variety of questions on whether this income shock would substantially affect their situation and what kind of sacrifices they would need to make. In the second scenario people explain how they would deal with a situation in which they need to come up with an amount of money: In the hard (easy) financial scenario respondents are asked how they would come up with $3000 ($150) in a short notice. The order with which these financial scenarios is presented is randomized. Respondents write down how they might deal with the financial scenarios. The aim of exposure to these scenarios is to trigger feelings of poverty.

We have made two main changes to the primes used by Mani et al. (2013): first, we increased the amounts for the hard financial scenarios. Second, we removed two financial scenarios because they did not seem well-suited for the MTurk population. We have conducted a pilot study with a sample of 350 participants on August 1st in which we document that our two primes successfully affect financial worries. In particular, poorer individuals from our sample are quite strongly affected by our treatment: They display substantially stronger financial worries. The primes are further explained in Appendix A. Moreover, at the very end of the document we attach the exact experimental instructions.
Experimental Design Details
Randomization Method
Randomization is done by a computer.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
972 individuals
Sample size: planned number of observations
972 individuals
Sample size (or number of clusters) by treatment arms
486 in the treatment group.
486 in the control group.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The chosen sample size of 972 participants for each of the two experiments ensures that we can detect an effect size of about 0.18 at a significance level of 0.05 with a power of 0.8.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Princeton Institutional Review Boeard
IRB Approval Date
2015-07-22
IRB Approval Number
6800
Analysis Plan

Analysis Plan Documents

Poverty and Social Capital PAP Revised

MD5: daafb5743d8860bd0850cb47b51b8551

SHA1: 5d7c1ab4078520a41583148739c5ae167654b947

Uploaded At: August 16, 2015

Poverty and Social Capital PAP

MD5: 3746fdaee1e9d0d3aa91bc9ae05c5250

SHA1: 7b2d9ace83cdfaa2f0ba184af9a4b81174d75e1f

Uploaded At: August 15, 2015

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials