1. 1 CAPRI CAPSTRAT Workshop Bologna, 24 th and 25 th March 2003 Improved Mediterranean submodule

2. 2 CAPRI CAPSTRAT Workshop Bologna, 24 th and 25 th March 2003 Objectives  Methodological work for modelling  Data base for perennials at the regional level for major producing regions.  Perennial sub-module in GAMS. Working paper 02 - 07 Sources identified. Almost all data compiled. Further operations needed Decision to be taken about the software to perform estimation and integration into GAMS

3. 3 CAPRI CAPSTRAT Workshop Bologna, 24 th and 25 th March 2003 Methodological considerations  Problem  Approaches: Based on Time Series Analysis Available statistical regional information on permanent crops is scarce To capture the heterogenity of the production capacity To capture the lagged decision making process State Space Approach: Kalman Filter (KF1 and KF2) Multinomial Logit Model (MLM)

4. 4 CAPRI CAPSTRAT Workshop Bologna, 24 th and 25 th March 2003 Assesment and conclusions  The KF1 model  The KF2 model .  The MLM improves the CAPRI approach by: Might be practical for the case of selected regions with available information, not for the whole system. Seems potentially feasible and innovative. However, still too many parameters to elicit. Estimation not sure to be ready and assessed during CAPSTRAT span Extending the regional information (CAPRI only used data for one triennial period). Introducing economic variables at the RHS. Making simulations possible..

5. 5 CAPRI CAPSTRAT Workshop Bologna, 24 th and 25 th March 2003 Methodological remarks I: Multinomial Logit Model Purpose: to obtain consistent estimated values for the shares of different crops in the total arable land. Shares are dependent on exogenous variables and error terms. Mathematical tools in order to get equations which are linear in parameters. From: W it =(exp (f it +u it ))/  j (exp (f jt +u jt )) Log(W it )=f it +u it -log(  j exp (f jt +u jt )) To: Log(W it /W t )=a i +  j b ij X jt +u it This method allows us to create a dynamic system by means of lagged, dependent variables. Log(W it /W t )≡Y it =a i +  j b ij X jt +   d ik Y kt-1 +u it

6. 6 CAPRI CAPSTRAT Workshop Bologna, 24 th and 25 th March 2003 Methodological remarks II: State-space approach Advantages: filling information gaps at regional level, separating estimation of the qualitatively different planting and removal decisions. State-space equations: y(k) = C x(k) + e yk x(k +1) = A x(k)+ B u(k)+ e xk  Kalman filter: Given currents estimates of the state variables x^(k|k), the Kalman filter predicts the state value at the next period k+1, and then adjust the prediction with the measurement information.

7. 7 CAPRI CAPSTRAT Workshop Bologna, 24 th and 25 th March 2003 Model Specifications: the MLM approach (I) First Stage: national level. Autorregresive models + Multinomial Logit Model Original data Olives Vineyards Fruits Olives for oil Table olives Table grapes Table wines Other wines Apples,... Citrus Other fruits Original data Olives Vineyards Fruits Second Stage: regional level Autorregresive models Result: estimates of the shares of the 8 CAPSTRAT activities into the broader ones at the national level Result: estimates of the broader activities at the regional level

8. 8 CAPRI CAPSTRAT Workshop Bologna, 24 th and 25 th March 2003 Model Specifications: the MLM approach (II) Third Stage: combination of previous calculations Main assumption: the growing rate pattern observed at the national level inside each broad activity is “transferred” to the regional level  = (1+ r j )/(1+ r k ) First stage information: j and k CAPSTRAT activities at the national level and the annual rate of changes for the projection period projected regional ratio (j/k)= (initial ratio j/k)  Second stage projections: broad activity= j+k Final result: estimates of the 8 perennial CAPSTRAT activities at the regional level, incorporating economic variables in the projections

9. 9 CAPRI CAPSTRAT Workshop Bologna, 24 th and 25 th March 2003 Model Specifications: the State- Space approach (I) Young trees Comprehensive and detailed model (see WP 02-07) Original data: acreage of a perennial activity Productive trees Projected acreage Young trees Productive trees Exogenous forecasting STATE VARIABLES SYSTEM FORECASTS

10. 10 CAPRI CAPSTRAT Workshop Bologna, 24 th and 25 th March 2003 Model Specifications: the State- Space approach (II) Sub-activity 1 Allocation model: breakdown of a broad activity into more detailed ones Original data: acreage of a broad activity Sub-activity 2 Projected acreage Sub-activity 1 Sub-activity 2 Exogenous forecasting STATE VARIABLES SYSTEM FORECASTS Economic variables Simulation: changes in the economic variables