Technical efficiency of U.S. Western Great Plains wheat farms using stochastic frontier analysis

References

• Agahi, H., Zarafshani, K., & Behjat, A. (2008). The effect of crop insurance on TE of wheat farmers in Kermanshah Province: A corrected ordinary least square approach. Journal of Applied Science, 8(5), 891–25. https://doi.org/10.3923/jas.2008.891.894
   Google Scholar
• Aigner, D. J., Lovell, C. A. K., & Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6(1), 21–37. https://doi.org/10.1016/0304-4076(77)90052-5
   Google Scholar
• Alem, H., Lien, G., & Hardaker, J. B. (2018). Economic performance and efficiency determinants of crop-producing farms in Norway. International Journal of Productivity and Performance Management, 67(9), 1418–1434. https://doi.org/10.1108/IJPPM-01-2018-0026
   Web of Science ®Google Scholar
• Ali, M. B. (2002). Characteristics and production costs of U.S. wheat farms. Economic Research Service. U.S. Department of Agriculture. Statistical Bulletin Number 974-5.
   Google Scholar
• Allen, W. B. (2005). Managerial economics: Theory, applications, and cases. W.W. Norton.
   Google Scholar
• Alvarez, A., Amsler, C., Orea, L., & Schmidt, P. (2006). Interpreting and Testing the Scaling Property in Models where Inefficiency Depends on Firm Characteristics. Journal of Productivity Analysis, 25(3), 201–212.
   Web of Science ®Google Scholar
• Andow, D. A. (1991). Vegetational diversity and arthropod population response. Annual Review Entomology, 36(1), 561–586. https://doi.org/10.1146/annurev.en.36.010191.003021
   Google Scholar
• Battese, G. E., & Coelli, T. J. (1992). Frontier production functions, TE and panel data: With application to paddy farmers in India. Journal of Productivity Analysis, 3(1–2), 153–169. https://doi.org/10.1007/BF00158774
   Google Scholar
• Battese, G. E., & Coelli, T. J. (1993). A stochastic frontier production incorporating a model for technical inefficiency effects. Working paper in Econometrics and Applied Statistics, Department of Econometrics, University of New England.
   Google Scholar
• Battese, G. E., & Coelli, T. J. (1995). A model for technical inefficiency effects in a stochastic frontier production for panel data. Empirical Economics, 20(2), 325–332. https://doi.org/10.1007/BF01205442
   Google Scholar
• Bojnec, Š., & Latruffe, L. (2008). Measures of farm business efficiency. Industrial Management & Data Systems.
   Google Scholar
• Bravo-Ureta, B. E., Greene, W., & Solis, D. (2012). Technical efficiency analysis correcting for biases from observed and unobserved variables: An application to a natural resource management project. Empirical Economics, 43(1), 55=72. https://doi.org/10.1007/s00181-011-0491-y
   Web of Science ®Google Scholar
• Byrnes, P., Fare, R., Grosskopf, S., & Kraft, S. (1987). TE and size: The case of Illinois grain farms. European Review of Agricultural Economics, 14(4), 367–381. https://doi.org/10.1093/erae/14.4.367
   Google Scholar
• Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444. https://doi.org/10.1016/0377-2217(78)90138-8
   Web of Science ®Google Scholar
• Chauhan, B. S., Gill, G., & Preston, C. (2006). Seedling recruitment pattern and depth of recruitment of 10 weed species in minimum tillage and no-till seeding systems. Weed Science, 54(4), 658–668. https://doi.org/10.1614/WS-05-135R.1
   Web of Science ®Google Scholar
• Chavas, J., & Aliber, M. (1993). An analysis of economic efficiency in agriculture: A nonparametric approach. Journal of Agricultural and Resource Economics, 18, 1–16. https://doi.org/10.22004/ag.econ.30811
   Web of Science ®Google Scholar
• Chen, N., Yang, X., & Shadbolt, N. (2020). The balanced scorecard as a tool evaluating the sustainable performance of Chinese emerging family farms—evidence from Jilin province in china. Sustainability, 12(17), 6793. https://doi.org/10.3390/su12176793
   Web of Science ®Google Scholar
• Clark, I. G. (1958). Then came the railroads: The century from steam to diesel in the Southwest. University of Oklahoma Press.
   Google Scholar
• Coelli, T. J., & Henningsen, A. (2019). R package for stochastic frontier analysis: FRONTIER version 1.1-6. In Centre for efficiency and productivity analysis (CEPA) (pp. 1–42). University of New England.
   Google Scholar
• Coelli, T. J., Prasada Rao, D. S., & Battese, G. E. (2003). An introduction to efficiency and production analysis. Kluwer Academic Publishers.
   Google Scholar
• Cornwell, C., Schmidt, P., & Sickles, R. C. (1990). Production Frontiers with Time-Series Variation in Efficiency Levels. Journal of econometrics, 46, 185–200.
   Web of Science ®Google Scholar
• Dye, R. W. (2003, December/January). Keeping score. CMA Management, 18–23.
   Google Scholar
• Elliott, N. C. (2006). Wheat Production and Pest Management for the Great Plains Region. CSU Extension XCM235.
   Google Scholar
• Farrell, M. J. (1957). The measurement of productive efficiency. Journal of Royal Statistical Society, 120(3), 253–290. https://doi.org/10.2307/2343100
   Web of Science ®Google Scholar
• Featherstone, A. M., Langemeier, M. R., & Ismet, M. (1997). A nonparametric analysis of efficiency for a sample of Kansas beef cow farms. Journal of Agricultural and Applied Economics, 29(1), 175–184. https://doi.org/10.1017/S1074070800007653
   Google Scholar
• Førsund, F., Lovell, C. A. K., & Schmidt, P. (1980). A Survey of Frontier Production Functions and of Their Relationship to Efficiency Measurement. Journal of econometrics, 13, 5–25.
   Web of Science ®Google Scholar
• Gardiner, M. M., Landis, D. A., Gratton, C., Difonzo, C. D., O’neal, M., Chacon, J. M., Wayo, M. T., Schmidt, N. P., Mueller, E. E., & Heimpel, G. E. (2009). Landscape diversity enhances biological control of an introduced crop pest in the North-Central USA. Ecological Applications, 19(1), 143–154. https://doi.org/10.1890/07-1265.1
   PubMed Web of Science ®Google Scholar
• Giannakas, K., Schoney, R., & Tzouvelekas, V. (2001). TE, technological change and output growth of wheat farms in saskatchewan. Canadian Journal of Agricultural Economics, 49(2), 135–152. https://doi.org/10.1111/j.1744-7976.2001.tb00295
   Web of Science ®Google Scholar
• Greene, W. H. (1993). The Econometric Approach to Efficiency Analysis. In H. Fried, C. A. K. Lovell, & S. Schmidt (Eds.), The Measurement of Productive Efficiency. New York: Oxford University Press.
   Google Scholar
• Heather, K. (2002). The economics of industries and firms. Pearson Education.
   Google Scholar
• Hilmola, O. (2011). Benchmarking efficiency of public passenger transport in larger cities”. Benchmarking: An International Journal, 18(1), 23–41.
   Google Scholar
• Hoque, Z. (2014). 20 years of studies on the balanced scorecard: Trends, accomplishments, gaps and opportunities for future research. The British Accounting Review, 46(1), 33–59. https://doi.org/10.1016/j.bar.2013.10.003
   Web of Science ®Google Scholar
• Kalaitzandonakes, N. G., Wu, S., & Ma, J. (1992). The relationship between TE and firm size revisited. Canadian Journal of Agricultural Economics, 40(3), 427–442. https://doi.org/10.1111/j.1744-7976.1992.tb03705.x
   Google Scholar
• Kaplan, R. S., & Norton, D. P. (1992, January/February). The balanced scorecard: Measures that drive performance. Harvard Business Review, 70(1), 71–79.
   PubMed Web of Science ®Google Scholar
• Kumbhakar, S. C. (2002). Specification and estimation of production risk, risk preferences and TE. American Journal of Agricultural Economics, 84(1), 8–22. https://doi.org/10.1111/1467-8276.00239
   Web of Science ®Google Scholar
• Langemeier, M. (2005). Impact of the adoption of less tillage practices on overall efficiency. SAEA conference proceeding, Little Rock, Arkansas, pp. 1–12.
   Google Scholar
• Langemeier, M., & Bradford, K. (2005, February 6–9). An examination of the relationship between overall efficiency and farm experience. Paper presented at the annual meeting of Southern Agricultural Economic Association, Little Rock, AR.
   Google Scholar
• Latruffe, L., Bravo-Ureta, B. E., Carpentier, A., Desjeux, Y., & Moreira, V. H. (2017). Subsidies and TE in agriculture: Evidence from European dairy farms. American Journal of Agricultural Economics, 99(3), 783–799. https://doi.org/10.1093/ajae/aaw077
   Web of Science ®Google Scholar
• Lichtenberg, E. (2014). Conservation, the Farm Bill, and U.S. Agri-Environmental Policy. Choices, (3). Available online. http://choicesmagazine.org/choices-magazine/theme-articles/3rd-quarter-2014/conservation-the-farm-bill-and-us-agri-environmental-policy
   Google Scholar
• LIMDEP 11, 2021, Econometric Software. Inc.
   Google Scholar
• Meeusedn, W., & van den Broeck, J. V. (1977). Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review, 18(2), 435–444. https://doi.org/10.2307/2525757
   Web of Science ®Google Scholar
• Mekonnen, D. K., Spielman, D. J., Fonsah, E. G., & Dorfman, J. H. (2015). Innovation systems and technical efficiency in developing‐country agriculture. Agricultural Economics, 46(5), 689–702. https://doi.org/10.1111/agec.12164
   Web of Science ®Google Scholar
• Mugera, M. W., & Langemeier, M. R. (2011). Does farm size and specialization matter for productive efficiency? Results from Kansas. Journal of Agriculture and Applied Economics, 43(4), 515–528. https://doi.org/10.1017/S1074070800000043
   Google Scholar
• Oklahoma Wheat Variety Report. (2019, April). Agriculture-NASS; United States Department of Agriculture-NASS. OKlahoma State University.
   Google Scholar
• Olmstead, A. L., & Rhode, P. W. (2011). Adapting North American wheat production to climatic challenges, 1839–2009. Proceedings of the National Academy of Sciences, 108(2), 480–485. https://doi.org/10.1073/pnas.1008279108
   PubMed Web of Science ®Google Scholar
• Olson, K., & Vu, L. (2009). Economic efficiency in farm households: Trends, explanatory factors, and estimation methods. Agricultural Economics, 40(5), 587–599. https://doi.org/10.1111/j.1574-0862.2009.00400
   Web of Science ®Google Scholar
• Paul, C. M., Nehring, R., Banker, D., & Somwaru, A. (2004). Scale economies and efficiency in U.S. agriculture: Are traditional farms history? Journal of Productivity Analysis, 22(3), 185–205. https://doi.org/10.1007/s11123-004-7573-1
   Web of Science ®Google Scholar
• Paustian, M., Wellner, M., & Theuvsen, L. (2015). The balanced scorecard as a management tool for arable farming. Proceedings in Food System Dynamics, Jelgava, Latvia, 262–275.
   Google Scholar
• Pitt, M., & Lee, L. (1981). The measurement and sources of technical inefficiency in Indonesian weaving industry. Journal of Development Economics, 9(1), 43–64. https://doi.org/10.1016/0304-3878(81)90004-3
   Web of Science ®Google Scholar
• Routroy, S., & Pradhan, S. K. (2013). Evaluating the critical success factors of supplier development: a case study. Benchmarking: An International Journal, 20(3), 322–341.
   Google Scholar
• Rowland, W. W., Langemeier, M. R., Schurle, B. W., & Featherstone, A. M. (1998). A nonparametric efficiency analysis for a sample of Kansas swine operations. Journal of Agricultural and Applied Economics, 30(1), 189–199. https://doi.org/10.1017/S107470800008166
   Google Scholar
• Schmidt, P. (1986). Frontier Production Functions. Econometric Reviews, 4, 289–328.
   Google Scholar
• Stewart, B. A., Thapa, S., Xue, Q., & Shrestha, R. (2018). Climate change effect on winter wheat (Triticum aestivum L.) yields in the US great plains. Journal of Soil and Water Conservationonon, 73(6), 601–609. https://doi.org/10.2489/jswc.73.6.601
   Web of Science ®Google Scholar
• Taraka, K., Latif, A., Shamsudin, M., & Sidique, A. (2012). Estimation of TE for rice farms in central Thailand using stochastic frontier approach. Asian Journal of Agriculture and Development, 9(2), 1–11.
   Google Scholar
• Tawse, A., & Tabesh, P. (2022). Thirty years with the balanced scorecard: What we have learned. Business Horizons.
   Google Scholar
• U.S.D.A. National Agricultural Statistics Service(NASS). (2016). Quick stats. http://quickstats.nass.usda.gov/
   Google Scholar
• U.S. Department of Agriculture 2000-2018. (n.d.). Commodity Cost and Returns. U.S. Department of Agriculture, Economic Research Service. Retrieved December 31, 2020, from http://www.ers.usda.gov/data-products/commodity-costs-and-returns.aspx/2000-2018./
   Google Scholar
• U.S. Environmental Protection Agency. (2017). Climate Impacts in the Great Plains. Retrieved January 26, 2021, from https://19january2017snapshot.epa.gov/climate-impacts/climate-impacts-great-plains.html/
   Google Scholar
• Vitale, P. P., Vitale, J., & Epplin, F. (2019). Factors affecting efficiency measures of Western great plains wheat dominant farms. Journal of Agricultural and Applied Economics, 51(1), 69–103. https://doi.org/10.1017/aae2018.24
   Web of Science ®Google Scholar
• Websters, J. A., Amosson, S., Brooks, L., Hein, G., Johnson, G., Legg, D., Massey, B., Morrison, P., Peairs, F., & Weiss, M. (1994). Economic Impact of the Russian Wheat Aphid in the Western United States: 1992-1993. Western Great Plains Agricultural Council, Stillwater, Oklahoma.
   Google Scholar
• West, S. C., Mugera, A. W., & Kingwell, R. S. (2022). The choice of efficiency benchmarking metric in evaluating firm productivity and viability. Journal of Productivity Analysis, 57(2), 193–211.
   Web of Science ®Google Scholar