IDEAS home Printed from https://ideas.repec.org/p/nzt/nztans/an25-06.html

Microeconomic heterogeneity in wages, hours, and assets to inform an OLG model for New Zealand

Author

Listed:
  • Andrew Binning
  • Susie McKenzie
  • Murat Özbilgin
  • Christie Smith

    (The Treasury)

Abstract

This paper illustrates microeconomic evidence on wages, hours and net worth, which is used to inform the calibration of the overlapping generations (OLG) model under development at the Treasury. Using cross-sectional survey data, we compute quantiles of lifetime profiles for wages, net worth, and hours-worked. Hourly wages are a particularly important input into the OLG model since they affect both productivity and retirement decisions. Our microeconomic evidence is used to characterise five exogenous types of agents with varying productivity levels. These exogenous types approximate the diversity of wage outcomes and wealth levels seen in New Zealand, reflecting high-, low-, and middle-income people. Wage and asset heterogeneity is important in our OLG model to be able to evaluate policies that affect different groups of people differently. For example, a degree of heterogeneity is needed to consider how different tax rates or tax types (such as a capital income or wealth taxes) might affect people with few and many assets or how changes to the universality of superannuation might affect distributional and aggregate outcomes.

Suggested Citation

  • Andrew Binning & Susie McKenzie & Murat Özbilgin & Christie Smith, 2025. "Microeconomic heterogeneity in wages, hours, and assets to inform an OLG model for New Zealand," Treasury Analytical Notes Series an25/06, New Zealand Treasury.
  • Handle: RePEc:nzt:nztans:an25/06
    as

    Download full text from publisher

    File URL: https://www.treasury.govt.nz/sites/default/files/2025-08/an25-06.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rupert, Peter & Zanella, Giulio, 2015. "Revisiting wage, earnings, and hours profiles," Journal of Monetary Economics, Elsevier, vol. 72(C), pages 114-130.
    2. Johnson, Richard W & Neumark, David, 1996. "Wage Declines among Older Men," The Review of Economics and Statistics, MIT Press, vol. 78(4), pages 740-748, November.
    3. Jacob A. Mincer, 1974. "Introduction to "Schooling, Experience, and Earnings"," NBER Chapters, in: Schooling, Experience, and Earnings, pages 1-4, National Bureau of Economic Research, Inc.
    4. Fair, Ray C, 1994. "How Fast Do Old Men Slow Down?," The Review of Economics and Statistics, MIT Press, vol. 76(1), pages 103-118, February.
    5. Mas-Colell, Andreu & Whinston, Michael D. & Green, Jerry R., 1995. "Microeconomic Theory," OUP Catalogue, Oxford University Press, number 9780195102680.
    6. Grant M. Scobie & Katherine Henderson, 2009. "Saving Rates of New Zealanders: A Net Wealth Approach," Treasury Working Paper Series 09/04, New Zealand Treasury.
    7. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1, August.
    8. Michał Myck, 2010. "Wages and Ageing: Is There Evidence for the ‘Inverse‐U’ Profile?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(3), pages 282-306, June.
    9. Heckman, James J, 1990. "Varieties of Selection Bias," American Economic Review, American Economic Association, vol. 80(2), pages 313-318, May.
    10. Manuel Arellano & Stéphane Bonhomme, 2017. "Quantile Selection Models With an Application to Understanding Changes in Wage Inequality," Econometrica, Econometric Society, vol. 85, pages 1-28, January.
    11. James Heckman, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    12. Chen, Songnian & Wang, Qian, 2023. "Quantile regression with censoring and sample selection," Journal of Econometrics, Elsevier, vol. 234(1), pages 205-226.
    13. Heckman, James J, 1974. "Shadow Prices, Market Wages, and Labor Supply," Econometrica, Econometric Society, vol. 42(4), pages 679-694, July.
    14. John Gibson & Grant Scobie, 2001. "A cohort analysis of household income, consumption and saving," New Zealand Economic Papers, Taylor & Francis Journals, vol. 35(2), pages 196-216.
    15. Dean Hyslop & Amy Rice & Hayden Skilling, 2019. "Understanding labour market developments in New Zealand, 1986-2017," Reserve Bank of New Zealand Discussion Paper Series DP2019/02, Reserve Bank of New Zealand.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Michał Myck, 2010. "Wages and Ageing: Is There Evidence for the ‘Inverse‐U’ Profile?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(3), pages 282-306, June.
    2. Meghir, Costas & Rivkin, Steven, 2011. "Econometric Methods for Research in Education," Handbook of the Economics of Education, in: Erik Hanushek & Stephen Machin & Ludger Woessmann (ed.), Handbook of the Economics of Education, edition 1, volume 3, chapter 1, pages 1-87, Elsevier.
    3. van der Klaauw, Bas, 2014. "From micro data to causality: Forty years of empirical labor economics," Labour Economics, Elsevier, vol. 30(C), pages 88-97.
    4. Kadija Charni & Stephen Bazen, 2017. "Do earnings really decline for older workers?," International Journal of Manpower, Emerald Group Publishing Limited, vol. 38(1), pages 4-24, April.
    5. Yasser Razak Hussain & Pranab Mukhopadhyay, 2023. "How Much do Education, Experience, and Social Networks Impact Earnings in India? A Panel Data Analysis Disaggregated by Class, Gender, Caste and Religion," SAGE Open, , vol. 13(4), pages 21582440231, December.
    6. Carlos Alberto Foronda Rojas, "undated". "Evaluación de los efectos de las políticas de exportación y de productividad en la distribución del ingreso a partir de microsimulaciones," Investigación & Desarrollo 0206, Universidad Privada Boliviana.
    7. Thierry Debrand & Sophie Pennec & Anne-Gisèle Privat, 2003. "Un modèle de microsimulation pour la projection des retraites du régime général," Economie & Prévision, La Documentation Française, vol. 0(4), pages 215-230.
    8. Bushra Yasmin, 2009. "Trade Liberalization and the Lead Role of Human Capital and Job Attributes in Wage Determination: The Case of Pakistan’s Labor Market," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 14(1), pages 1-37, Jan-Jun.
    9. Cunha, Flavio & Heckman, James J., 2007. "Identifying and Estimating the Distributions of Ex Post and Ex Ante Returns to Schooling," Labour Economics, Elsevier, vol. 14(6), pages 870-893, December.
    10. CHEN, Guifu & HAMORI, Shigeyuki, 2009. "Economic returns to schooling in urban China: OLS and the instrumental variables approach," China Economic Review, Elsevier, vol. 20(2), pages 143-152, June.
    11. Suqin Ge & João Macieira, 2024. "Unobserved Worker Quality and Inter‐Industry Wage Differentials," Journal of Industrial Economics, Wiley Blackwell, vol. 72(1), pages 459-515, March.
    12. Lili Kang & Fei Peng, 2012. "A selection analysis of returns to education in China," Post-Communist Economies, Taylor & Francis Journals, vol. 24(4), pages 535-554, March.
    13. Alexey Zamnius & Andrey Polbin, 2021. "Estimating intertemporal elasticity of substitution of labor supply for married women in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 64, pages 23-48.
    14. Patrinos, Harry Anthony & Rivera-Olvera, Angelica, 2025. "Education and Earnings in Arkansas," IZA Discussion Papers 17963, IZA Network @ LISER.
    15. Min Qin & James Brown & Sabu Padmadas & Li Bohua & Qi Jianan & Jane Falkingham, 2016. "Gender Inequalities in Employment and Wage-earning among Economic Migrants in Chinese Cities," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 34(6), pages 175-202.
    16. Blundell, R. & French, E. & Tetlow, G., 2016. "Retirement Incentives and Labor Supply," Handbook of the Economics of Population Aging, in: Piggott, John & Woodland, Alan (ed.), Handbook of the Economics of Population Aging, edition 1, volume 1, chapter 0, pages 457-566, Elsevier.
    17. Liu, Ruixuan & Yu, Zhengfei, 2022. "Sample selection models with monotone control functions," Journal of Econometrics, Elsevier, vol. 226(2), pages 321-342.
    18. Ferraz, Diogo & Ribeiro de Oliveira, Fabíola Cristina, 2018. "Impact of the National Professional Qualification Program (PNQ) on Income: An Econometric Analysis in Piracicaba/SP-Brazil," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 28(2), pages 105-123.
    19. Rupert, Peter & Zanella, Giulio, 2015. "Revisiting wage, earnings, and hours profiles," Journal of Monetary Economics, Elsevier, vol. 72(C), pages 114-130.
    20. Hans Dietrich & Harald Pfeifer & Felix Wenzelmann, 2016. "The more they spend, the more I earn? Firms' training investments and post-training wages of apprentices," Economics of Education Working Paper Series 0116, University of Zurich, Department of Business Administration (IBW).

    More about this item

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J1 - Labor and Demographic Economics - - Demographic Economics
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nzt:nztans:an25/06. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CSS I&T Web & Publishing, The Treasury (email available below). General contact details of provider: https://edirc.repec.org/data/tregvnz.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.