Arbeitsmarktforschung und Arbeitsmarktstatistik aus der Sicht der wirtschaftspolitischen Beratung: Erfahrungen und Perspektiven

Zusammenfassung: Dieser Beitrag beleuchtet aus der Sicht der wirtschaftspolitischen Beratung einige Anforderungen an die Arbeitsmarkt?konomik und Arbeitsmarktstatistik. Drei Bereiche werden angesprochen: die Arbeitslosenstatistik, die Tariflohnpolitik und die aktive Arbeitsmarktpolitik. Dabei werden zun?chst die Bemühungen hinsichtlich einer realistischeren Erfassung der Unterbesch?ftigung gewürdigt, zugleich aber Hinweise auf Verbesserungsm?glichkeiten gegeben. Anforderungen an die amtliche Statistik ergeben sich des Weiteren hinsichtlich der Tarifentgelte. In diesem Zusammenhang wird die Umsetzung der Erkenntnisse der Arbeitsmarkt?konomik in eine lohnpolitische Orientierungshilfe skizziert. Schlie?lich erfolgt eine kritische Einsch?tzung des Erfolgs der aktiven Arbeitsmarktpolitik, wobei eine zunehmende Willigkeit zur Bereitstellung der für die Evaluation erforderlichen Daten konstatiert werden kann.

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Summary: This paper deals with three demands on labor economics and labor statistics put forward from the point of view of an advisor to economic policy. Despite several improvements of unemployment statistics, a lot of work remains to be done. With respect to wage policy attempts by the German Council of Economic Experts are discussed how to formulate a guidance for wage policy both on scientific grounds and understandable by the public. Finally, a critical assessment of active labor market policies is presented together with a plea for adequate individual data in order to carry out a sound evaluation of these policies.

* Vortrag für die „Statistische Woche“, die Jahrestagung der Deutschen Statistischen Gesellschaft am 20. September 2004 in Frankfurt/Main. Der Vortragsstil wurde beibehalten. Die hier vorgetragenen Auffassungen liegen allein in der Verantwortung des Autors und stellen nicht notwendigerweise die Auffassungen anderer Institutionen dar. Ich danke Bernd Fitzenberger (Universit?t Frankfurt/Main und ZEW), Joachim M?ller (Universit?t Regensburg), Bernhard Boockmann und Tobias Hagen (ZEW), Irmtraud Beuerlein und Dirk Heinlein (Statistisches Bundesamt) für hilfreiche Kommentare und Anregungen. Verbleibende M?ngel gehen—leider—zu meinen Lasten.     

Monitoring means and covariances of multivariate non linear time series with heavy tails

In this paper, the focus is on sequential analysis of multivariate financial time series with heavy tails. The mean vector and the covariance matrix of multivariate non linear models are simultaneously monitored by modifying conventional control charts to identify structural changes in the data. The considered target process is a constant conditional correlation model (cf. Bollerslev, 1990 Bollerslev, T. (1990). Modeling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH model. Rev. Econ. Stat. 72:498–505.[Crossref], [Web of Science ®] , [Google Scholar]), an extended constant conditional correlation model (cf. He and Teräsvirta, 2004 He, C., Teräsvirta, T. (2004). An extended constant conditional correlation GARCH model and its fourth-moment structure. Economet. Theory 20:904–926.[Crossref], [Web of Science ®] , [Google Scholar]), a dynamic conditional correlation model (cf. Engle, 2002 Engle, R.F. (2002). Dynamic conditional correlation: A simple class of multivariate GARCH models. J. Bus. Econ. Stat. 20(3):339–350.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]), or a generalized dynamic conditional correlation model (cf. Capiello et al., 2006 Capiello, L., Engle, R., Sheppard, K. (2006). Asymmetric correlations in the dynamics of global equity and bond returns. J. Financial Economet. 4(4):537–572.[Crossref] , [Google Scholar]). For statistical surveillance we use control charts based on residuals. Further, the procedures are constructed for t-distribution. The detection speed of these charts is compared via Monte Carlo simulation. In the empirical study, the procedure with the best performance is applied to log-returns of the stock market indices FTSE and CAC.     

Activation,Public Employment Services and their Clients: The Role of Social Class in a Continental Welfare State

This article fills a gap in the existing literature by investigating how public employment service (PES) staff actually deal with their clients under a continental regime of activation. The results reported here are based on interviews both with PES staff and their unemployed clients in Germany. We argue that due to its Bismarckian origins as an insurance‐based system of ‘unemployment protection’, Germany's system of unemployment compensation is attractive not only for the marginalized, but also for core workers. As a result, PES staff deal with clients from very heterogeneous class backgrounds. We demonstrate that social class is a significant factor in client outcomes, and that earlier research has perhaps overemphasized the role of frontline staff as ‘street‐level bureaucrats’. While staff do have considerable power, the result of the encounters between the administration and clients also depends on the capabilities of the clients, which, in turn, are strongly related to social class.     

In Conclusion: Current Themes in Bereavement and Widowhood Research

A number of important themes and controversies emerged from the preceding papers. These include (a) what kinds of losses lead to grief; (b) how long grief lasts; (c) how to conceptualize "recovery," (d) the nature of "normal" grief; (e) whether bereavement has lasting effects on health; and (f) what characteristics of the individual, the relationship, or the nature of the death create a greater risk for poor outcome of bereavement. Consideration of these issues should help develop more effective strategies for intervention with sufferers, and social policies sensitive to the needs of those at greatest risk.     

Mean-variance portfolios using Bayesian vector-autoregressive forcasts

Protfolio optimization is very sensitive to the forecats of returns and (co-)variances of the underlying assets. This paper applies a Bayesian vector-autoregression of the asset universe to predict the returns. Further, the co-variance matrix is forecasted by an Augmented GARCH estimation of the most volatile principle components of the return series. As an empirical illustration, the daily stock returns of the German stocks index DAX have been used to calculate some well-known mean-variance portfolios. Back-testing is used to evaluate the performance. The approach seems to be promising.