IDEAS home Printed from https://ideas.repec.org/a/bla/jorssa/v184y2021i3p842-867.html

Modelling non‐linear age‐period‐cohort effects and covariates, with an application to English obesity 2001–2014

Author

Listed:
  • Zoë Fannon
  • Christiaan Monden
  • Bent Nielsen

Abstract

We develop an age‐period‐cohort model for repeated cross‐section data with individual covariates, which identifies the non‐linear effects of age, period and cohort. This is done for both continuous and binary dependent variables. The age, period and cohort effects in the model are represented by a parametrization with freely varying parameters that separates the identified non‐linear effects and the unidentifiable linear effects. We develop a test of the parametrization against a more general ‘time‐saturated’ model. The method is applied to analyse the obesity epidemic in England using survey data. The main non‐linear effects we find in English obesity data are age‐related among women and cohort‐related among men.

Suggested Citation

  • Zoë Fannon & Christiaan Monden & Bent Nielsen, 2021. "Modelling non‐linear age‐period‐cohort effects and covariates, with an application to English obesity 2001–2014," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 842-867, July.
    • Handle: RePEc:bla:jorssa:v:184:y:2021:i:3:p:842-867
    DOI: 10.1111/rssa.12685
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/rssa.12685
    Download Restriction: no
    File URL: https://libkey.io/10.1111/rssa.12685?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Wenjiang Fu, 2016. "Constrained Estimators and Consistency of a Regression Model on a Lexis Diagram," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(513), pages 180-199, March.
    2. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    3. Hruby, A. & Manson, J.E. & Qi, L. & Malik, V.S. & Rimm, E.B. & Sun, Q. & Willett, W.C. & Hu, F.B., 2016. "Determinants and consequences of obesity," American Journal of Public Health, American Public Health Association, vol. 106(9), pages 1656-1662.
    4. Mette Ejrnæs & Stefan Hochguertel, 2013. "Is Business Failure Due to Lack of Effort? Empirical Evidence from a Large Administrative Sample," Economic Journal, Royal Economic Society, vol. 123, pages 791-830, September.
    5. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    6. Baum II, Charles L. & Ruhm, Christopher J., 2009. "Age, socioeconomic status and obesity growth," Journal of Health Economics, Elsevier, vol. 28(3), pages 635-648, May.
    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. Zoë Fannon & Christiaan Monden & Bent Nielsen, 2018. "Age-period-cohort modelling and covariates, with an application to obesity in England 2001-2014," Economics Papers 2018-W05, Economics Group, Nuffield College, University of Oxford.
    2. Tesfaye, Wondimagegn & Tirivayi, Nyasha, 2020. "Crop diversity, household welfare and consumption smoothing under risk: Evidence from rural Uganda," World Development, Elsevier, vol. 125(C).
    3. Dennis Shen & Peng Ding & Jasjeet Sekhon & Bin Yu, 2022. "Same Root Different Leaves: Time Series and Cross-Sectional Methods in Panel Data," Papers 2207.14481, arXiv.org, revised Oct 2022.
    4. Chung‐Hua Shen & Hsing‐Hua Hsu, 2022. "The determinants of Asian banking crises—Application of the panel threshold logit model," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 248-277, March.
    5. Ali Uyar & Simone Pizzi & Fabio Caputo & Cemil Kuzey & Abdullah S. Karaman, 2022. "Do shareholders reward or punish risky firms due to CSR reporting and assurance?," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(5), pages 1596-1620, July.
    6. Volonté, Christophe, 2015. "Boards: Independent and committed directors?," International Review of Law and Economics, Elsevier, vol. 41(C), pages 25-37.
    7. Shinichi Yamaguchi & Hirohide Sakaguchi & Kotaro Iyanaga, 2018. "The Boosting Effect of E-WOM on Macro-level Consumption: A Cross-Industry Empirical Analysis in Japan," The Review of Socionetwork Strategies, Springer, vol. 12(2), pages 167-181, December.
    8. Richard H. Spady & Sami Stouli, 2018. "Simultaneous Mean-Variance Regression," Bristol Economics Discussion Papers 18/697, School of Economics, University of Bristol, UK.
    9. Jeffrey M. Wooldridge, 2001. "Applications of Generalized Method of Moments Estimation," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 87-100, Fall.
    10. Min, Yijie & Liao, Yi-Chuan & Chen, Zhijun, 2022. "The side effect of business group membership: How do business group isomorphic pressures affect organizational innovation in affiliated firms?," Journal of Business Research, Elsevier, vol. 141(C), pages 380-392.
    11. Santosh Jatrana & Ken Richardson & Samba Siva Rao Pasupuleti, 2018. "Investigating the Dynamics of Migration and Health in Australia: A Longitudinal Study," European Journal of Population, Springer;European Association for Population Studies, vol. 34(4), pages 519-565, October.
    12. Juliana D. Araujo & Povilas Lastauskas & Chris Papageorgiou, 2017. "Evolution of Bilateral Capital Flows to Developing Countries at Intensive and Extensive Margins," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(7), pages 1517-1554, October.
    13. Yingying Dong & Arthur Lewbel, 2015. "A Simple Estimator for Binary Choice Models with Endogenous Regressors," Econometric Reviews, Taylor & Francis Journals, vol. 34(1-2), pages 82-105, February.
    14. Marcelo Moreira & Geert Ridder, 2019. "Efficiency loss of asymptotically efficient tests in an instrumental variables regression," CeMMAP working papers CWP03/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Andrea A. Naghi & Máté Váradi & Mikhail Zhelonkin, 2021. "Robust Estimation of Probit Models with Endogeneity," Tinbergen Institute Discussion Papers 21-004/III, Tinbergen Institute.
    16. Álvarez, Inmaculada C. & Barbero, Javier & Zofío, José L., 2017. "A Panel Data Toolbox for MATLAB," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i06).
    17. Kugler, Adriana & Pica, Giovanni, 2008. "Effects of employment protection on worker and job flows: Evidence from the 1990 Italian reform," Labour Economics, Elsevier, vol. 15(1), pages 78-95, February.
    18. Russo, Angeloantonio & Vurro, Clodia & Nag, Rajiv, 2019. "To have or to be? The interplay between knowledge structure and market identity in knowledge-based alliance formation," Research Policy, Elsevier, vol. 48(3), pages 571-583.
    19. W. A. Naudé, 2004. "The effects of policy, institutions and geography on economic growth in Africa: an econometric study based on cross-section and panel data," Journal of International Development, John Wiley & Sons, Ltd., vol. 16(6), pages 821-849.
    20. Niels-Hugo Blunch, 2018. "Just like a woman? New comparative evidence on the gender income gap across Eastern Europe and Central Asia," IZA Journal of Migration and Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 8(1), pages 1-41, December.

    More about this item

    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:bla:jorssa:v:184:y:2021:i:3:p:842-867. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.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.