Technological change in energy systems: Learning curves, logistic curves and input-output coefficients

Learning curves have recently been widely adopted in climate-economy models to incorporate endogenous change of energy technologies, replacing the conventional assumption of an autonomous energy efficiency improvement. However, there has been little consideration of the credibility of the learning curve. The current trend that many important energy and climate change policy analyses rely on the learning curve means that it is of great importance to critically examine the basis for learning curves. Here, we analyse the use of learning curves in energy technology, usually implemented as a simple power function. We find that the learning curve cannot separate the effects of price and technological change, cannot reflect continuous and qualitative change of both conventional and emerging energy technologies, cannot help to determine the time paths of technological investment, and misses the central role of R&D activity in driving technological change. We argue that a logistic curve of improving performance modified to include R&D activity as a driving variable can better describe the cost reductions in energy technologies. Furthermore, we demonstrate that the top-down Leontief technology can incorporate the bottom-up technologies that improve along either the learning curve or the logistic curve, through changing input-output coefficients. An application to UK wind power illustrates that the logistic curve fits the observed data better and implies greater potential for cost reduction than the learning curve does.     

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.     

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     

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.     

Delegation and strategic incentives for managers in contests

Owners usually want their managers to maximize profits. As the literature on strategic delegation has shown it may be beneficial to owners to put a positive weight on sales in the optimal linear incentive scheme for managers to make them behave more aggressively in the market. This paper shows that if the competition between the managers can be characterized as a contest, owners may induce their managers to maximize sales. Moreover, there is a first‐mover advantage for owners when choosing their incentive schemes. If delegation is endogenous the type of contest will determine whether all owners delegate their decisions to managers or not. Copyright © 2002 John Wiley & Sons, Ltd.     

Asymptotic confidence bands for the estimated autocovariance and autocorrelation functions of vector autoregressive models

This paper provides closed-form formulae for computing the asymptotic covariance matrices of the estimated autocovariance and autocorrelation functions of stable VAR models by means of the delta method. These covariance matrices can be used to construct asymptotic confidence bands for the estimated autocovariance and autocorrelation functions to assess the underlying estimation uncertainty. The usefulness of the formulae for empirical work is illustrated by an application to inflation and output gap data for the U.S. economy indicating the existence of a significant short-run Phillips-curve tradeoff.First version received: November 2002/Final version received: September 2003