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Sectoral Structure and Economic Growth

Author

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  • Dobrescu, Emilian

    (Centre for Macroeconomic Modelling, Romanian Academy)

Abstract

The main goal of the present work is to reveal the advantages of introducing the so-called structural coefficient (SC) in economic analysis. SC is defined as an indicator of the similarity between a given sectoral structure and another, which is admitted as a referential. Consequently, the paper is organized as follows. The first chapter is consecrated to computational formulas applicable for the estimation of such a measure. Ten possible algorithms are examined and five are retained as adequate for empirical investigations. The second chapter discusses, using WB Statistics for the World Economy, two important questions concerning the structural coefficient (SC): “Is SC an authentic “numeraire”? and “Can SC be rather considered as an “attractor”?”. The paper inclines towards the second supposition. In the third chapter, the famous binomial “sectoral structure-economic growth”, comments based on analytical valences of the structural coefficient (SC) are provided. With this aim, the Toda–Yamamoto version of Granger causality test is applied. Several conclusions and further research lines end the paper. The necessary statistical appendices and references are included.

Suggested Citation

  • Dobrescu, Emilian, 2011. "Sectoral Structure and Economic Growth," Working Papers of Macroeconomic Modelling Seminar 112401, Institute for Economic Forecasting.
    • Handle: RePEc:rjr:wpmems:112401
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    3. Dinu, Marin & Marinas, Marius-Corneliu & Socol, Cristian & Socol, Aura-Gabriela, 2014. "Testing the Endogeneity of Trade and Financial Integration and Sectoral Specialization in an Enlarged Euro Area," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 86-104, March.
    4. Dorin JULA & Nicolae-Marius JULA, 2017. "Foreign Direct Investments and Employment. Structural Analysis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 29-44, June.
    5. Raileanu Szeles, Monica, 2014. "A Multidimensional Approach to the Inclusiveness of economic Growth in the New Member States," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-24, June.
    6. Emilian Dobrescu, 2015. "Net Indirect Taxes and Sectoral Structure of Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-29, June.
    7. Jula, Dorin & Jula, Nicolae Marius, 2013. "Economic Growth and Structural Changes in Regional EmploymenT," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 52-69, June.
    8. Albu, Lucian Liviu, 2013. "Foreign Trade and FDI as Main Factors of Growth in the EU," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 7-17, June.
    9. Carolina Román & Henry Willebald, 2024. "The structural and historical relevance of services in Uruguay. A long run approach (1870-2020)," Documentos de Trabajo (working papers) 24-09, Instituto de Economía - IECON.
    10. Mihaela-Nona Chilian & Marioara Iordan & Carmen Beatrice Pauna, 2016. "Real and structural convergence in the Romanian counties in the pre-accession and post-accession periods," ERSA conference papers ersa16p320, European Regional Science Association.

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    More about this item

    Keywords

    structure; structural coefficient; economic growth; Granger causality test;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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