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

Finger, Robert and Hediger, Werner (2007): The Application of Robust Regression to a Production Function Comparison – the Example of Swiss Corn.

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.

• Item Type: MPRA Paper
• Institution: ETH Zürich, Institute for Environmental Decisions
• Language: English
• Keywords: production function estimation; production function comparison; robust regression; crop response
• Subjects: Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture > Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C67 - Input-Output Models; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture; D - Microeconomics > D2 - Production and Organizations > D24 - Production ; Cost ; Capital ; Capital, Total Factor, and Multifactor Productivity ; Capacity; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General

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