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The Application of Robust Regression to a Production Function Comparison – the Example of Swiss Corn

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Abstract

The adequate representation of crop response functions is crucial for agri-environmental modeling and analysis. So far, the evaluation of such functions focused on the comparison of different functional forms. The perspective is expanded in this article by considering an alternative regression method. This is motivated by the fact that exceptional crop yield observations (outliers) can cause misleading results if least squares regression is applied. We show that such outliers are adequately treated if robust regression is used instead. The example of simulated Swiss corn yields shows that the use of robust regression narrows the range of optimal input levels across different functional forms and reduces potential costs of misspecification.

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  • Robert Finger & Werner Hediger, 2008. "The Application of Robust Regression to a Production Function Comparison – the Example of Swiss Corn," IED Working paper 08-02, IED Institute for Environmental Decisions, ETH Zurich.
    • Handle: RePEc:ied:wpsied:08-02
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    3. Blasch, Julia & Farsi, Mehdi, 2012. "Retail demand for voluntary carbon offsets – a choice experiment among Swiss consumers," MPRA Paper 41259, University Library of Munich, Germany.
    4. Michele Baggio, 2012. "The Optimal Management of a Natural Resource with Switching Dynamics," IED Working paper 12-19, IED Institute for Environmental Decisions, ETH Zurich.
    5. Sarkar, Sampriti & Lupi, Frank, 2022. "Modelling mid-western corn yield response to phosphorus fertilizer in Michigan," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322478, Agricultural and Applied Economics Association.
    6. Boere, Esther & Mosnier, Aline & Bocqueho, Geraldine & Krisztin, Tamas & Havlik, Petr, 2016. "Developing country-wide farm typologies: An analysis of Ethiopian smallholders’ income and food security," 2016 Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 246924, African Association of Agricultural Economists (AAAE).
    7. Thomas Bernauer & Lena Maria Schaffer, 2010. "Climate Change Governance," IED Working paper 10-12, IED Institute for Environmental Decisions, ETH Zurich.
    8. Finger, R. & Gerwig, C.N., . "The Impact of Climate Change on the Profitability of Site Specific Technologies," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 43.
    9. Rohling, Moritz & Ohndorf, Markus, 2012. "Prices vs. Quantities with fiscal cushioning," Resource and Energy Economics, Elsevier, vol. 34(2), pages 169-187.
    10. Salvatore Di Falco & Marcella Veronesi, 2014. "Managing Environmental Risk in Presence of Climate Change: The Role of Adaptation in the Nile Basin of Ethiopia," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 57(4), pages 553-577, April.
    11. Dewbre, Joshua, 2010. "Improving resource allocation and incomes in Vietnamese agriculture," IFPRI discussion papers 984, International Food Policy Research Institute (IFPRI).
    12. Thomas Epper & Helga Fehr-Duda & Renate Schubert, 2011. "Energy-Using Durables: The Role of Time Discounting in Investment Decisions," IED Working paper 11-16, IED Institute for Environmental Decisions, ETH Zurich.
    13. Späti, Karin & Huber, Robert & Finger, Robert, 2021. "Benefits of Increasing Information Accuracy in Variable Rate Technologies," Ecological Economics, Elsevier, vol. 185(C).
    14. Claassen, Roger & Duquette, Eric & Horowitz, John & Kohei, Ueda, 2014. "Additionality in U.S. Agricultural Conservation and Regulatory Offset Programs," Economic Research Report 180414, United States Department of Agriculture, Economic Research Service.
    15. Severini, Simone & Tantari, Antonella & Di Tommaso, Giuliano, 2016. "The instability of farm income. Empirical evidences on aggregation bias and heterogeneity among farm groups," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 5(01), pages 1-19, April.
    16. Ines Kapphan & Pierluigi Calanca & Annelie Holzkaemper, 2011. "Climate Change, Weather Insurance Design and Hedging Effectiveness," IED Working paper 11-17, IED Institute for Environmental Decisions, ETH Zurich.
    17. Finger, Robert, 2010. "Evidence of slowing yield growth - The example of Swiss cereal yields," Food Policy, Elsevier, vol. 35(2), pages 175-182, April.
    18. Horowitz, John & Ueda, Kohei, 2013. "Paying Farmers to Reduce Nitrogen Application on Corn: The Baseline Approach," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150561, Agricultural and Applied Economics Association.
    19. Markus Ohndorf, 2010. "Optimal Monitoring for project-based Emissions Trading Systems under incomplete Enforcement," IED Working paper 10-13, IED Institute for Environmental Decisions, ETH Zurich.
    20. Finger, Robert, 2011. "Reductions of Agricultural Nitrogen Use Under Consideration of Production and Price Risks," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114356, European Association of Agricultural Economists.
    21. Finger, Robert, "undated". "How strong is the “natural hedge”? The effects of crop acreage and aggregation levels," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122538, European Association of Agricultural Economists.
    22. Finger, Robert, 2012. "Nitrogen use and the effects of nitrogen taxation under consideration of production and price risks," Agricultural Systems, Elsevier, vol. 107(C), pages 13-20.
    23. Finger, Robert, 2012. "Modeling the sensitivity of agricultural water use to price variability and climate change—An application to Swiss maize production," Agricultural Water Management, Elsevier, vol. 109(C), pages 135-143.

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    Keywords

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    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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