Yield trend estimation in the presence of non-constant technological change and weather effects

Sarah Conradt, Raushan Bokusheva (), Robert Finger and Talgat Kussaiynov

No 122541, 123rd Seminar, February 23-24, 2012, Dublin, Ireland from European Association of Agricultural Economists

Abstract: The application of yield time series in risk analysis prerequisites the estimation of technological trend which might be present in the data. In this paper, we show that in presence of highly volatile yield time series and non-constant technology, the consideration of the weather effect in the trend equation can seriously improve trend estimation results. We used ordinary least squares (OLS) and MM, a robust estimator. Our empirical analysis is based on weather data as well as farm-level and county-level yield data for a sample of grain-producing farms in Kazakhstan.

Keywords: Risk; and; Uncertainty (search for similar items in EconPapers)
Pages: 16
Date: 2012-02-23
New Economics Papers: this item is included in nep-agr
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:ags:eaa123:122541

DOI: 10.22004/ag.econ.122541

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