Jens J. Krüger

PRODUCTIVITY AND STRUCTURAL CHANGE: A REVIEW OF THE LITERATURE

This paper is a survey of the existing research on structural change at various levels of aggregation with a special focus on the relation to productivity and technological change. The exposition covers the research concerning the development of the three main sectors of the private economy, multisector growth models and recent evolutionary theories of structural change. Empirical studies of the reallocation of market or sector shares as a result of differential productivity developments are also discussed. The synthesis emphasizes the crucial interaction of supply- and demand-side forces in shaping structural change. Copyright 2008 The Author. Journal compilation

A Monte Carlo study of old and new frontier methods for efficiency measurement

This study presents the results of an extensive Monte Carlo experiment to compare different methods of efficiency analysis. In addition to traditional parametric–stochastic and nonparametric–deterministic methods recently developed robust nonparametric–stochastic methods are considered. The experimental design comprises a wide variety of situations with different returns-to-scale regimes, substitution elasticities and outlying observations. As the results show, the new robust nonparametric–stochastic methods should not be used without cross-checking by other methods like stochastic frontier analysis or data envelopment analysis. These latter methods appear quite robust in the experiments.

Knowledge and Creative Destruction over the Industry Life Cycle: The Case of the German Automobile Industry

This paper investigates how the survival of firms over the industry life cycle is affected by different kinds of knowledge, namely post-entry experience, pre-entry experience, and knowledge acquired by innovative activity. Therefore, a statistical survival analysis is performed for the German automobile industry over the period 1886- 1939 which applies a new approach that links instrumental variable estimation with the Cox regression. The main results are that all three knowledge components exert a significantly positive effect on the survival of firms. Furthermore, innovative activity is able to compensate for lacking pre-entry or post-entry experience, completely in accord with Schumpeterian creative destruction.

Optimal Directions for Directional Distance Functions: An Exploration of Potential Reductions of Greenhouse Gases

This study explores the reduction potential of greenhouse gases for major pollution emitting countries of the world using nonparametric productivity measurement methods and directional distance functions. In contrast to the existing literature we apply optimization methods to endogenously determine optimal directions for the e ciency analysis. These directions represent the compromise of output enhancement and emissions reduction. The results show that for reasonable directions the adoption of best-practices would lead to sizable emission reductions in a range of about 20 percent compared to current levels.

Capacity utilization and technology shocks in the US manufacturing sector

The ability of real business cycle models to generate reasonable aggregate fluctuations depends on the time series properties of technology shocks measured by the change of total factor productivity. Three specifications of a non‐parametric productivity analysis which correct to different degrees for variations of capacity utilization are compared in this article using data for three‐ and four‐digit US manufacturing industries during the years 1958–1996. The results show that correcting for utilization generally leads to substantially smaller technology shocks that are less strongly correlated with growth of output and hours. Moreover, the probability of technological regress is considerably lower after the correction.

THE SOURCES OF AGGREGATE PRODUCTIVITY GROWTH: US MANUFACTURING INDUSTRIES, 1958–1996

The sources of aggregate productivity growth are explored using detailed data for four-digit US manufacturing industries during 1958-96 and a decomposition formula that allows us to quantify the contribution of structural change. Labour productivity as well as total factor productivity are considered with either value-added or employment shares serving as aggregation weights. It is shown that structural change generally works in favour of industries with increasing productivity. This effect is particularly strong in the years since 1990, in high-tech industries and in durable goods producing industries. The impact of the computer revolution can be clearly identified.

Inspecting the Poverty-Trap Mechanism: A Quantile Regression Approach

The issue of poverty traps is assessed using quantile regression. An augmentation of the usual convergence regressions by quadratic and cubic terms is used with emphasis on curve fitting rather than parameter estimation. The results show that the generic mechanism leading to poverty traps predominantly applies to countries with relatively low levels of income per capita or per worker that simultaneously have low growth rates in the vicinity and below the lowest quintile of the growth rate distribution. The validity of the results is supported by a nonparametric variant of quantile regression.

Knowledge, profitability and exit of German car manufacturing firms

In this paper, the profitability of German car manufacturing firms is related to different indicators for the knowledge incorporated in the firms since the birth of the industry in 1886. The analysis is performed with an ordered probit model, where information about the mode of exit of the firms is exploited to construct a latent variable for profitability. Knowledge is represented by the number of patents, learning-by-doing and entrepreneurial experience before entry. The results show that knowledge is significantly positively related to firm profitability and that each of the three knowledge forms exerts an independent effect.

Comment on "A new clustering approach using data envelopment analysis"

In a recent paper Po, Guh and Yang [Po, R.-W., Guh, Y.-Y., Yang, M.-S., 2009. A new clustering approach using data envelopment analysis. European Journal of Operational Research 199, 276-284] propose a new algorithm for forming clusters from the results of a DEA analysis. In this comment it is explained that the algorithm only generates information that is readily available from the usual DEA results.

Small Sample Properties of the Wilcoxon Signed Rank Test with Discontinuous and Dependent Observations

This Monte-Carlo study investigates sensitivity of the Wilcoxon signed rank test to certain assumption violations in small samples. Emphasis is put on within-sample-dependence, between-sample dependence, and the presence of ties. Our results show that both assumption violations induce severe size distortions and entail power losses. Surprisingly, these consequences do vary substantially with other properties the data may display. Results provided are particularly relevant for experimental settings where ties and within-sample dependence are frequently observed.