Resumé
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Oxford Bulletin of Economics and Statistics |
| Vol/bind | 80 |
| Udgave nummer | 4 |
| Sider (fra-til) | 822-842 |
| Antal sider | 21 |
| ISSN | 0305-9049 |
| DOI | |
| Status | Udgivet - aug. 2018 |
Bibliografisk note
Published online: 17 November 2017Citer dette
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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 tidsskrift › Tidsskriftartikel › Forskning › peer review
TY - JOUR
T1 - Forecasting Macroeconomic Labour Market Flows
T2 - What Can We Learn from Micro-level Analysis?
AU - Wilke, Ralf
N1 - Published online: 17 November 2017
PY - 2018/8
Y1 - 2018/8
N2 - 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.
AB - 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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U2 - 10.1111/obes.12222
DO - 10.1111/obes.12222
M3 - Journal article
VL - 80
SP - 822
EP - 842
JO - Oxford Bulletin of Economics and Statistics
JF - Oxford Bulletin of Economics and Statistics
SN - 0305-9049
IS - 4
ER -