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The Timing of Daily Demand for Goods and Services – Multivariate Probit Estimates and Microsimulation Results for an Aged Population with German Time Use Diary Data

  • Merz, Joachim
  • Hanglberger, Dominik
  • Rucha, Rafael

Though consumption research provides a broad spectrum of theoretical and empirical founded results, studies based on a daily focus are missing. Knowledge about the individual timing of daily demand for goods and services, opens – beyond a genuine contribution to consumption research – interesting societal and macro economic as well as individual personal and firm perspectives: it is important for an efficient timely coordination of supply and demand in the timing perspective as well as for a targeted economic, social and societal policy for a better support of the every day coordination of life. Last not least, the individual daily public and private living situations will be visible, which are of particular importance for the social togetherness in family and society. Our study contributes to the timing of daily consumption for goods and services with an empirical founded microanalysis on the basis of more than 37.000 individual time use diaries of the nationwide Time Budget Survey of the German Federal Statistical Office 2001/02. We describe the individual timing of daily demand for goods and services for important socio-demographic groups like for women and men, the economic situation with income poverty and daily working hour arrangements. The multivariate microeconometric explanation of the daily demand for goods and services is based on a latent utility maximizing approach over a day. We estimate an eight equation Multivariate/Simultaneous Probit Model, which allows the decision for multiple consumption activities in more than one time period a day. The estimates quantify effects on the timing of daily demand by individual socio-economic variables, which encompasses, personal, household, regional characteristics as well as daily working hour arrangements within a flexible labour market. The question about individual effects of an aged society on the timing of daily demand for goods and services is analyzed with our microsimulation model ServSim and a population forecast for 2020 by the German Federal Statistical Office. Main result: There are significant differences in explaining the timing of daily demand for goods compared to services on the one hand and in particular for different daily time periods. The conclusion: without the timing aspects an important and significant dimension for understanding individual consumption behaviour and their impacts on other individual living conditions would be missing.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 16303.

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Date of creation: Mar 2009
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Handle: RePEc:pra:mprapa:16303
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  1. Joachim Merz, 2002. "Time Use Research and Time Use Data – Actual Topics and New Frontiers," FFB-Discussionpaper 32, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)), LEUPHANA University Lüneburg.
  2. Lorenzo Cappellari & Stephen P. Jenkins, 2003. "Multivariate probit regression using simulated maximum likelihood," Stata Journal, StataCorp LP, vol. 3(3), pages 278-294, September.
  3. Gronau, Reuben, 1987. "Home production -- A survey," Handbook of Labor Economics, in: O. Ashenfelter & R. Layard (ed.), Handbook of Labor Economics, edition 1, volume 1, chapter 4, pages 273-304 Elsevier.
  4. Joachim Merz, 1994. "Microdata Adjustment by the Minimum Information Loss Principle," FFB-Discussionpaper 10, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)), LEUPHANA University Lüneburg.
  5. Pencavel, John, 1987. "Labor supply of men: A survey," Handbook of Labor Economics, in: O. Ashenfelter & R. Layard (ed.), Handbook of Labor Economics, edition 1, volume 1, chapter 1, pages 3-102 Elsevier.
  6. Joachim Merz & Dominik Hanglberger & Rafael Rucha, 2009. "The Timing of Daily Demand for Goods and Services – Multivariate Probit Estimates and Microsimulation Results for an Aged Population with German Time Use Diary Data," FFB-Discussionpaper 77, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)), LEUPHANA University Lüneburg.
  7. Vassilis A. Hajivassiliou & Axel Borsch-Supan, 1990. "Smooth Unbiased Multivariate Probability Simulators for Maximum Likelihood Estimation of Limited Dependent Variable Models," Cowles Foundation Discussion Papers 960, Cowles Foundation for Research in Economics, Yale University.
  8. Hamermesh, Daniel S., 2000. "Timing, Togetherness and Time Windfalls," IZA Discussion Papers 173, Institute for the Study of Labor (IZA).
  9. Harvey, Andrew & Fisher, Kimberly & Gershuny, Jonathan & Akbari, Ather, 2000. "Examining working time arrangements using time use survey data," ISER Working Paper Series 2000-22, Institute for Social and Economic Research.
  10. Stephen J. Ferris, 1988. "Time, Space And Shopping: The Regulation Of Shopping Hours," Carleton Industrial Organization Research Unit (CIORU) 88-06, Carleton University, Department of Economics.
  11. Merz, Joachim & Böhm, Paul & Hanglberger, Dominik & Rucha, Rafael & Stolze, Henning, 2007. "Wann werden Serviceleistungen nachgefragt? – Ein Mikrosimulationsmodell alternativer Ladenöffnungszeiten mit Daten der Zeitbudgeterhebung ServSim," MPRA Paper 9034, University Library of Munich, Germany.
  12. Jacobsen, Joyce P. & Kooreman, Peter, 2005. "Timing constraints and the allocation of time: The effects of changing shopping hours regulations in The Netherlands," European Economic Review, Elsevier, vol. 49(1), pages 9-27, January.
  13. Robert E. Hall, 1981. "Intertemporal Substitution in Consumption," NBER Working Papers 0720, National Bureau of Economic Research, Inc.
  14. Blundell, Richard & Macurdy, Thomas, 1999. "Labor supply: A review of alternative approaches," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 27, pages 1559-1695 Elsevier.
  15. Killingsworth, Mark R. & Heckman, James J., 1987. "Female labor supply: A survey," Handbook of Labor Economics, in: O. Ashenfelter & R. Layard (ed.), Handbook of Labor Economics, edition 1, volume 1, chapter 2, pages 103-204 Elsevier.
  16. Hamermesh, Daniel S, 1998. "When We Work," American Economic Review, American Economic Association, vol. 88(2), pages 321-25, May.
  17. Merz, Joachim, 1991. "Microsimulation -- A survey of principles, developments and applications," International Journal of Forecasting, Elsevier, vol. 7(1), pages 77-104, May.
  18. Blundell, Richard & Pashardes, Panos & Weber, Guglielmo, 1993. "What Do We Learn About Consumer Demand Patterns from Micro Data?," American Economic Review, American Economic Association, vol. 83(3), pages 570-97, June.
  19. Hamermesh, Daniel S, 1999. "The Timing of Work over Time," Economic Journal, Royal Economic Society, vol. 109(452), pages 37-66, January.
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