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Serial correlation in dynamic panel data models with weakly exogenous regressor and fixed effects
(2005)
Our paper wants to present and compare two estimation methodologies for dynamic panel data models in the presence of serially correlated errors and weakly exogenous regressors. The ¯rst is the ¯rst di®erence GMM estimator as proposed by Arellano and Bond (1991) and the second is the transformed Maximum Likelihood Estimator as proposed by Hsiao, Pesaran, and Tahmiscioglu (2002). Thereby, we consider the ¯xed e®ects case and weakly exogenous regressors. The ¯nite sample properties of both estimation methodologies are analysed within a simulation experiment. Furthermore, we will present an empirical example to consider the performance of both estimators with real data. JEL Classification: C23, J64
The effects of vocational training programmes on the duration of unemployment in Eastern Germany
(2005)
Vocational training programmes have been the most important active labour market policy instrument in Germany in the last years. However, the still unsatisfying situation of the labour market has raised doubt on the efficiency of these programmes. In this paper, we analyse the effects of the participation in vocational training programmes on the duration of unemployment in Eastern Germany. Based on administrative data for the time between the October 1999 and December 2002 of the Federal Employment Administration, we apply a bivariate mixed proportional hazards model. By doing so, we are able to use the information of the timing of treatment as well as observable and unobservable influences to identify the treatment effects. The results show that a participation in vocational training prolongates the unemployment duration in Eastern Germany. Furthermore, the results suggest that locking-in effects are a serious problem of vocational training programmes. JEL Classification: J64, J24, I28, J68
In recent methodological work the well known ACD approach, originally introduced by Engle and Russell (1998), has been supplemented by the involvement of an unobservable stochastic process which accompanies the underlying process of durations via a discrete mixture of distributions. The Mixture ACD model, emanating from the specialized proposal of De Luca and Gallo (2004), has proved to be a moderate tool for description of financial duration data. The use of one and the same family of ordinary distributions has been common practice until now. Our contribution incites to use the rich parameterized comprehensive family of distributions which allows for interacting different distributional idiosyncrasies. JEL classification: C41, C22, C25, C51, G14.
We propose a new framework for modelling the time dependence in duration processes being in force on financial markets. The pioneering ACD model introduced by Engle and Russell (1998) will be extended in a manner that the duration process will be accompanied by an unobservable stochastic process. The Discrete Mixture ACD framework provides us with a general methodology which puts the idea into practice. It is established by introducing a discrete-valued latent regime variable which can be justified in the light of recent market microstructure theories. The empirical application demonstrates its ability to capture specific characteristics of intraday transaction durations while alternative approaches fail. JEL classification: C41, C22, C25, C51, G14.