I FORECASTS FOR AUSTRIAN AGRICULTURE TO THE YEAR 2000 I1 THE FOOD AND AGRICULTURE MODEL FOR AUSTRIA
Karl Michael Ortner
Federal I n s t i t u t e of Agricultural E c o n o m i c s , V i e n n a , A u s t r i a
RR-83-22
September 1983
Originally published a s "Das Model1 der osterreichischen Agrarwirtschaft", in
~ s t e r r e i c h
-
P r o g n o s e n bis z u m Jahr 2000, and "Prognosen fiir die Land- wirtschaft bis zum Jahr 2000", in Methoden u n d Modelle z u d e n ~ s t e r r e i c h-
P r o g n o s e n b i s z u m J a h r 2000, published by Oldenbourg-Verlag, Munich (1982).
INTERNATIONAL INSTITUTE FOR APPLIED SYSTEMS ANALYSIS Laxenburg, Austria
Research Repods. which record research conducted a t IIASA, are independently reviewed before publication. However, the views and opinions they express a r e not necessarily those of the Institute or the National Member Organizations that support it.
Copyright O 1982 Oldenbourg-Verlag, Munich.
Reprinted with permission.
All rights resewed. No part of this publication may be reproduced or transmitted in any form or by any means. electronic or mechanical, including photocopy, recording, or any information storage or retrieval system without permission in writing from the copyright holder.
Cover design by Anka James
Printed by Novographic, Vienna. Austria
FOREWORD
Understanding t h e policy options available t o alleviate the food problem h a s b e e n the focal point of t h e Food and Agriculture Program (FAP) of t h e International Institute for Applied Systems Analysis (IlASA) since t h e p r o g r a m began in 1977.
National agricultural s y s t e m s a r e highly i n t e r d e p e n d e n t and y e t major policy options exist a t t h e national level. To explore these options, t h e r e f o r e , it is necessary both t o develop policy models for national economies a n d t o link t h e m t o g e t h e r by t r a d e and by capital transfers. For g r e a t e r realism t h e models in this s c h e m e of analysis a r e k e p t descriptive r a t h e r t h a n normative.
Models of some 20 countries (where the CMEA a n d EC countries with common agricultural policies a r e counted a s single units), which t o g e t h e r account for nearly 80% of s u c h i m p o r t a n t agricultural a t t r i b u t e s a s a r e a , production, population, exports and imports, a r e linked together t o constitute t h e basic linked s y s t e m .
As a p a r t of this system and t o explore t h e agricultural policy options available t o Austria in t h e context of its open economy, a policy analysis model was developed for Austria by Karl Michael Ortner of t h e Federal Institute of Agricultural Economics, Vienna, in collaboratiorl with the FAP of IIASA.
In t h e s e two p a p e r s , t h e author p r e s e n t s t h e first version of t h e Food and Agriculture Model for Austria (FAMA-I), and forecasts for Austrian agriculture based on this model, respectively. These p a p e r s a r e English translations of articles originaIly published i n German by Oldenbourg-Verlag, Munich, in a book consisting of two volumes entitled: ~ s t e n e i c h - P r o g n o s e n b i s z u m J a h r 2 0 0 0 , and M e t h o d e n u n d Modelle z u d e n ~ s t e r r e i c h - P r o g n o s e n b i s z u m J a h r 2 0 0 0 , edited by Christoph Mandl ( S e p t e m b e r 1982), and a r e reprinted with permission.
KIRIT S. PARIKH P r o g r a m L e a d e r Food and Agriculture P r o g r a m
CONTENTS
FORECASTS FOR AUSTRIAN AGRICULTURE TO THE YEAR 2000
INDICATORS OF AUSTRIAN AGRICULTURE THE FUTURE
FORECASTS FOR AGRICULTURE SPECIFICATION OF SCENARIOS 4.1 Variant S
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Standard4.2 Variant E
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Export-Oriented Agricultural Policy 4.3 Variant D-
Domestic-Oriented Agricultural Policy RESULTS OF FORECASTS FOR THE YEAR 20005.1 Agricultural Prices
5.2 Gross Domestic Product of Agriculture 5.3 Employment in Agriculture
5.4 Coarse Grains
5.5 Other Agricultural Products SUMMARY AND CONCLUSIONS
THE
FOOD AND AGRICULTURE MODEL FOR AUSTRIAINTRODUCTION MODEL STRUCTURE
COMMODITY CLASSIFICATION RESOURCE SUPPLY
PRODUCTION
5.1 Production of Agricultural Goods 5.2 Feed Requirements
5.3 Nonagricultural Production
7 TRADE
7.1 The Demand System 7.2 Foreign Trade
7.3 Raw Materials and Final Products B POLICY MEASURES AND SIMULATION RUNS
Research Report RR-83-22. September 1983
I FORECASTS FOR AUSTRIAN AGRICULTURE TO THE YEAR 2000
Karl Michael Ortner
I n A u s t r i a n a g r i c u l t u r e s u b s t a n t i a l t e c h n i c a l p r o g r e s s h a s b e e n a c h i e v e d s i n c e World W a r 11, a n d this h a s l e d t o h i g h s e l f - s u f i c i e n c y r a t i o s f o r f o o d s . d e c r e a s i n g r e l a t i v e p r i c e s f o r a g r i c u l t u r a l p r o d u c t s , a n d i n c r e a s e d m i g r a t i o n of l a b o r o u t of a g r i c u l t u r e . As f o r e c a s t s , t h r e e s c e n a r i o s w e r e a s s u m e d , w h i c h d i f f e r a c c o r d i n g to t h e l e v e l of p r o d u c t i o n o f a g r i c u l t u r a l g o o d s d e s i r e d b y p o l i c y m a k e r s : ( I ) a c o n t i n u a t i o n of p a s t p r i c e t r e n d s ; (2) a c o n t i n u a t i o n of
c u r r e n t s e l f - s u f f i c i e n c y r a t i o s ; a n d (3) i n c r e a s e d e z p o r t s . I t a p p e a r s that d e v e l o p m e n t s o b s e r v e d in t h e p a s t w i l l c o n t i n u e i n t o t h e f u t u r e b u t with m o d i f i c a t i o n s that c r i t i c a l l y d e p n d o n t h e t a r g e t s o f a g r i c u l t u r a l p o l i c i e s a n d t h e m e a s u r e s t a k e n t o p u r s u e t h e m . T h e r e s u l t s a l s o d e m o n s t r a t e t h a t t h e e c o n o m e t r i c p o l i c y a n a l y s i s s i m u l a t i o n m o d e l c a n p r o v i d e v a l u a b l e i n f o r m a - tion a n d c a n
-
with s o m e i m p r o v e m e n t-
b e c o m e a tool f o r e v a l u a t i n g a g r i - c u l t u r a l p o l i c y a l t e r n a t i v e s a n d t h e i r o u t c o m e s .1 INDICATORS OF AUSTRIAN AGRICULTURE
Within t h e Austrian econoiny agriculture plays a r a t h e r modest role, a s measured by t h e value of its output. In 1980 agricultural output was worth 50.4 billion Austrian schillings ( A S ) , which contributed 3.6% to t h e gross domestic product (GDP). Two-thirds of the value of agricultural production is m a d e up by livestock products. Self-sufficiency ratios a r e usually close t o
100%; i t is highest for milk, and recently the ratios for grains and wine have come close to t h a t of milk. On t h e other hand, with. protein feeds and veget- able oils and f a t s , self-sufficiency ratios a r e particularly low, a t less t h a n 5%.
These products a r e obtained from crops t h a t could be grown in Austria, b u t a t high costs.
Agricultural productivity in Austria has increased rapidly in r e c e n t decades. Improved breeding, feeding, and fertilization techniques, a s well a s
mechanization, b e t t e r education, more efficient farm sizes, production tech- nologies, and transparent markets have contributed to this progress, and have made it possible to reduce significantly the labor input to food production.
The agriculture and forestry sector employed 1 million people in 1950, b u t by 1980 this figure had been reduced to 298800, with increased output (for a n estimate of labor employed in agriculture, see Puwein 1975).
In the past, Austrian agriculture was characterized by the fact t h a t in most instances i t was uneconomic to export agricultural products. Since domestic consumption reacts inelastically to price changes, increased output depresses farm prices, which then no longer cover (labor) costs so t h a t some farmers decide to phase out production and look for employment elsewhere.
The prices of most agricultural products have decreased in real t e r m s and allowed Austrians to buy food more cheaply compared with other goods of t h e same quality and level of processing. According t o a 1974 consumer survey, 26.5% of the expenditure of Austrian households was on food, compared with 34.3% t e n years previously.
Despite the improvements in productivity already achieved, however, there is still considerable potential for further increases in efficiency. Bigger farms in suitable locations can produce a t lower costs and a t higher profit margins, but this usually leads to a disparity in incomes within the agricul- tural sector, which can be compensated for by off-agricultural employment.
In 1979 in 62% of all farms this option was chosen; in t h a t year for the first time the number of full-time farms (116565) was less than t h a t of mountain farms. The average farm size was 8 . 3 hectares of reduced* agricultural land in
1979.
The aim of Austrian agricultural policy is t o achieve self-sufficiency in food. This objective is being given high priority because of the large number of people employed in the agricultural sector, whose a'bsorption into other sec- tors of the economy would entail social hardships t h a t should be avoided as far as possible. Therefore, agricultural m a r k e t s have to be protected from exter- nal shocks t h a t might disturb the desired continuity and price levels. The most effective way of doing this is by imposing limits on exports and imports a n d / o r on the time in which foreign trade is free. Furthermore, tariffs and levies c a n be imposed to make foreign produce more expensive, thus increas- ing t h e competitiveness of Austrian produce on t h e domestic m a r k e t .
Production speczifically for export is rarely successful in the agricultural sector. Wor1.d m a r k e t prices a r e more or less biased through t h e foreign t r a d e regulations of various countries and vary widely because of fluctuating sup- plies resulting, for example, from unstable weather conditions. Only goods of high quality, to be sold through bilateral trade agreements if possible, a r e advisable for export production. Other goods should be offered a t low prices, but these a r e usually a drain on the domestic economy.
*Marginal areas have been reduced by factors of up to 1 2 .
Forecasts for Auslrian Agriculture to the Year 2000
2 THE FUTURE
The f u t u r e of Austrian agriculture will depend on t h e determination and t h e room for action of policy m a k e r s , and t h e l a t t e r will b e m o r e i m p o r t a n t t h a n t h e b e s t wishes directed toward agriculture. The desire t o improve agri- cultural incomes has increased recently with t h e p r o s p e c t of introducing onto t h e m a r k e t a new agricultural p r o d u c t -alcohol. If t h e government decides t o b a n lead additives t o gas a s a m e a n s of reducing atmospheric pollution, alcohol is a n ideal s u b s t i t u t e , and it c a n also serve a s a n anti-knock s u b s t a n c e . However, i t is likely t h a t imported alcohol will be c h e a p e r t h a n t h a t produced in Austria a n d , m o r e importantly, c r u d e oil is c h e a p e r t h a n alcohol. Thus dras- t i c policy m e a s u r e s will have t o be instituted t o realize t h e s e hopes. Also, t h e hope of producing m o r e protein feeds and oil crops s e e m s t o be unrealistic since t h e costs of domestic production a r e too high a t p r e s e n t t o be competi- tive with imports.
Thus t h e challenge for Austrian agriculture lies in e x p o r t s , b u t will t h e prices of agricultural goods rise on t h e world m a r k e t ? Unfortunately, this is unlikely because developing countries i m p o r t technological goods, and pay for t h e m with e x p o r t s of minerals and agricultural p r o d u c t s . Only high-quality, processed agricultural goods c a n therefore be successful on international m a r k e t s and f e t c h an adequate price. Generally, agricultural exports will only t h e n m a k e s e n s e if Austria is able t o d e c r e a s e production c o s t s t o below those of its competitors and t o increase t h e quality of goods for e x p o r t in o r d e r t o be able t o c h a r g e higher prices.
3 FORECASTS FOR AGRICUI.TURE
From a forecast of t h e f u t u r e of agriculture we a r e i n t e r e s t e d not only in t h e r e s u l t s , b u t also in t h e conditions t h a t produce t h e s e r e s u l t s and in ways of influencing t h e s e conditions s o t h a t o t h e r , more desirable resu!ts evolve. In order t o arrive a t s u c h forecasts, c o m p u t e r simulation models have b e e n for- mulated and used. FAMA-1 is one s u c h model, produced in cooperation with scientists of IIASA ( P a r i k h and Rabar 1981). The model r e p r e s e n t s Austrian agriculture mathematically and c a n delineate probable p a t h s of development.
The m o s t i m p o r t a n t insights t h a t c a n be gained from f0recast.s for agri- c u l t u r e a r e t h e development of incomes, employment, prices, regional and s t r u c t u r a l change, foreign t r a d e , and t h e s t a t u s of agriculture within t h e econ- omy. FAMA-1, with t h e exception of regional and s t r u c t u r a l change. produces indicators of all t h e problems mentioned above, provided t h e conditions t h a t accompany t h e development a r e specified thoroughly; whether a c e r t a i n specification is realistic is open Lo subjective judgment. Thus i t is advisable t o r u n various alternatives, c o m p a r e t h e m , and in s o doing t o d e t e r m i n e whether opportunities exist for agricultural policy m a k e r s t o influence and control agricultural s e c t o r development. Conditions governing t h e calculation of fore- c a s t s in this p a r t i c u l a r s t u d y a r e agricultural policy t a r g e t s a n d t h e way in which policy i n s t r u m e n t s a r e used t o zero in on t h e s e t a r g e t s .
The aspect now receiving most attention by agricultural policy makers is the improvement of agricultural incomes. In order to realize this, marly meas- u r e s can be taken, s u c h a s income transfer payments t o mountain f a r m e r s , public investment into infrastructure, subsidized investment credits (see Min- istry of Agriculture and Forestry), and foreign t r a d e management aimed a t raising t h e prices of agricultural goods.
The success of price policies is limited, however, because higher prices encourage higher production and this may lead t o surpluses whose control may become too expensive for the government. However, p e r capita agricul- t u r a l incomes can also rise through the migration of workers t o jobs in o t h e r sectors. If we now wish to choose a criterion t h a t is closely connected with agricultural policy measures taken to control domestic prices, t h e improve- m e n t of incomes does not s e e m t o be a particularly good choice, since it depends too much on t h e size of t h e labor force engaged in agriculture and forestry.
Let us now consider t h e development of prices, which t o a large extent determines levels of income. What price movements are probable? The sim- plest answer is clearly t h a t prices will continue to move a s they have done in the p a s t . But relative prices change and so does the composition of agricul- tural production: more profitable goods will be favored by producers (e.g., industrial-commercial goods), while others will be neglected. However, t h e r e is a chance in this case t h a t either the objective of s e c u r e food supplies or avoid- ing surplus production will n o t be m e t in t h e case of some commodities. Thus prices cannot rise in the future a s they have done in the past if these aims a r e to be achieved. At a certain point in time price ratios m u s t change, mainly when the self-sufficiency t a r g e t of a product is critically low or in t h e process of reaching a n upper limit. Price changes a r e t h u s t h e consequence of t h e vio- lation of certain self-sufficiency t a r g e t s , and these targets can be used t o define t h e conditions t h a t will govern the future development of t h e agricul- tural sector.
4 SPECIFICATION OF SCENARIOS
The scenario variants given below differ firstly in the assumed develop- m e n t of prices during the initial years of the forecast, and secondly in t h e lower and upper limits of self-sufficiency ratios accepted by agricultural po1ic:y m a k e r s and t h e resulting adjustments of prices. The self-sufficiency ratios themselves stay within these limits because producer prices will b e changed over time such t h a t production is guided accordingly. By imposing quotas on imports and exports it is possible, if necessary, t o influence consumption and consumer prices too.
Forecosts for Austriun Agriculture t o the Year 2000
4.1 Variant S - Standard
The prices of all goods increase linearly until 1985 as they did o n average from 1970 t o 1980, and increase proportionally t h e r e a f t e r (with the comsumer price index). These prices a r e protected against world m a r k e t fluctuations through tariffs, levies, and export subsidies. Food security and the avoidance of surpluses a r e defined such t h a t i h e self-sufficiency ratio of an agricultural product may change from its c u r r e n t value by 20% a t the most; these targets become fully effective in 1990 and t h e r e a f t e r .
4.2 Variant E - Export-Oriented Agricultural Policy
In this scenario agricultural prices gradually approach world m a r k e t lev- els, b u t a r e higher than in variant S and t h u s encourage excess output. The prices of "other food" (vegetables, fruits, wine, sugar, potatoes, fats and oils, and coffee) a r e particularly high, in c o n t r a s t with t h e low price of "bovine and ovine meat". Acceptable self-sufficiency ratios a r e t h e n t h e same as in variant S, b u t a r e effective from 1985 onwards in determining price ratios.
4.3 Variant D -Domestic-Oriented Agricultural Policy
As in variant E, the relative prices of agricltural products gradually approach world m a r k e t levels, and these prices favor agricultural expansion.
The self-sufficiency ratios t h a t prevailed around 1979 m u s t again be achieved from 1985 onwards but should not exceed their c u r r e n t levels by more t h a n 5 percentage points.
From a brief comparison of t h e three variants, t h e following picture emerges: In variant S t h e r e a r e a t t e m p t s to continue previous price s t r u c - t u r e s into the future through agricultural policy. In variant E prices change
-
contrary to observation
-
in favor of agriculture and exports are supported and admissible to a greater extent t h a n i n variant D. In the latter, prices change such t h a t domestic consumption is covered by production. as has been observed, b u t additional exports a r e generally limited. Both alternatives t o variant S assume high prices for "other food" (energy crops?).5 RESULTS OF FORECASTS FOR THE YEAR 2000
5.1 Ag:ricultural Prices
Since price policy is important in guiding agricultural production and, since price policy depends on production, t h e a c t u a l development of prices in the alternative variants is of primary i n t e r e s t . The ratio of agricultural prices
t o the general price level ( t h e GDP deflator), gives an overview of that, as showri in Figure 1. In variant S, relative agricultural prices decrease until 1987, increase again until 1990, and fall slightly t h e r e a f t e r . The unexpected u p t u r n in prices occurs because for some products i t becomes necessary t o increase prices in order to motivate f a r m e r s toward higher production t o reduce the amount of imports required. Since these prices a r e not subse- quently adjusted downwards, self-sufficiency ratios increase and t h e real prices of t h e corresponding goods have t o be reduced later so t h a t exports do not rise above the s e t limits.
Variant S
, , ,,, , Variant E
,. -.-.-.
Variant DFIGURE 1 Index of agricultural p r i c e s a s a p e r c e n t a g e of t h e overall price index (1976 = 100).
In variants E and D agricultural prices increase rapidly in t h e early 1980s, partly t o t a k e advantage of the export opportunities offered in this case, and partly to s e c u r e t h e self-sufficiency targets of those products wh.ich, in t h e process of restructuring agriculture, would otherwise be neglected. Higher prices induce f a r m e r s t o invest, expand livestock herds. increase production capacities, and eventually t o produce so m u c h t h a t t h e upper bound for financing surpluses is reached. Exports a r e constrained, domestic prices fall rapidly and bring about a contraction phase. In the 1990s price movements gradually level off.
Forecasts for Aushicm Agriculture t o the Year ZOO0
5.2 Gross Domestic Product of Agriculture
The real gross domestic product of agriculture measures the quantity of food produced. A t the relatively low real prices of agricultural goods during t h e 1980s in variant S i t is not surprising t h a t production grows least (see Fig- u r e 2). A remarkable, smooth growth occurs only in t h e 1990s, during which t i m e t h o s e prices t h a t have been raised in the late 1980s in order t o maintain domestic food supplies above critical levels come into effect.
lo
r
,-.,- - - - - .. - -
Variant Variant Variant S E DI
FIGURE 2 Gross domestic product of agriculture in billion Austrian schllings (1976) In variant E the increase in production is highest. The opportunities t o export dairy products and to substitute imports of "other food" a r e fully util- ized. In variant
I>
these opportunities are smaller because t h e y a r e limited t o t h e c u r r e n t self-sufficiency ratios plus 5%. Agricultural production t h e n rises, a s i n variant E, but only for as long as is allowed for by the diminishing inclina- tion of the government t o finance exports.The growth of agricultural production until t h e year 2000 is between 1 . 3 and 2.3% annually, depending o n the price and trade policies t h e n being pur- sued. 'l'he share of agriculture in the G D P shown in Figure 3 demonstrates once again t h e effects of the different agricultural policy t a r g e t s in variants S, E, and D. The observed decrease of this share from 1970 t o 1980 essentially disappears by the year 2000. In the variants with higher self-sufficiency ratios for agricultural products i t rises t o 4%, although it eventually levels out to between 1.8 and 2.6%. How cIosely the share of agriculture in the G D P is reIated t o t h e movements of agricultural prices c a n be s e e n by comparing Fig- u r e s 1 and 3.
Variant S
, , , ,
-
Variant E,.-.-.-
Variant DIn t h e model FAMA-1 t h e GDP for 1980 was overestimated by AS 13 billion (base 1976) because t h e recessions of 1975 and 1978 were not t a k e n into account. Until the year 2000, the growth r a t e of t h e GDP is estimated t o b e 2.3% per annum in variant S. The highest growth r a t e is predicted in variant D, where agricultural production is constrained according t o domestic d e m a n d , t h u s freeing labor for use in o t h e r sectors of t h e economy.
0
5.3 Employment in Agriculture
I I
As a result of t h e unfavorable development of agricultural prices in vari- a n t S, labor migration out of agriculture increases dramaticaly until 1990.
Only from t h e n o n do policies aimed a t maintaining c e r t a i n self-sufficiency t a r g e t s for foods s t a r t t o be effective because of rising agricultural prices in r e a l t e r m s and improvements in agricultural incomes. Out-migration virtually halts, and t h e flow even reverses slightly (see Figure 4). The minimum n u m b e r of persons required in agriculture and forestry is 190000, which is approached o n t h e s a m e development p a t h in t h e forecast of t h e Institute of Economic Research (Schneider 1978).
Out-migration until 1983 is high, and is virtually t h e s a m e in all variants, although in variants E a n d D agriculture experiences massive price increases during t h a t period. The reason is t h e slow economic growth a t t h e end of t h e 1970s, which held back mobile labor in agriculture b u t was disregarded by t h e model. The immobility of t h e labor force during t h a t period is compensated for by t h e model in t h e first years of t h e forecast through increased out-
1970 1980 1990 2000
FIGURE 3 GDP of agriculture as a percentage of GDP.
Forecasts for Austtian Agriculture t o the Year 2000
/ - - -
-- - --
0
.. .. -- -
0
..
200
-. -
0
----.-.-
Variant S
, , , , , Variant E
,
. , . ,.-
Variant D0
1970 1980 1990 2000
FIGURE 4 Labor employed in agriculture and forestry (in thousands).
migration. In 1986, however, t h a t t r e n d reverses and agriculture s t a r t s t o a t t r a c t m o r e labor, which soon results in a n undesirable surplus of agricul- t u r a l p r o d u c t s , the imposition of export quotas, and a severe slump in f a r m prices. Workers move o u t of agriculture, leaving only 1'70 000 by the year 2000 in variant D.
In variant E the favorable development of agricultural prices and t h e maximal utilization of t h e world m a r k e t for the export of dairy goods, pork, and grains, accompanied by high production of "other food" (fruits, wine.
sugar, e t c . ) have a serious effect on employment. Only a f t e r 1990 a r e addi- tional food supplies n o t exported any m o r e , and t h u s have a depressing effect on domestic p r i c e s so t h a t t h e n u m b e r employed in agriculture and forest.ry d e c r e a s e s t o 240 000 by the y e a r 2000. The production of t h e s e workers is s o high t h a t only protein crops and beef do n o t r e a c h the upper admissible limits of self-sufficiency ratios.
5.4 Coarse Grains
The model results on t h e individual s e c t o r s of agriculture a r e certainly interesting, b u t a r e not r e p o r t e d h e r e in full for reasons of space a n d c l a r i t y . However, one example will be described: t h e s e c t o r of coarse grains (excluding wheat and rice), i . e . , barley, rye, oats, mixed grains, and corn, was chosen because it is t h e m o s t i m p o r t a n t crop s e c t o r in Austria.
Wheat is excluded because it is t r e a t e d as a s e p a r a t e s e c t o r in t.he model a n d is s u b j e c t t o s t r i c t e r controls by t h e grains marketing board. The
forecasts for wheat eventually t u r n out to be little different from those f o r coarse grains, which a r e mainly used for livestock feed. The prices of these grains determine profitability, feed consumption, total domestic consumption, t h e self-sufficiency ratio, and even foreign t r a d e policy because export quotas a r e determined a s a function of domestic consumption. The model results account f o r all t h e s e effects and i t is thei-efore difficult to find simple explana- tions for t h e changes t h a t occur from year t o y e a r .
Let us first look a t t h e development of real prices, as illustrated in Figure 5. Up t o 1985 variant S prices follow earlier t r e n d s , but in 1986 production increases unexpectedly, and f u r t h e r decreases in real prices become neces- sary in o r d e r to constrain exports to desired levels. By 1989 t h a t has b e e n accomplished and prices remain c o n s t a n t in r e a l t e r m s . Livestock production increases, feed consumption goes up, coarse grain output rises t o m e e t t h e demand, and in 1996 reaches a level a t which exports a r e so high t h a t down- ward adjustments in real prices have to be made in o r d e r to discourage f u r t h e r increases in coarse grain production. The corresponding development of production is displayed in Figure 6.
Variant S
, , , , , Variant E
,
., , . .,
Variant DFIGURE 5 Real producer prices of coarse grains in AS/kg (base year 1976)
In variant E real prices increase until 1985 and t h e n fluctuate a t about t h e s a m e level while production expands. In o r d e r to halt f u r t h e r production increases and t o re-establish competitiveness with wheat, grain prices have t o fall steeply in r e a l t e r m s in t h e following years. In t h e 1990s in variant E exports continue a t about 900 000 tonnes p e r a n n u m , while in variant D 250 000 tonnes is t h e admissible maximum. That n o t only depresses t h e real price of
Forecasts fwr Austrian Agriculture to the Year 2000 11
-
. -.-
, / a I.@... \Variant S
-
, , , , , Variant E,
.
,. , . -
Variant D1
FIGURE 6 Production of coarse grains.
grain b u t also those of all other agricultural goods, mainly because livestock feed becomes cheaper. Out-mjgration from agriculture increases and farmers invest less in their businesses. In variant D structural change occurs until 1993 and agriculture is carried on m u c h less intensively. In the year 2000 coarse grain production is 4 . 3 million tonnes, whereas in variant E it is 6.3 mil- lion tonnes (on almost the same agricultural a r e a ) . The higher production costs in variant E a r e of course only acceptable a t higher prices for products.
5.5 Other Agricultural Products
If prices of agricultural products lag a s f a r behind those of other goods and services as they do in variant S i t is not surprising t h a t agricultural pro- duction stagnates or even falls. The highest falls occur in the categories bovine and ovine m e a t , milk, and "other food", whereas grains and "other m e a t and eggs" production increases. The drop in milk output is remarkable because it is not t h e consequence of individual f a r m quotas (introduced in 1978), but of t h e price policy assumed in this scenario. In t h e late 1980s agricultural prices have t o rise, with t h e effect t h a t production increases steadily after 1987 without reaching the upper limits of admissible exports The upper limits of self-sufficiency ratios a r e only reached by grains and "other meat".
In the export-oriented variant E t h e real prices of "other food" increase until 1989, t o almost double those in variant S. For t h a t reason the production of "other food" is expanded by some 50% until 1990. Since these products a r e labor- and capital-intensive many persons and investment goods are employed
a t the expense of the production of other agricultural commodities. To main- tain their competitiveness, the price of this "other food" therefore also has to be raised in both variants E and D during the 1980s.
Prices a r e changed in order t o ensure t h a t the self-sufficiency ratio of a commodity group stays within admissible limits. The price of "other food" in variant E increases toward world market levels only until 1989, when self- sufficiency ratios approach the admissible maximum, a s shown in Figure 7. In variant D this happens earier and in variant S even t h e lower limit is violated and is only reached again in 1990, a s required in t h a t scenario.
-
/ - - - - - / \ # -/
.-
/. ./-
/-
-*- . -.
0 . / . e m - - . -
.-./. -
-
Variant S
, , ,,, , Variant E
,
.
,. ,.,
Variant DI
FIGURE 7 Self-sufficiency ratios of "other food"
In the period of high prices during t h e 1980s t h e agricultural sector expands and i n variant E the upper limits of self-sufficiency a r e not m e t only by the commodities "bovine and ovine meat" and protein crops. For bovine and ovine m e a t the t a r g e t prices a r e particularly low. In variant D self- sufficiency ratios a r e constrained within narrow ranges and sometimes even fluctuate between t h e m . Otherwise, t h e t r e n d s follow closely those of variant E except t h a t the process of expansion is followed by a contraction a t a n earlier point in time and the contraction is more radical.
Forecasts lor A a t r i u n Agriculture to the Year 2000
6 SUMMARY AND CONCLUSIONS
The results of the model runs a r e clearly somewhat different from what one would ideally wish and expect from forecasts. Agricultural development in the alternative scenarios vary widely, particularly during the years 1980-90.
The s t a n d a r d and t h e other two variants differ from one a n o t h e r substantially.
Only in the 1990s does a somewhat parallel development occur among all vari- a n t s after agriculture has adjusted t o the new economic conditions.
Obviously the conditions assumed in the alterative scenarios a r e impor- t a n t : agricultural policy is one aspect of these conditions; the position of domestic agriculture in relation t o foreign countries is another. Both a r e interconnected, for just the political determination t o s e t up a n export- oriented agricultural system is not sufficient. There m u s t also be s u p p o r t from t h e f a r m e r s t o supply products cheaply s o t h a t they a r e competitive on foreign m a r k e t s . The dilemma is t h a t a t low domestic prices t h e agricultural sector shrinks and produces less t h a t can b e exported, and a t high prices t h e competiveness t h a t is so urgently needed for exports disappears.
The a r t of agricultural policy making, keeping overall economic efficiency in mind, is t o And a way out of this dilemma, and t h a t way is greatly d e t e r - mined by t h e development of world m a r k e t prices. This is shown by variants E and D, particularly in t h e 1980s, when agriculture deviates from its previously quite smooth development, when prices a r e favorable and exports financed by t h e government. However, one has to ask whether such radical changes s u c h as, for instance. t h e increases in consumer food prices (see Figure 1) would be readily accepted. That is improbable, and the agricultural s e c t o r is unlikely t o have t o face the price rises and slumps forecast by variants E and D for t h e 1980s. Nonetheless, it is reasonable t o assume t h a t these variants delimit the range of conditions within which agriculture will operate during the 1990s.
In addition, t h e variant S forecast for the 1990s is not. completely realis- tic. Agricultural prices fall too far, for to long a tirne, too many people migrate from employment in agriculture too quickly, and the original agricultural pol- icy has to be suspended eventually. But since, once changed, prices remain a t a higher level, t h e r e is a phase when agriculture s t a r t s t o expand from t h e lower to the upper limits of self-sufficiency. In reality, this expansion would be controlled in an a t t e m p t to regulate production according t o domestic con- sumptlon, as is done in variant D. The future development of agriculture is thus likely t o be between variacts S and D: in the 1980s closer. t o variant S, and in the 1990s closer t o variant D. Variant E should be considered a s an upper limit of t h a t development begun in variant D towards production for export, but stopped early.
This study has shown t h a t t h e future of Austrian agriculture depend.^ cru- cially on t h e conditions t h a t evolve arcund t h e r e s t of the domestic economy and foreign t r a d e . Furtht:rmore, agricultural policy will guide its development t o a large e x t e n t by deciding on domestic supply t a r g e t s , and on the measures t h a t should be t a k e n to attain these t a r g e t s . However, t h e s e policy decisions a r e also subject t o the prevailing conditions and t h u s policy m a k e r s only parti- cipate in a n overall development t h a t is h a r d to predict if one wishes to take interdependencies into account. The forecasts of this r e p o r t to a considerable
degree do just t h a t , and a r e thus useful in providing further insights into t h e funtioning of t h e Austrian economic system. However, b e t t e r insights and more a c c u r a t e forecasts and prescriptions a r e only possible if t h e task of shedding light on t h e complexities of t h e agricultural sector through mathematical abstraction is continued and intensified. This may t h e n lead t o a model t h a t can be used t o help analyze p r e s e n t and pressing agricultural pol- icy problems.
REFERENCES
Bundesministerium fur Land- und Forstwirtschaft (annually) Bericht uber die Lage der osterreichschen Landwirtschaft. Wien.
Parikh, K. S. and F. Rabar (Eds) (1981) Food for All in a Sustainable World: The IIASA Food and Agriculture Program. SR-81-2. Laxenburg, Austria: International Insti- tute for Applied Systems Analysis.
Puwein, W. (1975) Arbeitskrafte in der Land- und Forstwirtschaft. WIFO Monatsbe- richte 48: 334-47 (In German only).
Schneider M . (1978) Entwicklungsmoglichkeiten d e r osterreichischen Land- und Forstwirstschaft irn Rahmen d e r Gesamtwirtschaft. Der Forderungsdienst 26:
145-9 ( ~ n German only).
Research Report RR-83-22. September 1983
I1 THE FOOD AND AGRICULTURE MODEL FOR AUSTRIA
Karl Michael Ortner
T h e Food a n d A g r i c u l t u r e P r o g r a m of IIASA is a n a l y z i n g t h e w o r l d food s i t u a t i o n a n d t h e p r o b l e m s e n c o u n t e r e d . I n o r d e r t o m a k e i t p o s s i b l e t o e v a l u - a t e t h e o u t c o m e s of p a r t i c u l a r p o l i c i e s , d y n a m i c a l l y r e c u r s i v e e c o n o m e t r i c m o d e l s f o r t h e e c o n o m i e s of i n d i v i d u a l c o u n t r i e s a n d c o u n t r y g r o u p s h a v e b e e n d e v e l o p e d a n d l i n k e d t o g e t h e r b y t h e i m p o s i t i o n of g e n e r a l e q u i l i b r i u m c o n d i t i o n s . A m o n g t h e s e e f f o r t s a first v e r s i o n of t h e Food a n d A g r i c u l t u r e Model f o r A u s t r i a (FAMA-1) w a s s e t u p a n d isd e s c r i b e d in this p a p e r . I t d i s - t i n g u i s h e s n i n e a g r i c u l t u r a l c o m m o d i t i e s a n d t h e r e s t of t h e e c o n o m y , a n d is u s e d t o s i m u l a t e e c o n o m i c d e v e l o p m e n t o v e r a m e d i u m - t e r m t i m e h o r i z o n . E x o g e n o u s t o t h e m o d e l a r e p o l i c y t a r g e t s a n d d e c i s i o n s , in p a r t i c u l a r p r i c e s a n d f o r e i g n t r a d e q u o t a s .
1 INTRODUCTION
The simulation model for Austrian agriculture presented here evolved from the Food a n d Agricu.lture Program (FAP) of IIASA. The aims of the FAP a r e (Parikh and Rabar 1981, Rabar, 1981, Ortner, 1981).
t o evaluate t h e world food situation and its dimensions;
t o identify the causes of problems in it; and
t o analyze and suggest policy actions towards their solution
The world food problem is a problem of individual countries, and the pol- icy actions for its solution a r e decided upon a t the national level. World m a r k e t conditions influence these actions, and the actions of individual coun- tries in t u r n influence t h e world markets. It follows t h a t a global model is necessary for a n analysis of how the world food problem can be disposed of, and t h a t national governments are t h e actors in this model and decide upon
m e a s u r e s to be taken.
The global model of t h e FAP consists of a linkage algorithm and national models t h a t have certain common features: a descriptive type of model; a common commodity classification a t t h e international exchange level; annual time increments; a dynamically recursive linkage of supply and demand; a time horizon of 15-20 years, and linear homogeneity in prices. These f e a t u r e s have b e e n incorporated in order to e n s u r e t h a t national models can be linked and s o t h a t a general equilibrium c a n be attained in all national and interna- tional commodity markets.
A national model is supposed in particular t o serve a s a tool in t h e pro- cess of arriving a t economic policy decisions by showing
how domestic economic development depends on events t h a t occur in foreign countries;
what results can be expected from various proposed or implemented economic policy measures;
t o what e x t e n t political i n s t r u m e n t s a r e consistent with t h e t a r g e t s towards which they a r e directed; and
which policy measures a r e necessary or advisable in o r d e r t o avoid undesirable developments and to bring about desired ones.
The work of producing national models was partly carried o u t by r e s e a r c h e r s a t IIASA and partly delegated t o national collaborating institu- tions. At IIASA a databank was s e t up with t h e support of t h e FAO, essentially covering t h e food balances of most countries, and this was used t o s e t up models for t h e so-called basic linked system (BLS). The BLS is t h e first ver- sion of a global model representing roughly 80% of t h e world's population, agri- cultural production, and foreign t r a d e by individual national models.
In order t o come up with t h e BLS in a short time, the models for a s e t of countries organized as m a r k e t economies were c o n s t r u c t e d using a common s c h e m e . The d a t a for their construction a r e available a t IIASA and were sup- plemented with d a t a from national a n d international statistical sources. In this way t h e model of t h e Austrian economy presented h e r e evolved a s p a r t of t h e work devoted t o the development of the BLS. Of those persons who contri- buted significantly t o t h e Austrian model I should like to acknowledge Fischer and Frohberg (1980) who undertook many of t h e tasks of estimating, program- ming, concept.unlizing, and formulating the model. The original concept of t h e study was outlined by De Haen (1978).
The work on t h e food and agriculture model for Austria (FAMA) is still in its early stages. We intend to produce a model t h a t depicts t h e agric!ultural economy in a s much detail as possible, its relations t o o t h e r s e c t o r s of t h e economy, and its dependence on t h e prevalent economic s t r u c t u r e and agri- cultural policy. In particular, we hope t h a t the model will be used b y t h e Aus- trian Federal Ministry of Agriculture and Forestry a s a means of simulating and forecasting t h e effects of alternative agricultural policy m e a s u r e s and t o help e n s u r e t h a t decisions towards t h e realization of agricultural policy t a r - g e t s c a n be t a k e n with more confidence.
Food and Agnculhtre Model for Austria 17
Since t h e cost of producing models increases exponentially a s they become more complex, various intermediate versions of FAMA can be developed. One of these is presented h e r e and applied in order t o generate discussion, give critical advice a chance t o influence t h e model, and possibly to encourage the involvement of other interested parties. A t the same time, we wish t o demonstrate
-
with currently r a t h e r confined means-
the types of uses we anticipate for t h e model. In any case t h e reader is asked t o keep in mind t h a t the version presenied h e r e is t h a t of May 1981 and does not exploit all possibilities since offered by the algorithm (FAMA-1).2 MODEL STRUCTURE
Generally speaking, FAMA consists of a supply component, a demand component, and a policy component. The l a t t e r defines t h e conditions t h a t guide production and demand over time and which a r e determined by policy measures and decisions. The connection between supply and demand is not simultaneous b u t recursive, i.e., production takes place before goods a r e traded. When domestic supply e n t e r s t h e m a r k e t , quantities a r e Axed, and t h e prices determine domestic demand and foreign t r a d e . A t this point agri- cultural policies a r e crucial.
Policies Expected prices
FIGURE 1 Structure of t h e model FAMA.
Target prices World market Actual prices prices
Figure 1 depicts t h e model s t r u c t u r e in somewhat more detail and also reveals t h e series of decisions taken by producers, consumers, and t h e government t h a t s e t t h e agricultural system in motion. We s t a r t a t t h e point when t h e economic agents in the various sectors have earned some income, which pays for their contribution of factors of production and thus provides some indication of how t h e s e factors should be allocated in the future.
F u r t h e r indicators a r e t h e prices that a r e expected t o prevail for products and factors of production, which depend on t h e economic performance of the previous period. The input supply component specifies, according t o actual wages, t h e quantities of individual factors t h a t will be employed in the various economic s e c t o r s during t h e c u r r e n t period. The factor allocation model
Demand I Foreign trade
specifies the uses of factors of production in t h e production of various goods within a n e c o n x n i c sector. Factor allocation is governed by expected prices and technology and determines, a t given production functions and possibly within politically decreed constraints, t h e quantities of various commodities t h a t will be produced in a sector. The intermediate inputs required per unit of production a r e of course accounted for in the allocation decision. Finally, t h e supply component calculates in t h e form of domestically produced goods t h e endowments of actors available for exchange on t h e m a r k e t .
In addition t o the endowments of economic actors t h e r e a r e their demands for goods and services. These demands a r e primarily determined by t h e prices of final goods and by the incomes of consumers. The latter vary according to t h e economic sector in which they are employed. Demand can b e m e t partly by domestic and partly by foreign products, b u t foreign t r a d e is subject to certain conditions with which t h e public sector has to comply.
Differing prices on domestic and foreign m a r k e t s a r e possible only if t h e r e a r e t r a d e restrictions, levies, tariffs, or export subsidies, and foreign t r a d e has t o close with a certain balance.
The results of running the exchange component of the model a r e domes- tic prices and net t r a d e quantities (exports minus imports) of the various commodity aggregates. In addition, t h e financial drain on t h e national budget by t h e corresponding export subsidies (minus import revenues) is determined.
Since production prices a n d external drains on the national budget a r e known, i t is t h e n possible t o calculate t h e GDP and the incomes of economic agents.
A national model can be run independently of t h e global model; t h e only requirement is t h a t world market prices a r e given exogenously and do not depend on specific national decisions. Austria is hardly likely t o influence world m a r k e t prices through its trade policy, so this precondition can reason- ably be assumed to hold. Thus simulation runs for t h e Austrian economy c a n be m a d e for any kind of scenarios concerning the world m a r k e t without having t o apply the global model.
The public sector is able t o influence and control economic development a t any level: a t the level of factor supply through t h e management of i n t e r e s t r a t e s and t h e willingness to save; a t the factor allocation level thr.ough c r e d i t policies and supply quotas; and a t the demand level through fiscal and foreign t r a d e policies These are only some of the most important measures and indi- cate those areas in which alternative policy instruments primarily operate.
With t h e s e instruments the course of the economy is guided towards t h e overall social optimum for the population, and our i n t e r e s t concentrates on analyzing t h e effects of certain measures. These measures, or the rules according t o which policy instruments a r e s e t , a r e t h u s more or less exo- genous to t h e model and provide t h e background against wh.ich the model simulates economic development in a particular application.
In the following sections I present t h e components of the FAMA-I used t o calculate t h e results reported in the preceding paper. Some of t h e s e com- ponents have not y e t passed t h e entire validation stage of model building and will be replaced by b e t t e r ones a s time allows and know-how and data become available. 1 t h u s deliberately abstain from critical comments and r a t h e r just p r e s e n t t h e approach chosen for discussion.
Food a n d Agriculture Model for Rustria
3 COPY ODITY CLASSIFICATION
FAMA-1 differentiates seven primary products, 20 intermediate goods, and t e n final (consumer) goods, a s listed in Table 1. Data on a r e a harvested yield p e r h e c t a r e , production, imports, changes in stocks, exports, feed, seed, industrial consumption, and waste, were obtained from t h e F'AO on magnetic t a p e . They covered t h e years 1961-76 and some 5 0 0 agricultural products, classified according to the Standard International Commodity Classiflcation (SITC). These products were aggregated into some 250 goods and f u r t h e r to t h e commodity groups listed, using content coefficients or average world m a r k e t prices in the years 1969-71 as weights.
Domestic producer prices were taken from Paritatsspiegel and exclude value-added tax. The prices of consumer goods a r e obtained from these prices by t h e addition of t h e value of nonagricultural services t h a t transform t h e raw product t o the consumer good.
TABLE 1 Commodity classification in the food and agriculture model FAMA.
Unit 1000 t PE
1000 t
Aggregate
Y" Q XC
Wheat 1 1 1
Rice (2) 2 2
Coarse grains 3 3 3
Ruminant protein 7 17
Bovine and ovine meat 4 4 I
PE
Million US$ (1970) FE f
Million US0 (1970)
Milk 5 5
Other meat, eggs and fish 8 6 6
Protein feed 7
Protein crops 4 7
Meat meal 13
Fish meal 14
Other food 8 8
Nonoile 5 19
Oils and fats 20
oils of Q7 18
fats of Q, 11
fats of Q6 12
NonIood agriculture
Industrial crops (hops, tobacco) 6 9
Wool and h d e s of ruminants 15
I
Hides of other animals 16
Nonagricultural goods and services 10 10
1
a A t production level.
Products and byproducts.
A t trade level.
Protein equivalent = 1000 t crude protein.
Sugar, potatoes, fruits, vegetables, wine, beverages.
f Fat equivalent = 1000 t p u r e fat.
In the following equations, capital l e t t e r s designate time series variables, and other characters r e p r e s e n t p a r a m e t e r s estimated econometrically or oth- erwise. Superscripts relate t o commodity groups (see Table 1) and subscripts a r e used t o differentiate goods or economic sectors. Variables without sub- scripts depict in this case the s u m over subscripted variables; however, in definitions they represent any one of them. A post- and subscript -1 indicates a variable relating to t h e previous year.
In t h e first round of decisions taken by producers t h r e e variable factors of production can be identifed: human labor, capital stock, and fertilizer util- ized. The size of the labor force is given by
L = b POP b = b ( T), where
L = number of persons employed and self-employed P O P = population (exogenous)
b = participation r a t e of t h e population in employment T = time t r e n d .
The labor force is divided into two sectors, agriculture ( A ) and nonagri- culture (N, t h e r e s t of t h e economy), depending on t h e capacity of agriculture t o release or absorb labor:
LA = 1. 177(VA v ~ ) ~ ' ~ ~ ~ ( L ~ ) - ~
where
LA = labor force in agriculture LN = labor force in nonagriculture
V = value of gross production per person employed G = gross domestic product.
Capital stock in t h e two sectors is calculated from initial capital, gross investment (which is split between t h e sectors), and depreciation rates:
-
I = 0.312(G
+
~ ) - ~ + 0 . 2 0 7 ( ~ - ,-
&)-13.222 -I = I / D , where
I = gross investment
D = GDP deflator (Divisia index)
- = sign for real values (base year 1970)
B
= balance of t r a d e .Food a n d A p i c u l t u r e Model for Austria
where
-
K = capital stockk = depreciation r a t e of capital
The application of fertilizer depends o n its real price and on the previous year's production of crops:
M = c ~ ( ~ ~ / F ~ ) ! ~ " "
- - PM
= c 2 P N c = c ( T ) whereM
= (nitrogen) mineral fertilizer comsumption _Gc-
= r e a l value of crop productionPJ,
= r e a l price of fertilizerPN
= r e a l price of the nonagricultural ( t h e n t h ) goods c = proportionality coefficients.5 PRODUCTION
5.1 Production of Agricultural Goods
The decision rule of agricultural producers is assumed t o be t h e principle of profit maximization. The factors of production in agriculture will be allo- c a t e d t o the various commodities such t h a t t h e value of goods will be as high a s possible. The measure for this value is t h e expected n e t revenue of goods t o be produced. In addition, the production decision is governed by technical factors (the technology), which can be represented by linear or neoclassical production functions. The advantage of t h e l a t t e r is t h a t they allow for con- tinuous substitution between factors of production and t h u s need f a r fewer p a r a m e t e r s t o r e p r e s e n t technology. The amount of d a t a would even suffice for statistical estimation of these parameters.
Unfortunately, for t h e allocation of factors of production t o individual agricultural sectors no historical d a t a exist, s o if we still wish t o produce a n econometric model, both the allocation and the p a r a m e t e r s of t h e production functio.1~ have to be determined simultaneously. This c r e a t e s considerable methodological problems, b u t they can be solved through t h e development of a n appropriate iterative estimation procedure. Agricultural technology is represented by a system of particular Cobb-Douglas production functions, which incorporate t h e property t h a t r e t u r n s t o scale diminish if t h e
distribution of factors of production to t h e various goods changes. The pro- duction function for t h e agricultural sector a s a whole is linearly homogene- ous. The available factors a r e diverted for the production of goods according to a n objective function with expected n e t r e t u r n s . A naive price expectation scheme is assumed.
Agricultural producers maximize with a given technology t h e following objective function:
where
(11, 13, 15) (12, 14, 16)
(1, 2, 3, 5 , 7, 8, 13, 14) a (PI, T )
expected prices (for explanation of superscripts s e e Table 1) feed requirements of commodity Qi per unit of production of commodity Z;- (see Section 2)
quantity of commodity Qi produced per unit of production of commodity Z;. (byproduct i of j)
s e t of indices of Q designating byproducts of bovine and ovine m e a t , and other animals, respectively
s e t of indices of Q designating
commodities
t h a t a r e partly used as feeds.The expected prices of the disaggregated products and byproducts depend o n t h e prices of traded goods in t h e previous year through t h e use of fixed-value shares of particular goods, namely protein feeds, "oils and fats", and "other food". The prices of "oils and fats" and "rest of other food" stay in constant proportion. A time dependence of these s h a r e s , proportionality coefficients, feed requirements, and byproduct coefficients was only allowed for in t h e reference period 1961-76. The prices of f e e d s ( P K ) a r e slightly lower t h a n their m a r k e t prices in order to account for quality deficiencies and t h e lack of marketing costs.
Maximization of t h e objective function is subject t o t h e technical and organizational level attained in the agricultural s e c t o r , which is represented in t h e model by a system of nonlinear equations. The system is linearly horno- geneous for the agricultural sector a s a whole and has diminishing r e t u r n s to scale for individual commodities as their share in t h e factors of production increases. Substitution between factors is possible and is characterized by a n elasticity of substitution of unity. Technical progress is represented in t h e fol- lowing production functions through time-dependent production elasticities
( E , p) (embodied technical progress):
Food a n d Agriculture Model for Austria
where
ci = constant
Ki = capital used in the production of commodity i
L+
= labor used in the production of commodity i Mi = fertilizer used in the production of commodity iu+ = stochastic disturbance.
In the production functions for meat (Y7 and Yo ) t h e variables concern- ing fertilizer are disregarded. Fertilizer used for meadows and pastures is determined before simultaneous allocation of the remaining fertilizer on the basis of expected production of bovine and ovine protein. Since the distribu- tion of factors to t h e various production activities has not been observed, the estimation of production function parameters s t a r t s a t the most probable allocation of factors, judging from normative experience. That allocation in all years of the reference period satisfies the condition
C R ~
s R f o r R =i
The objective of the estimation of parameters representing technology is the minimization of
where w, (= 0.1) is a weighting factor for resource R (capital, labor, fertilizer).
The estimation is made through a n iterative procedure, beginning with assumed initial estimates for the parameters and by trying to minimize p (by changing t h e parameters) assuming t h a t the disturbance t e r m is indepen- dently normally distributed. A program for nonlinear least-squares estimation developed by Giinther Fischer (IIASA) was used. This allows for simultaneous estimation of the parameters of any system of equations a t inequality con- straints for t h e domain of parameters. The estimates of parameters of t h e production functions were subject to t h e following inequality constraints:
Additional constraints, i.e., t h a t some parameters have to be greater t h a n zero or less t h a n or equal to one, follow from the Cobb-Douglas specification. Since the estimation leads t o either a local or a global minimum
downgrade their importance, a n additional p a r a m e t e r was added t o t h e sys- t e m of equations, namely a constant p by which t h e p a r a m e t e r s
8 ,
y , and 6 of t h e production functions are multiplied. F u r t h e r m o r e , p serves a s a n exponent of t h e expected net revenues in t h e objective function and, since it was estimated a t 0.784, decreases the price elasticity of production. The scale elasticity of t h e sector ( t h e sum of the exponents of K A , LA and M ) remains unchanged a t unity.5.2 Feed Requirements
Feed requirements of the two livestock categories are covered b y feed commodities Q from the index s e t K. Considering t h a t some substitution between feeds is possible, the following allocation rule was assumed: F a r m e r s minimize feed costs Zl subject to the conditon t h a t Yi units of livestock com- modity 1 ( 1 = 7 , 8 ) can be produced:
C
f k i = 1k EK
where
pi = expected price of feed k Fkl = use of feed k by livestock 1
f = production elasticity of feed k for livestock 1 .
The feed requirement coefficients aki are t h e solutions to this minimiza- tion problem and are needed and used in the objective function of agricultural producers (see Section 5 . 1 ) .
5.3 Nonagricultural Production
Technology is represented by a linearly homogeneous Cobb-Douglas pro- duction function with changing factor shares. Nonagricultural production is thus:
Y l o = ~ O . ? ' ( K ~ ) ~ N ( L ~ ) ~ - ~ N
E N = 0 . 3 7 8 / ( 1
