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sensitivity_analysis [2020/03/26 09:37]
matsz
sensitivity_analysis [2020/03/26 09:38] (current)
matsz
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   * The elasticities of demand (DemElas) for meat and dairy products. We recalibrated the demand systems for all countries so that the own-price demand elasticities would be as close as possible to +/- 50% of the standard value, while observing relevant regularity conditions for demand systems.   * The elasticities of demand (DemElas) for meat and dairy products. We recalibrated the demand systems for all countries so that the own-price demand elasticities would be as close as possible to +/- 50% of the standard value, while observing relevant regularity conditions for demand systems.
   * Substitution elasticities (CES) between imports and domestic products and between different import sources were also set to +/- 50% of the standard values. The standard values differ per product, ranging from 2 to 10.   * Substitution elasticities (CES) between imports and domestic products and between different import sources were also set to +/- 50% of the standard values. The standard values differ per product, ranging from 2 to 10.
-  * GHG emission factors (EF) per commodity outside of the EU. Emissions leakage depends more on the relationship between EF in the EU to those outside the EU than on the absolute level. Therefore, we chose to vary only the factors outside of the EU. Since, in general, N<​sub>​2</​sub>​O factors are considered less certain than emissions of CH<​sub>​4</​sub>,​ which in turn are less certain than CO<​sub>​2</​sub>,​ we chose to apply the uncertainty ranges of the IPCC (Blanco et al. 2014) to construct the hi and lo scenarios. The ranges used were +/- 60% for N2O and +/- 20% for CH<​sub>​4</​sub>​.+  * GHG emission factors (EF) per commodity outside of the EU. Emissions leakage depends more on the relationship between EF in the EU to those outside the EU than on the absolute level. Therefore, we chose to vary only the factors outside of the EU. Since, in general, N<​sub>​2</​sub>​O factors are considered less certain than emissions of CH<​sub>​4</​sub>,​ which in turn are less certain than CO<​sub>​2</​sub>,​ we chose to apply the uncertainty ranges of the IPCC (Blanco et al. 2014) to construct the hi and lo scenarios. The ranges used were +/- 60% for N<​sub>​2</​sub>​O ​and +/- 20% for CH<​sub>​4</​sub>​.
  
 We do not know the covariance of the uncertain parameters across countries and products. In order to avoid running a very large number of simulation experiments,​ we chose to implement only the most extreme variants given by setting all parameters of the same type to lo/ML/hi simultaneously (e.g., elasticities of supply of all ruminants in all countries being hi, ML or lo simultaneously,​ etc.). We thus obtained 3×3×3×3 = 81 result sets; this should span the extremes of the result space. We do not know the covariance of the uncertain parameters across countries and products. In order to avoid running a very large number of simulation experiments,​ we chose to implement only the most extreme variants given by setting all parameters of the same type to lo/ML/hi simultaneously (e.g., elasticities of supply of all ruminants in all countries being hi, ML or lo simultaneously,​ etc.). We thus obtained 3×3×3×3 = 81 result sets; this should span the extremes of the result space.
sensitivity_analysis.txt · Last modified: 2020/03/26 09:38 by matsz