IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/5890.html
   My bibliography  Save this paper

Produtividade Total Dos Fatores Nas Principais Lavouras De Grãos Brasileiras: Análise De Fronteira Estocástica E Índice De Malmquist

Author

Listed:
  • Rivera Rivera, Edward Bernard Bastiaan
  • Costantin, Paulo Dutra

Abstract

The objective of this paper is to use the techniques of Stochastic Frontier Analysis (SFA) to estimate the increase or decrease of inefficiencies through time, as well as the linear programming procedure Data Envelopment Analysis (DEA) and the Malmquist index in order to analyze the sources of changes in TFP in the main Brazilian grain crops – rice, beans, maize, soybeans and wheat – throughout the period 2001-2006. The results indicate that, although there have been positive changes in TFP for the sample analyzed, a decline in the use of technology has been evidenced for all the main Brazilian grain crops between 2005/2006 – period in which we observe a remarkable downfall in the use of inputs in Brazilian agriculture.

Suggested Citation

  • Rivera Rivera, Edward Bernard Bastiaan & Costantin, Paulo Dutra, 2007. "Produtividade Total Dos Fatores Nas Principais Lavouras De Grãos Brasileiras: Análise De Fronteira Estocástica E Índice De Malmquist," MPRA Paper 5890, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:5890
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/5890/1/MPRA_paper_5890.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Afriat, Sidney N, 1972. "Efficiency Estimation of Production Function," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 13(3), pages 568-598, October.
    2. 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.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stephen M. Miller & Terrence M. Clauretie & Thomas M. Springer, 2006. "Economies Of Scale And Cost Efficiencies: A Panel‐Data Stochastic‐Frontier Analysis Of Real Estate Investment Trusts," Manchester School, University of Manchester, vol. 74(4), pages 483-499, July.
    2. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.
    3. Voigt, Peter, 2004. "Russlands Weg vom Plan zum Markt: Sektorale Trends und regionale Spezifika. Eine Analyse der Produktivitäts- und Effizienzentwicklungen in der Transformationsphase," Studies on the Agricultural and Food Sector in Transition Economies, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), volume 28, number 93021, September.
    4. B.C. Okoye & A. Abass & B. Bachwenkizi & G. Asumugha & B. Alenkhe & R. Ranaivoson & R. Randrianarivelo & N. Rabemanantsoa & I. Ralimanana, 2016. "Differentials in technical efficiency among smallholder cassava farmers in Central Madagascar: A Cobb Douglas stochastic frontier production approach," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1143345-114, December.
    5. Zuniga-Gonzalez, C.A, 2009. "Analisis de la eficiencia tecnica de la unidad de VPN UNAN-LEON utilizando funcion de produccion stochastic frontier, 2007-2008 [Technical efficiency analysis of the PNV unit UNAN-Leon using produc," MPRA Paper 110950, University Library of Munich, Germany, revised 14 Jan 2009.
    6. Jianxu Liu & Sanzidur Rahman & Songsak Sriboonchitta & Aree Wiboonpongse, 2017. "Enhancing Productivity and Resource Conservation by Eliminating Inefficiency of Thai Rice Farmers: A Zero Inefficiency Stochastic Frontier Approach," Sustainability, MDPI, vol. 9(5), pages 1-18, May.
    7. Yang Li & Shin-Yi Chen, 2010. "The Impact of FDI on the Productivity of Chinese Economic Regions," Asia-Pacific Journal of Accounting & Economics, Taylor & Francis Journals, vol. 17(3), pages 299-312.
    8. Blazek, David & Sickles, Robin C., 2010. "The impact of knowledge accumulation and geographical spillovers on productivity and efficiency: The case of U. S. shipbuilding during WWII," Economic Modelling, Elsevier, vol. 27(6), pages 1484-1497, November.
    9. Daniela Schettini & Carlos Roberto Azzoni & Antonio Páez, 2011. "Neighborhood and Efficiency in Manufacturing in Brazilian Regions: a Spatial Markov Chain Analysis," ERSA conference papers ersa10p1052, European Regional Science Association.
    10. Jean-François Brun & Constantin Thierry Compaore, 2021. "Public Expenditures Efficiency On Education Distribution in Developing Countries," Working Papers hal-03116615, HAL.
    11. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    12. Gauri Khanna, 2006. "Technical Efficiency in Production and Resource Use in Sugar Cane: A Stochastic Frontier Production Function Analysis," IHEID Working Papers 15-2006, Economics Section, The Graduate Institute of International Studies.
    13. Dilawar Khan & Muhammad Nouman & Arif Ullah, 2023. "Assessing the impact of technological innovation on technically derived energy efficiency: a multivariate co-integration analysis of the agricultural sector in South Asia," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(4), pages 3723-3745, April.
    14. Dilawar Khan & Muhammad Nouman & József Popp & Muhammad Asif Khan & Faheem Ur Rehman & Judit Oláh, 2021. "Link between Technically Derived Energy Efficiency and Ecological Footprint: Empirical Evidence from the ASEAN Region," Energies, MDPI, vol. 14(13), pages 1-16, June.
    15. Forsund, Finn R. & Sarafoglou, Nikias, 2005. "The tale of two research communities: The diffusion of research on productive efficiency," International Journal of Production Economics, Elsevier, vol. 98(1), pages 17-40, October.
    16. Coelli, Tim J., 1995. "Recent Developments In Frontier Modelling And Efficiency Measurement," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 39(3), pages 1-27, December.
    17. Quaranta, Anna Grazia & Raffoni, Anna & Visani, Franco, 2018. "A multidimensional approach to measuring bank branch efficiency," European Journal of Operational Research, Elsevier, vol. 266(2), pages 746-760.
    18. Edward Ebo ONUMAH & Bernhard BRÜMMER & Gabriele HÖRSTGEN-SCHWARK, 2010. "Productivity of the hired and family labour and determinants of technical inefficiency in Ghana's fish farms," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 56(2), pages 79-88.
    19. Finn Førsund & Nikias Sarafoglou, 2002. "On the Origins of Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 23-40, January.
    20. Kexin Li & Jianxu Liu & Yuting Xue & Sanzidur Rahman & Songsak Sriboonchitta, 2022. "Consequences of Ignoring Dependent Error Components and Heterogeneity in a Stochastic Frontier Model: An Application to Rice Producers in Northern Thailand," Agriculture, MDPI, vol. 12(8), pages 1-17, July.

    More about this item

    Keywords

    Agriculture; Total Factor Productivity; Stochastic Frontier; Data Envelopment Analysis;
    All these keywords.

    JEL classification:

    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:5890. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.