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Technical Efficiency and Public Policies in Agriculture: An Analysis for the Eastern Amazon Region

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  • Juliana de Sales Silva

Abstract

The agricultural sector in one of the most dynamic industries of the Brazilian economy and is responsible for about 30% of the GDP of the state of Pará, located in the Brazilian Eastern Amazon region. This is mainly due to the public policies developed for the sector, with emphasis on the National Policy of Technical Assistance and Rural Extension (PNATER) and Rural Credit, in addition to conditional cash transfer programs such as Bolsa Família (Family Allowance). Given this scenario, the purpose of this research is to determine the technical efficiency of the agricultural rural facilities of Pará, and observe the effect of these policies on their inefficiency. The methodology employed in order to achieve these objectives is the stochastic frontier approach, and the data used was obtained from a special tabulation based on the 2006 Agricultural Census. The main results evidence that rural credit policies, social welfare programs, and technical support are important to reduce the technical inefficiency of the rural facilities of the State of Pará. The latter, however, is not statistically significant. Resumen El sector agrícola es uno de los más dinámicos de la economía brasilera y es responsable —aproximadamente— del 30% del PIB del estado de Pará, ubicado en la Amazonía oriental brasilera. Esto se debe —principalmente— a las políticas públicas desarrolladas para el sector, con énfasis en la Política Nacional de Asistencia Técnica y Extensión Rural (PNATER) y Crédito Rural, además de los programas condicionales de transferencia de efectivo, como Bolsa Familia. Ante este escenario, el objetivo de este artículo es determinar la eficiencia técnica de las instalaciones agrícolas rurales en Pará y observar el efecto de estas políticas en su ineficiencia. La metodología utilizada es el enfoque de la frontera estocástica Los datos utilizados se obtuvieron en una tabulación especial basada en el Censo Agrícola de 2006. Los principales resultados muestran que las políticas de crédito rural, los programas de asistencia social y el apoyo técnico son importantes para reducir la ineficiencia técnica de las instalaciones rurales en el Estado de Pará. Sin embargo, esta última no es estadísticamente significativa.

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  • Juliana de Sales Silva, 2021. "Technical Efficiency and Public Policies in Agriculture: An Analysis for the Eastern Amazon Region," Ensayos de Economía 19349, Universidad Nacional de Colombia Sede Medellín.
  • Handle: RePEc:col:000418:019349
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    1. Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May.
    2. Helfand, Steven M. & Levine, Edward S., 2004. "Farm size and the determinants of productive efficiency in the Brazilian Center-West," Agricultural Economics, Blackwell, vol. 31(2-3), pages 241-249, December.
    3. Tim Coelli & Antonio Estache & Sergio Perelman & Lourdes Trujillo, 2003. "A Primer on Efficiency Measurement for Utilities and Transport Regulators," World Bank Publications - Books, The World Bank Group, number 15149, December.
    4. Jock R. Anderson, 2004. "Agricultural Extension: Good Intentions and Hard Realities," The World Bank Research Observer, World Bank, vol. 19(1), pages 41-60.
    5. Nicholas E. Rada & Steven T. Buccola, 2012. "Agricultural policy and productivity: evidence from Brazilian censuses," Agricultural Economics, International Association of Agricultural Economists, vol. 43(4), pages 355-367, July.
    6. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    7. Rada, Nicholas E. & Fuglie, Keith O., 2019. "New perspectives on farm size and productivity," Food Policy, Elsevier, vol. 84(C), pages 147-152.
    8. Chambers,Robert G., 1988. "Applied Production Analysis," Cambridge Books, Cambridge University Press, number 9780521314275.
    9. Ferreira, Monaliza de Oliveira & Ramos, Lúcia Maria & Rosa, Antônio Lisboa Teles da, 2006. "Crescimento da agropecuária cearense: comparação entre as produtividades parciais e total," Brazilian Journal of Rural Economy and Sociology (Revista de Economia e Sociologia Rural-RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 44(3), pages 1-22, September.
    10. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    11. Barros, Emanoel de Souza & Costa, Ecio de Farias & Sampaio, Yony, 2004. "Análise de Eficiência das Empresas Agrícolas do Pólo Petrolina/Juazeiro Utilizando a Fronteira Paramétrica Translog," Brazilian Journal of Rural Economy and Sociology (Revista de Economia e Sociologia Rural-RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 42(4), pages 1-18, December.
    12. Helfand, Steven M. & Magalhaes, Marcelo M. & Rada, Nicholas E., 2015. "Brazil's Agricultural Total Factor Productivity Growth by Farm Size," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 204875, Agricultural and Applied Economics Association.
    13. Sauer, Sérgio & Leite, Sergio Pereira, 2012. "Expansão Agrícola, Preços e Apropriação de Terra Por Estrangeiros no Brasil," Brazilian Journal of Rural Economy and Sociology (Revista de Economia e Sociologia Rural-RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 50(3), pages 1-22, September.
    14. Ajax R. B. Moreira & Steve M. Helfand & Adriano M. R. Figueiredo, 2007. "Explicando as diferenças na produtividade agrícola no Brasil," Discussion Papers 1254, Instituto de Pesquisa Econômica Aplicada - IPEA.
    15. Helfand, Steven M. & Magalhaes, Marcelo M. & Rada, Nicholas E., 2015. "Brazil's Agricultural Total Factor Productivity Growth by Farm Size," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 204875, Agricultural and Applied Economics Association;Western Agricultural Economics Association.
    16. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    17. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    More about this item

    Keywords

    technical efficiency; Agriculture; stochastic production frontier; public policy; parametric; rural extension.;
    All these keywords.

    JEL classification:

    • B22 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Macroeconomics
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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