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--- the_regionalised_data_base_capreg [2020/02/11 08:30] – matsz
+++ the_regionalised_data_base_capreg [2020/02/11 09:09] – matsz
@@ Line 102: / Line 102: @@
 The proceedure for gross output (GROF) is similar to the one for activity levels, as correction factors are applied to line up regional yields with given national production:
+\begin{align}
+\begin{split}
+CORR_{GROF,o} &= \sum_{j,r}{Levl_{j,r}O_{j,r}}/GROF_{o,n}\\
+O_{j,r}^*&=O_{j,r}*CORR_{GROF,o}
+\end{split}
+\end{align}
+In case of missing statistical information for regional yields, national yields are used. A special rule is used for fodder maize yields, where regional yields are derived from national fodder maize yields, and the relation between regional and national average cereal yields.
+For grassland and fodder from arable land, missing yields are derived from national ones using the relation between regional and national stocking densities of ruminants, in combination with assumed share of concentrates in terms of a weighted sum of energy and protein per ruminant activity in CAPRI. Those shares are then scaled with a uniform factor to exhaust on average the available energy and protein from concentrates at the national level. Accordingly, higher fodder yields are expected where ruminant stocking densities are high, acknowledging differences in concentrate shares. If e.g. the stocking densities solely stem from sheep and goat, the assumed impacts on yields is higher. In order to avoid unrealistic low or high yields, those are bounded to a 25%-400% range compared to the regional aggregate.
+The input allocation in any given year should not be linked to realised, but to expected yields. Expected yields are constructed using the following modified Hodrick-Prescott filter:
+\begin{equation}
+\text{min} \quad hp=1000 \sum_{1<t<T-1}({y_{t+1}^*-y_{t-1}^*})^2 + \sum_{t}({y_t^*-y_t})^2
+\end{equation}