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CAPRI CAPRI

CAPSTRAT Workshop Bologna, 24th and 25th March 2003

Improved Mediterranean

submodule

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CAPRI CAPRI

CAPSTRAT Workshop Bologna, 24th and 25th 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 performestimation and integration into GAMS

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CAPRI CAPRI

CAPSTRAT Workshop Bologna, 24th and 25th 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)

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CAPRI CAPRI

CAPSTRAT Workshop Bologna, 24th and 25th 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..

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CAPRI CAPRI

CAPSTRAT Workshop Bologna, 24th and 25th 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:

Wit=(exp (fit+uit))/j(exp (fjt+ujt))

Log(Wit)=fit+uit-log(jexp (fjt+ujt))

To:

Log(Wit/Wt)=a

i+jbij

Xjt+u

it

This method allows us to create a dynamic system by means of lagged, dependent variables.

Log(Wit/Wt)≡Y

it=a

i+jbij

Xjt+dik

Ykt-1

+uit

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CAPRI CAPRI

CAPSTRAT Workshop Bologna, 24th and 25th 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) + eyk

x(k +1) = A x(k)+ B u(k)+ exk

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.

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CAPRI CAPRI

CAPSTRAT Workshop Bologna, 24th and 25th 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 winesApples,...

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

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CAPRI CAPRI

CAPSTRAT Workshop Bologna, 24th and 25th 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+ rj)/(1+ rk)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

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CAPRI CAPRI

CAPSTRAT Workshop Bologna, 24th and 25th March 2003

Model Specifications: the State-Space approach (I)

Young treesComprehensive 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

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CAPRI CAPRI

CAPSTRAT Workshop Bologna, 24th and 25th March 2003

Model Specifications: the State-Space approach (II)

Sub-activity 1Allocation 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

Economic variables

Simulation: changes in the

economic variables