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Long-term Forecasts of Age-specific Labour Market Participation Rates with Functional Data Models

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  • Thomas Url

    (WIFO)

  • Rob J. Hyndman
  • Alexander Dokumentov

Abstract

Many countries have implemented social programmes providing long-term financial or in-kind entitlements. These programmes often focus on specific age-groups and consequently their expenditure streams are subject to demographic change. Given the strains already existing on public budgets, long-term forecasts are an increasingly important instrument to monitor the budgetary consequences of social programmes. The expected development of the labour force is a key input to these forecasts. We suggest combining a functional data approach to age-profiles of labour market participation rates with information on education, marital status and other exogenous variables to improve long-term forecasts of labour supply.

Suggested Citation

  • Thomas Url & Rob J. Hyndman & Alexander Dokumentov, 2016. "Long-term Forecasts of Age-specific Labour Market Participation Rates with Functional Data Models," WIFO Working Papers 510, WIFO.
    • Handle: RePEc:wfo:wpaper:y:2016:i:510
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    References listed on IDEAS

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    Cited by:

    1. Karl Aiginger & Marcus Scheiblecker, 2016. "Österreich 2025 – Eine Agenda für mehr Dynamik, sozialen Ausgleich und ökologische Nachhaltigkeit. Fortschrittsbericht," WIFO Studies, WIFO, number 58885.
    2. Thomas Url & Rob J Hyndman & Alexander Dokumentov, 2016. "Long-term forecasts of age-specific participation rates with functional data models," Monash Econometrics and Business Statistics Working Papers 3/16, Monash University, Department of Econometrics and Business Statistics.
    3. Sandra Bilek-Steindl & Christian Glocker & Serguei Kaniovski & Thomas Url, 2016. "Austria 2025 – The Effect of Human Capital Accumulation on Output Growth," WIFO Studies, WIFO, number 59175.
    4. Thomas Url, 2016. "Langfristige Prognose des Aufwands für Langzeitpflege," WIFO Studies, WIFO, number 58844.

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    Keywords

    forecast; labour supply; age-profile; smoothing;
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