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Estimates of a Labor Supply Function Using Alternative Measures of Hours of Work

In: The Economics of Time Use

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  • N. Anders Klevmarken

Abstract

Depending on data source, estimates of hours of work give widely different results both as to level and change. In this paper three alternative measures of hours worked are used to estimate a simple labour supply function to investigate if estimated wage rate and income effects are data dependent as well. The measures used include those from time-use surveys and those from regular surveys. The latter are based on the responses to a question about normal weekly hours of market work. The results suggest that estimates of the wage rate effects become much smaller when measures of normal hours are used compared to data collected for a well-defined time period close to the date of interview, such as time-use data. The income effects appear less sensitive to the choice of data.
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  • N. Anders Klevmarken, 2004. "Estimates of a Labor Supply Function Using Alternative Measures of Hours of Work," Contributions to Economic Analysis, in: The Economics of Time Use, pages 149-173, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:ceazzz:s0573-8555(04)71006-8
    DOI: 10.1016/S0573-8555(04)71006-8
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    1. 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.
    2. Klevmarken, Anders, 1998. "Microeconomic Analysis of Time-use Data. Did we reach the promised land?," Working Paper Series 1998:12, Uppsala University, Department of Economics.
    3. Brownstone, David & Valletta, Robert G, 1996. "Modeling Earnings Measurement Error: A Multiple Imputation Approach," The Review of Economics and Statistics, MIT Press, vol. 78(4), pages 705-717, November.
    4. Schwierz, Christoph, 2003. "The Effects of Taxes and Socioeconomic Variables on Market Work and Home Production in Norway in the Years 1970 to 2000," Memorandum 33/2003, Oslo University, Department of Economics.
    5. Carlin, Paul S. & Flood, Lennart, 1997. "Do children affect the labor supply of Swedish men? Time diary vs. survey data," Labour Economics, Elsevier, vol. 4(2), pages 167-183, June.
    6. Klevmarken, Anders, 1982. "Household Market and Nonmarket Activities (HUS) – A Pilot Study," Working Paper Series 77, Research Institute of Industrial Economics.
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    Cited by:

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    2. Gimenez-Nadal, J. Ignacio & Molina, Jose Alberto, 2015. "Health status and the allocation of time: Cross-country evidence from Europe," Economic Modelling, Elsevier, vol. 46(C), pages 188-203.
    3. Philip Trostel & Ian Walker, 2006. "Education and Work," Education Economics, Taylor & Francis Journals, vol. 14(4), pages 377-399.
    4. J. Ignacio Gimenez-Nadal & José Alberto Molina, 2016. "Commuting Time And Household Responsibilities: Evidence Using Propensity Score Matching," Journal of Regional Science, Wiley Blackwell, vol. 56(2), pages 332-359, March.
    5. Bessho, Shun-ichiro & Hayashi, Masayoshi, 2011. "Labor supply response and preferences specification: Estimates for prime-age males in Japan," Journal of Asian Economics, Elsevier, vol. 22(5), pages 398-411, October.
    6. Charlene Kalenkoski & David Ribar & Leslie Stratton, 2009. "The influence of wages on parents’ allocations of time to child care and market work in the United Kingdom," Journal of Population Economics, Springer;European Society for Population Economics, vol. 22(2), pages 399-419, April.
    7. J. Ignacio Gimenez-Nadal & Jose Alberto Molina & Raquel Ortega, 2017. "Like my parents at home? Gender differences in children’s housework in Germany and Spain," Empirical Economics, Springer, vol. 52(4), pages 1143-1179, June.
    8. Steffen Otterbach & Alfonso Sousa-Poza, 2010. "How Accurate are German Work-time Data? A Comparison of Time-diary Reports and Stylized Estimates," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 97(3), pages 325-339, July.
    9. Gimenez-Nadal, Jose Ignacio & Sevilla, Almudena, 2012. "Trends in time allocation: A cross-country analysis," European Economic Review, Elsevier, vol. 56(6), pages 1338-1359.
    10. Jorge Gonz�lez, 2015. "Estimating income elasticities of leisure activities using cross-sectional categorized data," Documentos de Trabajo dt2015-02, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
    11. Giménez-Nadal, J. Ignacio & Molina, Jose Alberto & Ortega, Raquel, 2015. "As my parents at home? Gender differences in childrens’ housework between Germany and Spain," MPRA Paper 62699, University Library of Munich, Germany.
    12. J. Ignacio Gimenez-Nadal & José Alberto Molina & Yu Zhu, 2018. "Intergenerational mobility of housework time in the United Kingdom," Review of Economics of the Household, Springer, vol. 16(4), pages 911-937, December.
    13. Hyytinen, Ari & Ruuskanen, Olli-Pekka, 2006. "What makes an entrepreneur independent? Evidence from time use survey," Discussion Papers 1029, The Research Institute of the Finnish Economy.
    14. Bandara, Amarakoon, 2014. "How effective are countercyclical policy tools in mitigating the impact of financial and economic crises in Africa?," Journal of Policy Modeling, Elsevier, vol. 36(5), pages 840-854.

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    More about this item

    JEL classification:

    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other

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