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Pattern of investment allocation to chemical inputs and technical efficiency: A stochastic frontier analysis of farm households in Laguna, Philippines

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  • Velarde, Orlee
  • Pede, Valerien O.

Abstract

This study focuses on the pattern between investment in chemical inputs such as fertilizer, pesticides and herbicides and technical efficiency of farm households in Laguna, Philippines. Using a one‐stage maximum likelihood estimation procedure, the stochastic production frontier model was estimated simultaneously with the determinants of efficiency. Results show that farmers with a low technical efficiency score have a high investment share in chemical inputs. Farmers who invested more in chemical inputs relative to other variable inputs attained the same or even lower output and were less efficient than those farmers who invested less. The result shows that farmers who invested wisely in chemical inputs can encourage farmers to apply chemical inputs more optimally.

Suggested Citation

  • Velarde, Orlee & Pede, Valerien O., 2013. "Pattern of investment allocation to chemical inputs and technical efficiency: A stochastic frontier analysis of farm households in Laguna, Philippines," 2013 Conference (57th), February 5-8, 2013, Sydney, Australia 152203, Australian Agricultural and Resource Economics Society.
    • Handle: RePEc:ags:aare13:152203
    DOI: 10.22004/ag.econ.152203
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    References listed on IDEAS

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    1. Villano, Renato A. & Fleming, Euan M., 2004. "Analysis of Technical Efficiency in a Rainfed Lowland Rice Environment in Central Luzon Philippines Using a Stochastic Frontier Production Function with a Heteroskedastic Error Structure," Working Papers 12906, University of New England, School of Economics.
    2. Munir Ahmad & Ghulam Mustafa Chaudhry & Mohammad Iqbal, 2002. "Wheat Productivity, Efficiency, and Sustainability: A Stochastic Production Frontier Analysis," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 41(4), pages 643-663.
    3. Alene, Arega D. & Hassan, Rashid M., 2003. "Measuring The Impact Of Ethiopia'S New Extension Program On The Productive Efficiency Of Farmers," 2003 Annual Meeting, August 16-22, 2003, Durban, South Africa 25919, International Association of Agricultural Economists.
    4. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-286, July.
    5. Marinda, Pamela & Bangura, Arnold & Heidhues, Franz, 2006. "Technical Efficiency Analysis in Male and Female-Managed Farms: A Study of Maize Production in West Pokot District, Kenya," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25599, International Association of Agricultural Economists.
    6. ABEDULLAH* & Sushil PANDE** & Saima JABEEN*, 2009. "Time Varying Technical Efficiency, Evidences From Rainfed Rice Areas Of The Philippines," Pakistan Journal of Applied Economics, Applied Economics Research Centre, vol. 19(1), pages 19-33.
    7. Richard T. Yao & Gerald E. Shively, 2007. "Technical Change and Productive Efficiency: Irrigated Rice in the Philippines," Asian Economic Journal, East Asian Economic Association, vol. 21(2), pages 155-168, June.
    8. 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.
    9. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    10. 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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    Keywords

    Crop Production/Industries; Environmental Economics and Policy; Research and Development/Tech Change/Emerging Technologies;
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