New Economics Papers
on Efficiency and Productivity
Issue of 2012‒04‒17
ten papers chosen by

  1. Measuring Italian university efficiency: a non-parametric approach By Monaco, Luisa
  2. Efficiency evaluation of Greek equity funds By Vassilios, Babalos; Guglielmo-Maria, Caporale; Philippas, Nikolaos
  3. Selecting between different productivity measurement approaches: An application using EU KLEMS data By Giraleas, Dimitris; Emrouznejad , Ali; Thanassoulis, Emmanuel
  4. Linkage between productivity and innovation in different service sectors By Rõigas, Kärt
  5. The Costs of Corruption in the Italian Solid Waste Industry By Graziano Abrate; Fabrizio Erbetta; Giovanni Fraquelli; Davide Vannoni
  6. The Agricultural Productivity Gap in Developing Countries By Douglas Gollin; David Lagakos; Michael E. Waugh
  7. Asymmetric trade liberalization, sector heterogeneity and industry productivity growth By Antonio Navas Ruiz
  8. Productivity and the Welfare of Nations By Susanto Basu; Luigi Pascali; Fabio Schiantarelli; Luis Serven
  9. A decomposition of profit inefficiency into price expectation error, preferences towards risk and technical inefficiency By Jean-Philippe Boussemart; David Crainich; Hervé Leleu
  10. Bank firm nexus and its impact on firm performance: an Indian case study By Saumitra, Bhaduri; Sunanda, Rathi

  1. By: Monaco, Luisa
    Abstract: This work analyses the performance of Italian universities taking into account technical efficiency. The study provides an assessment of levels of technical efficiency taking into account also environmental factors. We focus on the relationship between levels of technical efficiency and university students dropouts. The efficiency analysis, using Data Envelopment Analysis, w.r.t. the 2009/10 academic year, shows that universities belonging to the private sector have higher efficiency scores than public owned universities. Moreover, a difference arises on a geographical basis where centre-northern universities are generally more efficient than southern ones.
    Keywords: Technical efficiency – DEA – Second stage analysis; Technical efficiency – DEA – Second stage analysis JEL Classification:
    JEL: C14 I23 I21
    Date: 2011–12–10
  2. By: Vassilios, Babalos; Guglielmo-Maria, Caporale; Philippas, Nikolaos
    Abstract: This study assesses the relative performance of Greek equity funds employing a non-parametric method, namely Data Envelopment Analysis (DEA). Specifically, we evaluate the funds’ total productivity change using the DEA-based Malmquist Index. Our results reveal significant losses in funds’ productivity for the period of 2003–2009, which calls for the attention of domestic policy makers and market regulators. Significant implications for the investors’ fund selection process arise from our analysis since we are able to identify potential sources of operational inefficiencies. Employing a panel logit model we document a significant negative relationship between the probability of being efficient and funds’ size, a finding which may be related to the microstructure of the domestic stock market.Furthermore, we provide evidence against the notion of funds’ mean-variance efficiency.
    Keywords: Data envelopment analysis;Operational efficiency;Equity funds DEA-Malmquist productivity index
    JEL: G14 G15 G23 G21
    Date: 2012–05
  3. By: Giraleas, Dimitris; Emrouznejad , Ali; Thanassoulis, Emmanuel
    Abstract: Over the years, a number of different approaches were developed to measure productivity change, both in the micro and the macro setting. Since each approach comes with its own set of assumptions, it is not uncommon in practice that they produce different, and sometimes quite divergent, productivity change estimates. This paper introduces a framework that can be used to select between the most common productivity measurement approaches based on a number of characteristics specific to the application/dataset at hand; these were selected based on the results of previous simulation analysis that examined the accuracy of different productivity measurement approaches under different conditions. The characteristics in question include input volatility through time, the extent of technical inefficiency and noise present in the dataset and whether the parametric approaches are likely to suffer from functional form miss-specification and are examined using a number of well-established diagnostics and indicators. Once assessed, the most appropriate approach can be selected based on its relative accuracy under these conditions; accuracy can in turn be assessed using simulation analysis, either previously published or designed specifically to emulate the characteristics of the application/dataset at hand. As an example of how this selection framework can be implemented in practice, we assess the productivity performance of a number of EU countries using the EU KLEMS dataset.
    Keywords: Data envelopment analysis; Productivity and competitiveness; Simulation; Stochastic Frontier Analysis; Growth accounting
    JEL: O47 C15 D24
    Date: 2012–03
  4. By: Rõigas, Kärt
    Abstract: The purpose of the paper is to find out whether linkages between productivity and innovation are different among Estonian service sector sub-sectors. In this paper productivity is measured as value added per employee. An original approach toward measurement of productivity is used, decomposing it into three components: labour costs, depreciation and gross profit per employee. Four types of innovation are studied: product, process, organizational and marketing innovation. The empirical analysis is based on productivity data from the Estonian Business Register and innovation data from the Estonian Community Innovation Survey 5, covering the period between 2004 and 2006. Results based on Estonian service sectors reveal that in different sub-sectors different types of innovation are linked to productivity. Still, all linkages between innovation and productivity or its components are positive. There is one exception: among assisting services marketing innovation and gross profit are negatively associated with each other. --
    Keywords: service sector,productivity,productivity components,four innovation types
    Date: 2011
  5. By: Graziano Abrate (Department of Business Management and Environment, University of Eastern Piedmont); Fabrizio Erbetta (Department of Business Management and Environment, University of Eastern Piedmont); Giovanni Fraquelli (Department of Business Management and Environment, University of Eastern Piedmont); Davide Vannoni (Department of Economics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino, Italy)
    Abstract: The paper investigates the link between corruption and efficiency by using a rich micro-level dataset concerning solid waste collection activities in 529 Italian municipalities observed over the years 2004-2006. In order to test the impact of corruption on cost efficiency we estimate a stochastic latent class frontier approach, which accounts for technological heterogeneity across units. The results of our estimates show that corruption significantly increases inefficiency, a finding which is robust to the inclusion of alternative local corruption indicators and of other control variables such as geographical, demographic and political factors. Finally, we find that the impact of corruption tends to be greater in the southern regions of the country and for those municipalities which are less involved in recycling activities.
    Keywords: corruption, cost inefficiency, latent class stochastic frontier, solid waste
    JEL: C33 D24 D73 Q53
    Date: 2012–04
  6. By: Douglas Gollin; David Lagakos; Michael E. Waugh
    Date: 2011
  7. By: Antonio Navas Ruiz (Dpto. Fundamentos del Análisis Económico)
    Date: 2012–03
  8. By: Susanto Basu; Luigi Pascali; Fabio Schiantarelli; Luis Serven
    Abstract: We show how to relate the welfare of a country's infinitely-lived representative consumer to observable aggregate data. To a first order, welfare is summarized by total factor productivity and by the capital stock per capita. These variables suffice to calculate welfare changes within a country, as well as welfare differences across countries. The result holds regardless of the type of production technology and the degree of market competition. It applies to open economies as well, if total factor productivity is constructed using domestic absorption, instead of gross domestic product, as the measure of output. It also requires that total factor productivity be constructed with prices and quantities as perceived by consumers, not firms. Thus, factor shares need to be calculated using after-tax wages and rental rates and they will typically sum to less than one. These results are used to calculate welfare gaps and growth rates in a sample of developed countries with high-quality total factor productivity and capital data. Under realistic scenarios, the U.K. and Spain had the highest growth rates of welfare during the sample period 1985-2005, but the U.S. had the highest level of welfare.
    JEL: D24 D90 E20 O47
    Date: 2012–04
  9. By: Jean-Philippe Boussemart (IESEG School of Management (LEM-CNRS) and University Lille 3); David Crainich (CNRS-LEM (UMR 8179) and IESEG School of Management); Hervé Leleu (CNRS-LEM (UMR 8179) and IESEG School of Management)
    Abstract: The paper addresses the decomposition of firms’ profit inefficiency (i.e. the difference between the observed profit and the maximal profit that could have been earned) in a context of output price uncertainty. More precisely, we separate this inefficiency into price expectation error, expected profit loss due to risk preference and technical inefficiency. Within this decomposition, the allocative inefficiency is explicitly defined as the result of price expectation error and risk attitude instead of being a residual (as in the traditional profit inefficiency decomposition). Our theoretical model is then implemented in a Data Envelopment Analysis framework which allows the separate estimation of each term of the decomposition. Besides, we offer an operational tool to reveal producers’ risk preferences and to measure their intensity. While the DEA approach is appealing since it imposes very few assumptions on the production set, its main drawback lies in the sensitivity of the measure to outliers. We therefore adapt our model to a robust approach.
    Keywords: Profit Inefficiency, Allocative Inefficiency, Technical Inefficiency, Risk Preference, Risk Aversion, Data Envelopment Analysis, Robust DEA
    JEL: D21 D81
    Date: 2012–03
  10. By: Saumitra, Bhaduri; Sunanda, Rathi
    Abstract: The paper examines the role of banking relationships on firm performance for a sample of Indian manufacturing firms. The two variables used to portray banking relationships are: the extent of bank borrowing and the number of banking relationships maintained by a firm. Analysis suggests that while the extent of bank borrowing has a negative impact on firm performance, the multiple banking relationships maintained by a firm positively enhances firm performance. In addition, firm performance plays an important role in influencing bank borrowing and the number banking relationships a firm maintains. While banking relationships are positively impacted by firm performance, results suggest nonlinearity between bank financing and firm performance, suggesting the possibility of a potential debt overhang concern. This implies that firms with low growth opportunities tend to borrow more from banks due to lack of other opportunities to finance their investments. However, firms beyond a certain threshold of profitability tend to employ lesser debt to finance their investments in order to prevent the wealth transfer from shareholders to creditors.
    Keywords: Bank Firm Realationship India
    JEL: E52
    Date: 2012–04–10

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