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Precautionary saving and old-age provisions: Do subjective saving motive measures work?

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  • Lothar Essig

    (Munich Center for the Economics of Aging (MEA))

Abstract

literature on precautionary saving provides contradictory views on the importance of precautionary saving. The SAVE data offer the possibility to generate some of the frequently used instruments known from the literature in order to measure the extent of precautionary savings. This paper compares the influence of these instruments on long-run and short-run saving measures. In addition, SAVE contains information on a broad range of saving motives. This paper uses these short-run and long-run savings motives to describe differences in savings, saving rates and wealth accumulation.

Suggested Citation

  • Lothar Essig, 2005. "Precautionary saving and old-age provisions: Do subjective saving motive measures work?," MEA discussion paper series 05084, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
  • Handle: RePEc:mea:meawpa:05084
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    Cited by:

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    2. Nikolaus Bartzsch, 2006. "Vorsichtssparen und Einkommensunsicherheit privater Haushalte in Deutschland: eine ökonometrische Untersuchung auf Basis von SOEP-Daten," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 75(4), pages 109-120.
    3. Najat El Mekkaoui de Freitas & Bérangère Legendre, 2014. "Constitution d’un revenu complémentaire de retraite : quels sont les facteurs déterminants?," Économie et Statistique, Programme National Persée, vol. 472(1), pages 153-167.
    4. Johannes Geyer, 2011. "The Effect of Health and Employment Risks on Precautionary Savings," SOEPpapers on Multidisciplinary Panel Data Research 408, DIW Berlin, The German Socio-Economic Panel (SOEP).
    5. Frank M. Fossen & Davud Rostam-Afschar, 2013. "Precautionary and Entrepreneurial Savings: New Evidence from German Households," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(4), pages 528-555, August.

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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