IDEAS home Printed from https://ideas.repec.org/a/ove/journl/aid10414.html
   My bibliography  Save this article

The impact of aging on regional employment: Linking spatial econometrics and population projections for a scenario analysis of future labor market outcomes in Nordic regions

Author

Listed:
  • Torben Dall Schmidt
  • Aki Kangasharju
  • Timo Mitze
  • Daniel Rauhut

Abstract

Ageing is a key challenge for many countries. The purpose of this paper is to simulate how ageing affects future regional labour market outcomes. We develop a simulation procedure based on data for 71 Nordic regions in Finland, Norway, Sweden and Denmark. The procedure combines spatial econometrics and population projections for scenario analyses of future employment patterns up to 2021. Compared to a “benchmark scenario†based on projections of the working age population, we find that predicted regional labour market outcomes tell a much richer story if a combination of estimation results and population projections is used. To this end, our results can be helpful for economic policymaking, which is constantly in need of accurate regional labor market forecasts.

Suggested Citation

  • Torben Dall Schmidt & Aki Kangasharju & Timo Mitze & Daniel Rauhut, 2014. "The impact of aging on regional employment: Linking spatial econometrics and population projections for a scenario analysis of future labor market outcomes in Nordic regions," Economics and Business Letters, Oviedo University Press, vol. 3(4), pages 232-246.
  • Handle: RePEc:ove:journl:aid:10414
    as

    Download full text from publisher

    File URL: https://reunido.uniovi.es/index.php/EBL/article/view/10414
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Michael Beenstock & Daniel Felsenstein, 2007. "Spatial Vector Autoregressions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 2(2), pages 167-196.
    2. Blien, Uwe & Suedekum, Jens & Wolf, Katja, 2006. "Local employment growth in West Germany: A dynamic panel approach," Labour Economics, Elsevier, vol. 13(4), pages 445-458, August.
    3. Jean-Marc Burniaux & Romain Duval & Florence Jaumotte, 2004. "Coping with Ageing: A Dynamic Approach to Quantify the Impact of Alternative Policy Options on Future Labour Supply in OECD Countries," OECD Economics Department Working Papers 371, OECD Publishing.
    4. Charles M. Tiebout, 1956. "A Pure Theory of Local Expenditures," Journal of Political Economy, University of Chicago Press, vol. 64(5), pages 416-416.
    5. Jean‐Michel Josselin & Yvon Rocaboy & Christophe Tavéra, 2009. "The influence of population size on the relevance of demand or supply models for local public goods: Evidence from France," Papers in Regional Science, Wiley Blackwell, vol. 88(3), pages 563-574, August.
    6. Peter Sandholt Jensen & Torben Dall Schmidt, 2011. "Testing for Cross-sectional Dependence in Regional Panel Data," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 423-450, July.
    7. Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2014. "Estimating and Forecasting with a Dynamic Spatial Panel Data Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 112-138, February.
    8. Badi H. Baltagi & Ying Deng, 2015. "EC3SLS Estimator for a Simultaneous System of Spatial Autoregressive Equations with Random Effects," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 659-694, December.
    9. J.Paul Elhorst, 2005. "Models for Dynamic Panels in Space and Time - an Application to Regional Unemployment in the EU," ERSA conference papers ersa05p81, European Regional Science Association.
    10. Axel Boersch-Supan, 2001. "Labor Market Effects of Population Aging," NBER Working Papers 8640, National Bureau of Economic Research, Inc.
    11. Timo Mitze, 2012. "Empirical Modelling in Regional Science," Lecture Notes in Economics and Mathematical Systems, Springer, edition 127, number 978-3-642-22901-5, October.
    12. J. Paul Elhorst, 2014. "Dynamic Spatial Panels: Models, Methods and Inferences," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 95-119, Springer.
    13. Thomas Nechyba, 1996. "Fiscal federalism and local public finance: A computable general equilibrium (CGE) framework," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 3(2), pages 215-231, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dagmara Nikulin & Aneta Sobiechowska‐Ziegert, 2018. "Informal work in Poland – a regional approach," Papers in Regional Science, Wiley Blackwell, vol. 97(4), pages 1227-1246, November.

    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. Paelinck, Jean & Mur, Jesús & Trivez, F. Javier, 2015. "Modelos para datos espaciales con estructura transversal o de panel. Una revisión/Models for Spatial Data with Panel or Cross-Sectional Structure. A Review," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 33, pages 7-30, Enero.
    2. Zheng, Xinye & Li, Fanghua & Song, Shunfeng & Yu, Yihua, 2013. "Central government's infrastructure investment across Chinese regions: A dynamic spatial panel data approach," China Economic Review, Elsevier, vol. 27(C), pages 264-276.
    3. Atems, Bebonchu, 2015. "Another look at tax policy and state economic growth: The long-run and short-run of it," Economics Letters, Elsevier, vol. 127(C), pages 64-67.
    4. Sven Wardenburg & Thomas Brenner, 2021. "Analysing the spatio-temporal diffusion of economic change - advanced statistical approach and exemplary application," Working Papers on Innovation and Space 2021-01, Philipps University Marburg, Department of Geography.
    5. Anupam Nanda & Jia-Huey Yeh, 2016. "Reflected Glory Versus Repulsive Envy: How Do the Smiths Feel About the House of the Joneses?," Asian Economic Journal, East Asian Economic Association, vol. 30(3), pages 317-341, September.
    6. Miriam Hortas-Rico & Vicente Rios, 2020. "Is there an optimal size for local governments? A spatial panel data model approach," Regional Studies, Taylor & Francis Journals, vol. 54(7), pages 958-973, July.
    7. Oumarou Zallé & Pousseni Bakouan, 2024. "Spillover effects of fiscal decentralization on access to basic social services in Burkina Faso," Growth and Change, Wiley Blackwell, vol. 55(1), March.
    8. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2019. "A time-space dynamic panel data model with spatial moving average errors," Regional Science and Urban Economics, Elsevier, vol. 76(C), pages 13-31.
    9. Dechun Liu & Xinye Zheng & Yihua Yu, 2022. "Public Debt Competition in Local China: Evidence and Mechanism of Spatial Interactions," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(S2), pages 91-105, November.
    10. Kun Duan & Tapas Mishra & Mamata Parhi & Simon Wolfe, 2019. "How Effective are Policy Interventions in a Spatially-Embedded International Real Estate Market?," The Journal of Real Estate Finance and Economics, Springer, vol. 58(4), pages 596-637, May.
    11. Leopoldo Catania & Anna Gloria Billé, 2017. "Dynamic spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(6), pages 1178-1196, September.
    12. Yang, Kai & Lee, Lung-fei, 2021. "Estimation of dynamic panel spatial vector autoregression: Stability and spatial multivariate cointegration," Journal of Econometrics, Elsevier, vol. 221(2), pages 337-367.
    13. Roman Liesenfeld & Jean‐François Richard & Jan Vogler, 2017. "Likelihood‐Based Inference and Prediction in Spatio‐Temporal Panel Count Models for Urban Crimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 600-620, April.
    14. Montmartin, Benjamin & Herrera, Marcos, 2015. "Internal and external effects of R&D subsidies and fiscal incentives: Empirical evidence using spatial dynamic panel models," Research Policy, Elsevier, vol. 44(5), pages 1065-1079.
    15. Vassilis Tselios, 2011. "Is Inequality Good for Innovation?," International Regional Science Review, , vol. 34(1), pages 75-101, January.
    16. Süleyman Taşpınar & Osman DoĞan & Jiyoung Chae & Anil K. Bera, 2021. "Bayesian Inference in Spatial Stochastic Volatility Models: An Application to House Price Returns in Chicago," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(5), pages 1243-1272, October.
    17. Jean-François Richard, 2015. "Likelihood Based Inference and Prediction in Spatio-temporal Panel Count Models for Urban Crimes," Working Paper 5657, Department of Economics, University of Pittsburgh.
    18. Lee, Lung-fei & Yu, Jihai, 2015. "Estimation of fixed effects panel regression models with separable and nonseparable space–time filters," Journal of Econometrics, Elsevier, vol. 184(1), pages 174-192.
    19. Cong Yu & Linke Hou & Yuxia Lyu & Qi Zhang, 2022. "Political competition, spatial interactions, and default risk of local government debts in China," Papers in Regional Science, Wiley Blackwell, vol. 101(3), pages 717-743, June.
    20. Broekel, Tom & Alfken, Christoph, 2015. "Gone with the wind? The impact of wind turbines on tourism demand," Energy Policy, Elsevier, vol. 86(C), pages 506-519.

    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:ove:journl:aid:10414. 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: Francisco J. Delgado (email available below). General contact details of provider: https://edirc.repec.org/data/deovies.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.