wtode1sy the importance of adequate agg~egation of agricultura! data will be hi~hlighted using a sirnpte forecasting 11odel on wheat pro­ duction. 1~ ~country model. the pfanne~s have available ao 11 year time series of aggregated data on wheat pr-oduction. This titlle series, startinq in year TO up to the year flG, comprises data at the national tevef on har~ested ar-ea, production and fertilizer consum~tion related to wheat produ~tion and total arab1e land. The data are given in table l as follo~s: 8 Year Arable Harvested TO TlO Annual growth (per cent) land area (Millions of hect -ares) I 0.46 l 0 .. 55 0 1.8 -9 - Production (Thousands of tons) 392 560 .3.6 Yield (T/ha) 0.85 1.02 r.a fertilizers (kg/ha) (Thousancts of tons) 8 3.6 33 18 15 t 7.5 In order to build up a forecasting model• the plann~r wants to explain the increase t n area for wheat harvesting by the i:ncr ease in the procurement prices of wheat. During the period under review the relative price of wheat, announced before each sowing season. increased at an annual rate of 10 per cent. The basic assumption of the mooel is that, al1 other things remaining equal. the f•usner adjusts the percentage of area planted in wheat to the prices. The refation is as follo~s: A{t) -A(t-1) = o (P{t) -P(t-1)) fl) A(t-1) P{t-1) A. wheat area as per cent of arable farmland P. wheat relative pr~ce b. coefficient of adjustment t. time index fhe r-elation (1) can be expressed as follows: = At t) DP{t) = A{t-1)• ( l • b. OP ( t) J {2) P(t} -P{t-1) P(t-1) 9 -lO - As OP(t) was constant al1 over the period an equal to 0.10~ (2) can be written: Aft) = A(O). t t t + o.t o) 
**Analysis**
The text appears to be focused on analyzing the relationship between wheat production and price, using a simple forecasting model. The data provided is related to agricultural production, harvested area, and fertilizer consumption, which suggests a strong connection to the agricultural sector. The model is designed to explain the increase in harvested area for wheat by the increase in procurement prices of wheat.

**Category**
Agriculture, forestry and fishing