SHORT-AND LONG-RUN FARM PLANNING UNDER UNCERTAINTY; INTEGRATION OF LINEAR PROGRAMMING AND DECISION TREE ANALYSIS

The paper presents an approach to an integrated long-run and short-run farm planning under uncertainty, based on a decomposition of the problem into (i) a series of short-run plans, and (ii) a master long-run plan. The series of the short-run plans are parametrically solved by linear programming "variable right hand" techniques and are later integrated into a long-run program using a (computerized) decision tree analysis. The attitude towards risk of the farm operator is expressed in the willingness to maximize the expected value of the income stream over the planning horizon subject to the restriction that alternatives which may lead to lack of liquidity must be eliminated.
Ce travail présenle une approche tentative ďintégrer, sous conditions incertaines, une planification de ferme à court et long terme. La planification est basée sur la partition du problème en (i) série de courte durée et (ii) de tongue durée. Les séries de courte durée sont résolues àľaide dun programme linéaire, et intégreés ensuite dans un programme à long terme àľaide de ľanalyse de "décision arbre."ľattitude envers les risques de ľentrepreneur est exprimée par la volonté-de maxiliser la valeur de revenu prévu au delá de la planification sous resérve de la restriction que des alternatives qui peuvent conduire à un manque de moyens liquides, doivent être éliminees.     

AN ANALYSIS OF PEASANT FARM PRODUCTION UNDER CONDITIONS OF UNCERTAINTY*

In this paper the impact of cotton on a traditional food crop system in a semi-arid area of Kenya is analysed using a linear programming model and sensitivity analysis. Alternative criteria, maximax, maximin, and a standard average return maximand, are used in turn. The solutions are all evaluated as ‘best year’, ‘worst year’, and average values. This gives a range of results that cakes account of the uncertainty in the farming situation. Several policy conclusions follow from the analysis. It is argued that the approach used is more realistic than an approach in which a single maximand is used, and that the simplicity of the approach brings it within reach of many involved in farm production analysis.     

THE USE OF A DECISION MAKER'S UTILITY FUNCTION IN A LINEAR PROGRAMMING ANALYSIS OF AGRICULTURAL POLICY*

A decision theoretic approach to agricultural policy decision making is examined to discover whether a utility function of an Australian Wool Corporation decision maker can be established and, if so, whether this can be used to improve the policy analysing performance of an agricultural sector linear programming model. After discussing the theoretical requirements of the utility function elicitation and the elicitation procedures, the characteristics of the resulting functions are examined. A means for its inclusion in a linear programming framework is described and some analysis of policy is carried out. The general conclusions are that the relevance of the agricultural sector analysis is enhanced by the use of such a utility function.     

A QUADRATIC PROGRAMMING INTERREGIONAL TRADE MODEL: AN APPLICATION AND A PERSPECTIVE*

This paper presents a theoretical activity-type model of U.S. interregional trade for the agricultural sector as an extension of the broad non-linear programming formulation of Samuelson [4] and the quadratic programming reformulation of Takayama and Judge [5]. A shorter model is applied to the problem of examination of the short-run competitive strength of Wisconsin, particularly in beef and pork (interregional) trade. The conclusions for Wisconsin suggest competitive price disadvantages in beef and beef feeding but with belter prospects for expansion for a pork sector At a time of growing interest in the probable impact of expanded and freer Canada-US. trade, this type of programming model is suggested as a significant approach to problems of Canada-U.S. trade. In addition, in an apparently emerging era of regulated marketing and production control, the employing of such a model for interregional market share analysis appears a major possible policy avenue Ce papier présenle un modèle théorique “Type-activiie” du commerce interregional aux Etats-Unis, pour le secteur agricuhurel, en guise ?extension du propos de vaste programmation non-lineaire, tel que formule par Samuelson [4], ainsi que celui de Takayama el Judge [5], qui proposent une réformulation de programmation quadraiique. Un plus petit modèle est appliqué au probleme ?examinalion de la force immédiate et compétitive de Wisconsin, tout particulièrement dans le commerce (interrégional) du boeuf et du pore. Les conclusions tirées pour Wisconsin suggèrenl un prix com-pétitif qui désavantagerait le boeuf el ?alimentaiion du boeuf, mais qui favoriserait ?expansion du secieur du pore A un temps oú?on se préoccupe de ?impact tout probable dûà un commerce plus libre et plus étendu entre le Canada el les Etals-Unis, ce genre de modéle de programmation est suggéré comme étant une approche significative aux problèmes de commerce Canada-Eiats-Unis. En plus, en celle époque qui semble mettre de plus en plus ?emphase sur le marché ajuslé et le comrôle de production, les possibililés ?employer un lei modéle pour ?analyse de la part du marché interrégional nous apparait comme étanl une possibilité majeure en fait de ligne de conduiie.     

PRODUCTION SCHEDULING AND ALLOCATION: A NORMATIVE DECISION MODEL FOR SUGAR MILLING*

An inter-temporal equilibrium model is developed for the purpose of optimizing the scheduling of production in Australian sugar mills. An application of this quadratic programming model is then discussed, and the procedures used to estimate coefficients are outlined. Two tentative conclusions are that mills tend to commence crushing before the optimal starting date and that in many cases they would have been unable to cover their marginal processing costs when producing No.2 Pool sugar in recent seasons.     

ASSESSMENT OF THE OUTPUT OF A STOCHASTIC DECISION MODEL

The concept of stochastic dominance is described and its use is illustrated in relation to the evaluation of the output of a systems simulation model of lucerne haymaking in south-west Spain. Two alternative machinery systems are ranked for various lucerne areas using the criteria of stochastic dominance, and These results are compared with those obtained using mean-variance analysis.     

IMPLICATIONS OF AGGREGATION BIAS FOR THE CONSTRUCTION OF STATIC AND DYNAMIC LINEAR PROGRAMMING SUPPLY MODELS*

Aggregation bias is acknowledged to be one of the more serious problems confronting the Linear Programming approach to supply analysis. Whilst the literature abounds with theoretical solutions to the problem there is a notable lack of ideas on how these solutions might be made operational. This conclusion holds a fortiori for the dynamic case. This paper discusses a practical methodology for the classification of farms in order to minimise aggregation bias, and also the implications of avoiding bias for the specification of dynamic linear models.     

A DYNAMIC PROGRAMMING MODEL OF EARLY POTATO HARVESTING

A vegetable producer often faces complex harvest decisions where yield increases through time and varies across crop area, price is determined in erratic seasonal markets, and harvest rate is constrained. In this paper, a simplified two-period potato harvest problem is developed to define a set of marginal conditions for an optimum. The model is then extended to the multi-period case and numerical solutions are generated for a representative farm in South Wales using dynamic programming. The model provides a general framework for analysing crop harvesting systems and prescribing marginal changes, such as adjustments in the harvest capacity, which improve profitability over myopic harvest patterns.     

FOOD SECURITY IN KWAZULU: RESULTS OF A HOUSEHOLD-BASED PROGRAMMING MODEL

A mathematical programming model of rural KwaZulu, excluding three northern districts, was developed to simulate agricultural production in regions of high and low cropping potential. This model aggregates enterprise levels predicted for four representative households of which two are in the high-potential region and two in the low-potential region. Several economic scenarios are simulated with the model to predict, inter alia, responses to changes in cereal prices, input subsidies, changes in off-farm employment and a rental market for crop land. Long-run food supply response is estimated to be inelastic with respect to changes in product and input prices. Higher food prices harm the majority of rural households. Lower input prices have little impact on household welfare. Conversely, it is predicted that a rental market for arable land could have a large positive impact on crop production and would improve household welfare.     

A TEST OF BAYESIAN LEARNING FROM FARMER TRIALS OF NEW WHEAT VARIETIES*

In this study, elicited estimates of farmers' subjective beliefs about the mean and variance of wheat variety yields were used to test propositions about Bayesian learning developed in the recent literature on innovation adoption. A series of empirical tests of the Bayesian adoption model were conducted using beliefs elicited from farm surveys conducted in 1982, 1983 and 1984. The results of the analysis neither confirm nor reject the Bayesian approach as a model of how farmers revise subjective beliefs, but do raise serious doubts about its realism, and suggest some issues requiring further investigation. Shortcomings in the elicitation techniques are discussed and the assumptions of the Bayesian model are reviewed.