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Technical efficiency analysis correcting for biases from observed and unobserved variables: an application to a natural resource management project

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  • Boris Bravo-Ureta

    ()

  • William Greene
  • Daniel Solís

Abstract

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File URL: http://hdl.handle.net/10.1007/s00181-011-0491-y
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Bibliographic Info

Article provided by Springer in its journal Empirical Economics.

Volume (Year): 43 (2012)
Issue (Month): 1 (August)
Pages: 55-72

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Handle: RePEc:spr:empeco:v:43:y:2012:i:1:p:55-72

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Related research

Keywords: Stochastic frontiers; Technical efficiency; Propensity score matching; Sample selection; Honduras; D24; Q2; Q12; Q16;

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References

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  1. Natália Pimenta Monteiro, 2004. "Using propensity matching estimators to evaluate the impact of privatisation on wages," NIPE Working Papers 12/2004, NIPE - Universidade do Minho.
  2. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
  3. Guido Imbens & Jeffrey Wooldridge, 2008. "Recent developments in the econometrics of program evaluation," CeMMAP working papers CWP24/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  4. Alan Collins & Richard I. D. Harris, 2005. "The Impact Of Foreign Ownership And Efficiency On Pollution Abatement Expenditure By Chemical Plants: Some Uk Evidence," Scottish Journal of Political Economy, Scottish Economic Society, vol. 52(5), pages 747-768, November.
  5. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January.
  6. Caliendo, Marco & Kopeinig, Sabine, 2005. "Some Practical Guidance for the Implementation of Propensity Score Matching," IZA Discussion Papers 1588, Institute for the Study of Labor (IZA).
  7. 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.
  8. 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.
  9. William Greene, 2010. "A stochastic frontier model with correction for sample selection," Journal of Productivity Analysis, Springer, vol. 34(1), pages 15-24, August.
  10. 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.
  11. Daniel Solís & Boris E. Bravo-Ureta & Ricardo E. Quiroga, 2009. "Technical Efficiency among Peasant Farmers Participating in Natural Resource Management Programmes in Central America," Journal of Agricultural Economics, Wiley Blackwell, vol. 60(1), pages 202-219.
  12. 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.
  13. 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.
  14. Dillon, Andrew, 2010. "Do differences in the scale of irrigation projects generate different impacts on poverty and production?," IFPRI discussion papers 1022, International Food Policy Research Institute (IFPRI).
  15. Rodriguez, Divina Gracia P. & Rejesus, Roderick M. & Aragon, Corazono T., 2007. "Impacts of an Agricultural Development Program for Poor Coconut Producers in the Philippines: An Approach Using Panel Data and Propensity Score Matching Techniques," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 32(03), December.
  16. 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).
  17. Pedro Cerdán-Infantes & Alessandro Maffioli & Diego Ubfal, 2008. "The Impact of Agricultural Extension Services: The Case of Grape Production in Argentina," OVE Working Papers 0508, Inter-American Development Bank, Office of Evaluation and Oversight (OVE).
  18. 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.
  19. 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, 03.
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Cited by:
  1. Abdoulaye, Ibrahim Djido & Sanders, John H., 2013. "A Matching Approach to Analyze the Impact of New Agricultural Technologies: Productivity and Technical Efficiency in Niger," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150434, Agricultural and Applied Economics Association.
  2. Cordero, José Manuel & Santín, Daniel & Sicilia, Gabriela, 2013. "Dealing with the Endogeneity Problem in Data Envelopment Analysis," MPRA Paper 47475, University Library of Munich, Germany.

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