matara district

IN COCONUT ASSOCIATIONS

4.1 Introduction

The survey analyses discussed in Chapter 3 reveals the basic

characteristics of the farms being studied. The appropriate planning

needs were also discussed at the end of the Chapter.

One of the important finding was that most of these farms try to operate in a multi-product environment in which coconut is a major, but

not the sole concern. Their land holdings are small and no

possibilities for expansion are apparent. Most of them consider

farming as the major source of income, and therefore, they appear to be

trying to maximise their returns out of the available limited

resources; basically land and labour. While the need to maximise the resource use efficiency is most pertinent, it is somewhat restricted by a limited choice of alternatives, and their commitments to already established enterprises, such as, asweddumized paddy and perennial tree crops^.

This seems to suggest that, the problem in hand is a limiting and optimising one and therefore the research technique used should be able to optimise in the presence of several constraints in an multiproduct

environment. The basic research tool often adopted in this area in Sri

Lanka is budgeting and it's variants (DMEC, 1981; Etherington and

Karunanayake, 1981; Government of Sri Lanka, Ministry of Finance and

Planning, 1981, 1984). ’While simple budgeting is employed for the

A

Most of the areas where lowland rice is now being cultivated have been derived from the swamp lands and scrub jungles in the lower plains and the valley bottoms. The process of converting these lands to paddy fields for cultivation of rice is locally known as 'uswedduma' and

evaluation of annual enterprises, procedures followed for the evaluation of multiperiod enterprises include; computing the Present Value of the expected flow of future net returns, the Internal Rate of Return from such flows, or the minimum Pay Back Period for the relevant investment alternatives.

Though budgeting is renowned for its simplicity, it has a limited capacity to consider interdependencies among different production variables. Budgeting provides a useful way of considering a given level of resource allocation for farm improvement, but, it is difficult to obtain a set of activities that maximise a given objective of a farmer, with a set of limited resources. This task becomes increasingly difficult as one tries to budget in a multiperiod multiproduct situation. Though, the handling of multiproduct, multiperiod situation has been made easier by the use of computer packages like spreadsheets and specialised packages such as MULBUD (Etherington, 1984) budgeting could still be considered a weak tool for it's inability to optimise while taking into account the many constraints that are working at regional, sectoral and the farm levels.

Based on the background information on the farms and the resource constraints discussed in the preceding Chapter, design and evaluation of alternate farming systems for different size categories of farms will be attempted in the remainder of this Chapter. These analyses will be based on Linear Programming techniques.

4.2 Application of Linear Programming for Farm Planning

Linear Programming (LP) is a planning technique that is often helpful in decisions requiring a choice among a large number of alternatives. The method, when properly defined, is capable of producing an optimal2 mathematical solution to a given set of alternatives and constraints. Though the theoretical basis for this optimising technique has been known for years, its widespread application in planning problems occured only after the invention of

p

An optimal solution is a feasible plan which takes the highest ( l o w e s t ) v a l u e for the objective function that is being maximised (minimised). The feasible plans are those that satisfy certain restrictions (such as resource availabilities) defined in the model.

t h e s i m p l e x a l g o r i t h m f o r s o l v i n g LP p r o b l e m s by D a n t z i g ( 1 9 5 1 ) - S u b s e q u e n t i m p r o v e m e n t s i n t h e met hod and t h e a d v a n c e m e n t s o f t h e e l e c t r o n i c c o m p u t e r , h a v e made LP a u s e f u l a n a l y t i c a l t o o l f o r f a r m p l a n n i n g .

Due t o i t s c omp le x n a t u r e and t h e r e q u i r e m e n t o f c o m p u t e r s f o r e f f i c i e n t m a n i p u l a t i o n o f LP p r o b l e m s , i t s a p p l i c a t i o n i s m o s t l y f o u n d i n t h e d e v e l o p e d w o r l d . However, t h e t e c h n i q u e h a s e f f e c t i v e l y b e e n u s e d f o r d e v e l o p i n g w o r l d a p p l i c a t i o n s by s e v e r a l e c o n o m i s t s . H e y e r ( 1 9 7 1 ) on p e a s a n t f a r m s i n Kenya; Lee ( 1 9 7 4 ) on s m a l l f a r m d i v e r s i f i c a t i o n i n T a i w a n ; Wa rd ha n i ( 1974) f o r l a n d s e t t l e m e n t p l a n n i n g i n I n d o n e s i a a r e some e x a m p l e s . B i g g s ( 1 9 7 4 ) a p p l i e d t h e t e c h n i q u e f o r r u r a l p o l i c y p l a n n i n g i n t h e K o s i r e g i o n o f B i h a r , I n d i a , and s e v e r a l o t h e r s h a v e u s e d t h e t e c h n i q u e f o r m u l t i l e v e l p l a n n i n g . The w e l l known CHAC model i s one e x amp l e ( Gor eux and Manne, 1973)* R e c e n t l y t h e LP t e c h n i q u e h a s b e e n empl oyed f o r a g r i c u l t u r a l d e v e l o p m e n t p l a n n i n g i n T h a i l a n d ( N i c o l e t . a l . , 1 9 8 2 ) . Wit h r e f e r e n c e t o S r i La n ka , t h i s p l a n n i n g t e c h n i q u e h a s b e e n u s e d a t d i f f e r e n t l e v e l s . A m a r a s i n g h e ( 1 9 7 4 ) d e m o n s t r a t e d i t s u s e f u l n e s s f o r s e t t l e m e n t p l a n n i n g i n t h e d r y zone o f S r i L a n k a . S i r i s e n a ( 1 9 7 6 ) d e v e l o p e d a m u l t i s e c t o r a l model o f p r o d u c t i o n f o r t h e S r i La n ka n economy u s i n g LP. De S i l v a and L i y a n a g e ( 1 97 8 ) d e m o n s t r a t e d i t s a p p l i c a b i l i t y f o r f ar m l e v e l p l a n n i n g by a p p l y i n g i t t o a c o c o n u t i n t e r c r o p p i n g p r o b l e m , and S e n a n a y a k e (1979 ) u s e d t h e t e c h n i q u e t o e x ami n e t h e i m p a c t o f new t e c h n o l o g y on s m a l l f a r m e r s i n t h e d r y z o n e o f S r i La n ka . R e c e n t l y , B o g a h a w a t t e ( 1 98 4) e xa mi n ed t h e m u l t i p l e e n t e r p r i s e s m a l l f a r m s i n t h e M o n a r a g a l a d i s t r i c t o f S r i L a n k a , u s i n g a s t a t i c LP model and c r o s s - s e c t i o n d a t a . Though he f o l l o w e d t h e wh ol e f ar m a p p r o a c h , d i d n o t c o n s i d e r an y i n t e r c r o p s i n h i s m o d e l . 4 . 2 . 1 A p p l i c a b i l i t y o f LP f o r t h e De v e l o p me n t o f O p t i m a l Farm P l a n s f o r S r i La nk an C o c on u t F a r m e r s As s t a t e d e a r l i e r , t h e u s u a l f a r m p l a n n i n g t o o l i n S r i Lanka h a s b e e n B u d g e t i n g and G r o s s M a r g i n A n a l y s i s . F o r t h e f a r m e r s h o w e v e r , t h e p o p u l a r e v a l u a t i o n met ho d i s ' c o m p a r i s o n ' w i t h t h e n e i g h b o u r s l a n d . De s i l v a and L i y a n a g e ( 1 9 7 8 ) d e m o n s t r a t e d t h e u s e o f LP method f o r p l a n n i n g i n t e r c r o p p i n g i n c o c o n u t l a n d s , i n an e l e m e n t a r y s t a t i c m o d e l . B u r g e s s ( 1 9 7 7 ) u s e d m u l t i s t a g e L i n e a r P r og r ammi ng f o r p l a n n i n g

intercropping in Western Samoa. Several other instances of application of the technique for cropping system design are found in literature(E.g: Kapur and Kahlon, 1964; McCarl and Nuthall, 1982; Hanson and Oborne, 1985).

These different applications of LP both in static and dynamic models, demonstrates the possibility of specifying the interrelationships between different productive processes. Dynamic or intertemporal models could handle interrelationships between perennial and annual crops and the use of flexibility restraints-^ allows one to define crop linkages over time.

Heady (1971) showed how efficiently the programming techniques could be used for planning in different environments. He emphasised that the technique is universally applicable, but what matters is how the planning model is formulated to suit the planning environment in question. The task, as he saw, was in the hands of the analyst. He described that there is sufficient generality in all farms which enabled one to use the optimising technique. He added that all farms have plans, whether formal or informal; they face physical constraints such as land and labour; all farms have institutional or subjective restraints which restrict the range of feasible plans available for actual operation. Finally, all farms have an objective function of some type to be maximised or a goal to be achieved, and have alternative enterprises or activities which compete for the use of resources. He noted that the contribution from these alternative enterprises, to the objective to be optimized could effectively be modelled, using relevant weights, which often exist in all economic environments. Thus, he concluded that the ability of the analyst in effectively specifying the situation under study determine the validity of the model. In fact this holds true for all modelling studies in general.

As discussed in the preceeding two Chapters, the problem in hand could be effectively specified within a programming framework. The ability to consider the choice of alternative technologies (such as different cropping patterns) , is considered to be one of the major

restraint used to define minimum or maximum limits of an activity in successive time periods.

advantages of a LP model. The ability of LP to handle both equality and inequality constraints, resource transfer betwen activities and ability to handle lower and upper bounds, increases the reality of a model. Further the Simplex algorithm for solving LP problems provides two solutions. One relates to the activities is called the Primal and the other relates to the constraints is called the Dual. It can be shown that the Primal solution implies the solution of it’s Dual or vice versa. When one specifies the resource allocation problem in quantity terms one can obtain the price solution for resources as the Dual. This is conceptually the same as the valuation of resources in a competitive economy.

There are a wide range of crops and enterprises which are technically feasible in coconut associations. These enterprises could be combined in different ways to produce an infinite number of combinations. While it is not possible to consider all the combinations, nor all of those would be socially acceptable and feasible. Even if a few of those combinations are to be evaluated to identify the profit maximising combinations, within the availability of resources, the conventional budgeting techniques would require enormous amount of planning time. The National Planning Division of the Ministry of Planning, Sri lanka, in fact considered that for such an analysis LP as the appropriate analytical tool(Government of Sri Lanka, 1984).

For these reasons and the other advantages of LP discussed earlier in this Chapter, LP was considered appropriate for the present planning situation. Formulation of the planning model and its underlying assumptions are discussed in the preceeding section^.

4.3 The Planning Model

Two basic models are considered. One is a static model aimed at obtaining the combination of activities in a cross sectional situation, while the other is an intertemporal model extending over a planning horizon of ten years. In principle both models are partial optimization

No discussion on the underlying assumptions of the LP techniques or its limitations will be discussed here, since it has been extensively discussed in variuos texts(e.g.; Baumöl, 1977; Sposito, 1975; Wagner,

models. Here we fix the level of some activities namely; lowland rice, tea and rubber, as the case may be for each zone, and permit the levels of the remaining activities to be decided in the programming process.

In a conventional programming model we define a set of constraints, coefficients, and activities and seek to determine the bundle of activities which would maximize the stated objetive function. By contrast, in the partial optimization approach, we fix the level of certain activities and observe the effect on the objective function and other resource requirements such as capital, as in the present model.

In document Planning multiple enterprise farming systems in coconut associations : Matara district of Sri Lanka (Page 73-96)