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Occupy Wall Street and Financial Decision-Making
Last registered on December 06, 2019


Trial Information
General Information
Occupy Wall Street and Financial Decision-Making
Initial registration date
December 05, 2019
Last updated
December 06, 2019 10:23 AM EST
Primary Investigator
Boston College
Other Primary Investigator(s)
Additional Trial Information
Start date
End date
Secondary IDs
This RCT studies the effects of exposure to anti-finance rhetoric on individual choice under risk as well as the economic channels that might transmit any effects. Whether anti-finance rhetoric is a cultural byproduct of economic crises or whether it might in turn affect economic choices is an open and unexplored question, which can be barely tackled in the field due to the fact that anti-finance rhetoric arises in times of economic crises when other major aggregate and individual economic shocks affect decision-making. To answer this question, I recruit 400 subjects on a large US-based internet platform. I restrict the sample to users with a US tax identifier. The experimental condition consists of exposing subjects randomly to one of two experimental arms, i.e. a control arm and an anti-finance rhetoric arm. In the control arm, subjects read a text on a short introduction about the role of stock markets and their players, as well as the pros and cons of investing in stocks. In the anti-finance rhetoric arm, I replace ideologically neutral cues of the control text with anti-finance rhetoric cues typical of the Occupy Wall Street movement as studied in Applied Linguistics and Sociology. The aim of this intervention is to randomly manipulate the salience of anti-finance rhetoric. After the manipulation, subjects perform a set of investment choices under risk a la Gneezy and Potters (2009), lottery choice tasks a la Holt and Laury (2002), and answer a set of questions about their trust in a set of institutions, including the stock market and investment banks, among others.
External Link(s)
Registration Citation
D'Acunto, Francesco. 2019. "Occupy Wall Street and Financial Decision-Making." AEA RCT Registry. December 06. https://doi.org/10.1257/rct.5147-1.0.
Experimental Details
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
The experiment focuses on the following variables:
1. Extensive margin of investment under risk (choice whether to invest or not)
2. Intensive margin of investment under risk (choice of amounts invested, if any)
3. Number of certainty equivalent choices in Holt and Laury (2002) lotteries
4. Categorical elicitation of trust in 7 institutions
5. Categorical elicitation of ideological bias in the experimental test (debriefing)
6. Categorical elicitation of informational content of the experimental test (debriefing)
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
In the first stage, subjects answered four background questions including their country of residence, gender, age bracket (18-22, 23-35, 36-45, 46-60, 60+), and education bracket (high school or lower, some college, college degree or higher). Then, subjects were randomly assigned to one of the two experimental arms, and read the text associated with their experimental condition. Subjects had to complete each task in the experiment in full before proceeding, but they could leave the experiment at any time. After reading the text, subjects were asked a question as a manipulation check.

In the second part of the experiment, subjects made choices regarding incentivized risky financial investment opportunities a la Gneezy and Potters (1997). I explicitly framed the opportunities as investments in a company's stock. I gave each subject a virtual endowment of $100 at the beginning of each of three periods. Each period, subjects faced an opportunity and decided whether to invest any of their per-period endowment, and if so, how much. The first opportunity, which I label low-risk opportunity, succeeded with probability 1/2 and paid off 3 times the invested amount in case of success. The second opportunity, which I label negative expected-value (EV) opportunity, succeeded with probability 1/3 and paid off 2.5 times the invested amount. This opportunity has a negative EV because in expectations keeping the endowment intact and not investing any money in the opportunity would leave subjects with a higher expected payoff. The third opportunity, which I label high-risk opportunity, succeeded with probability 1/6 and paid off 8 times the invested amount. I presented the three opportunities to the subjects in random order.

In the third part of the experiment, I elicited subjects' risk tolerance. Subjects faced two screens of lottery choices (Holt and Laury, 2002). Each choice included a degenerate lottery paying a positive outcome for sure (certainty equivalent), and a lottery paying a positive outcome with probability 1/2, and 0 otherwise. The lottery choices were not framed as financial or investment opportunities. I did not consider the answers of 16 subjects, because they switched more than once in the lottery-choice task. The excluded subjects represent 4% of the overall sample. The elicitation of subjects' risk aversion was also incentive compatible, because subjects knew that one line at random in each screen would be picked, and their pay would be a scaled amount of the certainty equivalent, or of the results of the lottery, based on their choice.

In the last part of the experiment, I elicited subjects' trust toward a series of institutions, which included the stock market, investment banks, commercial banks, family and friends, IT companies, and the Supreme Court. I presented the institutions to subjects in random order..

Finally, after the experiment, to test for potential demand effects I explicitly asked subjects (i) if they thought the texts they read were ideologically biased, and (ii) if they thought the texts were biased against the stock market and investment banks. This task was incentivized---subjects had to guess the degree of bias in favor, bias against, or neutrality regarding the financial sector and knew they would be paid a bonus based on how close they were to the actual degree of bias a financial-market expert had determined separately at the end of the experiment.
Experimental Design Details
Randomization Method
Randomization is obtained through an algorithm that assigns subjects recruited on the online platform to one of the two experimental arms by running a lottery that with a 50% chance to deliver each of two numbers.
Randomization Unit
The unit of randomization is the individual
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
200 (control) and 200 (treated)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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Document Description
Treatment Text condition

MD5: a6dab9791d5b27ca8b2243f3cc0c7fc6

SHA1: 2454479074b7c9ee014d60c70b36c7bb80c524c6

Uploaded At: December 05, 2019

Document Name
Document Type
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Control Text

MD5: f74f61d94f296f901b4de003a3bd78fc

SHA1: f5b611762bf14ca17d229f6ed419a86ee0675d46

Uploaded At: December 05, 2019

IRB Name
University of Maryland College Park (UMCP) IRB
IRB Approval Date
IRB Approval Number
Post Trial Information
Study Withdrawal
Is the intervention completed?
Intervention Completion Date
October 25, 2017, 12:00 AM +00:00
Is data collection complete?
Data Collection Completion Date
October 25, 2017, 12:00 AM +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
Final Sample Size (or Number of Clusters) by Treatment Arms
199 treated individuals, 197 control individuals
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)