Alexander Schiersch

Temporary Agency Work and Firm Competitiveness: Evidence from German Manufacturing Firms

This paper addresses the relationship between the utilization of temporary agency workers by firms and their competitiveness measured by unit labor costs, using a rich, newly built, data set of German manufacturing enterprises. The analysis is conducted by applying different panel data models while taking the inherent selection problem into account. Making use of dynamic panel data models allows us to control for firm specific fixed effects as well as for potential endogeneity of explanatory variables. The results indicate a U-shaped relationship between the extent that temporary agency workers are used and the competitiveness of firms.

Empiricism Meets Theory: Is the Boone-Indicator Applicable?

Boone (2008a) proposes a new competition measure based on Relative Profit Differences (RPD) with superior theoretical properties. However, the empirical applicability and robust-ness of the Boone-Indicator is still unknown. This paper aims to address that question. Using a rich, newly built, data set for German manufacturing enterprises, we test the empirical valid-ity of the Boone-Indicator using cartel cases. Our analysis reveals that the traditional regres-sion approach of the indicator fails to correctly indicate competition. A proposed augmented indicator based on RPDs performs better. The traditional Lerner-Index is still the only meas-ure that correctly indicates the expected competitive changes.

Is the Boone-Indicator Applicable? – Evidence from a Combined Data Set of German Manufacturing Enterprises

Summary Boone (2008a) proposes a new competition measure based on Relative Profit Differences (RPD) that, from its theoretical properties, proves to be more robust than the Lerner-Index. However, the proof of the empirical practicability and robustness of the Boone-Indicator is missing. To fill this gap, we use a rich, newly built, data set for German manufacturing enterprises and test its empirical validity using cartel cases. Since all of the identified cartels significantly restricted market competition, we expect fiercer competition after the uncovering. We asses the validity of the indicators by comparing the indicated competition levels before and after the cartels were uncovered and stopped. The Boone-Indicator is calculated as RPDs and as a beta coefficient of a log-log regression. The Lerner-Index is used as a benchmark. Our analysis finds that the Boone-Indicator, based on a simple regression approach, fails to correctly indicate competition. Since the Boone-Indicator, based on pure RPDs, proves to be inapplicable, we propose an augmented indicator based on size-adjusted RPDs, which performs better. However, our findings suggest that, given the information typically available in census data, the Lerner-Index is still the only measure that correctly indicates competitive changes.

Inefficiency in the German Mechanical Engineering Sector

This paper aims to examine the relative efficiency of German engineering firms using a sample of roughly 23,000 observations between 1995 and 2004. As these firms had been successful in the examination period in terms of output- and export-growth, it is expected that a majority of firms is operating quite efficiently and that the density of efficiency scores is skewed to the left. Moreover, as the German engineering industry is dominated by medium sized firms, the question arises whether these firms are the most efficient ones. Finally an increasing efficiency gap between size classes over time is important since that would be a signal for a structural problem within the industry. The analysis - using recently developed DEA methods like bootstrapping or outlier detection - contradicts the two first expectations. The firms proved to operate quite inefficiently with an overall mean of 0.69, and efficiency differs significantly with firm size whereas medium sized firms being on average the least efficient ones. When looking at changes in efficiency over time, we find a decreasing efficiency gap between size classes.

TFP, Labor Productivity and the (Un)Observed Labor Input: Temporary Agency Work

The study focuses on the question of whether productivity estimates are biased due to the emergence of a new input that is usually omitted: temporary agency worker (TAW). The study analyzes labor productivity and TFP by means of a structural approach using a representative dataset of German manufacturing firms. The empirical results show, once TAW is taken into account, that: i) labor productivity in most manufacturing sectors is significantly lower; ii) average TFP differs significantly in most sectors; but iii) the coefficients for regular labor are not significantly different between estimations with and without TAW.

Why is TFP growth sectorally concentrated

Research shows that total factor productivity (TFP) growth is weak in European countries. This is inter alia attributed to the fact that substantial TFP growth is limited to a few industries. Because TFP growth is typically understood as technological progress, it is concluded that technology diffusion between sectors in Europe is hampered. We use EU KLEMS data sets to decompose sectoral TFP for nine European countries by means of a Malmquist approach in order to identify potential sources besides technical progress. Applying Harberger diagrams, we describe the sectoral distribution of TFP growth, efficiency gains and losses, economies of scale and technological progress. The analysis reveals that technological progress is quite evenly distributed across sectors in most European countries. The wide scattering of TFP growth is explained by deviating efficiency developments and the unused economies of scale. We conclude that the technology transfer between sectors in most European countries seems to work. Therefore, Europe in general does not need a new technology policy, but a further integration of the markets and a reduction of national market entry barriers. This requires further unification of pan-European standards in fields like trade and crafts codes or consumer protection policies.

Is Technical Progress Sectorally Concentrated?: An Empirical Analysis for Western European Countries

Previous research shows that technical progress at the industry level, measured by sectoral TFP growth, is more localized in continental European countries than in Anglo-Saxon countries. We use EU KLEMS data sets to decompose sectoral TFP for nine European countries by means of a Malmquist approach, in order to separate technical change. Applying Harberger diagrams, we describe the sectoral patterns of technical progress. The analysis reveals that in most European countries technological progress is much more evenly distributed across sectors than TFP.