The Importance of Sampling Frequency for Estimates of Well-Being Dynamics

Stephen Hoskins, David Johnston, Johannes S. Kunz (), Michael A. Shields () and Kevin Staub
Additional contact information
Stephen Hoskins: Singapore Management University
Johannes S. Kunz: Monash University
Michael A. Shields: Monash University

No 17101, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Using a high-frequency panel survey, we examine the sensitivity of estimated self-reported well-being (SWB) dynamics to using monthly, quarterly, and yearly data. This is an important issue if SWB is to be used to evaluate policy. Results from autoregressive models that account for individual-level heterogeneity indicate that the estimated persistence using yearly data is near zero. However, estimated persistence from monthly and quarterly data is substantial. We estimate that persistence to shocks typically lasts around six months and has a net present value of 75-80 per cent of the contemporaneous effect. Estimates are similar for different domains of SWB.

Keywords: well-being; life satisfaction; happiness; dynamic panel data; panel autoregression; adaptation; persistence (search for similar items in EconPapers)
JEL-codes: I1 I3 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2024-06
New Economics Papers: this item is included in nep-hap and nep-sea
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Related works:
Journal Article: The importance of sampling frequency for estimates of well-being dynamics (2024)
Working Paper: The importance of sampling frequency for estimates of well-being dynamics (2024)
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