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A modelling framework for fisheries development planning
Ocean & Shoreline Management 14 (1990) 11-33
A Modelling Framework for Fisheries Development Planning M. Khorshid Techno-Economics Division, Kuwait Institute of Scientific Research (KISR), PO Box 24885, 13109 Safat, Kuwait and Cairo University, Giza, Egypt
& G. R. Morgan Marine Culture and Fisheries Department, Kuwait Institute of Scientific Research (KISR), PO Box 24885, 13109 Safat, Kuwait (Received 12 September 1989; accepted 15 December 1989)
ABSTRACT An approach to model building is described which begins with the establishment of a matrix reflecting the basic features of the fisheries sector, and then proceeds to incorporate these features into a model structure. The model includes a set of policy objectives and constraints, and is formulated as a mathematical programming problem. The modelling framework enables quantitative data on fish resources, production techniques (including aquaculture), market demand forecasts and other biological, economic and marketing parameters to be utilized in assessing the implications of various fishery policy objectives. The model not only estimates the real cost of alternative policies but also takes into account the various biological and economic constraints to production. Rapid assessment of a range of policy objectives is therefore made possible. As an example of the application of the modelling framework, the development of a fisheries sector plan for Kuwait is described. Such planning involved establishing the most appropriate way to maximize fresh fish self-sufficiency while reconciling the production from a multi-gear, multi-species capture fishery with the need to develop an aquaculture industry in the country. The modelling framework allowed the rapid identification of appropriate development policies consistent with the biological, economic and marketing constraints of the fisheries sector and also allowed an assessment of the cost of each policy objective. 11
Ocean & Shoreline Management 0951-8312/90/$03.50 © 1990 Elsevier Science Publishers Ltd, England. Printed in Northern Ireland
12
M. Khorshid, G. R. Morgan
1 INTRODUCTION Utilization of fish resources, whether for food or for recreational use, is a tradition which, up to the middle part of the 20th century, developed by evolution rather than by directed management aimed at the optimum utilization of the available resources. Beginning in the 1950s, however, and receiving considerable impetus from the Law of the Sea discussions, interest in the management and development of these fisheries resources increased rapidly so that today, most countries and international development agencies have some form of fisheries development programme, no matter how loosely framed. This surge of interest in fisheries development, particularly in developing countries, was, as Royce (1987) points out, t a result of the combination of several decades of rapid growth in world fish production; and also the perceived opportunities available from the new authority granted by the acceptance, in 1974, of the concept of a 200-mile Exclusive Economic Zone (EEZ). Many countries saw this event as an occasion for gaining control over vast (and commonly overestimated) and valuable fisheries resources, and proceeded to prepare plans for the development and exploitation of this new-found wealth. The manner in which many fisheries development plans were conceived, however, assumed that the previous rapid growth in world fish production would continue and, as a result, took little account of the limitations to development imposed by the fish stocks themselves. The often poor state of knowledge of these fish-stocks compounded the problem. This has led to several spectacular calamities and the failure of many development plans to achieve their original aims. 2 Such failures, and the experience being accumulated with fisheries development programmes in many regions has led to the now widespread understanding that fisheries development needs to be based initially on a detailed understanding of the fish resources and the way they respond to changes in fishing effort or fishing techniques. This implies an ongoing scientific programme to better understand the limitations on production of the various fish stocks, and the way in which these production limits can be best achieved. However, in addition to quantitative data on the fish stocks, which is necessary for making fisheries management decisions, the broader function of fisheries development also requires data on the social, economic (including marketing), and infrastructural aspects of the sector. The need for quantitative data of these types in the formulation of fisheries development programmes has been less recognized, although such data are often collected and available. Also, since there is often interaction,
A modellingframework for fisheries developmentplanning
13
either at the social, economic or marketing levels, between the fisheries sector and other sectors (particularly agriculture), the extent of such interaction needs to be understood and quantified. The evolution of fisheries development planning from purely descriptive plans which reflected short term, often political, aspirations to those based on quantitative data (including projections from those data) is proceeding rapidly in a number of countries. However, until now, integration of the various data, and the analyses based on them, translated into a comprehensive development plan was not possible since there was no generally applicable analytical tool available to analyse such multi-input, multi-objective problems. The objective of this paper is, therefore, to present a mathematical modelling framework which has been developed in Kuwait to assist in this process of analysing a variety of quantitative data from various sources within the fisheries sector. The model also provides assistance in examining the implications of various policy objectives. The model is not intended to replace the administrative and political decision-making processes which are a necessary part of the formulation of any development plan, but rather to act as a tool for the rapid assessment of policy decisions on supply sources and particularly on costs. The real cost to the fisheries sector of any policy objective can therefore be easily and rapidly estimated.
2 THE NEED FOR A PLANNING TOOL Development planners are generally faced with the central problem of using limited resources to satisfy growing needs. The optimum allocation of these limited resources is then one of their major concerns. The selection of an appropriate allocation pattern necessarily implies a comparison among a considerable number of alternative development policies and planners, both at the national and sectorial level; and the need to have an analytical tool or model capable of comparing various development options and assessing their impact on a selected set of policy objectives. In addition, development planners generally work in an environment of uncertainty (for example, oil sector planners in 1979, when oil was $40 per barrel, did not consider the effects of a price of $13 per barrel which occurred in 1986); so that a tool which provides rapid assessments of alternative scenarios becomes necessary in examining the effects of a larger range of possible external influences. In the fisheries sector, any development programme involves multiobjective scenarios which may include increasing (or decreasing)
14
M. Khorshid, G. R. Morgan
employment in the sector, maximizing fishermen's incomes, maximizing export earnings, satisfying future demand for fisheries products from local resources, and so on. These various objectives are often not mutually compatible so that, in the formulation of a development plan, some criteria must be established to select or give weight to one or more principal objectives. Often, such criteria are politically based, and reflect broader national development policies. One of the common criteria used is the cost to the Government (or the cost to the sector as a whole) of the various development options compared with the potential benefits to be derived. Since the fisheries sector is a highly complex and dynamic mix of biological responses, market responses and varying production costs (both over time and according to various fishing methods), the assessment of such development costs needs to be carried out within the framework of a theory which takes into account the biological, marketing and economic interactions within the sector. In addition, such development costs will change with time according to trends in demand, limitations of the fish-stocks and changes in fishing method; and such changes also need to be estimated by a practical model. In summary, given the various objectives and constraints, fisheries sector planners can use a practical model to efficiently allocate resources among alternative uses. Such optimum allocation of resources is just as important for a net fish exporting country as it is for a net importer, since decisions still need to be made, and resources allocated, to satisfy the demands of both the domestic market and the export customer. In Kuwait, the decision to prepare a fisheries development plan covering the next 20 years was prompted by the Government's concern that fish demand was increasing rapidly while production had stagnated. This had led to a surge in imports, particularly for fresh fish which increased from 1593 metric tonnes in 1983 to 4258 tonnes in 1987. Moreover, the fishing fleet, which is based on traditional wooden dhows and small speed-boats, utilized low technology methods and employed a large number of foreign fishermen. Therefore, the Government's objectives were, in accordance with national economic objectives, to reduce the dependence on imported fish and to upgrade the technological level of the industry, thus reducing foreign labour requirements in the sector. In addition, Government support for the development of an aquaculture industry was seen as a high priority, since such an industry had the capital intensive, high technology characteristics which the Government wanted to encourage. The objectives of the development plan for Kuwait could, however,
A modellingframework forfisheries developmentplanning
15
be achieved under a number of different scenarios. At one extreme, the intensive development of aquaculture technology could conceivably satisfy all future demand for fish in Kuwait while, within the capture fisheries sector, many possible combinations of fishing method and fishing effort level could be used to achieve maximum production. Such combinations are further complicated by the interactions between fishing methods and effort levels as a result of the multi-species, multi-gear nature of the fishery, in addition to being constrained by the response of the individual fish stocks to exploitation. All of these scenarios have different operating cost structures and capital requirements which could only be analysed by the development of an analytical model which reflected the biological and economic realities of the fishery and of the aquaculture industry, and which would enable the rapid estimation of the cost characteristics of the various options.
3 THE MODELLING FRAMEWORK The planning model used to study the development options of the fisheries sector is completely determined by five main steps (see Fig. 1). The first step determines the structural features of the fisheries sector. This includes, for example, the fish species to be considered by the model, the species composition by fishing method, the types of vessels and fishing methods used and the possible options for expanding domestic production. This latter item may include new fishing methods, exploitation of new species or development of new technologies such as aquaculture. In the second step, this information is converted into a modelling matrix. The rows of the matrix indicate the various fish species, whereas the columns reflect the domestic supply options. Each nonempty cell of the matrix estimates annual production by species and production method. Given the modelling matrix, the third step is to formulate production and cost functions for each species-method combination (non-empty cells). This matrix approach provides a useful and efficient way of controlling and systematizing the model-building process. In fact, the output of the modelling exercise can be described as a series of matrices reflecting the structural changes and growth prospects of the fisheries sector during the selected planning period. The fourth step involves determining the set of objectives and constraints which govern the performance and functioning of the sector. Such constraints and objectives will inevitably include the limits to
M. Khorshid, G. R. Morgan
16 (1)
Identify the structural features of the fisheries sector
I (21
Build the modelling matrix linking fish species with different domestic supply options
(3)
Estimate production and cost functions associated with each supply method--fish species combination
(41
Identify sectoral strategy, policy objectives and system constraints
1 I
(5)
1
I Formulate the mathematical programming model
I Fig. 1.
Steps for building the planning model of the fisheries sector.
production of each species imposed by their biological characteristics, the demand characteristics of each species and the production capacity of the fishing fleet in addition to whatever policy objectives (for example, import quotas or encouragement of a particular production technology such as aquaculture) are selected. In step five, the above model-building steps, which are shown in Fig. 1, are then unified in a mathematical programming framework that consists of an objective function and a set of constraints. In the following paragraphs, these five steps for building a planning model for the fisheries sector are described briefly. 3.1 Structure o f the fisheries sector
The first step in the model formulation is to identify the types and numbers of fish species to be included in the model. The selection of these fish categories should be based on several criteria such as the relative importance of the species in the pattern of domestic or export demand, the importance of the species in the landings, the potential contribution of the species to fish supply through new production
A modellingframework for fisheries developmentplanning
17
technologies, and so on. At this stage of the formulation, the species need to be classified by method of production and degree of substitutibility in the market and the structure or supply determined. Figure 2 provides a generalized domestic supply structure for fresh fish supplies (industrial fish products are excluded at this stage, but could easily be incorporated into the model framework) which would be applicable to most countries. The model divides the supply according to four levels of aggregation. In the first level, the domestic supply is broken down into fresh catch (i.e. from the capture fisheries) and aquaculture production. The aquaculture technique is commonly selected to complement the fresh catch production and to increase the level of self-sufficiency (where this is an important policy consideration) and has the advantage of generally being independent of the capture fisheries. The second level of aggregation divides the capture fisheries supply source into that derived from vessels operating within territorial waters and that derived from a far seas fleet. This distinction is necessary to reflect the differences in modes of operation, species composition and particularly the extent of control that exists over the management of, and production from, the resources taken by a far seas fleet. The third level of aggregation divides the fresh catch supply into a set of fishing methods for each vessel type. Here again, the selected set of fishing methods will be country specific. Given the possibility of operating the vessels at different effort levels, through appropriate management decisions, and the need to assess the impact of various effort levels on the selected supply option, the fourth level of aggregation considers different relative fishing effort levels for each fishing method. Finally, the aquaculture supply option is broken down into a number of possible production methods, each of which will have its own supply and production cost characteristics. 3.2 The modelling matrix Given the above technical background, the modelling framework is designed to generate alternative future supply options for the sector under various constraints and objectives. A supply option consists of annual production broken down by fish species, fishing method and relative fishing effort values. Table 1 shows the organization of such output in a matrix format, where rows indicate fish species and columns reflect the method of production. The arrangement of the columns follows the disaggregation scheme for the domestic supply of fish shown in Fig. 2.
~evo,, i
I
i
i
Fig. 2.
i I Other Fishing I Efforts
Domestic supply options for the fisheries sector.
I FishingEffort3 I
i
Jloe~,~e,hod~ O*h°r
I FishingEffort2 I
l
,_ev,~,, i Relative EffortValues IFishingEffortll (FE)
l "*"
l,~a,-~eaVes~o,~l l','eoho,qoe~J l','ec~n,q,.,e,~ I
I
1
I AquacultureMethod j
l O'"N°* l
so,',,,or,a,
i
1
I FreshCatchMethod I
,oM,°~M~*ho° ~,~h','~0~
,~,oo, sype
,_~ve,~
Method
Production
1
I DomesticSupplyof Fish I
~,
g
0
Fo
FEI[
FE1
[ FE2
[ --
[
Relative fishing efforts
Relative fishing efforts [
Gear methods
Gear methods
FE2 [
Far sea vessels
I
1
Territorial water vessels
Fresh Catch fish
Domestic supply offish
LGM--Gear methods used with territorial water vessels. OGM--Gear methods used with open sea vessels. FE--Fishing effort. - - signifies additional methods can be included.
Shrimp Pomphret Grouper Mullet Grunt Sea Bream (+ other fish types)
Fishspecies
TABLE
The Modelling Matrix.
~"
~"
"~
e~
Technique 1 Technique 2 . -- . ~ "~:
Aquaculture
20
M. Khorshid, G. R. Morgan
The modelling matrix, shown in Table 1, can be seen as a way to illustrate the annual production plan of the fisheries sector. This matrix, if projected over time, is able to form the basis of development planning for the fisheries sector and, at any time, indicates the expected levels and sources of supply, vessel requirements and aquaculture development schedules. 3.3 Production and cost functions Two functions can be associated with each non-empty cell in the modelling matrix; a production function and a cost function. The production function defines the gross output of fish as a function of inputs to the production process. Such inputs include fishing method, relative fishing effort and vessel type and size for the capture fisheries, and land, water and labour availability for the aquaculture sector. In addition, the output generated by each fishing method will represent a characteristic species composition for that method and so the selection of a particular fishing method determines the species composition of the gross production. Given the above background, the output from the capture fisheries can be determined by a two-level production function. The first estimates gross output as a function of fishing method and effort. The second level distributes this output to various fish species according to a predetermined species composition. Given the functional forms of the production functions for the capture fisheries and aquaculture, operating costs can be assigned to each production method and to each fishing effort or (in the case of aquaculture) capacity level. 3.4 Objectives and system constraints Rational producers of fish, or any other commodity, generally seek to maximize their profits (or minimize costs) subject to technological constraints (the production function). The production decisions at the micro level, however, are not necessarily consistent with the policy objectives and constraints of the fisheries sector as a whole. Market mechanisms fail, in many cases, to achieve the objectives of the sector, and Government intervention is often required to achieve overall national goals. Government can enter the market as a fish producer. It can also affect the performance of the sector through fiscal policy instruments such as subsidies, taxes, import tariffs, quantity restriction and transfers. To account for the above points, the model needs to explicitly
A modelling framework for fisheries development planning
f
• Species composition by fishing method • Production functions
I • Operating cost per ton broken / down by fishing method and effort • Trade margins and taxes (or subsidies) by fish species
21
• Domestic demand by fish species and maximum possible fresh catch from local sea
Mathematical Model Objectives
, Breakdown by fish species, fishing method and fishing effort
• Feasible aquaculture prod. technique
• Sales price of fish species • Capital cost of vessels by fishing method
• Minimize operating cost • Increase level of selfsufficiency ~ • Implement new production techniques (aquaculture) • Optimize the utilization of fish stock in territorial water • Expand fleet operations to new fishing areas (far seas) ~
~
• Maximum possible fresh catch from local sea
r
_~ [
Constraints
• Demand constraint by species • Maximum fresh catch from territorial water • Fresh catch technical constraints (production function) • Aquaculture technical constraints • Capital budget constraints • Currently available vessels constraint • Constraints on far seas fresh catch
• Possible production size from far seas fleet
• Number of currently available vessels by fishing method
l
Model Output • Optimum domestic supply of fish broken down into fresh catch and aquaculture • Fresh catch production by fishing method and effort • Domestic production of fish by species • Operating and capital cost by supply option • Level of self-sufficiency
Fig. 3.
The overall modelling framework for the fisheries sector.
22
M. Khorshid, G. R. Morgan
consider policy objectives and constraints. The mathematical programming technique provides a direct and efficient means of incorporating such objectives and constraints, in addition to biologically-based constraints, into the modelling framework. The overall modelling framework of the fisheries sector is shown in Fig. 3. The central part of the figure is the mathematical model, which uses various structural parameters of the sector coupled with policy objectives and constraints to generate the appropriate supply option. Development efforts might be directed to minimize operating costs, increase the level of self-sufficiency, implement new production techniques and/or explore new fishing methodologies. The selected supply option is also affected by several technical and economic constraints such as demand satisfaction, capacity of the fish stocks, budget constraints, and so on. In summary, by grouping the structural and technical features of the fisheries sector with policy objectives and constraints, the sectorial planning model is completely determined and can be formulated as a mathematical programming problem, a:
4 AN APPLICATION TO KUWAIT'S FISHERIES SECTOR Kuwait's fishing industry is based largely on a fleet of small, inshore vessels (which include some 207 traditional wooden dhows and about 770 glass fibre speedboats) which take a variety of demersal and pelagic species. Production of fish from these vessels was around 6500 tonnes in 1988, which represented about 55% of the total fresh fish demand in Kuwait. The gap between demand and domestic supply was made up by imports of fresh fish, mainly from India, Pakistan, and the other Gulf countries. In addition to the fresh fish catches, all of which is consumed within the country, there exists a major shrimp fishery which is export orientated. These shrimp catches are taken by a fleet of some 70 industrial trawlers, in addition to about 120 wooden dhows which operate in the shallow water areas. Catches from these two fleets during the 1987/88 fishing season were 2065 tonnes of shrimp, of which 1000 tonnes were exported and the remainder consumed in the domestic markets. In assembling the quantitative data required for inclusion in the modelling framework, the response of the fish and shrimp stocks to changes in the level of exploitation first need to be estimated. Although the fishery is complicated because of its multi-species, multi-gear characteristics, sufficient information was available on the major species to allow a cohort analysis technique 5 to be applied and which enabled
A modelling framework ]:orfisheries development planning
23
the estimation of not only the response of the species to changes in overall exploitation rate but also took into account the interactions between the various fishing gears. Any possible biological interactions between species (for example, via the food-chain) was, however, not explicitly considered. The major fishing techniques which were included were small mesh gill nets (which are used to take small inshore species such as mullets), large mesh gill nets (which are used to target on pomphrets), fixed stake nets, trawling and fish traps. In addition, longlining was considered as a development option, although the technique is not currently practised in Kuwait. These fishing techniques account for over 95% of the fish catches in Kuwait. Changes in overall exploitation rates were considered on a relative basis, with the present level (1988) being considered as 100. Expected yields by species were then calculated, using the cohort analysis technique, for relative exploitation rates from 25 to 200 in steps of 25. These yields by species at the various levels of exploitation rate were then considered in the model as a constraint on production of each species. Since Kuwait does not have (and other studies advised against the development of) a far seas fishing fleet, the option of securing supplies from fisheries resources outside those already exploited was not considered. For each of the fishing methods considered, the percentage species composition of the catch was estimated using actual data for the period 1983-88. This species composition was assumed not to change with changes in exploitation rate so that, when combined with the analysis of the effects of changing exploitation level, this allowed the estimation of the expected yield by species by fishing method at any level of exploitation. The characteristics of the fish species and fishing methods utilized in the study are shown in Table 2. Future demand for fresh fish in Kuwait was estimated from both monthly price and quantity data, which were available from 1975 to the present; and from family budget surveys carried out in 1977-79 and 1986-87. The full methodology and results of these analyses are given in Shaban (1988). 6 Results of this demand study also showed that some species of fish were substitutible in the market. For example, hamoor, sobaity, sheem and sheim (see Table 2) were found to be substitutable at the consumer level, as were maid, hamra and nakroor. The implication of this substitutability is that the model seeks to satisfy the overall demand for each substitutable set rather than satisfying the demand for each of the component fish species. Finally, although there are presently no commercial aquaculture
Local name
Shrimp Zobaidy Hamoor Hamra Maid Sobaity Nakroor Sheim Sheem Tilapia Others
Shrimp Pomphret Grouper Snapper Mullet Sea Bream Grunt Sea Bream Threadfin Tilapia Others
Fish species
Common name
Total
TABLE 2
100
58-3
23.8
100
41.6
26-7 0-3
37.8 11.4
0.1
100
47.9
1.5 3.3
25.7
21-6
Gargoor Large Small (fish gill gill traps) net net
100
9.4
0.2 1-4
1.7 0.4
86-2 0-1 0.6
100
66.1
5-4
23.2 4.4
0.9
Hadra (stake Trawl nets)
Fresh catch fish
100
31.00
2.00 5.00 2.00 5.00
30.00 25.00
Long line
100
100
Sobaity
Domestic supply offish
100
100
Hamoor
100
100
Tech. 1
1000
100
Tech. 2
Tilapia
Aquaculture
Domestic Supply, Fish Species and Percentage Species Composition for Kuwait's Fisheries Sector.
100
50
50
Tilapia sobaity mix
.~
t,O 4~
A modellingframework for fisheries developmentplanning
25
facilities in Kuwait, production technology and costs could be determined from a series of investment feasibility studies which have been undertaken. 7'8 Such studies have indicated that at the present time, only two species could be successfully cultured profitably (the criterion of profitability was necessary for aquaculture development, since Government policy was to provide initial assistance to the development of a viable private sector industry rather than the long term support of unprofitable technology) in Kuwait. These were a local sea bream (locally known as sobaity; see Table 2), for which an already good market demand existed; and tilapia, which although not presently marketed in quantity in Kuwait, appeared as a result of test marketing to have a potential demand of up to 2000 tonnes by the year 2 0 0 8 . 6 Given the above structural features, the planning model for Kuwait included two production techniques (capture fisheries and aquaculture), eleven fish species, six fishing gear methods and eight relative effort values. The production function by fishing method and species was estimated as described above, while the cost function for each fishing method and at each fishing effort level was estimated using data collected in 1988 on the detailed operational costs of the various vessel types. 9 Direct production costs, distribution costs, trade margins and transportation fees from the ports to the final market were included. In addition, taxes and subsidies (or both) were incorporated into the cost function for two reasons. First, this allowed a direct assessment of the impact of the adopted tax or subsidy policy on the choice of the future supply options. Second, the use of these fiscal tools in the model enabled a reflection of Government or consumer preference for a specific fish species. Since cost minimization is a selection criterion in the model, subsidies (or taxes) increase (or decrease) the probability of selecting one species over another as part of domestic production. Given the objectives and structure of the fisheries sector in Kuwait, the model concentrates on the following development issues: (a)
(b)
Minimize the operating cost and increase the revenues of both producers and fishermen by the optimum selection of fishing method and effort levels. This policy issue is incorporated into the model as an objective function. Adopt a food security policy directed at increasing the level of self-sufficiency consistent with the availability and sustainable catches of the country's fish stocks. This policy is incorporated into the model by the introduction of a lower limit on overall production by fish species and, by iteration using varying lower limits, identifying the maximum feasible level of self-sufficiency.
M. Khorshid, G. R. Morgan
26
(c)
Diversify the means of domestic production by the development of aquaculture.
These three policy objectives are coupled with a number of economic and technical constraints to arrive at a complete model structure. Constraints of the model can be grouped into four main categories. The first category relates to the demand satisfaction by fish species. These constraints assume that domestic production must not exceed the projected annual demand, although this constraint could be readily modified to take into account the possibility of an export market for some species. However, such export markets for the Kuwait species are not competitive with the domestic market. As noted earlier, demands constraints are divided into two sets depending on the degree of substitution between fish species. Non-substitutible species have separate constraints, whereas demand for substitutible species are grouped in one constraint. The second set of constraints is concerned with the maximum quantity of fresh fish available to Kuwait (apart from imports), and reflects the production limits of the various fish stocks. The third set of constraints is concerned with the optimal utilization of the presently available vessels, and a budget constraint on the purchase of any new vessels. The first of these guarantees that the current fleet is fully utilized before a commitment is made to increasing the fleet size, while the latter constraint imposes a limit on the investment expenditure for acquisition of new vessels. Finally, the last set of constraints is related to technical aspects of the sector, such as the species composition by various fishing methods, maximum production limits per vessel and the feasible species mix of the fish production. The model was used to conduct comparative static experiments covering the period 1988-2008. The planning horizon was broken down into three benchmark years (1988, 1995 and 2008) in order to estimate the development path of the sector.
5 POLICY ANALYSIS The model was used to address a set of specific policy questions considered to be of particular relevance to Kuwait's fisheries sector. Three strategic issues were considered. First, what is the maximum level of satisfaction of domestic demand for fresh fish that can be achieved from local production sources by the year 2008, and what is
A modelling frameworkforfuheries development planning
27
the production mix of fish species corresponding to this level? Second, what is the lowest cost mixture of supply sources, in terms of production techniques, fishing gear methods and fishing effort levels, required to achieve various levels of self-sufficiency in fresh fish? Third, what are the number and costs (both capital and operating) of new vessels or aquaculture facilities required to achieve various levels of selfsufficiency, and what is the schedule for their introduction? 5.1 Optimal utilization of the current fleet
Table 3 summarizes the results of using the current fishing fleet to satisfy different levels of domestic demand up to the year 2008. The table indicates three important points. First, the maximum level of self-sufficiency achievable using the existing fleet decreased from 57% in 1988 to about 42% of demand in 2008, despite the increase in production of fish from 6897 tonnes to 7200 tonnes during the period. Second, the gross operating costs of the fishing fleet is positively correlated to the level of sufficiency achieved. Thus, increasing the level of self-sufficiency from 30% to 57% in 1988 could only be achieved at the expense of more than doubling the operating costs of the fleet from 1.8 million Kuwaiti dinars to 3-9 million Kuwaiti dinars (1 Kuwaiti dinar = $US3.5 approximately). This resulted from the fact that at the lower level of self-sufficiency requirement, the fleet was able to operate at lower effort levels where production costs were correspondingly low. Third, the maximum catch taken by the existing fishing fleet is less than the maximum possible production from all species combined. This is a result of the species interactions between fishing gear. 5.2 The need for an increase in capacity
The above results demonstrate that, given the various constraints on stock production, demand by species and the characteristics of the presently used vessels and fishing gear, the existing fishing fleet is not able to supply more than 42% of the domestic demand for fresh fish by 2008, and even to reach this level would incur significant costs in terms of increased operating costs of the fishing fleet. Accordingly, to improve the level of self-sufficiency and to reduce the gap between domestic demand and supply, an increase in production capacity would be needed. This production capacity increase can be achieved through expanding the existing fishing fleet, or by the development of aquaculture. Various experiments, the results of which are summarized in Table 4, were
20O8
Operating cost (KD) Production (tonnes)
Operating cost (KD) 1995 Production (tonnes)
Operating 1988 Cost (KD) Production (tonnes)
Year
TABLE 3
35
40
4,235
4,840
4,620
5,280
42
5,145
6,003
6,860
7,203
4,291,473 4,916,495 6,556,794 7,922,255
3,960
2,252,422 2,591,505 2,986,578
3,831
1,816,732 1,968,732 2,248,194
30
50
6,050
52
5,940
6,600
6,864
3,441,770 4,049,505 4,599,886
5,445
2,560,605 2,926,076
45
Degree of satisfaction of demand (%) 56
57
6,655
6,776
6,897
3,414,861 3,562,038 3,903,610
55
Cost and Production of Fish Species Using the Current Fleet of Kuwait's Fisheries Sector.
a
.~
OO
Fresh catch Aquaculture Total
59.30 -59.30
3456354
--
7182 -7182
57.00 15.00 72.00
6255792
4.535
7257 1814 9071
Exp. 2
51-80 25-20 77.00
7963218
7.635
6649 3054 9703
Exp. 3
51.00 -51-00
4152814
--
7242 -7242
Exp. 1
51.20 12.80 64-00
685239
4.545
7271 1818 9089
Exp. 2
1995
49-60 23-40 73.00
9049988
8.330
7033 3333 10366
Exp. 3
° Experiment 1: Only additional fish catch vessels are allowed. No aquaculture is considered. Experiment 2: Aquaculture production should represent 20% of domestic supply. Experiment 3: Aquaculture production should be greater than or equal to 0.
Satisfaction Fresh catch of demand (%) Aquaculture Total
Operating cost (KD)
Number of aquaculture plants
Production (tonnes)
Exp. 1u
1988
40.00 -40.00
7479389
--
7660 -7660
Exp. 1
40-00 10-00 50.00
9928674
4.788
7660 1915 9575
Exp. 2
2008
38.40 27.60 66.00
15098000
13-200
7359 5280 12639
Exp. 3
TABLE 4 The Impact of an Increase in Production Capacity on Satisfaction of Domestic Demand for Fish in Kuwait.
tO
~.-~
~" o, ~"
~"
~-
o~
30
M. Khorshid, G. R. Morgan
carried out and aimed at determining possible expansion of production capacity, and allocation of this increased production to the capture fisheries and aquaculture. In the first experiment, the model was used to estimate the maximum level of self-sufficiency in 2008 that could be achieved by only considering additions to the fishing fleet. The second experiment incorporated aquaculture production, but constrained its contribution to a maximum of 20% of domestic fish supply. Finally, in a third experiment, aquaculture production was unconstrained. The results of these experiments (Table 4) have demonstrated a number of interesting points. First, when only new additions to the fishing fleet are considered, the maximum level of self-sufficiency achievable is 59% in 1988, 51% in 1995 and 40% in 2008. Fish production increases from 7180 tonnes in 1988 to 7660 tonnes in 2008 with further increases being constrained by the biological capacity of the fish stocks. Second, when aquaculture production is fixed at 20% of domestic supply, the level of self-sufficiency increases to 72% in 1988, 64% in 1995 and 50% in 2008. However, this increase is at the expense of significant increases in overall operating costs, since aquaculture production costs are generally higher than production costs of the capture fisheries. Third, when the constraint on aquaculture production is relaxed, the percentage of domestic demand which can be satisfied by local production reaches 77% in 1988, 73% in 1995 and 66% in 2008---although again this is at the expense of further increases in production costs. These levels of self-sufficiency are, therefore, the maximum that can be reached from local production in Kuwait, and they indicate that total self-sufficiency in fresh fish cannot be achieved under the existing pattern of demand and with the constraints imposed by the marketing, technological and biological characteristics of the fisheries and aquaculture sector. 5.3 Budget constraint and fleet size The optimum number of new vessels required to increase fish production from the capture fisheries is dependent, among other things, on the the level of fishing effort at which these vessels operate. At lower levels of fishing effort, per vessel operating costs are minimized while initial capital costs are large because of the relatively large number of new vessels required. At higher fishing effort levels, the reverse applies. To further investigate this interaction between operating costs, initial capital costs and fishing effort levels, two additional experiments were conducted using the model. The first of these determined the optimal
A modellingframework forfisheries developmentplanning
31
supply option in the absence of any budget constraint on capital cost. The second imposed an upper limit on the amount of available capital. These experiments indicated that an upper limit on available capital of KD600 000 for the purchase of new vessels, in each of the three base years, resulted in a high level of self-sufficiency being achieved (76% in 1988, 70% in 1995 and 65% in 2008); although this was at the expense of an increase in total operating costs between 1988 and 2008 of 108%. However, without the budget constraint, total capital requirements were KD23.3 million in 1988, KD16.8 million in 1995 and KD17-1 million in 2008 while gross operating costs still increased by 90% between 1988 and 2008. There was little change in the level of self-sufficiency when compared with the budget-constrained scenario; these being 78% in 1988, 73% in 1995 and 66% in 2008. Obviously, some constraint on the capital budget for new vessel purchase would not only be desirable, but would be efficient in achieving these relatively high levels of self-sufficiency.
6 CONCLUSIONS The development of a generalized modelling framework into which the various quantitative data on the fisheries sector could be fitted has provided a valuable tool for the assessment of various policy options for Kuwait's fisheries sector. Without the availability of such a framework, it is unlikely that the full implications of the policy options would be known; and consequently, development decisions would need to be made without the full knowledge of their impact on the sector and on Government expenditure. This latter aspect is particularly important, since the modelling framework has enabled rapid assessments of the real cost to the sector of various policy options to be made. In the case of Kuwait, such assessments highlighted, among other things, the rapid escalation in operating costs resulting from a policy option to achieve maximum self-sufficiency in fresh fish products. Aiming at a policy of a little less than maximum possible self-sufficiency therefore resulted in considerable annual savings in operating costs of the sector. In addition to focussing the attention of policy-makers on the cost of their selected policies, the model was also able to set limits on the maximum achievable production and levels of self-sufficiency which could be attained. Such limits were the result of not only the biological limits to production imposed by the fish stocks themselves, but also the limits imposed as a result of present and future market demand and prices. This restriction on the range of possible policy objectives was
32
M. Khorshid, G. R. Morgan
found to be an extremely useful tool in maintaining a sense of realism in the development plans for the Kuwait fisheries sector. While the mathematical modelling framework described in this paper has been of proven value in examining the implications of fisheries policy decisions in Kuwait, the framework was initially established with the aim of creating a generally applicable analytical tool which could be applied to other country's fisheries sectors in a similar way to which it has been applied in Kuwait. Accordingly, the modelling framework is able to accommodate information on a wide range of supply options, including domestic fisheries, far seas fisheries, imports and aquaculture; and is designed to examine the most appropriate mix of production sources to achieve given policy objectives. Provided that quantitative data exist, or are able to be collected on the fisheries resources, the future market demand and cost of production from each of the possible supply sources, the modelling framework should be generally applicable to any situation where planning for the development of the fisheries sector needs to be carried out in a structured and realistic manner.
ACKNOWLEDGEMENTS The authors express their appreciation to Ms Eman Abu-Hijleh of the Techno-economics Division of Kuwait Institute for Scientific Reserch, who provided invaluable assistance with programming and running the model; and to the Agricultural Affairs and Fisheries Resources Authority of the Government of Kuwait for financial support.
REFERENCES 1. Royce, W. F., Fishery Development, Academic Press, New York, 1987, 248pp. 2. Allsopp, W. H. L., Fishery Development Experiences, Fishing News Books Ltd, Surrey, UK, 1985, 159pp. 3. Hadley, G., Linear Programming, Addison-Wesley, Reading, Mass., 1962 520pp. 4. Brooke, A., Kendrik, D. & Meeraus, A. Generalized Algebraic Modelling System (GAMS)---A users guide, The Scientific Press, NY, 1988, 318pp. 5. Jones, R., The assessment of long-term effects of changes in gear selectivity and fishing effort. Mar. Res. (Scotland), 2 (1961) 1-19. 6. Shaban, R., The demand for fish in Kuwait. Kuwait Institute for Scientific Research Technical Report No. KISR 2784, Sept. 1988, 57pp.
A modellingframework for fisheries developmentplanning
33
7. Al-Shatti, A. M., Shehadeh, Z. & Dashti, R., Development of technology for commercial culture of sobaity fish in Kuwait. Volume IV. Economic feasibility assessment of a sobaity cage farm. Kuwait Institute for Scientific Research, Report No. KISR 2269 (confidential), 1987 113pp. 8. Hopkins, K. D., Abdel-Halim, M. M., Hopkins, M. L., Dan, N. & Maheshwari, G., Tilapia culture in Kuwait: A feasibility study. Volume 2. Market potential, project concept and economics. Kuwait Institute for Scientific Research, Report No. KISR 1637, 1985, 145pp. 9. EI-Musa, M., Costs, revenues and profitability of the existing fishing fleets of Kuwait. In: Strategic framework and master plan for fisheries development in Kuwait. Kuwait Institute for Scientific Research, final report submitted to Agriculture Affairs and Fisheries Resources Authority (Restricted), 1988, 15pp.
A Modelling Framework for Fisheries Development Planning M. Khorshid Techno-Economics Division, Kuwait Institute of Scientific Research (KISR), PO Box 24885, 13109 Safat, Kuwait and Cairo University, Giza, Egypt
& G. R. Morgan Marine Culture and Fisheries Department, Kuwait Institute of Scientific Research (KISR), PO Box 24885, 13109 Safat, Kuwait (Received 12 September 1989; accepted 15 December 1989)
ABSTRACT An approach to model building is described which begins with the establishment of a matrix reflecting the basic features of the fisheries sector, and then proceeds to incorporate these features into a model structure. The model includes a set of policy objectives and constraints, and is formulated as a mathematical programming problem. The modelling framework enables quantitative data on fish resources, production techniques (including aquaculture), market demand forecasts and other biological, economic and marketing parameters to be utilized in assessing the implications of various fishery policy objectives. The model not only estimates the real cost of alternative policies but also takes into account the various biological and economic constraints to production. Rapid assessment of a range of policy objectives is therefore made possible. As an example of the application of the modelling framework, the development of a fisheries sector plan for Kuwait is described. Such planning involved establishing the most appropriate way to maximize fresh fish self-sufficiency while reconciling the production from a multi-gear, multi-species capture fishery with the need to develop an aquaculture industry in the country. The modelling framework allowed the rapid identification of appropriate development policies consistent with the biological, economic and marketing constraints of the fisheries sector and also allowed an assessment of the cost of each policy objective. 11
Ocean & Shoreline Management 0951-8312/90/$03.50 © 1990 Elsevier Science Publishers Ltd, England. Printed in Northern Ireland
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M. Khorshid, G. R. Morgan
1 INTRODUCTION Utilization of fish resources, whether for food or for recreational use, is a tradition which, up to the middle part of the 20th century, developed by evolution rather than by directed management aimed at the optimum utilization of the available resources. Beginning in the 1950s, however, and receiving considerable impetus from the Law of the Sea discussions, interest in the management and development of these fisheries resources increased rapidly so that today, most countries and international development agencies have some form of fisheries development programme, no matter how loosely framed. This surge of interest in fisheries development, particularly in developing countries, was, as Royce (1987) points out, t a result of the combination of several decades of rapid growth in world fish production; and also the perceived opportunities available from the new authority granted by the acceptance, in 1974, of the concept of a 200-mile Exclusive Economic Zone (EEZ). Many countries saw this event as an occasion for gaining control over vast (and commonly overestimated) and valuable fisheries resources, and proceeded to prepare plans for the development and exploitation of this new-found wealth. The manner in which many fisheries development plans were conceived, however, assumed that the previous rapid growth in world fish production would continue and, as a result, took little account of the limitations to development imposed by the fish stocks themselves. The often poor state of knowledge of these fish-stocks compounded the problem. This has led to several spectacular calamities and the failure of many development plans to achieve their original aims. 2 Such failures, and the experience being accumulated with fisheries development programmes in many regions has led to the now widespread understanding that fisheries development needs to be based initially on a detailed understanding of the fish resources and the way they respond to changes in fishing effort or fishing techniques. This implies an ongoing scientific programme to better understand the limitations on production of the various fish stocks, and the way in which these production limits can be best achieved. However, in addition to quantitative data on the fish stocks, which is necessary for making fisheries management decisions, the broader function of fisheries development also requires data on the social, economic (including marketing), and infrastructural aspects of the sector. The need for quantitative data of these types in the formulation of fisheries development programmes has been less recognized, although such data are often collected and available. Also, since there is often interaction,
A modellingframework for fisheries developmentplanning
13
either at the social, economic or marketing levels, between the fisheries sector and other sectors (particularly agriculture), the extent of such interaction needs to be understood and quantified. The evolution of fisheries development planning from purely descriptive plans which reflected short term, often political, aspirations to those based on quantitative data (including projections from those data) is proceeding rapidly in a number of countries. However, until now, integration of the various data, and the analyses based on them, translated into a comprehensive development plan was not possible since there was no generally applicable analytical tool available to analyse such multi-input, multi-objective problems. The objective of this paper is, therefore, to present a mathematical modelling framework which has been developed in Kuwait to assist in this process of analysing a variety of quantitative data from various sources within the fisheries sector. The model also provides assistance in examining the implications of various policy objectives. The model is not intended to replace the administrative and political decision-making processes which are a necessary part of the formulation of any development plan, but rather to act as a tool for the rapid assessment of policy decisions on supply sources and particularly on costs. The real cost to the fisheries sector of any policy objective can therefore be easily and rapidly estimated.
2 THE NEED FOR A PLANNING TOOL Development planners are generally faced with the central problem of using limited resources to satisfy growing needs. The optimum allocation of these limited resources is then one of their major concerns. The selection of an appropriate allocation pattern necessarily implies a comparison among a considerable number of alternative development policies and planners, both at the national and sectorial level; and the need to have an analytical tool or model capable of comparing various development options and assessing their impact on a selected set of policy objectives. In addition, development planners generally work in an environment of uncertainty (for example, oil sector planners in 1979, when oil was $40 per barrel, did not consider the effects of a price of $13 per barrel which occurred in 1986); so that a tool which provides rapid assessments of alternative scenarios becomes necessary in examining the effects of a larger range of possible external influences. In the fisheries sector, any development programme involves multiobjective scenarios which may include increasing (or decreasing)
14
M. Khorshid, G. R. Morgan
employment in the sector, maximizing fishermen's incomes, maximizing export earnings, satisfying future demand for fisheries products from local resources, and so on. These various objectives are often not mutually compatible so that, in the formulation of a development plan, some criteria must be established to select or give weight to one or more principal objectives. Often, such criteria are politically based, and reflect broader national development policies. One of the common criteria used is the cost to the Government (or the cost to the sector as a whole) of the various development options compared with the potential benefits to be derived. Since the fisheries sector is a highly complex and dynamic mix of biological responses, market responses and varying production costs (both over time and according to various fishing methods), the assessment of such development costs needs to be carried out within the framework of a theory which takes into account the biological, marketing and economic interactions within the sector. In addition, such development costs will change with time according to trends in demand, limitations of the fish-stocks and changes in fishing method; and such changes also need to be estimated by a practical model. In summary, given the various objectives and constraints, fisheries sector planners can use a practical model to efficiently allocate resources among alternative uses. Such optimum allocation of resources is just as important for a net fish exporting country as it is for a net importer, since decisions still need to be made, and resources allocated, to satisfy the demands of both the domestic market and the export customer. In Kuwait, the decision to prepare a fisheries development plan covering the next 20 years was prompted by the Government's concern that fish demand was increasing rapidly while production had stagnated. This had led to a surge in imports, particularly for fresh fish which increased from 1593 metric tonnes in 1983 to 4258 tonnes in 1987. Moreover, the fishing fleet, which is based on traditional wooden dhows and small speed-boats, utilized low technology methods and employed a large number of foreign fishermen. Therefore, the Government's objectives were, in accordance with national economic objectives, to reduce the dependence on imported fish and to upgrade the technological level of the industry, thus reducing foreign labour requirements in the sector. In addition, Government support for the development of an aquaculture industry was seen as a high priority, since such an industry had the capital intensive, high technology characteristics which the Government wanted to encourage. The objectives of the development plan for Kuwait could, however,
A modellingframework forfisheries developmentplanning
15
be achieved under a number of different scenarios. At one extreme, the intensive development of aquaculture technology could conceivably satisfy all future demand for fish in Kuwait while, within the capture fisheries sector, many possible combinations of fishing method and fishing effort level could be used to achieve maximum production. Such combinations are further complicated by the interactions between fishing methods and effort levels as a result of the multi-species, multi-gear nature of the fishery, in addition to being constrained by the response of the individual fish stocks to exploitation. All of these scenarios have different operating cost structures and capital requirements which could only be analysed by the development of an analytical model which reflected the biological and economic realities of the fishery and of the aquaculture industry, and which would enable the rapid estimation of the cost characteristics of the various options.
3 THE MODELLING FRAMEWORK The planning model used to study the development options of the fisheries sector is completely determined by five main steps (see Fig. 1). The first step determines the structural features of the fisheries sector. This includes, for example, the fish species to be considered by the model, the species composition by fishing method, the types of vessels and fishing methods used and the possible options for expanding domestic production. This latter item may include new fishing methods, exploitation of new species or development of new technologies such as aquaculture. In the second step, this information is converted into a modelling matrix. The rows of the matrix indicate the various fish species, whereas the columns reflect the domestic supply options. Each nonempty cell of the matrix estimates annual production by species and production method. Given the modelling matrix, the third step is to formulate production and cost functions for each species-method combination (non-empty cells). This matrix approach provides a useful and efficient way of controlling and systematizing the model-building process. In fact, the output of the modelling exercise can be described as a series of matrices reflecting the structural changes and growth prospects of the fisheries sector during the selected planning period. The fourth step involves determining the set of objectives and constraints which govern the performance and functioning of the sector. Such constraints and objectives will inevitably include the limits to
M. Khorshid, G. R. Morgan
16 (1)
Identify the structural features of the fisheries sector
I (21
Build the modelling matrix linking fish species with different domestic supply options
(3)
Estimate production and cost functions associated with each supply method--fish species combination
(41
Identify sectoral strategy, policy objectives and system constraints
1 I
(5)
1
I Formulate the mathematical programming model
I Fig. 1.
Steps for building the planning model of the fisheries sector.
production of each species imposed by their biological characteristics, the demand characteristics of each species and the production capacity of the fishing fleet in addition to whatever policy objectives (for example, import quotas or encouragement of a particular production technology such as aquaculture) are selected. In step five, the above model-building steps, which are shown in Fig. 1, are then unified in a mathematical programming framework that consists of an objective function and a set of constraints. In the following paragraphs, these five steps for building a planning model for the fisheries sector are described briefly. 3.1 Structure o f the fisheries sector
The first step in the model formulation is to identify the types and numbers of fish species to be included in the model. The selection of these fish categories should be based on several criteria such as the relative importance of the species in the pattern of domestic or export demand, the importance of the species in the landings, the potential contribution of the species to fish supply through new production
A modellingframework for fisheries developmentplanning
17
technologies, and so on. At this stage of the formulation, the species need to be classified by method of production and degree of substitutibility in the market and the structure or supply determined. Figure 2 provides a generalized domestic supply structure for fresh fish supplies (industrial fish products are excluded at this stage, but could easily be incorporated into the model framework) which would be applicable to most countries. The model divides the supply according to four levels of aggregation. In the first level, the domestic supply is broken down into fresh catch (i.e. from the capture fisheries) and aquaculture production. The aquaculture technique is commonly selected to complement the fresh catch production and to increase the level of self-sufficiency (where this is an important policy consideration) and has the advantage of generally being independent of the capture fisheries. The second level of aggregation divides the capture fisheries supply source into that derived from vessels operating within territorial waters and that derived from a far seas fleet. This distinction is necessary to reflect the differences in modes of operation, species composition and particularly the extent of control that exists over the management of, and production from, the resources taken by a far seas fleet. The third level of aggregation divides the fresh catch supply into a set of fishing methods for each vessel type. Here again, the selected set of fishing methods will be country specific. Given the possibility of operating the vessels at different effort levels, through appropriate management decisions, and the need to assess the impact of various effort levels on the selected supply option, the fourth level of aggregation considers different relative fishing effort levels for each fishing method. Finally, the aquaculture supply option is broken down into a number of possible production methods, each of which will have its own supply and production cost characteristics. 3.2 The modelling matrix Given the above technical background, the modelling framework is designed to generate alternative future supply options for the sector under various constraints and objectives. A supply option consists of annual production broken down by fish species, fishing method and relative fishing effort values. Table 1 shows the organization of such output in a matrix format, where rows indicate fish species and columns reflect the method of production. The arrangement of the columns follows the disaggregation scheme for the domestic supply of fish shown in Fig. 2.
~evo,, i
I
i
i
Fig. 2.
i I Other Fishing I Efforts
Domestic supply options for the fisheries sector.
I FishingEffort3 I
i
Jloe~,~e,hod~ O*h°r
I FishingEffort2 I
l
,_ev,~,, i Relative EffortValues IFishingEffortll (FE)
l "*"
l,~a,-~eaVes~o,~l l','eoho,qoe~J l','ec~n,q,.,e,~ I
I
1
I AquacultureMethod j
l O'"N°* l
so,',,,or,a,
i
1
I FreshCatchMethod I
,oM,°~M~*ho° ~,~h','~0~
,~,oo, sype
,_~ve,~
Method
Production
1
I DomesticSupplyof Fish I
~,
g
0
Fo
FEI[
FE1
[ FE2
[ --
[
Relative fishing efforts
Relative fishing efforts [
Gear methods
Gear methods
FE2 [
Far sea vessels
I
1
Territorial water vessels
Fresh Catch fish
Domestic supply offish
LGM--Gear methods used with territorial water vessels. OGM--Gear methods used with open sea vessels. FE--Fishing effort. - - signifies additional methods can be included.
Shrimp Pomphret Grouper Mullet Grunt Sea Bream (+ other fish types)
Fishspecies
TABLE
The Modelling Matrix.
~"
~"
"~
e~
Technique 1 Technique 2 . -- . ~ "~:
Aquaculture
20
M. Khorshid, G. R. Morgan
The modelling matrix, shown in Table 1, can be seen as a way to illustrate the annual production plan of the fisheries sector. This matrix, if projected over time, is able to form the basis of development planning for the fisheries sector and, at any time, indicates the expected levels and sources of supply, vessel requirements and aquaculture development schedules. 3.3 Production and cost functions Two functions can be associated with each non-empty cell in the modelling matrix; a production function and a cost function. The production function defines the gross output of fish as a function of inputs to the production process. Such inputs include fishing method, relative fishing effort and vessel type and size for the capture fisheries, and land, water and labour availability for the aquaculture sector. In addition, the output generated by each fishing method will represent a characteristic species composition for that method and so the selection of a particular fishing method determines the species composition of the gross production. Given the above background, the output from the capture fisheries can be determined by a two-level production function. The first estimates gross output as a function of fishing method and effort. The second level distributes this output to various fish species according to a predetermined species composition. Given the functional forms of the production functions for the capture fisheries and aquaculture, operating costs can be assigned to each production method and to each fishing effort or (in the case of aquaculture) capacity level. 3.4 Objectives and system constraints Rational producers of fish, or any other commodity, generally seek to maximize their profits (or minimize costs) subject to technological constraints (the production function). The production decisions at the micro level, however, are not necessarily consistent with the policy objectives and constraints of the fisheries sector as a whole. Market mechanisms fail, in many cases, to achieve the objectives of the sector, and Government intervention is often required to achieve overall national goals. Government can enter the market as a fish producer. It can also affect the performance of the sector through fiscal policy instruments such as subsidies, taxes, import tariffs, quantity restriction and transfers. To account for the above points, the model needs to explicitly
A modelling framework for fisheries development planning
f
• Species composition by fishing method • Production functions
I • Operating cost per ton broken / down by fishing method and effort • Trade margins and taxes (or subsidies) by fish species
21
• Domestic demand by fish species and maximum possible fresh catch from local sea
Mathematical Model Objectives
, Breakdown by fish species, fishing method and fishing effort
• Feasible aquaculture prod. technique
• Sales price of fish species • Capital cost of vessels by fishing method
• Minimize operating cost • Increase level of selfsufficiency ~ • Implement new production techniques (aquaculture) • Optimize the utilization of fish stock in territorial water • Expand fleet operations to new fishing areas (far seas) ~
~
• Maximum possible fresh catch from local sea
r
_~ [
Constraints
• Demand constraint by species • Maximum fresh catch from territorial water • Fresh catch technical constraints (production function) • Aquaculture technical constraints • Capital budget constraints • Currently available vessels constraint • Constraints on far seas fresh catch
• Possible production size from far seas fleet
• Number of currently available vessels by fishing method
l
Model Output • Optimum domestic supply of fish broken down into fresh catch and aquaculture • Fresh catch production by fishing method and effort • Domestic production of fish by species • Operating and capital cost by supply option • Level of self-sufficiency
Fig. 3.
The overall modelling framework for the fisheries sector.
22
M. Khorshid, G. R. Morgan
consider policy objectives and constraints. The mathematical programming technique provides a direct and efficient means of incorporating such objectives and constraints, in addition to biologically-based constraints, into the modelling framework. The overall modelling framework of the fisheries sector is shown in Fig. 3. The central part of the figure is the mathematical model, which uses various structural parameters of the sector coupled with policy objectives and constraints to generate the appropriate supply option. Development efforts might be directed to minimize operating costs, increase the level of self-sufficiency, implement new production techniques and/or explore new fishing methodologies. The selected supply option is also affected by several technical and economic constraints such as demand satisfaction, capacity of the fish stocks, budget constraints, and so on. In summary, by grouping the structural and technical features of the fisheries sector with policy objectives and constraints, the sectorial planning model is completely determined and can be formulated as a mathematical programming problem, a:
4 AN APPLICATION TO KUWAIT'S FISHERIES SECTOR Kuwait's fishing industry is based largely on a fleet of small, inshore vessels (which include some 207 traditional wooden dhows and about 770 glass fibre speedboats) which take a variety of demersal and pelagic species. Production of fish from these vessels was around 6500 tonnes in 1988, which represented about 55% of the total fresh fish demand in Kuwait. The gap between demand and domestic supply was made up by imports of fresh fish, mainly from India, Pakistan, and the other Gulf countries. In addition to the fresh fish catches, all of which is consumed within the country, there exists a major shrimp fishery which is export orientated. These shrimp catches are taken by a fleet of some 70 industrial trawlers, in addition to about 120 wooden dhows which operate in the shallow water areas. Catches from these two fleets during the 1987/88 fishing season were 2065 tonnes of shrimp, of which 1000 tonnes were exported and the remainder consumed in the domestic markets. In assembling the quantitative data required for inclusion in the modelling framework, the response of the fish and shrimp stocks to changes in the level of exploitation first need to be estimated. Although the fishery is complicated because of its multi-species, multi-gear characteristics, sufficient information was available on the major species to allow a cohort analysis technique 5 to be applied and which enabled
A modelling framework ]:orfisheries development planning
23
the estimation of not only the response of the species to changes in overall exploitation rate but also took into account the interactions between the various fishing gears. Any possible biological interactions between species (for example, via the food-chain) was, however, not explicitly considered. The major fishing techniques which were included were small mesh gill nets (which are used to take small inshore species such as mullets), large mesh gill nets (which are used to target on pomphrets), fixed stake nets, trawling and fish traps. In addition, longlining was considered as a development option, although the technique is not currently practised in Kuwait. These fishing techniques account for over 95% of the fish catches in Kuwait. Changes in overall exploitation rates were considered on a relative basis, with the present level (1988) being considered as 100. Expected yields by species were then calculated, using the cohort analysis technique, for relative exploitation rates from 25 to 200 in steps of 25. These yields by species at the various levels of exploitation rate were then considered in the model as a constraint on production of each species. Since Kuwait does not have (and other studies advised against the development of) a far seas fishing fleet, the option of securing supplies from fisheries resources outside those already exploited was not considered. For each of the fishing methods considered, the percentage species composition of the catch was estimated using actual data for the period 1983-88. This species composition was assumed not to change with changes in exploitation rate so that, when combined with the analysis of the effects of changing exploitation level, this allowed the estimation of the expected yield by species by fishing method at any level of exploitation. The characteristics of the fish species and fishing methods utilized in the study are shown in Table 2. Future demand for fresh fish in Kuwait was estimated from both monthly price and quantity data, which were available from 1975 to the present; and from family budget surveys carried out in 1977-79 and 1986-87. The full methodology and results of these analyses are given in Shaban (1988). 6 Results of this demand study also showed that some species of fish were substitutible in the market. For example, hamoor, sobaity, sheem and sheim (see Table 2) were found to be substitutable at the consumer level, as were maid, hamra and nakroor. The implication of this substitutability is that the model seeks to satisfy the overall demand for each substitutable set rather than satisfying the demand for each of the component fish species. Finally, although there are presently no commercial aquaculture
Local name
Shrimp Zobaidy Hamoor Hamra Maid Sobaity Nakroor Sheim Sheem Tilapia Others
Shrimp Pomphret Grouper Snapper Mullet Sea Bream Grunt Sea Bream Threadfin Tilapia Others
Fish species
Common name
Total
TABLE 2
100
58-3
23.8
100
41.6
26-7 0-3
37.8 11.4
0.1
100
47.9
1.5 3.3
25.7
21-6
Gargoor Large Small (fish gill gill traps) net net
100
9.4
0.2 1-4
1.7 0.4
86-2 0-1 0.6
100
66.1
5-4
23.2 4.4
0.9
Hadra (stake Trawl nets)
Fresh catch fish
100
31.00
2.00 5.00 2.00 5.00
30.00 25.00
Long line
100
100
Sobaity
Domestic supply offish
100
100
Hamoor
100
100
Tech. 1
1000
100
Tech. 2
Tilapia
Aquaculture
Domestic Supply, Fish Species and Percentage Species Composition for Kuwait's Fisheries Sector.
100
50
50
Tilapia sobaity mix
.~
t,O 4~
A modellingframework for fisheries developmentplanning
25
facilities in Kuwait, production technology and costs could be determined from a series of investment feasibility studies which have been undertaken. 7'8 Such studies have indicated that at the present time, only two species could be successfully cultured profitably (the criterion of profitability was necessary for aquaculture development, since Government policy was to provide initial assistance to the development of a viable private sector industry rather than the long term support of unprofitable technology) in Kuwait. These were a local sea bream (locally known as sobaity; see Table 2), for which an already good market demand existed; and tilapia, which although not presently marketed in quantity in Kuwait, appeared as a result of test marketing to have a potential demand of up to 2000 tonnes by the year 2 0 0 8 . 6 Given the above structural features, the planning model for Kuwait included two production techniques (capture fisheries and aquaculture), eleven fish species, six fishing gear methods and eight relative effort values. The production function by fishing method and species was estimated as described above, while the cost function for each fishing method and at each fishing effort level was estimated using data collected in 1988 on the detailed operational costs of the various vessel types. 9 Direct production costs, distribution costs, trade margins and transportation fees from the ports to the final market were included. In addition, taxes and subsidies (or both) were incorporated into the cost function for two reasons. First, this allowed a direct assessment of the impact of the adopted tax or subsidy policy on the choice of the future supply options. Second, the use of these fiscal tools in the model enabled a reflection of Government or consumer preference for a specific fish species. Since cost minimization is a selection criterion in the model, subsidies (or taxes) increase (or decrease) the probability of selecting one species over another as part of domestic production. Given the objectives and structure of the fisheries sector in Kuwait, the model concentrates on the following development issues: (a)
(b)
Minimize the operating cost and increase the revenues of both producers and fishermen by the optimum selection of fishing method and effort levels. This policy issue is incorporated into the model as an objective function. Adopt a food security policy directed at increasing the level of self-sufficiency consistent with the availability and sustainable catches of the country's fish stocks. This policy is incorporated into the model by the introduction of a lower limit on overall production by fish species and, by iteration using varying lower limits, identifying the maximum feasible level of self-sufficiency.
M. Khorshid, G. R. Morgan
26
(c)
Diversify the means of domestic production by the development of aquaculture.
These three policy objectives are coupled with a number of economic and technical constraints to arrive at a complete model structure. Constraints of the model can be grouped into four main categories. The first category relates to the demand satisfaction by fish species. These constraints assume that domestic production must not exceed the projected annual demand, although this constraint could be readily modified to take into account the possibility of an export market for some species. However, such export markets for the Kuwait species are not competitive with the domestic market. As noted earlier, demands constraints are divided into two sets depending on the degree of substitution between fish species. Non-substitutible species have separate constraints, whereas demand for substitutible species are grouped in one constraint. The second set of constraints is concerned with the maximum quantity of fresh fish available to Kuwait (apart from imports), and reflects the production limits of the various fish stocks. The third set of constraints is concerned with the optimal utilization of the presently available vessels, and a budget constraint on the purchase of any new vessels. The first of these guarantees that the current fleet is fully utilized before a commitment is made to increasing the fleet size, while the latter constraint imposes a limit on the investment expenditure for acquisition of new vessels. Finally, the last set of constraints is related to technical aspects of the sector, such as the species composition by various fishing methods, maximum production limits per vessel and the feasible species mix of the fish production. The model was used to conduct comparative static experiments covering the period 1988-2008. The planning horizon was broken down into three benchmark years (1988, 1995 and 2008) in order to estimate the development path of the sector.
5 POLICY ANALYSIS The model was used to address a set of specific policy questions considered to be of particular relevance to Kuwait's fisheries sector. Three strategic issues were considered. First, what is the maximum level of satisfaction of domestic demand for fresh fish that can be achieved from local production sources by the year 2008, and what is
A modelling frameworkforfuheries development planning
27
the production mix of fish species corresponding to this level? Second, what is the lowest cost mixture of supply sources, in terms of production techniques, fishing gear methods and fishing effort levels, required to achieve various levels of self-sufficiency in fresh fish? Third, what are the number and costs (both capital and operating) of new vessels or aquaculture facilities required to achieve various levels of selfsufficiency, and what is the schedule for their introduction? 5.1 Optimal utilization of the current fleet
Table 3 summarizes the results of using the current fishing fleet to satisfy different levels of domestic demand up to the year 2008. The table indicates three important points. First, the maximum level of self-sufficiency achievable using the existing fleet decreased from 57% in 1988 to about 42% of demand in 2008, despite the increase in production of fish from 6897 tonnes to 7200 tonnes during the period. Second, the gross operating costs of the fishing fleet is positively correlated to the level of sufficiency achieved. Thus, increasing the level of self-sufficiency from 30% to 57% in 1988 could only be achieved at the expense of more than doubling the operating costs of the fleet from 1.8 million Kuwaiti dinars to 3-9 million Kuwaiti dinars (1 Kuwaiti dinar = $US3.5 approximately). This resulted from the fact that at the lower level of self-sufficiency requirement, the fleet was able to operate at lower effort levels where production costs were correspondingly low. Third, the maximum catch taken by the existing fishing fleet is less than the maximum possible production from all species combined. This is a result of the species interactions between fishing gear. 5.2 The need for an increase in capacity
The above results demonstrate that, given the various constraints on stock production, demand by species and the characteristics of the presently used vessels and fishing gear, the existing fishing fleet is not able to supply more than 42% of the domestic demand for fresh fish by 2008, and even to reach this level would incur significant costs in terms of increased operating costs of the fishing fleet. Accordingly, to improve the level of self-sufficiency and to reduce the gap between domestic demand and supply, an increase in production capacity would be needed. This production capacity increase can be achieved through expanding the existing fishing fleet, or by the development of aquaculture. Various experiments, the results of which are summarized in Table 4, were
20O8
Operating cost (KD) Production (tonnes)
Operating cost (KD) 1995 Production (tonnes)
Operating 1988 Cost (KD) Production (tonnes)
Year
TABLE 3
35
40
4,235
4,840
4,620
5,280
42
5,145
6,003
6,860
7,203
4,291,473 4,916,495 6,556,794 7,922,255
3,960
2,252,422 2,591,505 2,986,578
3,831
1,816,732 1,968,732 2,248,194
30
50
6,050
52
5,940
6,600
6,864
3,441,770 4,049,505 4,599,886
5,445
2,560,605 2,926,076
45
Degree of satisfaction of demand (%) 56
57
6,655
6,776
6,897
3,414,861 3,562,038 3,903,610
55
Cost and Production of Fish Species Using the Current Fleet of Kuwait's Fisheries Sector.
a
.~
OO
Fresh catch Aquaculture Total
59.30 -59.30
3456354
--
7182 -7182
57.00 15.00 72.00
6255792
4.535
7257 1814 9071
Exp. 2
51-80 25-20 77.00
7963218
7.635
6649 3054 9703
Exp. 3
51.00 -51-00
4152814
--
7242 -7242
Exp. 1
51.20 12.80 64-00
685239
4.545
7271 1818 9089
Exp. 2
1995
49-60 23-40 73.00
9049988
8.330
7033 3333 10366
Exp. 3
° Experiment 1: Only additional fish catch vessels are allowed. No aquaculture is considered. Experiment 2: Aquaculture production should represent 20% of domestic supply. Experiment 3: Aquaculture production should be greater than or equal to 0.
Satisfaction Fresh catch of demand (%) Aquaculture Total
Operating cost (KD)
Number of aquaculture plants
Production (tonnes)
Exp. 1u
1988
40.00 -40.00
7479389
--
7660 -7660
Exp. 1
40-00 10-00 50.00
9928674
4.788
7660 1915 9575
Exp. 2
2008
38.40 27.60 66.00
15098000
13-200
7359 5280 12639
Exp. 3
TABLE 4 The Impact of an Increase in Production Capacity on Satisfaction of Domestic Demand for Fish in Kuwait.
tO
~.-~
~" o, ~"
~"
~-
o~
30
M. Khorshid, G. R. Morgan
carried out and aimed at determining possible expansion of production capacity, and allocation of this increased production to the capture fisheries and aquaculture. In the first experiment, the model was used to estimate the maximum level of self-sufficiency in 2008 that could be achieved by only considering additions to the fishing fleet. The second experiment incorporated aquaculture production, but constrained its contribution to a maximum of 20% of domestic fish supply. Finally, in a third experiment, aquaculture production was unconstrained. The results of these experiments (Table 4) have demonstrated a number of interesting points. First, when only new additions to the fishing fleet are considered, the maximum level of self-sufficiency achievable is 59% in 1988, 51% in 1995 and 40% in 2008. Fish production increases from 7180 tonnes in 1988 to 7660 tonnes in 2008 with further increases being constrained by the biological capacity of the fish stocks. Second, when aquaculture production is fixed at 20% of domestic supply, the level of self-sufficiency increases to 72% in 1988, 64% in 1995 and 50% in 2008. However, this increase is at the expense of significant increases in overall operating costs, since aquaculture production costs are generally higher than production costs of the capture fisheries. Third, when the constraint on aquaculture production is relaxed, the percentage of domestic demand which can be satisfied by local production reaches 77% in 1988, 73% in 1995 and 66% in 2008---although again this is at the expense of further increases in production costs. These levels of self-sufficiency are, therefore, the maximum that can be reached from local production in Kuwait, and they indicate that total self-sufficiency in fresh fish cannot be achieved under the existing pattern of demand and with the constraints imposed by the marketing, technological and biological characteristics of the fisheries and aquaculture sector. 5.3 Budget constraint and fleet size The optimum number of new vessels required to increase fish production from the capture fisheries is dependent, among other things, on the the level of fishing effort at which these vessels operate. At lower levels of fishing effort, per vessel operating costs are minimized while initial capital costs are large because of the relatively large number of new vessels required. At higher fishing effort levels, the reverse applies. To further investigate this interaction between operating costs, initial capital costs and fishing effort levels, two additional experiments were conducted using the model. The first of these determined the optimal
A modellingframework forfisheries developmentplanning
31
supply option in the absence of any budget constraint on capital cost. The second imposed an upper limit on the amount of available capital. These experiments indicated that an upper limit on available capital of KD600 000 for the purchase of new vessels, in each of the three base years, resulted in a high level of self-sufficiency being achieved (76% in 1988, 70% in 1995 and 65% in 2008); although this was at the expense of an increase in total operating costs between 1988 and 2008 of 108%. However, without the budget constraint, total capital requirements were KD23.3 million in 1988, KD16.8 million in 1995 and KD17-1 million in 2008 while gross operating costs still increased by 90% between 1988 and 2008. There was little change in the level of self-sufficiency when compared with the budget-constrained scenario; these being 78% in 1988, 73% in 1995 and 66% in 2008. Obviously, some constraint on the capital budget for new vessel purchase would not only be desirable, but would be efficient in achieving these relatively high levels of self-sufficiency.
6 CONCLUSIONS The development of a generalized modelling framework into which the various quantitative data on the fisheries sector could be fitted has provided a valuable tool for the assessment of various policy options for Kuwait's fisheries sector. Without the availability of such a framework, it is unlikely that the full implications of the policy options would be known; and consequently, development decisions would need to be made without the full knowledge of their impact on the sector and on Government expenditure. This latter aspect is particularly important, since the modelling framework has enabled rapid assessments of the real cost to the sector of various policy options to be made. In the case of Kuwait, such assessments highlighted, among other things, the rapid escalation in operating costs resulting from a policy option to achieve maximum self-sufficiency in fresh fish products. Aiming at a policy of a little less than maximum possible self-sufficiency therefore resulted in considerable annual savings in operating costs of the sector. In addition to focussing the attention of policy-makers on the cost of their selected policies, the model was also able to set limits on the maximum achievable production and levels of self-sufficiency which could be attained. Such limits were the result of not only the biological limits to production imposed by the fish stocks themselves, but also the limits imposed as a result of present and future market demand and prices. This restriction on the range of possible policy objectives was
32
M. Khorshid, G. R. Morgan
found to be an extremely useful tool in maintaining a sense of realism in the development plans for the Kuwait fisheries sector. While the mathematical modelling framework described in this paper has been of proven value in examining the implications of fisheries policy decisions in Kuwait, the framework was initially established with the aim of creating a generally applicable analytical tool which could be applied to other country's fisheries sectors in a similar way to which it has been applied in Kuwait. Accordingly, the modelling framework is able to accommodate information on a wide range of supply options, including domestic fisheries, far seas fisheries, imports and aquaculture; and is designed to examine the most appropriate mix of production sources to achieve given policy objectives. Provided that quantitative data exist, or are able to be collected on the fisheries resources, the future market demand and cost of production from each of the possible supply sources, the modelling framework should be generally applicable to any situation where planning for the development of the fisheries sector needs to be carried out in a structured and realistic manner.
ACKNOWLEDGEMENTS The authors express their appreciation to Ms Eman Abu-Hijleh of the Techno-economics Division of Kuwait Institute for Scientific Reserch, who provided invaluable assistance with programming and running the model; and to the Agricultural Affairs and Fisheries Resources Authority of the Government of Kuwait for financial support.
REFERENCES 1. Royce, W. F., Fishery Development, Academic Press, New York, 1987, 248pp. 2. Allsopp, W. H. L., Fishery Development Experiences, Fishing News Books Ltd, Surrey, UK, 1985, 159pp. 3. Hadley, G., Linear Programming, Addison-Wesley, Reading, Mass., 1962 520pp. 4. Brooke, A., Kendrik, D. & Meeraus, A. Generalized Algebraic Modelling System (GAMS)---A users guide, The Scientific Press, NY, 1988, 318pp. 5. Jones, R., The assessment of long-term effects of changes in gear selectivity and fishing effort. Mar. Res. (Scotland), 2 (1961) 1-19. 6. Shaban, R., The demand for fish in Kuwait. Kuwait Institute for Scientific Research Technical Report No. KISR 2784, Sept. 1988, 57pp.
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33
7. Al-Shatti, A. M., Shehadeh, Z. & Dashti, R., Development of technology for commercial culture of sobaity fish in Kuwait. Volume IV. Economic feasibility assessment of a sobaity cage farm. Kuwait Institute for Scientific Research, Report No. KISR 2269 (confidential), 1987 113pp. 8. Hopkins, K. D., Abdel-Halim, M. M., Hopkins, M. L., Dan, N. & Maheshwari, G., Tilapia culture in Kuwait: A feasibility study. Volume 2. Market potential, project concept and economics. Kuwait Institute for Scientific Research, Report No. KISR 1637, 1985, 145pp. 9. EI-Musa, M., Costs, revenues and profitability of the existing fishing fleets of Kuwait. In: Strategic framework and master plan for fisheries development in Kuwait. Kuwait Institute for Scientific Research, final report submitted to Agriculture Affairs and Fisheries Resources Authority (Restricted), 1988, 15pp.