New Economics Papers
on Efficiency and Productivity
Issue of 2011‒12‒05
seven papers chosen by



  1. The productivity performance of Finnish and Norwegian dairy farms: the effect of joining/not joining the EU By Marte Bjørnsen; Gudbrand Lien; Timo Sipiläinen
  2. Human Capital, R&D and Productivity Convergence of European Regions. A spatial analysis of RHOMOLO's semi endogenous growth approach. By Fabio Manca; Giuseppe Piroli
  3. PUBLIC SCHOOL EFFICIENCY USING DATA ENVELOPMENT ANALYSIS: AN EMPIRICAL APPLICATION FOR BRAZIL By Isabel Raposo; Tatiane Menezes
  4. URBAN DUTCH: Synergy Between Transport Infrastructures and Cities. Towars a Higher Productivity of the Economy By Hugo Priemus
  5. Productivity in the Spanish regions during the recent economic cycles By Simon Sosvilla-Rivero
  6. AGRICULTURAL PRODUCTIVITY AND OFF-FARM LABOR DECISIONS BY HEADS AND SPOUSES IN NICARAGUA: A SEMIPARAMETRIC ANALYSIS USING PANEL DATA By Alex Almeida; Boris Bravo-Ureta
  7. IDENTIFICATION OF TECHNOLOGICAL DISTRICTS: THE CASE OF SPAIN By Antonio Fuster Olivares; Jose Miguel Giner Pérez; MªJesús Santa María Beneyto

  1. By: Marte Bjørnsen; Gudbrand Lien; Timo Sipiläinen
    Abstract: Dairy production has long been the most important production line in Finnish and Norwegian agriculture. Prior to Finland joining the EU, farm structure as well as national agricultural policy was very similar in the two countries. In this paper, we explore development and differences in productivity and efficiency trends in the two countries before and after 1994 when Finland joined the EU. The challenge is to isolate the effect of EU-membership from other events like introduction of milk quotas, and more generally, changes in agricultural policy and macro-economic factors. We model productivity growth by means of standard production efficiency frontier models on twenty-year panels of Finnish and Norwegian farm accounts data.
    Date: 2011–09
    URL: http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa11p793&r=eff
  2. By: Fabio Manca; Giuseppe Piroli
    Abstract: The aim of the paper is to test the Benhabib and Spiegel (2005) productivity (TFP) catch-up framework on European regions. Differences in the stock of human capital across regions are hypothesized to be the cause of differences in the speed by which follower regions converge and catch-up with the technology frontier. We find robust empirical evidence for this hypothesis. Also, we find evidence of complementarities between R&D expenditures and human capital accumulation for which R&D impacts TFP growth as long as a critical mass for the stock of human capital is reached. The results are robust to sectoral disaggregations and to the choice of a country or sectoral specific leader in the TFP gap computation and to control for spatial dependence across European regions.
    Date: 2011–09
    URL: http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa11p816&r=eff
  3. By: Isabel Raposo; Tatiane Menezes
    Abstract: This paper studies the educational efficiency as determined only by the variables directly controlled by the school, isolated from the influence of other environmental characteristics, such as student’s socioeconomic status, that might influence efficiency as well. An alternative application of Simar and Wilson (2007) two-stage DEA’s approach is adopted using data from public schools in the basic education level from the Northeast Region of Brazil. The results have showed that the rank of efficiency becomes much more homogeneous after isolating from the effect of environmental variables as compared to the rank produced from a simple one-stage DEA.
    Date: 2011–09
    URL: http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa11p1594&r=eff
  4. By: Hugo Priemus
    Date: 2011–09
    URL: http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa11p1267&r=eff
  5. By: Simon Sosvilla-Rivero
    Abstract: The Spanish regions are facing a severe recession caused by the international financial crisis that has overlapped with the correction that had been recorded in the property market, which has led to a sharp drop in economic activity and a rapid destruction process employment. In these circumstances it is a priority to begin a new growth path based on a more productive and sustainable pattern, which enhances competitive sectors and contribute to the creation and consolidation of employment. This paper has attempted to shed light on what branches of production can be the basis for a new production model of the Spanish economy to overcome the weaknesses in the present, making special emphasis in services To this end, the behavior of productivity during expansions will be analyzed for twenty production branches by applying the methodology proposed by Leamer (2007), based on the decomposition of contributions to the growth of the productivity of each of these branches in 'normal' and 'outstanding'. The results will identify production branches that have contributed to the weakening of productivity during recessions as well as those that have created an important stimulus to productivity during expansions.
    Date: 2011–09
    URL: http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa11p57&r=eff
  6. By: Alex Almeida; Boris Bravo-Ureta
    Abstract: The objective of this paper is to analyze the determinants of off-farm labor supply by heads of household and their spouses in Nicaragua. Using a three-year balanced panel dataset, we refine the approach introduced by Jacoby (1993) and Skoufias (1994) to estimate shadow wages and shadow income, and we also apply the semiparametric approach developed by Kyriazidou (1997) to panel data which mitigates biases not only from some key individual and farm time-invariant characteristics but also from sample selection. The main findings suggest that the shadow wages and shadow income of household heads and their spouses play a major role in the supply of labor to off-farm activities. When the marginal productivity of agricultural households goes up, there is a reduction in hours allocated to off-farm activities. We also find that education, age, remittances, household size, and whether sons and daughters work are related to off-farm labor supply, with significant differences between their effect on heads and their spouses.
    Date: 2011–09
    URL: http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa11p508&r=eff
  7. By: Antonio Fuster Olivares; Jose Miguel Giner Pérez; MªJesús Santa María Beneyto
    Abstract: In recent years, several contributions have been focused on a new sort of productive systems that share some characteristics with Marshallian industrial districts. These contributions have analysed the competitiveness of these new areas and how have been promoted by policy makers. In this line, the Marshallian concept of industrial district has been increasingly related to high technology and innovation in order to analysis technological districts or clusters. The aim of this research is to show how these new areas have characteristics are not similar to those shown by traditional industrial districts. Therefore, framework and techniques for analysis that have been traditionally used for industrial districts must be adapted for identifying technological districts. Specifically, some reflections about the framework analysis of sector and spatial units are introduced in the first part of this research as well as those techniques that can be useful to identify and analyse technological districts. Next, the analysis is focused on the identification of technological districts in Spain. A multivariate analysis will be applied to calculate a synthetic index that will be used to identify those areas with a high degree of specialization in high and medium technology activities. This synthetic index will collect data about those technological activities that are involved not only in manufacturing but also in activities of innovation and R&D. Until now, there have been not many attempts to identify technological clusters through the application of quantitative methodologies; therefore, the purpose of this research is to contribute to the enhancement of knowledge about these areas in Spain. Keywords: technological districts, clusters, location, spatial agglomerations.
    Date: 2011–09
    URL: http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa11p1541&r=eff

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