input_allocation
Differences
This shows you the differences between two versions of the page.
| Both sides previous revisionPrevious revision | Next revisionBoth sides next revision | ||
| input_allocation [2020/02/11 09:44] – [Input Allocation] matsz | input_allocation [2020/02/11 09:45] – [Input allocation excluding young animals, fertiliser and feed] matsz | ||
|---|---|---|---|
| Line 21: | Line 21: | ||
| All of the econometric coefficients were required to be transformed into an ‘activity level’ form, due to the fact that this is the definition used in the CAPRI model. Before this could be done, it seemed necessary to fill up the matrix of estimated coefficients because some estimates were missing and others were negative. In order to this we constructed a number of coefficients that were weighted averages among certain groups. These mean coefficients were the following. | All of the econometric coefficients were required to be transformed into an ‘activity level’ form, due to the fact that this is the definition used in the CAPRI model. Before this could be done, it seemed necessary to fill up the matrix of estimated coefficients because some estimates were missing and others were negative. In order to this we constructed a number of coefficients that were weighted averages among certain groups. These mean coefficients were the following. | ||
| + | - //Mean coefficients of activity groups//. Each activity was allocated to a certain group (e.g. soft wheat belonged to cereals). For each group we built weighted averages among the positive estimates within a group using the estimated t statistics as weights. This coefficient only existed if there was at least one positive estimate inside that group and was then used to replace the gaps inside the coefficient matrix. If that mean coefficient was not available, due to no positive estimate inside a group at all, the next type of mean coefficients became relevant: | ||
| + | - //Mean coefficients for an activity among European regions//. This second type of mean coefficients calculates weighted averages among three types of regional clusters. These clusters are Northern European States, Southern European states and all European regions. Again, the estimated t statistics were used as aggregation weights. Unfortunately, | ||
| + | - //Mean coefficients for activity groups among regional clusters//. Here we calculated for the three regional clusters the averages of the first type of mean coefficients. As even the latter are synthetic, we gave each mean of them the same weight. Fortunately there was only a small probability that this coefficient did not exist for one of the groups as this was only the case if no coefficient inside a group over the entire EU had a positive estimate, which was not the case. | ||
| + | |||
input_allocation.txt · Last modified: 2022/11/07 10:23 by 127.0.0.1