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Assessment of Neighborhood and Spillover Effects on Technical Efficiency of Irrigated Rice Farmers

Author

Listed:
  • Zenaida M Sumalde

    (University of the Philippines Los Baños (UPLB))

  • Donald B. Villanueva

    (Assistant Scientist Social Sciences Division (SSD), International Rice Research Institute (IRRI))

  • Valerien O Pede

    (Social Sciences Division (SSD), International Rice Research Institute (IRRI))

  • Yolanda T Garcia

    (University of the Philippines Los Baños (UPLB))

  • U-Primo E Rodriguez

    (University of the Philippines Los Baños)

Abstract

Neighborhood and spillover effects on technical efficiency were investigated among 270 randomly drawn farming households from 18 irrigated villages in Guimba, Nueva Ecija, Philippines, using a two-step procedure. In the first stage, stochastic frontier production function was used to estimate farmer’s technical efficiency; in the second stage, appropriate spatial econometric models of technical efficiency were estimated. Spatial econometric models adopted in this study detected spatial dependency on technical efficiency in the error term of the spatial model across seasons and locations, which can be associated with unobserved factors that similarly influence farmers’ technical efficiencies at the same time. Farm size, income, and regular contact and consultation with agricultural technicians were found to significantly affect technical efficiency. Results of the spatial regression show that owner-cultivator status and loamy soil are associated with increased technical efficiency. The local government of Guimba can use findings of this study in formulating agricultural policies and implementing essential interventions to improve the technical efficiency of rice farmers.

Suggested Citation

  • Zenaida M Sumalde & Donald B. Villanueva & Valerien O Pede & Yolanda T Garcia & U-Primo E Rodriguez, 2017. "Assessment of Neighborhood and Spillover Effects on Technical Efficiency of Irrigated Rice Farmers," Asian Journal of Agriculture and Development, Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA), vol. 14(2), pages 103-125, December.
    • Handle: RePEc:sag:seajad:v:14:y:2017:i:2:p:103-125
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    Cited by:

    1. De Salvo, Maria & Capitello, Roberta & Gaudenzi, Barbara & Begalli, Diego, 2019. "Risk management strategies and residual risk perception in the wine industry: A spatial analysis in Northeast Italy," Land Use Policy, Elsevier, vol. 83(C), pages 47-62.
    2. Atsushi Iimi & Liangzhi You & Ulrike Wood-Sichra, 2020. "Spatial Autocorrelation Panel Regression: Agricultural Production and Transport Connectivity," Networks and Spatial Economics, Springer, vol. 20(2), pages 529-547, June.

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    Keywords

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    JEL classification:

    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • C59 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Other

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