Forecasting Macroeconomic Labour Market Flows: What Can We Learn from Micro-level Analysis?

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Resumé

Forecasting labour market flows is important for budgeting and decision-making in government departments and public administration. Macroeconomic forecasts are normally obtained from time series data. In this article, we follow another approach that uses individual-level statistical analysis to predict the number of exits out of unemployment insurance claims. We present a comparative study of econometric, actuarial and statistical methodologies that base on different data structures. The results with records of the German unemployment insurance suggest that prediction based on individual-level statistical duration analysis constitutes an interesting alternative to aggregate data-based forecasting. In particular, forecasts of up to six months ahead are surprisingly precise and are found to be more precise than considered time series forecasts.
Forecasting labour market flows is important for budgeting and decision-making in government departments and public administration. Macroeconomic forecasts are normally obtained from time series data. In this article, we follow another approach that uses individual-level statistical analysis to predict the number of exits out of unemployment insurance claims. We present a comparative study of econometric, actuarial and statistical methodologies that base on different data structures. The results with records of the German unemployment insurance suggest that prediction based on individual-level statistical duration analysis constitutes an interesting alternative to aggregate data-based forecasting. In particular, forecasts of up to six months ahead are surprisingly precise and are found to be more precise than considered time series forecasts.
SprogEngelsk
TidsskriftOxford Bulletin of Economics and Statistics
Vol/bind80
Udgave nummer4
Sider822-842
Antal sider21
ISSN0305-9049
DOI
StatusUdgivet - aug. 2018

Bibliografisk note

Published online: 17 November 2017

Citer dette

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abstract = "Forecasting labour market flows is important for budgeting and decision-making in government departments and public administration. Macroeconomic forecasts are normally obtained from time series data. In this article, we follow another approach that uses individual-level statistical analysis to predict the number of exits out of unemployment insurance claims. We present a comparative study of econometric, actuarial and statistical methodologies that base on different data structures. The results with records of the German unemployment insurance suggest that prediction based on individual-level statistical duration analysis constitutes an interesting alternative to aggregate data-based forecasting. In particular, forecasts of up to six months ahead are surprisingly precise and are found to be more precise than considered time series forecasts.",
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Forecasting Macroeconomic Labour Market Flows : What Can We Learn from Micro-level Analysis? / Wilke, Ralf.

I: Oxford Bulletin of Economics and Statistics, Bind 80, Nr. 4, 08.2018, s. 822-842.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

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