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Farm-Level Fertilizer Demand in Java: A Meta-Production Function Approach

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  • Mark M. Pitt

Abstract

This paper models seed variety choice and the demand for variable inputs as jointly determined by profit-maximizing cultivators. The approach parallels that of Hayami and Ruttan, who postulated that changes in the output-fertilizer price ratio induce movements along a meta-fertilizer response function, the envelope of individual variety-specific response surfaces. Ignoring the possibility of seed variety switching leads to underestimates of fertilizer demand elasticities. In addition, estimation with samples reflecting a single seed variety may involve serious selection bias. A two-stage procedure which adjusts for selectivity bias is used to estimate the model with farm-level data from Java.

Suggested Citation

  • Mark M. Pitt, 1983. "Farm-Level Fertilizer Demand in Java: A Meta-Production Function Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 65(3), pages 502-508.
    • Handle: RePEc:oup:ajagec:v:65:y:1983:i:3:p:502-508.
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    1. Bahta, Y. & Owusu-Sekyeer, E., 2018. "Nexus between homestead food garden programme and land ownership in South Africa: Implication on the income of vegetable farmers," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277732, International Association of Agricultural Economists.
    2. Freeman, H. A. & Ehui, Simeon K. & A. Jabbar, Mohammad, 1998. "Credit constraints and smallholder dairy production in the East African highlands: application of a switching regression model," Agricultural Economics, Blackwell, vol. 19(1-2), pages 33-44, September.
    3. Hongxing Liu & Wendong Zhang & Elena Irwin & Jeffrey Kast & Noel Aloysius & Jay Martin & Margaret Kalcic, 2020. "Best Management Practices and Nutrient Reduction: An Integrated Economic-Hydrologic Model of the Western Lake Erie Basin," Land Economics, University of Wisconsin Press, vol. 96(4), pages 510-530.
    4. Awudu Abdulai & Wallace Huffman, 2014. "The Adoption and Impact of Soil and Water Conservation Technology: An Endogenous Switching Regression Application," Land Economics, University of Wisconsin Press, vol. 90(1), pages 26-43.
    5. Keith Fuglie, 2004. "Productivity growth in Indonesian agriculture, 1961-2000," Bulletin of Indonesian Economic Studies, Taylor & Francis Journals, vol. 40(2), pages 209-225.
    6. Vincent Ngeno, 2017. "The Impact of Adoption of Recommended Tea Plucking Interval on Tea Yields in Kenya," Agrekon, Taylor & Francis Journals, vol. 56(3), pages 290-295, July.
    7. Wenjian He & Yiyang Liu & Huaping Sun & Farhad Taghizadeh-Hesary, 2020. "How Does Climate Change Affect Rice Yield in China?," Agriculture, MDPI, vol. 10(10), pages 1-16, September.
    8. Solis, Daniel & Bravo-Ureta, Boris E. & Quiroga, Ricardo E., 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 1-20.
    9. Solis, Daniel & Bravo-Ureta, Boris E. & Quiroga, Ricardo E., 2006. "The Effect Of Soil Conservation On Technical Efficiency: Evidence From Central America," 2006 Annual meeting, July 23-26, Long Beach, CA 21345, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Sanzidur Rahman, 2011. "Resource use efficiency under self‐selectivity: the case of Bangladeshi rice producers," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 55(2), pages 273-290, April.
    11. Christine Amsler & Christopher J. O’Donnell & Peter Schmidt, 2017. "Stochastic metafrontiers," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 1007-1020, October.
    12. Shaibu Mellon Bedi & Carlo Azzarri & Bekele Hundie Kotu & Lukas Kornher & Joachim von Braun, 2022. "Scaling-up agricultural technologies: who should be targeted?," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(4), pages 857-875.
    13. 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.
    14. Tsionas, Mike G., 2023. "Clustering and meta-envelopment in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 304(2), pages 763-778.
    15. Ray Trewin & L. Weiguo & Sjaiful Erwidodo & Sjaiful Bahri, 1995. "Analysis Of The Technical Efficiency Over Time Of West Javanese Rice Farms," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 39(2), pages 143-163, August.
    16. Bosch, Darrell J. & Fuglie, Keith O. & Keim, Russ W., 1994. "Economic and Environmental Effects of Nitrogen Testing for Fertilizer Management," Staff Reports 278741, United States Department of Agriculture, Economic Research Service.
    17. Bahta Yonas Tesfamariam & Enoch Owusu-Sekyere & Donkor Emmanuel & Tlalang Boipelo Elizabeth, 2018. "The impact of the homestead food garden programme on food security in South Africa," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(1), pages 95-110, February.
    18. Manda, Julius & Alene, Arega D. & Tufa, Adane H. & Abdoulaye, Tahirou & Wossen, Tesfamicheal & Chikoye, David & Manyong, Victor, 2019. "The poverty impacts of improved cowpea varieties in Nigeria: A counterfactual analysis," World Development, Elsevier, vol. 122(C), pages 261-271.
    19. Pitt, Mark M. & Sumodiningrat, Gunawan, 1988. "The Determinants of Rice Variety Choice in Indonesia," Bulletins 7500, University of Minnesota, Economic Development Center.
    20. Christine Amsler & Yi Yi Chen & Peter Schmidt & Hung Jen Wang, 2021. "A hierarchical panel data stochastic frontier model for the estimation of stochastic metafrontiers," Empirical Economics, Springer, vol. 60(1), pages 353-363, January.

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