Yield trend estimation in the presence of non-constant technological change and weather effects
AbstractThe 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.
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Bibliographic InfoPaper provided by European Association of Agricultural Economists in its series 123rd Seminar, February 23-24, 2012, Dublin, Ireland with number 122541.
Date of creation: 23 Feb 2012
Date of revision:
Yield detrending; weather information; robust trend estimation; aggregation; Risk and Uncertainty; Q19;
Find related papers by JEL classification:
- Q19 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Other
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