Replication data for: What Goes Up Must Come Down? Experimental Evidence on Intuitive Forecasting

Principal Investigator(s): View help for Principal Investigator(s) John Beshears; James J. Choi; Andreas Fuster; David Laibson; Brigitte C. Madrian

Version: View help for Version V1

Name	File Type	Size	Last Modified
Feedback.xls	application/vnd.ms-excel	28 KB	10/11/2019 02:35:PM
HS10.xls	application/vnd.ms-excel	914.5 KB	10/11/2019 02:36:PM
HS10_estimates.csv	text/plain	335 bytes	10/11/2019 02:35:PM
HS50.xls	application/vnd.ms-excel	2.9 MB	10/11/2019 02:36:PM
HS50_estimates.csv	text/plain	10 KB	10/11/2019 02:35:PM
LICENSE.txt	text/plain	14.6 KB	10/11/2019 02:36:PM
README.pdf	application/pdf	138.1 KB	10/11/2019 02:36:PM
processCoefficients.xlsx	application/vnd.openxmlformats-officedocument.spreadsheetml.sheet	9.3 KB	10/11/2019 02:36:PM
samplePlots.xlsx	application/vnd.openxmlformats-officedocument.spreadsheetml.sheet	1.7 MB	10/11/2019 02:36:PM
subjxs.csv	text/plain	66 MB	10/11/2019 02:36:PM

Project Citation:

Beshears, John, Choi, James J., Fuster, Andreas, Laibson, David, and Madrian, Brigitte C. Replication data for: What Goes Up Must Come Down? Experimental Evidence on Intuitive Forecasting. Nashville, TN: American Economic Association [publisher], 2013. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-10-11. https://doi.org/10.3886/E112636V1

Project Description

Summary: Do laboratory subjects correctly perceive the dynamics of a mean-reverting time series? In our experiment, subjects receive historical data and make forecasts at different horizons. The time series process that we use features short-run momentum and long-run partial mean reversion. Half of the subjects see a version of this process in which the momentum and partial mean reversion unfold over ten periods ("fast"), while the other subjects see a version with dynamics that unfold over 50 periods ("slow"). Typical subjects recognize most of the mean reversion of the fast process and none of the mean reversion of the slow process.

Scope of Project

JEL Classification:
C53 Forecasting Models; Simulation Methods
D84 Expectations; Speculations

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Published Versions

V1 [2019-10-11]

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