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Field
Experimental Design (Public)
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Before
The study uses a two-part online experimental design. In Part 1, participants are randomly assigned to one of three groups, each of which views the same sequence of numerical data generated from a stationary AR(1) process, with observations presented one at a time. The data-generating process differs across groups. After viewing the data sequence, participants provide assessments related to the process, including estimates of the underlying mean, as well as measures of recall of realized values.
Participants observe 20 numerical realizations from a stationary AR(1) process and displayed sequentially on separate screens. Participants are randomly assigned to one of three groups that vary the persistence and volatility of the underlying process.\footnote{These three series share an identical mean of 5 but differ in volatility.} Group~1 observes data generated from a low-persistence, low-volatility process $(\rho=0.1,\sigma=0.5)$. Group~2 observes data generated from a high-persistence, low-volatility process $(\rho=0.9,\sigma=0.5)$. Group~3 observes data generated from a high-persistence, high-volatility process $(\rho=0.9,\sigma=5)$. In all groups, the long-run mean of the process is fixed $(\mu=5)$ and unknown to participants. After viewing the sequence, participants are directed to some unrelated tasks. Afterward, they report their best estimate of the series average, with accuracy incentives, and then complete a free recall task in which they list any values they remember freely. This design mirrors the theoretical environment in which agents observe a common realized history but form beliefs based on stochastic recall.
Part 2 of the study is conducted approximately one day after Part 1. Participants are recontacted and asked a follow-up set of questions related to the same data sequence, including repeated belief elicitation about the mean of the process and recall of the previously presented values.
The experimental design allows for comparisons of beliefs and recall across participants exposed to the same data sequence and within individuals across the two parts of the study.
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After
The study uses a two-part online experimental design. In Part 1, participants are randomly assigned to one of three groups, each of which views the same sequence of numerical data generated from a stationary AR(1) process, with observations presented one at a time. The data-generating process differs across groups. After viewing the data sequence, participants provide assessments related to the process, including estimates of the underlying mean, as well as measures of recall of realized values.
Participants observe 20 numerical realizations from a stationary AR(1) process and displayed sequentially on separate screens. Participants are randomly assigned to one of three groups that vary the persistence and volatility of the underlying process. Group 1 observes a low-persistence, low-noise process and serves as the control condition. Group 2 observes a high-persistence, low-noise process Group 3 observes a high-persistence, high-noise process. In all groups, the long-run mean of the process is fixed at 5 and unknown to participants. After viewing the sequence, participants are directed to some unrelated tasks. Afterward, they report their best estimate of the series average, with accuracy incentives, and then complete a free recall task in which they list any values they remember freely. This design mirrors the theoretical environment in which agents observe a common realized history but form beliefs based on stochastic recall.
Part 2 of the study is conducted approximately one day after Part 1. Participants are recontacted and asked a follow-up set of questions related to the same data sequence, including repeated belief elicitation about the mean of the process and recall of the previously presented values.
The experimental design allows for comparisons of beliefs and recall across participants exposed to the same data sequence and within individuals across the two parts of the study.
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