IDEAS home Printed from https://ideas.repec.org/a/ove/journl/aid10235.html
   My bibliography  Save this article

Stochastic frontiers, productivity effects and development projects

Author

Listed:
  • Boris E. Bravo-Ureta

Abstract

A common objective of many development projects is to promote output growth as well as better management in order to improve incomes and reduce poverty. In other words, the purpose is to induce upwards shifts in the production frontier (i.e., technological change) while also promoting better management (i.e., narrowing the gap from the frontier). Given the link between managerial performance and technical efficiency, stochastic production frontiers are well suited for the task from a methodological point of view. Despite this suitability, work linking stochastic frontiers with impact evaluation methods has just begun and a major hurdle is resolving biases that might arise from selection on observables and unobservables. This article provides an overview of how impact evaluation and stochastic frontiers, two well-established areas in applied econometrics, are being brought together to shed light on the productivity effects of agricultural development interventions.Â

Suggested Citation

  • Boris E. Bravo-Ureta, 2014. "Stochastic frontiers, productivity effects and development projects," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 51-58.
    • Handle: RePEc:ove:journl:aid:10235
    as

    Download full text from publisher

    File URL: https://reunido.uniovi.es/index.php/EBL/article/view/10235
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Taylor, Timothy G. & Scott Shonkwiler, J., 1986. "Alternative stochastic specifications of the frontier production function in the analysis of agricultural credit programs and technical efficiency," Journal of Development Economics, Elsevier, vol. 21(1), pages 149-160, April.
    2. W. Cooper & C. Lovell, 2011. "History lessons," Journal of Productivity Analysis, Springer, vol. 36(2), pages 193-200, October.
    3. Daniel Solís & Boris E. Bravo-Ureta & Ricardo E. Quiroga, 2007. "Soil conservation and technical efficiency among hillside farmers in Central America: a switching regression model ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 51(4), pages 491-510, December.
    4. Independent Evaluation Group, 2011. "Impact Evaluations in Agriculture," World Bank Publications - Books, The World Bank Group, number 27794, December.
    5. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    6. Ravallion, Martin, 2008. "Evaluating Anti-Poverty Programs," Handbook of Development Economics, in: T. Paul Schultz & John A. Strauss (ed.), Handbook of Development Economics, edition 1, volume 4, chapter 59, pages 3787-3846, Elsevier.
    7. Boris E. Bravo‐Ureta & Daniel Solís & Horacio Cocchi & Ricardo E. Quiroga, 2006. "The impact of soil conservation and output diversification on farm income in Central American hillside farming," Agricultural Economics, International Association of Agricultural Economists, vol. 35(3), pages 267-276, November.
    8. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    9. Duflo, Esther & Glennerster, Rachel & Kremer, Michael, 2008. "Using Randomization in Development Economics Research: A Toolkit," Handbook of Development Economics, in: T. Paul Schultz & John A. Strauss (ed.), Handbook of Development Economics, edition 1, volume 4, chapter 61, pages 3895-3962, Elsevier.
    10. Boris Bravo-Ureta & Daniel Solís & Víctor Moreira López & José Maripani & Abdourahmane Thiam & Teodoro Rivas, 2007. "Technical efficiency in farming: a meta-regression analysis," Journal of Productivity Analysis, Springer, vol. 27(1), pages 57-72, February.
    11. Yair Mundlak, 1961. "Empirical Production Function Free of Management Bias," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 43(1), pages 44-56.
    12. Subal Kumbhakar & Efthymios Tsionas & Timo Sipiläinen, 2009. "Joint estimation of technology choice and technical efficiency: an application to organic and conventional dairy farming," Journal of Productivity Analysis, Springer, vol. 31(3), pages 151-161, June.
    13. Christopher B. Barrett & Michael R. Carter, 2010. "The Power and Pitfalls of Experiments in Development Economics: Some Non-random Reflections," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 32(4), pages 515-548.
    14. Ariel Dinar & Giannis Karagiannis & Vangelis Tzouvelekas, 2007. "Evaluating the impact of agricultural extension on farms' performance in Crete: a nonneutral stochastic frontier approach," Agricultural Economics, International Association of Agricultural Economists, vol. 36(2), pages 135-146, March.
    15. Joseph Terza, 2009. "Parametric Nonlinear Regression with Endogenous Switching," Econometric Reviews, Taylor & Francis Journals, vol. 28(6), pages 555-580.
    16. William Greene, 2010. "A stochastic frontier model with correction for sample selection," Journal of Productivity Analysis, Springer, vol. 34(1), pages 15-24, August.
    17. Hoch, Irving, 1976. "Production Functions and Supply Applications for California Dairy Farms," Monographs, University of California, Davis, Giannini Foundation, number 251911, December.
    18. Boris Bravo-Ureta & William Greene & Daniel Solís, 2012. "Technical efficiency analysis correcting for biases from observed and unobserved variables: an application to a natural resource management project," Empirical Economics, Springer, vol. 43(1), pages 55-72, August.
    19. Sanzidur Rahman & Aree Wiboonpongse & Songsak Sriboonchitta & Yaovarate Chaovanapoonphol, 2009. "Production Efficiency of Jasmine Rice Producers in Northern and North‐eastern Thailand," Journal of Agricultural Economics, Wiley Blackwell, vol. 60(2), pages 419-435, June.
    20. Shahidur R. Khandker & Gayatri B. Koolwal & Hussain A. Samad, . "Handbook on Impact Evaluation : Quantitative Methods and Practices," World Bank Publications, The World Bank, number 2693, September.
    21. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    22. Kaparakis, Emmanuel I & Miller, Stephen M & Noulas, Athanasios G, 1994. "Short-Run Cost Inefficiency of Commercial Banks: A Flexible Stochastic Frontier Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 26(4), pages 875-893, November.
    23. Todd, Petra E., 2008. "Evaluating Social Programs with Endogenous Program Placement and Selection of the Treated," Handbook of Development Economics, in: T. Paul Schultz & John A. Strauss (ed.), Handbook of Development Economics, edition 1, volume 4, chapter 60, pages 3847-3894, Elsevier.
    24. Alessandro Maffioli & Diego Ubfal & Gonzalo Vázquez Baré & Pedro Cerdán‐Infantes, 2011. "Extension services, product quality and yields: the case of grapes in Argentina," Agricultural Economics, International Association of Agricultural Economists, vol. 42(6), pages 727-734, November.
    25. Martin, John P & Page, John M, Jr, 1983. "The Impact of Subsidies on X-Efficiency in LDC Industry: Theory and an Empirical Test," The Review of Economics and Statistics, MIT Press, vol. 65(4), pages 608-617, November.
    26. W. David Bradford & Andrew N. Kleit & Marie A. Krousel-Wood & Richard N. Re, 2001. "Stochastic Frontier Estimation Of Cost Models Within The Hospital," The Review of Economics and Statistics, MIT Press, vol. 83(2), pages 302-309, May.
    27. Carlos D. Mayen & Joseph V. Balagtas & Corinne E. Alexander, 2010. "Technology Adoption and Technical Efficiency: Organic and Conventional Dairy Farms in the United States," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(1), pages 181-195.
    28. Timothy G. Taylor & H. Evan Drummond & Aloisio T. Gomes, 1986. "Agricultural Credit Programs and Production Efficiency: An Analysis of Traditional Farming in Southeastern Minas Gerais, Brazil," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(1), pages 110-119.
    29. Paul Winters & Lina Salazar & Alessandro Maffioli, 2010. "Designing Impact Evaluations for Agricultural Projects," SPD Working Papers 1007, Inter-American Development Bank, Office of Strategic Planning and Development Effectiveness (SPD).
    30. repec:zwi:journl:v:43:y:2012:i:1:p:55-72 is not listed on IDEAS
    31. Romina Cavatassi & Mario González & Paul Winters & Jorge Andrade-Piedra & Graham Thiele & Patricio Espinosa, 2009. "Linking Smallholders to the New Agricultural Economy: An Evaluation of the Plataformas Program in Ecuador," Working Papers 09-06, Agricultural and Development Economics Division of the Food and Agriculture Organization of the United Nations (FAO - ESA).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maria Vrachioli & Spiro E. Stefanou & Vangelis Tzouvelekas, 2021. "Impact Evaluation of Alternative Irrigation Technology in Crete: Correcting for Selectivity Bias," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 79(3), pages 551-574, July.
    2. Mohammed, Sadick & Abdulai, Awudu, 2021. "Extension Participation and Improved Technology Adoption: Impact on Efficiency and Welfare of Farmers in Ghana," 2021 Conference, August 17-31, 2021, Virtual 315362, International Association of Agricultural Economists.
    3. Yitayew, Asresu & Abdulai, Awudu & Yigezu, Yigezu A., 2023. "The effects of advisory services and technology channeling on farm yields and technical efficiency of wheat farmers in Ethiopia," Food Policy, Elsevier, vol. 116(C).
    4. Bravo-Ureta, Boris E. & Higgins, Daniel & Arslan, Aslihan, 2020. "Irrigation infrastructure and farm productivity in the Philippines: A stochastic Meta-Frontier analysis," World Development, Elsevier, vol. 135(C).
    5. Owusu, Eric S. & Bravo-Ureta, Boris E., 2022. "Reap when you sow? The productivity impacts of early sowing in Malawi," Agricultural Systems, Elsevier, vol. 199(C).
    6. Villano, Renato & Asante, Bright Owusu & Bravo-Ureta, Boris, 2019. "Farming systems and productivity gaps: Opportunities for improving smallholder performance in the Forest-Savannah transition zone of Ghana," Land Use Policy, Elsevier, vol. 82(C), pages 220-227.
    7. Asfaw, Solomon & Cattaneo, Andrea & Pallante, Giacomo & Palma, Alessandro, 2017. "Improving the efficiency targeting of Malawi's farm input subsidy programme: Big pain, small gain?," Food Policy, Elsevier, vol. 73(C), pages 104-118.

    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. Boris E. Bravo‐Ureta & Mario González‐Flores & William Greene & Daniel Solís, 2021. "Technology and Technical Efficiency Change: Evidence from a Difference in Differences Selectivity Corrected Stochastic Production Frontier Model," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(1), pages 362-385, January.
    2. Boris Bravo-Ureta & William Greene & Daniel Solís, 2012. "Technical efficiency analysis correcting for biases from observed and unobserved variables: an application to a natural resource management project," Empirical Economics, Springer, vol. 43(1), pages 55-72, August.
    3. Maria Vrachioli & Spiro E. Stefanou & Vangelis Tzouvelekas, 2021. "Impact Evaluation of Alternative Irrigation Technology in Crete: Correcting for Selectivity Bias," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 79(3), pages 551-574, July.
    4. González-Flores, Mario & Bravo-Ureta, Boris E. & Solís, Daniel & Winters, Paul, 2014. "The impact of high value markets on smallholder productivity in the Ecuadorean Sierra: A Stochastic Production Frontier approach correcting for selectivity bias," Food Policy, Elsevier, vol. 44(C), pages 237-247.
    5. Bravo-Ureta, Boris E. & Higgins, Daniel & Arslan, Aslihan, 2020. "Irrigation infrastructure and farm productivity in the Philippines: A stochastic Meta-Frontier analysis," World Development, Elsevier, vol. 135(C).
    6. Abdul-Rahaman, Awal & Abdulai, Awudu, 2018. "Do farmer groups impact on farm yield and efficiency of smallholder farmers? Evidence from rice farmers in northern Ghana," Food Policy, Elsevier, vol. 81(C), pages 95-105.
    7. Bravo-Ureta, Boris E. & Jara-Rojas, Roberto & Lachaud, Michee A. & Moreira L., Victor H. & Scheierling, Susanne M., 2015. "Water and Farm Efficiency: Insights from the Frontier Literature," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 206076, Agricultural and Applied Economics Association.
    8. Owusu, Eric S. & Bravo-Ureta, Boris E., 2022. "Reap when you sow? The productivity impacts of early sowing in Malawi," Agricultural Systems, Elsevier, vol. 199(C).
    9. De los Santos-Montero, Luis A. & Bravo-Ureta, Boris E., 2017. "Natural Resource Management and Household Well-being: The Case of POSAF-II in Nicaragua," World Development, Elsevier, vol. 99(C), pages 42-59.
    10. Luis A. De los Santos‐Montero & Boris E. Bravo‐Ureta, 2017. "Productivity effects and natural resource management: econometric evidence from POSAF‐II in Nicaragua," Natural Resources Forum, Blackwell Publishing, vol. 41(4), pages 220-233, November.
    11. Begin, Rosemarie & Tamini, Lota D. & Doyon, Maurice, 2014. "L'effet du travail hors-ferme sur l'efficacité technique des fermes laitières québécoises: un modèle intégrant les biais de sélection sur les observables et inobservables," Working Papers 187233, University of Laval, Center for Research on the Economics of the Environment, Agri-food, Transports and Energy (CREATE).
    12. K Hervé Dakpo & Laure Latruffe & Yann Desjeux & Philippe Jeanneaux, 2022. "Modeling heterogeneous technologies in the presence of sample selection: The case of dairy farms and the adoption of agri‐environmental schemes in France," Agricultural Economics, International Association of Agricultural Economists, vol. 53(3), pages 422-438, May.
    13. William Greene, 2010. "A stochastic frontier model with correction for sample selection," Journal of Productivity Analysis, Springer, vol. 34(1), pages 15-24, August.
    14. Sreejith Aravindakshan & Frederick Rossi & T. S. Amjath-Babu & Prakashan Chellattan Veettil & Timothy J. Krupnik, 2018. "Application of a bias-corrected meta-frontier approach and an endogenous switching regression to analyze the technical efficiency of conservation tillage for wheat in South Asia," Journal of Productivity Analysis, Springer, vol. 49(2), pages 153-171, June.
    15. Awal Abdul‐Rahaman & Gazali Issahaku & Wanglin Ma, 2023. "Agrifood system participation and production efficiency among smallholder vegetable farmers in Northern Ghana," Agribusiness, John Wiley & Sons, Ltd., vol. 39(3), pages 812-835, July.
    16. Khanal, Uttam & Wilson, Clevo & Rahman, Sanzidur & Lee, Boon & Hoang, Vincent, 2020. "Smallholder farmers’ adaptation to climate change and its potential contribution to UN’s sustainable development goals of zero hunger and no poverty," MPRA Paper 106917, University Library of Munich, Germany, revised 07 Sep 2020.
    17. Mattoo, Aaditya & Cadot, Olivier & Gourdon, Julien & Fernandes, Ana Margarida, 2011. "Impact Evaluation of Trade Interventions: Paving the Way," CEPR Discussion Papers 8638, C.E.P.R. Discussion Papers.
    18. Shaibu Baanni Azumah & Samuel Arkoh Donkoh & Joseph Agebase Awuni, 2019. "Correcting for sample selection in stochastic frontier analysis: insights from rice farmers in Northern Ghana," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 7(1), pages 1-15, December.
    19. Ayeduvor Selorm & D. B. S. Sarpong & Irene S. Egyir & Akwasi Mensah Bonsu & Henry An, 2023. "Does contract farming affect technical efficiency? Evidence from soybean farmers in Northern Ghana," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 11(1), pages 1-22, December.
    20. Ma, Wanglin & Renwick, Alan & Yuan, Peng & Ratna, Nazmun, 2018. "Agricultural cooperative membership and technical efficiency of apple farmers in China: An analysis accounting for selectivity bias," Food Policy, Elsevier, vol. 81(C), pages 122-132.

    More about this item

    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:ove:journl:aid:10235. 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: Francisco J. Delgado (email available below). General contact details of provider: https://edirc.repec.org/data/deovies.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.