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Field
Trial Status
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Before
in_development
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After
on_going
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Abstract
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Before
Economic decisions and productivity suffer when cognitive resources are limited. Recent papers have shown, for example, that productivity is reduced when poverty consumes mental resources (Kaur et al. 2023). We test whether political constraints impact economic outcomes through similar channels. In particular, we experimentally examine whether a minority’s uncertainty about their status within a nation generates psychological effects comparable to those generated by financial concerns. We test this with a labour market experiment in West Bengal. Workers complete data-processing tasks and we randomize incidental exposure to two types of exclusionary policies—policies that pose a direct, material threat and policies that pose a more symbolic threat. We test whether exposure to both types of policy affects productivity and cognitive outcomes.
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After
Economic decisions and productivity suffer when cognitive resources are limited. Recent papers have shown, for example, that productivity is reduced when poverty consumes mental resources (Kaur et al. 2023). We test whether political constraints impact economic outcomes through similar channels. In particular, we experimentally examine whether a minority’s uncertainty about their status within a nation generates psychological effects comparable to those generated by financial concerns. We test this with a labour market experiment in West Benga and online throughout India. Workers complete data-processing tasks and we randomize incidental exposure to two types of exclusionary policies—policies that pose a direct, material threat and policies that pose a more symbolic threat. We test whether exposure to both types of policy affects productivity and cognitive outcomes.
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Trial End Date
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Before
March 31, 2024
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After
August 31, 2024
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Last Published
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Before
December 21, 2023 08:02 AM
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After
July 15, 2024 06:43 AM
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Intervention End Date
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Before
February 29, 2024
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After
July 31, 2024
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Experimental Design (Public)
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Before
We invite workers in West Bengal to complete data-processing tasks. We randomize whether they are incidentally exposed to one of two types of exclusionary policies—policies that pose a direct, material threat and policies that pose a more symbolic threat. The control group is only exposed to anodyne policies—for example, new regulations about registering pet dogs. We test whether exposure to both types of policy affects productivity and cognitive outcomes.
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After
We invite workers in West Bengal to complete data-processing tasks. We randomize whether they are incidentally exposed to one of two types of exclusionary policies—policies that pose a direct, material threat and policies that pose a more symbolic threat. The control group is only exposed to anodyne policies—for example, new regulations about registering pet dogs. We test whether exposure to both types of policy affects productivity and cognitive outcomes.
We will do a second round of data collection completely online. The online experiment will largely follow the same protocol as the in-person study.
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Field
Planned Number of Observations
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Before
750 Muslim individuals and 750 Hindu individuals
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After
750 Muslim individuals and 750 Hindu individuals in person
1000 Muslim individuals and 1000 Hindu individuals online
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Field
Sample size (or number of clusters) by treatment arms
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Before
375 individuals will see the symbolic policies; 375 will see the mixed (material + symbolic) policies and 750 will see the control policies.
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After
In person: 375 individuals will see the symbolic policies; 375 will see the mixed (material + symbolic) policies and 750 will see the control policies.
Online: Approximately 650 individuals will see each type of policy (symbolic, mixed, control)
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Field
Intervention (Hidden)
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Before
We hire approximately 1500 Indians in West Bengal to work on basic data entry and information processing tasks. Workers are hired for half a day and work on tasks such as tagging the sentiment in Tweets or transcribing text from subtitles embedded in photos. The tagged Tweets and transcriptions are stored in a database that will be used by researchers in a separate project exploring human-machine interactions. We randomize whether workers encounter content that mentions exclusionary policies. This content is embedded in the Tweets as each Tweet contains a retweet of a news story about government policies. Thus we have two treatment arms and one control arm. In the symbolic treatment arm, majority of the Tweets that are tagged refer to news stories about policies that symbolically exclude minorities. In the material treatment arm, majority of the Tweets refer to news stories about policies that materially exclude minorities. In the control group, all Tweets refer to anodyne policies that do not mention national identity or religion—for example, new regulations about registering pet dogs. Our study investigates two main outcomes. We measure how exposure to exclusionary policies affects productivity on the unrelated transcription task. We also give workers the opportunity to select one of two payment contracts—either a piece rate for each transcription that turns out to be accurate or a contract based on bonuses for being amongst the best performers in a group. We measure how exposure to exclusionary policies changes the probability of choosing the “wrong” contract in terms of earnings (the top performing workers should choose the bonus while everyone else should choose the piece rate). Our main outcomes are accompanied by tests of cognitively demanding tasks (Raven’s Matrices and a numerical Stroop task) drawn from the psychology literature. These allow us to establish whether the treatments increase cognitive load as hypothesised.
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After
We hire approximately 1500 Indians in West Bengal to work on basic data entry and information processing tasks. Workers are hired for half a day and work on tasks such as tagging the sentiment in Tweets or transcribing text from subtitles embedded in photos. The tagged Tweets and transcriptions are stored in a database that will be used by researchers in a separate project exploring human-machine interactions. We randomize whether workers encounter content that mentions exclusionary policies. This content is embedded in the Tweets as each Tweet contains a retweet of a news story about government policies. Thus we have two treatment arms and one control arm. In the symbolic treatment arm, majority of the Tweets that are tagged refer to news stories about policies that symbolically exclude minorities. In the material treatment arm, majority of the Tweets refer to news stories about policies that materially exclude minorities. In the control group, all Tweets refer to anodyne policies that do not mention national identity or religion—for example, new regulations about registering pet dogs. Our study investigates two main outcomes. We measure how exposure to exclusionary policies affects productivity on the unrelated transcription task. We also give workers the opportunity to select one of two payment contracts—either a piece rate for each transcription that turns out to be accurate or a contract based on bonuses for being amongst the best performers in a group. We measure how exposure to exclusionary policies changes the probability of choosing the “wrong” contract in terms of earnings (the top performing workers should choose the bonus while everyone else should choose the piece rate). Our main outcomes are accompanied by tests of cognitively demanding tasks (Raven’s Matrices and a numerical Stroop task) drawn from the psychology literature. These allow us to establish whether the treatments increase cognitive load as hypothesised.
We will do a second round of data collection completely online. The online experiment will largely follow the same protocol as the in-person study. Our main outcome variable will remain the same as above. We will use numerical Stroop task and emotional Stroop task to uncover the underlying mechanisms.
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