The importance of sampling frequency for estimates of well-being dynamics

Stephen Hoskins (), David Johnston, Johannes S. Kunz (), Michael Shields and Kevin Staub
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Stephen Hoskins: Center for Research on Successful Ageing, Singapore Management University
Johannes S. Kunz: Monash University

No 2024-05, Working Papers from Centre for Health Economics, Monash University

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 het- erogeneity 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; dynamic panel data; adaptation; panel autoregression (search for similar items in EconPapers)
JEL-codes: I10 I30 I31 (search for similar items in EconPapers)
Date: 2024-04
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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