Dataset for the paper "Preferences after pan(dem)ics: Time and risk in the shadow of COVID-19" (2023)
Data creators :
Xavier Gassmann [1],
Antoine Malézieux [1],
Eli Spiegelman [1],
Jean-Christian Tisserand [1]
[1] : Centre de recherche sur les entreprises (Burgundy School of Business)
Description :
Dataset from incentive-compatible tasks used to simultaneously estimate risk and ambiguity aversion, time discounting, present bias, and prudence parameters before, during, and after the COVID-19 lockdown in France. The aim of the study was to use the COVID-19 health crisis to study how individual preferences respond to generalized traumatic events.
Discipline :
economics (social sciences)
Keywords :
General metadata
Data acquisition date :
from 1 May 2020 to 17 Sep 2020
Data acquisition methods :
- Experimental data : Pre-COVID-19 survey
The basic design uses the data from the BRISKEE project (Schleich et al.,2019) as a baseline for the different risk and uncertainty attitudes we measure. This original dataset, collected by Ipsos GmbH between July and August, 2016, included more than 15,000 subjects selected from major European countries using quota sampling to be demographically representative of each country. Because of the limited demographics of the new data target population, we kept only a subsample of the original BRISKEE data: the 128 French students between 18 and 25 years of age (hereafter Pre-COVID-19).
Waves during and after the pandemic
We adapted the Schleich et al. (2019) design to a Qualtrics questionnaire, using the same incentive-compatible tasks and payment levels. The experiment was distributed online to students at the Burgundy School of Business. We collected a total of 595 student responses in 3 different waves: one during Lockdown (01/05/2020), one just Post-Lockdown (17/05/2020 to 18/05/2020) and one 4 months Later (11/09/2020 to 17/09/2020).
Our questionnaire had five main sections. The first four were incentivized, using standard tools to measure (1) time preference and present bias; (2) risk aversion; (3) ambiguity aversion; and (4) prudence.3 The last section included non-incentivized questions on risk attitudes, patience, locus of control, demographics and experience in the COVID-19 pandemic. The incentive scheme was constrained to match the baseline incentives used in the BRISKEE project, as those data were used as our pre-pandemic reference point; see Schleich et al. (2019) for more details of the original design. The value of each incentivized choice was between €0 and €222. Subjects were told that they had a one in 100 chance of being selected to have one of their choices paid, in addition to a fixed, €3 participation fee. In the end, 5 out of 595 subjects were randomly drawn for payment, winning a total of €165. All incentivized questions were presented in a fixed sequence using the Multiple Price List format. In addition to sociodemographic questions such as age, gender, field of study, city of current residence, and country of origin, we collected several non-incentivized psychometric controls. First, we include a series of attitude questions. We also included a 13-item measure (not in the Pre-COVID-19) of locus of control (Rotter, 1966). Last, the survey included several optional questions about the subject’s direct experience with COVID-19. Finally, we controlled for the subjects’ perception of normality.
This finished the questionnaire. Subjects were then informed that the computer had randomly generated a number between 1 and 100, and were asked to also choose a number in the same range. If the numbers were the same, the computer would then select one of the incentivized questions randomly, and pay out the amount chosen, subject to the rules of the selected question.
Schleich, J., Gassmann, X., Meissner, T., & Faure, C. (2019). A large-scale test of the effects of time discounting, risk aversion, loss aversion, and present bias on household adoption of energy-efficient technologies. Energy Economics, 80, 377–393.
Rotter, J.B. (1966). Generalized expectancies for internal versus external control of reinforcement. Psychological Monographs, 80(1), 1–28.
Formats :
application/x-stata-do, application/x-stata-dta
Audience :
Research
Publications :
- Preferences after pan(dem)ics: Time and risk in the shadow of COVID-19 (doi:10.1017/S1930297500008925)
Data
2 files | |||
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Dataset_FinalRiskCovid2402.dtaPublished : 22/01/2025 16:03 Size : 2.70 MB
Description : Dataset for the paper "Preferences after pan(dem)ics: Time and risk in the shadow of COVID-19". Stata-backed data file developed by StataCorp LLC (.dta)
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Do_file_PAPFinal2024-02-22.doPublished : 22/01/2025 16:06 Size : 33.83 kB
Description : Code used to generate the results in the paper "Preferences after pan(dem)ics: Time and risk in the shadow of COVID-19"
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DOI and links
10.25666/DATAUBFC-2025-01-22
https://dx.doi.org/doi:10.25666/DATAUBFC-2025-01-22
https://search-data.ubfc.fr/FR-13002091000019-2025-01-22
Quotation
Xavier Gassmann, Antoine Malézieux, Eli Spiegelman, Jean-Christian Tisserand (2023): Dataset for the paper "Preferences after pan(dem)ics: Time and risk in the shadow of COVID-19". dataUBFC. doi:10.25666/DATAUBFC-2025-01-22
Record created 22 Jan 2025 by Cécile Schweitzer.
Last modification : 24 Jan 2025.
Local identifier: FR-13002091000019-2025-01-22.