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Small area estimation of labor productivity for the Italian manufacturing SME cross-classified by region, industry and size

Author

Listed:
  • Enrico Fabrizi
  • Maria Ferrante
  • Carlo Trivisano

Abstract

In this paper we propose a new small area estimation methodology aimed at the estimation of Value Added, Labor Cost and related competitiveness indicators for subsets of the population of Italian small and medium sized manufacturing firms classified according to geographical region, industrial sector and firms size. This disaggregation is needed in regional comparisons in order to avoid the confounding effect of sectorial and firm size composition of a region's manufacturing industry. We use data on the Small and Medium Enterprises sample survey conducted by the Italian National Statistical Institute (year 2009) that provided us this information in the framework of the BLUE-ETS project. The estimates obtained with our method are more reliable than those that would have been obtained using standard survey weighted estimators, and offer therefore the basis for more sound economic analysis. The small area methods that we propose are model based and take into account the peculiarities of business such as the skewness of target variables' distributions. For this reason the model we propose is based on the log-normal distribution. We consider a multivariate model in which two different variables (Value Added and Labor Cost) and jointly modeled in order to exploit their correlation. We adopt a Bayesian approach to inference. The problem of prior specification is considered and two alternative solutions compared. Since we produce estimates for several variables and hundreds of subset of the target population results are difficult to summarize. A general conclusion may be that, for Italy, the North-South divide in productivity levels is more apparent in capital and knowledge intensive sectors, especially when industrial districts are present. The productivity gap tends to grow for larger firms, but there exists several exception to this rule. Many industries traditionally associated to the Italian productive system (furniture, clothing, textile) are characterized by low labor productivity levels: in these cases the productivity gap between Northern and Southern regions is less pronounced or absent. As the paper is mostly about the methodology needed to obtain the estimates, it is relevant not only for those interested in Italian economy. The same ideas may be applied to data from other countries. The relevance of the mentioned indicators is highlighted by the increasing divergences in economic competitiveness among regions within the different EU member states observed in these last years.

Suggested Citation

  • Enrico Fabrizi & Maria Ferrante & Carlo Trivisano, 2013. "Small area estimation of labor productivity for the Italian manufacturing SME cross-classified by region, industry and size," ERSA conference papers ersa13p894, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa13p894
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    File URL: https://www-sre.wu.ac.at/ersa/ersaconfs/ersa13/ERSA2013_paper_00894.pdf
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    References listed on IDEAS

    as
    1. International Monetary Fund, 2011. "Italy: Selected Issues," IMF Staff Country Reports 2011/176, International Monetary Fund.
    2. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    3. R. A. Sugden & T. M. F. Smith & R. P. Jones, 2000. "Cochran's rule for simple random sampling," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 787-793.
    4. Enrico Fabrizi & Carlo Trivisano, 2011. "Bayes estimators of log-normal means with finite quadratic expected loss," Quaderni di Dipartimento 6, Department of Statistics, University of Bologna.
    5. Fabrizi, Enrico & Ferrante, Maria Rosaria & Pacei, Silvia & Trivisano, Carlo, 2011. "Hierarchical Bayes multivariate estimation of poverty rates based on increasing thresholds for small domains," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1736-1747, April.
    6. Dan HEDLIN, 2008. "Small Area Estimation: a Practitioner’s Appraisal," Rivista Internazionale di Scienze Sociali, Vita e Pensiero, Pubblicazioni dell'Universita' Cattolica del Sacro Cuore, vol. 116(4), pages 407-417.
    7. International Monetary Fund, 2007. "Italy: Selected Issues," IMF Staff Country Reports 2007/065, International Monetary Fund.
    8. International Monetary Fund, 2003. "Italy: Selected Issues," IMF Staff Country Reports 2003/352, International Monetary Fund.
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    Cited by:

    1. Timo Schmid & Nikos Tzavidis & Ralf Münnich & Ray Chambers, 2016. "Outlier Robust Small-Area Estimation Under Spatial Correlation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(3), pages 806-826, September.
    2. Schmid, Timo & Tzavidis, Nikos & Münnich, Ralf & Chambers, Ray, 2015. "Outlier robust small area estimation under spatial correlation," Discussion Papers 2015/8, Free University Berlin, School of Business & Economics.

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    More about this item

    Keywords

    competitiveness; value added; labor cost; sample survey; Bayesian inference;
    All these keywords.

    JEL classification:

    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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