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Can Survey Participation Alter Household Saving Behaviour?
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Can Survey Participation Alter Household Saving Behaviour?

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  • Thomas F. Crossley
  • Jochem Bresser
  • Liam Delaney
  • Joachim Winter

Abstract

Much empirical research in economics is based on data from household surveys. Panel surveys are particularly valuable for understanding dynamics and heterogeneity. A possible concern with panel surveys is that survey participation itself may alter subsequent behavior. We provide novel evidence of survey effects on a central life-cycle choice: household saving. We exploit randomized assignment to survey modules within the LISS Panel, an internet panel survey which is representative of the Dutch population. We find that households that respond to detailed questions on expenditures and needs in retirement reduced their non-housing saving rate by 3.5 percentage points, on average. This mean effect is driven by high-education households which have the highest pension and housing wealth. Our saving measure is based on linked administrative wealth data. Thus we can rule out the possibility that the effect is on reporting, rather than on the underlying saving behavior. One interpretation is that the survey acted as a salience shock, possibly with respect to reduced housing costs in retirement.
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  • Thomas F. Crossley & Jochem Bresser & Liam Delaney & Joachim Winter, 2017. "Can Survey Participation Alter Household Saving Behaviour?," Economic Journal, Royal Economic Society, vol. 127(606), pages 2332-2357, November.
    • Handle: RePEc:wly:econjl:v:127:y:2017:i:606:p:2332-2357
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    File URL: http://hdl.handle.net/10.1111/ecoj.2017.127.issue-606
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    1. Liran Einav & Jonathan Levin, 2014. "The Data Revolution and Economic Analysis," Innovation Policy and the Economy, University of Chicago Press, vol. 14(1), pages 1-24.
    2. Kremer, Michael R. & Karlan, D. S. & Hornbeck, Richard A. & Gine, X. & Duflo, E. & Pariente, W. & Null, C. & Miguel, E. & Devoto, F. & Crepon, B. & Banerjee, A. & Zwane, A. P. & Zinman, J. & Van Dusen, 2011. "Being Surveyed Can Change Later Behavior and Related Parameter Estimates," Scholarly Articles 11339433, Harvard University Department of Economics.
    3. Esther Duflo & William Gale & Jeffrey Liebman & Peter Orszag & Emmanuel Saez, 2006. "Saving Incentives for Low- and Middle-Income Families: Evidence from a Field Experiment with H&R Block," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(4), pages 1311-1346.
    4. Binswanger, Johannes & Schunk, Daniel, 2012. "What is an adequate standard of living during Retirement?," Journal of Pension Economics and Finance, Cambridge University Press, vol. 11(2), pages 203-222, April.
    5. de Bresser, Jochem & Knoef, Marike, 2015. "Can the Dutch meet their own retirement expenditure goals?," Labour Economics, Elsevier, vol. 34(C), pages 100-117.
    6. Marcel Das & Vera Toepoel & Arthur van Soest, 2011. "Nonparametric Tests of Panel Conditioning and Attrition Bias in Panel Surveys," Sociological Methods & Research, , vol. 40(1), pages 32-56, February.
    7. Markus Frölich & Blaise Melly, 2013. "Unconditional Quantile Treatment Effects Under Endogeneity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 346-357, July.
    8. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843, Elsevier.
    9. J.J. Heckman & E.E. Leamer (ed.), 2001. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 5, number 5.
    10. Fitzsimons, Gavan J & Shiv, Baba, 2001. "Nonconscious and Contaminative Effects of Hypothetical Questions on Subsequent Decision Making," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(2), pages 224-238, September.
    11. Stefano DellaVigna, 2009. "Psychology and Economics: Evidence from the Field," Journal of Economic Literature, American Economic Association, vol. 47(2), pages 315-372, June.
    12. Martin Browning & Thomas F. Crossley & Joachim Winter, 2014. "The Measurement of Household Consumption Expenditures," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 475-501, August.
    13. Morwitz, Vicki G & Johnson, Eric J & Schmittlein, David C, 1993. "Does Measuring Intent Change Behavior?," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(1), pages 46-61, June.
    14. Markus Frolich & Blaise Melly, 2010. "Estimation of quantile treatment effects with Stata," Stata Journal, StataCorp LP, vol. 10(3), pages 423-457, September.
    15. Bert Van Landeghem, 2012. "Panel Conditioning and Self-Reported Satisfaction: Evidence from International Panel Data and Repeated Cross-Sections," SOEPpapers on Multidisciplinary Panel Data Research 484, DIW Berlin, The German Socio-Economic Panel (SOEP).
    16. Martin Browning & Mette Gørtz & Søren Leth‐Petersen, 2013. "Housing Wealth and Consumption: A Micro Panel Study," Economic Journal, Royal Economic Society, vol. 0, pages 401-428, May.
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    Cited by:

    1. Pettinicchi, Yuri & Vellekoop, Nathanael, 2019. "Job loss expectations, durable consumption and household finances: Evidence from linked survey data," SAFE Working Paper Series 249, Leibniz Institute for Financial Research SAFE.
    2. Van Landeghem, Bert, 2019. "Stable traits but unstable measures? Identifying panel effects in self-reflective survey questions," Journal of Economic Psychology, Elsevier, vol. 72(C), pages 83-95.
    3. Bert Van Landeghem & Anneleen Vandeplas, 2016. "Lower in rank, but happier: the complex relationship between status and happiness," Working Papers of LICOS - Centre for Institutions and Economic Performance 556194, KU Leuven, Faculty of Economics and Business (FEB), LICOS - Centre for Institutions and Economic Performance.
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    5. Martin Browning & Thomas F. Crossley & Joachim Winter, 2014. "The Measurement of Household Consumption Expenditures," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 475-501, August.
    6. Yi Fan & Diana M. Weinhold, 2022. "Urban noise, sleep disruption and health," Applied Economics, Taylor & Francis Journals, vol. 54(50), pages 5782-5799, October.

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    More about this item

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance

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