Job Creation and Job Destruction in a Regulated Labor Market: The Case of Austria

We study Austrian job reallocation in the period of 1978 to 1998, using a large administrative dataset where we correct for spurious entries and exits of firms. We find that on average 9 out of 100 randomly selected jobs were created within the last year, and that about 9 out of randomly selected 100 jobs were destroyed within the next year. Hence, the magnitude of Austrian job flows seems to be comparable to other countries, similar to the well-known results of Davis et al. (1996) for the United States. Job reallocation appears to be driven primarily by idiosyncratic shocks. However, job creation increases significantly during cyclical upswings whereas job destruction rises in downturns. We also find substantial persistence of job creation and destruction. The pronounced pattern of job reallocation rates falling with firm size and age continues to hold when we use a set of controls. Finally, we show that – controlling for sector and firm size composition – Austrian job reallocation rates are only half the rates for the U.S. This result is not surprising given the impact of tighter regulation and labor law in Austria.     

Wealth and sustainable development: the role of David Pearce

Green net national product was thought to be one way of measuring sustainable income. However, David Pearce understood that a better measure of sustainable development was to look at what a generation is leaving in form of capital assets to later generations. In this article, his arguments and insights are highlighted against recent theoretical advances.     

Fair ranking of teachers

Economic theory suggests that it is optimal to reward teachers depending on the relative performance of their students. We develop an econometric approach, based on stochastic frontier analysis, to construct a fair ranking that accounts for the socio-economic background of students and schools and the imprecision inherent in achievement data. Using German PIRLS (IGLU) data, we exploit the hierarchical structure of the data to estimate the efficiency of each teacher. A parsimonious set of control variables suffices to get a “fair” estimate of unobserved teacher quality. A Hausman–Taylor type estimator is the preferred estimator because teacher efficiency and some exogenous variables may be correlated.     

Joseph A. Schumpeter’s contributions in the area of fiscal sociology: a first approximation

Fiscal sociology deals with the ramifications of the fiscal activities of the state into areas which are not their primary target. These effects may occur in sectors not directly affected such as related markets, but they may also occur outside the economic sphere proper, such as in politics, culture, religion, or society at large. Schumpeter contributed to the research project of fiscal sociology throughout his life. In this first approximation, his contribution is discussed in terms of his appreciation of three important scholars who all made landmark contributions to fiscal sociology: Franz Oppenheimer, Werner Sombart, and Gustav (von) Schmoller.JEL Classification: B15, H39     

Timing of Public Information and Cost Reduction

Received July 31, 2000; revised version received July 18, 2001     

Disequilibrium dynamics in a simple macroeconomic model

The dynamic behavior of a simple macroeconomic disequilibrium model is analyzed in which consumers' changes in money holdings constitute the dynamic link between any two periods. It is shown that, under constant government consumption, a constant production function (no investment), and fixed prices and wages, stationary states of Keynesian unemployment are stable whereas those of repressed inflation are globally unstable. Possibilities of unemployment and output cycles are indicated for fixed wages as well as for some very simple class of wage and price adjustment mechanisms.     

Modelling of repairable systems with various degrees of repair

The availability of a stochastic repairable system depends on the failure behaviour and on repair strategies. In this paper, we deal with a general repair model for a system using auxiliary counting processes and corresponding intensities which include various degrees of repair (between minimal repair and perfect repair). For determining the model parameters we need estimators depending on failure times and repair times: maximum likelihood (ML) estimator and Bayes estimators are considered. Special results are obtained by the use of Weibull-type intensities and random observation times.     

MSE-improvement of the least squares estimator by dropping variables

It is well known that dropping variables in regression analysis decreases the variance of the least squares (LS) estimator of the remaining parameters. However, after elimination estimates of these parameters are biased, if the full model is correct. In his recent paper, Boscher (1991) showed that the LS-estimator in the special case of a mean shift model (cf. Cook and Weisberg, 1982) which assumes no “outliers” can be considered in the framework of a linear regression model where some variables are deleted. He derived conditions under which this estimator outperforms the LS-estimator of the full model in terms of the mean squared error (MSE)-matrix criterion. We demonstrate that this approach can be extended to the general set-up of dropping variables. Necessary and sufficient conditions for the MSE-matrix superiority of the LS-estimator in the reduced model over that in the full model are derived. We also provide a uniformly most powerful F-statistic for testing the MSE-improvement.