New Economics Papers
on Efficiency and Productivity
Issue of 2008‒05‒31
ten papers chosen by

  1. Intra-Sectoral Structural Change and Aggregate Productivity Development. A Robust Stochastic Nonparametric Frontier Function Approach By Jens J. Krüger
  2. Firm Growth and Productivity Growth: Evidence from a Panel VAR By Alex Coad; Tom Broekel
  3. Measuring the Returns of Research and Development: An Empirical Study of the German Manufacturing Sector over 45 Years By Guenter Lang
  4. European Railway Deregulation: The Influence of Regulatory and Environmental Conditions on Efficiency By Heike Wetzel
  5. Local Innovation Systems and Benchmarking By Uwe Cantner
  6. Business Constraints and Growth Potential of Micro and Small Manufacturing Enterprises in Uganda By Esther K. Ishengoma; Robert Kappel
  7. Growth Processes of Italian Manufacturing Firms By Alex Coad; Rekha Rao
  8. Does Teacher Quality Affect Student Performance? Evidence from an Italian University By Maria, De Paola
  9. Spatial econometric analysis of the determinants of location of manufacturing industry and market services sectors in Poland By Tomasz Brodzicki; Dorota Ciolek
  10. The Effect of CSR on Stock Performance: New Evidence for the USA and Europe By Urs von Arx; Andreas Ziegler

  1. By: Jens J. Krüger (Friedrich-Schiller-University Jena, Department of Economics)
    Abstract: This paper investigates the sources of total factor productivity growth in the German manu- facturing sector, 1981-1998. Decomposition formulae for aggregate productivity growth are used to identify the effects of structural change and entry-exit on aggregate productivity growth. Documented is a substantial rise of productivity growth after the German reunifica- tion. The bulk of this rise can be attributed to structural change and entry-exit. Two methodo- logical refinements are implemented, the first is the application of a robust stochastic non- parametric approach to frontier function analysis and the second is the calculation of boot- strap confidence intervals for the components of the productivity decompositions.
    Keywords: productivity decomposition, structural change, manufacturing
    JEL: D24 O12 L60
    Date: 2008–05–06
  2. By: Alex Coad (Max Planck Institute of Economics, Jena, Germany; Centre d'Economie de la Sorbonne, Equipe MATISSE, Univ. Paris 1 - CNRS); Tom Broekel (Max Planck Institute of Economics, Jena, Germany)
    Abstract: This paper offers new insights into the processes of ï¬rm growth by applying a reduced-form vector autoregression (VAR) model to longitudinal panel data on French manufacturing ï¬rms. We observe the co-evolution of key variables such as growth of employment, sales, and gross operating surplus, as well as growth of multifactor productivity. It seems that employment growth is negatively associated with subsequent growth of productivity. This latter result, however, is sensitive to our choice of productivity indicator, i.e. multifactor productivity or labour productivity.
    Keywords: Firm Growth, Panel VAR, Productivity Growth, Industrial Dynamics, Non-parametric frontier analysis
    JEL: L25 L20
    Date: 2007–12–18
  3. By: Guenter Lang (Faculty of Management Technology, The German University in Cairo)
    Abstract: Motivated by recent statistics that show significant growth in labor productivity, this paper seeks to analyze the relationship between domestic R&D, knowledge stock and productivity dynamics. Time series data of the German manufacturing industry is used to estimate a variable cost function with the stock of knowledge being dependent upon current and past R&D spending. The estimates indicate that 50 percent of the effects of R&D on the knowledge stock appear within four years. However, the rate of return on R&D are shown to be drastically declining; recent rates of return on R&D are estimated to have reached an all-time low spanning the last 45 years. Current yields of R&D are only one third compared to the sixties. In conclusion, though the productivity slowdown of the seventies seems to have been overcome, this is not attributed to R&D investments.
    Keywords: Productivity, innovation, research, development, technology, productivity slowdown
    JEL: D24 L60 O31
    Date: 2008–05
  4. By: Heike Wetzel (Institute of Economics, Leuphana University of Lüneburg)
    Abstract: The objective of this paper is to analyze the impact of regulatory and environmental conditions on technical effciency of European railways. Using a panel data set of 31 railway firms from 22 European countries from 1994 to 2005, a multioutput distance function model, including regulatory and environmental factors, is estimated using stochastic frontier analysis. The results obtained indicate positive and negative effciency effects of different regulatory reforms. Furthermore, estimating models with and without regulatory and environmental factors clearly indicates that the omission of environmental factors, such as network density, substantially changes parameter estimates and, hence, leads to biased estimation results.
    Keywords: European railways, technical effciency, stochastic frontier analysis
    JEL: L92 L51 L22
    Date: 2008–05
  5. By: Uwe Cantner (Friedrich-Schiller University, Jena, Economics Department)
    Abstract: This paper reviews approaches used for evaluating the performance of local or regional innovation systems. This evaluation is performed by a benchmarking approach in which a frontier production function can be determined, based on a knowledge production function relating innovation inputs and innovation outputs. In analyses on the regional level and especially when acknowledging regional innovation systems those approaches have to take into account cooperative invention and innovation - the core of the innovation system approach. To make these interactive effects visible, a method is suggested to identify the relative regional impact on cooperative innovative activities.
    Keywords: benchmarking, regional innovation systems, frontier function approaches
    JEL: O3 R11 C2 C6
    Date: 2008–05–13
  6. By: Esther K. Ishengoma (Faculty of Commerce and Management, University of Dar es Salaam, Tanzania); Robert Kappel (GIGA German Institute of Global and Area Studies)
    Abstract: Ugandan micro- and small enterprises (MSEs) still perform poorly. The paper utilizes data collected in Uganda in March and April 2003 to analyze the business constraints faced by these MSEs. Using a stratified random sampling, a sample of 265 MSEs were interviewed. The study focuses on the 105 manufacturing firms that responded to all questions. It examines the extent to which the growth of MSEs is associated with business constraints, while also controlling for owners’ attributes and firms’ characteristics. The results reveal that MSEs’ growth potential is negatively affected by limited access to productive resources (finance and business services), by high taxes, and by lack of market access.
    Keywords: small enterprises, informal sector, growth, manufacturing, Uganda, productivity, business services
    JEL: D21 E26 G38 H25 L25 L26 L6 O12 O14
    Date: 2008–05
  7. By: Alex Coad (Max Planck Institute of Economics, Jena, Germany); Rekha Rao (Tanaka Business School, Imperial College London)
    Abstract: We apply a reduced-form vector autoregression model to analyze the growth processes of Italian manufacturing firms, 1989-1997. We focus in particular on lead-lag associations describing the coevolution of employment growth, sales growth, growth of profits and labour productivity growth. Employment growth precedes sales growth and growth of profits, and in turn sales growth is also associated with subsequent profits growth. There appears to be little feedback of either sales or profits on employment growth, however. There is no clear association of employment growth with subsequent changes in labour productivity, although at the second lag there is a small negative association. Productivity growth, however, is positively associated with subsequent growth of employment and sales. Quantile autoregressions find asymmetries between growth processes for growing and shrinking firms.
    Keywords: Firm Growth, Panel VAR, Employment Growth, Industrial Dynamics, Productivity Growth
    JEL: L25 L20
    Date: 2008–05–06
  8. By: Maria, De Paola
    Abstract: In this paper we analyse whether the characteristics of university teaching staff matter with regards students’ performance and interest in the discipline. We use data on about one thousand students enrolled on the first level degree course in Business and Economics at a medium sized Italian University. Thanks to the random assignment of students to different teaching sections during their first year, we are able to analyze the effect that teachers with different characteristics, in terms of experience and research productivity, produce both on students’ performance, measured in terms of the grades obtained at subsequent exams and courses chosen. Our results suggest that teacher quality has statistically significant effects on students’ grades on subsequent courses. These effects are also robust after controlling for unobserved individual characteristics. On the other hand, we find less clear evidence when relating teacher quality to student involvement with a subject. It emerges that more experienced teachers have a negative impact on the probability of a student’s undertaking additional courses in a subject, while research productivity does not produce a statistically significant effect.
    Keywords: teaching quality; student performance;
    JEL: A2
    Date: 2008–01
  9. By: Tomasz Brodzicki (Faculty of Economics, University of Gdansk); Dorota Ciolek (Faculty of Management, Department of Econometrics, University of Gdansk)
    Abstract: The paper comprises econometric analysis of location determinants of manufacturing industry and market services in Poland. A wide range of location determinants are analyzed taking into account exogenous and semi-endogenous region-specific aspects, sector-specific aspects (such as labor and capital intensity, economies of scale, intensity of forward and backward linkages, wage rates, knowledge intensity and technology level) as well as interactions between sector-specific and region-specific aspects. The analysis is carried out for an unbalanced data panel of manufacturing industry and market services sectors at the level of 3-digit NACE at the NUTS 2 level (16 voivodeships). The data cover the period from 1995 to 2006. We perform the estimation using Restricted Maximum Likelihood method (REML). The results point to positive spatial autocorrelation both for manufacturing industry and market services sectors. Sector-specific and region-specific effects as proxied by sectoral dummies are important.
    Keywords: location, industrial manufacturing, market services, Poland, spatial panel, Restricted Maximum Likelihood method
    JEL: R12 R15 C23 C31
    Date: 2008–05
  10. By: Urs von Arx (CER-ETH, Swiss Federal Institute of Technology (ETH) Zurich, Center of Economic Research); Andreas Ziegler (University of Zurich, Center for Corporate Responsibility and Sustainability)
    Abstract: This paper provides new empirical evidence for the effect of corporate social responsibility (CSR) on corporate financial performance. In contrast to former studies, we examine two different regions, namely the USA and Europe. Our econometric analysis shows that environmental and social activities of a firm compared with other firms within the industry are valued by financial markets in both regions. However, the respective positive effects on average monthly stock returns between 2003 and 2006 appear to be more robust in the USA and, in addition, to be nonlinear. Our analysis furthermore points to biased parameter estimations if incorrectly specified econometric models are applied: The seemingly significantly negative effect of environmental and social performance of the industry to which a firm belongs vanishes if the explanation of stock performance is based on the Fama-French threefactor or the Carhart four-factor models instead of the simple Capital Asset Pricing Model.
    Keywords: Corporate social responsibility, Environmental performance, Financial performance, Asset pricing models.
    JEL: Q56 M14 G12 Q01
    Date: 2008–05

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