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Correction of Measurement Error in Monthly USDA Pig Crop: Generating Alternative Data Series AgEcon
Kim, In Seck; Plain, Ronald L.; Bullock, J. Bruce; Jei, Sang Young.
The imputed pig death loss contained in the reported monthly U.S. Department of Agriculture (USDA) pig crop data over the December 1995–June 2006 period ranged from 24.93% to 12.75%. Clearly, there are substantial measurement errors in the USDA monthly pig crop data. In this paper, we present alternative monthly U.S. pig crop data using the biological production process, which is compatible with prior knowledge of the U.S. hog industry. Alternative pig crop data are applied to a slaughter hog model and tested comparatively to USDA pig crop. Test results reject the validity of USDA pig crop data in favor of the alternative data.
Tipo: Journal Article Palavras-chave: Biological production process; Measurement error; Monthly USDA pig crop data; Pig death loss; Agribusiness; Farm Management; Livestock Production/Industries; Q11; Q13; C12.
Ano: 2008 URL: http://purl.umn.edu/47208
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A Stochastic Analysis of the Impact of Volatile World Agricultural Prices on European and UK Agriculture AgEcon
Moss, Joan E.; Binfield, Julian C.R.; Zhang, Lichun; Patton, Myles; Kim, In Seck.
Successive Common Agricultural Policy (CAP) reforms and trade liberalisation have led to a more market-orientated European agricultural sector, with EU commodity prices now more closely linked to world prices. As a consequence EU prices have become more volatile. Greater price volatility increases uncertainty and raises fresh challenges for projections of policy impacts in the EU. To take account of world price volatility stochastic modelling has been applied to the FAPRI-EU partial equilibrium model, which includes a UK modelling system. Stochastic modelling provides a means to capture some of the inherent uncertainty associated with agricultural production systems. By varying assumptions about certain exogenous variables, stochastic models can be used to...
Tipo: Conference Paper or Presentation Palavras-chave: Agricultural policy; Stochastic modelling; Agricultural and Food Policy.
Ano: 2011 URL: http://purl.umn.edu/108771
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