Projections Vancouver

Modeling Supply, Demand, and Trade for Specific Fish Types in Asia

7 June 2003 Madan M. Dey (Corresponding author) Senior Scientist-Economist, WorldFish Center ([email protected]) Roehlano M. Briones Postdoctoral Fellow (Economics), WorldFish Center ([email protected]) Mahfuzzudin Ahmed Program Leader, Policy Research and Impact Assessment, WorldFish Center ([email protected])

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1 Abstract Quantitative modeling of supply, demand, and trade for fish is a useful tool for analyzing recent structural changes. Existing models are however limited by their use of highly aggregated fish categories and assumed (rather than estimated) elasticities. The paper a multimarket equilibrium model for disaggregated analysis of fish supply, demand and trade. Illustrative simulations of impact of resource degradation, technological change, and export market shocks are presented. Introduction Recent decades have witnessed a major transformation in global fish demand and supply. Per capita fish consumption has nearly doubled from 8 kg. in 1950 to almost 16 kg. in 1999 (FAO, 2001). Developing country exports of fish have increased even as traditional crop exports have declined. In most of developing Asia, the fish sector has grown steadily in terms of production, consumption, and trade (Ahmed, Rab, and Dey, 2002). Underlying these changes are structural factors such as technological change, policy reforms, and resource status. In the area of trade for example, tariffs on fish products have largely dropped, whereas other types of barriers (i.e. regulatory standards) have been erected. Another area of reform is management institutional change, particularly in capture fisheries, which have been implemented to address deteriorating fish stocks. However, little is known about the impact of these structural developments on prices, production, and earnings in the fish sector. A number of food sector models have been developed to study the impact of technology and policy changes on agriculture (e.g. Evenson et. al., 1993; Huang and Chen, 1999). Unfortunately, the fish sector is absent in

2 such models, despite its significant contribution to animal protein consumption as well as livelihood of the poor worldwide (Per Pinstrup-Anderson and Pandya-Lorch 1999). The omission of fish and other aquatic products is a common oversight in food security analysis (Williams 1999). A notable exception is the extended model developed by the International Food Policy Research Institute (Delgado et. al., 2003). The extended IMPACT model however adopts broad aggregates to classify fish types (e.g. low value fish, high value fish, etc). In fact, fish is highly heterogeneous (Westlund, 1995; Dey 2000). A more useful description of fish sector trends requires projections for specific fish types, which may guide directions for capital investment, development financing, and research priorities. This paper presents a multimarket fish sector model to address these issues. The model bases its parameters on a large-scale data set on fish production and consumption in nine Asian countries (China, India, Indonesia, Bangladesh, Philippines, Vietnam, Thailand, Malaysia, and Sri Lanka.) Fish is disaggregated by country into species groups, production categories, and market destinations. The model aims at generating numerical projections on prices, quantities, and the welfare of fish dependent sectors, based on plausible scenarios for changes in demographics, technology, institutions, and the resource base. Overview of Impact Analysis The purpose of the model is to analyze the impact of technology and policy on the fish sector. The first step entails a background analysis on technologies and policies affecting the fish sector, to identify shock variables for impact analysis. The next step is to develop a baseline model, which is a system of equations divided into a producer core,

3 a consumer core, and a trade core (Sadoulet and de Janvry, 1995). The system is solved by imposition of simultaneous equilibrium across markets. Impact analysis is undertaken by examining changes in equilibrium values, once shocks are incorporated in the baseline model. At the aggregate level, changes in equilibrium prices and quantities are calculated as an outcome of technological change, policy shifts, and other trends. These prices and quantities can be disaggregated by species group, production category, and destination market (i.e. exports and imports, urban and rural markets). Further disaggregation allows analysis of welfare impact by economic class (i.e. consumers, producers, factor suppliers, or income group). The third step would be the numerical specification of the baseline model, which would incorporate parameter estimates and benchmark data on prices, quantities, and other variables. Finally, supply and demand projections can be generated by incorporating the shock variables into the baseline model simulations. This paper discusses the baseline model equations (in structural form), as well as the method for numerical specification. The Model The producer core of the model disaggregates supply into production categories, namely: aquaculture (subdivided into freshwater, brackishwater, and marine, where relevant), and capture (subdivided into inland and marine, where relevant). Estimation follows a dual approach based on profit maximization (Squires, 1987; Kirkley and Strand, 1988). The approach uses a flexible functional form (supply equations are derived from a standard normalized quadratic profit function (Shumway, Jagasothy, and Alexander, 1987; Ball, et. al. 1997). Technological change is represented by a distinction

4 between actual and effective price (Dixon et. al., 1982; Alston, Norton, and Pardey 1995). The estimation strategy for the consumer core follows Dey (2000). The procedure applies a three-stage budgeting framework. In stage 1, total spending is divided food and nonfood spending; in stage 2, food is disaggregated into spending food aggregates, namely fish, meat, chicken, vegetables, and cereal. Each of these is measured by the corresponding expenditure item. In stage 3, fish itself is disaggregated into its major types. Estimation of this stage applies the quadratic form of the Almost Ideal Demand System or AIDS (Blundell et. al., 1991), implemented on a two-stage Heckman-type correction to deal with endogenous non-purchase of certain fish types (see Heien and Wessels, 1990). In each stage the appropriate restrictions on homogeneity (and where applicable, symmetry) are imposed. For the trade core, exports and imports are modeled using the Armington approach (Armington, 1969), which is a common technique in applied general equilibrium modeling. The adopted treatmemt follows Horridge, Parmenter, and Pearson, (1993). Export supply and import demand are determined in a flexible manner with parsimonious use of the data. By the small open economy assumption, world prices for exports and imports are kept fixed. A computable version of the model requires the assembly of a baseline data set consistent with equilibrium conditions for the endogenous variables. Parameters are calibrated for consistency with the estimated elasticities and baseline data, subject to the chosen functional forms. At the baseline, the model solution should replicate the data values; projections over time are generated by examining the implications of exogenous

5 variable trends on fish prices, demand, supply, prices, and trade, producer welfare, and consumer welfare. Applications To highlight the potential applications of the model, illustrative impact analysis are simulated in the following. The impact scenarios are as follows: Scenario 1.Supply shocks A. Increase in aquaculture supply (10% ) B. Decrease in capture supply (10%) Scenario 2. Market shock: Decline in export price (5% ) Scenario 1 represents the two major developments on fishery supply, namely the rapid growth of aquaculture (partly driven by technological change), and the declining supplies from capture fisheries (due to depletion of marine and inland fish stocks). The magnitudes refer to the change in production in the absence of price adjustments; the simulations reflect equilibrium after all the adjustments are made in response to the shocks. Scenario 2 meanwhile maps to the possible impact of market access regulations; in particular, the compliance with food safety standards such as HACCP and SPS (see Dey et . al, 2003) will lead to higher production costs, which can be captured by a reduction in the effective price received by exporters. The model uses actual data for a given base year for the nine Asian countries (each country model is solved independently). A balance (equilibrium between imports, exports, production, consumption, and other uses) was imposed for the base year. Elasticities partly from the estimation work (which is on-going) and partly on expert judgment were used for calibration. Due to the great number of endogenous variables

6 calculated by the model, simulation results are presented for selected variables and countries. For increase in aquaculture supply the simulation results pertain quantities produced and traded (Table 1). The selected country is China, owing to the large share of aquaculture in domestic production (over 60%). The results show that cultured fish experience a dramatic rise in output, though in lower magnitude than the initial shock. The largest increases are for the carp species. There is a different story for marine capture; due to substitution on the demand side, some marine capture species groups suffer a decline in production, while the bulk of capture supply rises mildly to the aquaculture shock. For decrease in marine supply the selected country is India, a large fishing nation which catches over 60% of its fish production. The supply contraction is sharp, particularly for marine fish; for fish that are simultaneously cultured (Indian Major Carp, other freshwater fish) the decline is much milder. The decline in consumption is also noticeable, but moderated (due to alternative sources, such as imports). The increase in consumer prices is likewise also attenuated, though it remains worrisome for the food security of India’s poor. Finally, for decrease in export price results are shown for traded good exports, production, and consumption, for Thailand (which exports nearly three-fourths of its fish production). The major export items (e.g. cultured shrimp) experience a decline in exports. There is a mild decline in production. Most of the traded items go through an increase in consumption, which is not surprising given the shift in production from foreign to domestic markets.

7 A simple supply and demand analysis suggests that an increase (decrease) in supply should lead to rising (falling) quantities and falling (rising) prices; finally declining world prices should lead to lower production and higher domestic consumption. However in a multicommodity framework these expectations may not materialize for each commodity, due to cross-price effects and market interactions. In our simulations, the expectations from a partial analysis hold in general, although exceptions are very evident. This illustrates one value of a modeling approach, which helps quantity, within an order of magnitude, the likely impacts both on the sector(s) directly affected and on related sectors. Concluding Remarks This paper discusses the need for and an approach to disaggregated, empiricallybased analysis of fish demand and supply. The approach consists of the formulation and estimation of a baseline model of the fish sector where commodities are defined over major fish types by country. The strategy outlined here addresses several in modeling production, consumption, and trade in the fish sector. A computable version of the model is developed and illustrative simulation results are presented to demonstrate its usefulness for disaggregated impact analysis. Further application of the model shall be made in terms of solidifying the parameters used, and expanding the range of scenarios to be explored (including the assessment of market supply and demand trends over a time horizon, say the next twenty years). These applications would further establish the usefulness of the model for planning and policy. Acknowledgments

8 The model presented in this paper is developed by the WorldFish Center, in collaboration with a number of national research institutes, with financial support from the Asian Development Bank. For details on the project, please refer to www.worldfishcenter.org/demandsupply. The authors are grateful for the comments of U. Primo E. Rodriguez, which has led to substantial revision of the trade core of the model. References Ahmed, M., Rab, M., and Dey, M. (2002) Changing Structure of Fish Supply, Demand, and Trade in Developing Countries – Issues and Needs. WorldFish Center Contribution No. 1688. Alston, J., Norton, G., and Pardey, P. (1995) Science Under Scarcity: Principles and Practice for Agricultural Research Evaluation and Priority Setting. Ithaca: Cornell University Press. Armington, P. (1969) A Theory of Demand for Products Distinguished by Place of Production. IMF Staff Papers 16, 159–178. Ball, E., Bureau, J.-F., Eakin, K., and Somwaru, A. (1997) Cap Reform: Modeling Supply Response Subject to the Land Set-Aside. Agricultural Economics 17, 277-288. Blundell, R., Pashardes, P., and Weber, G. (1993) What do we learn about consumer demand patterns from micro data? American Economic Review 83, 570-597. Delgado, C., Wada, N., Rosegrant, M., Meijer, S., and Ahmed, M. (2002) Fish to 2020: Supply and Demand in Changing Global Markets. Washington: International Food Policy Research Institute and WorldFish Center. Dey, M. (2000) Analysis of Demand for Fish in Bangladesh. Aquaculture Economics and Management 4, 63-79.

9 Dixon, P., Parmenter, B., Sutton, J., and Vincent, D. (1982) ORANI: A Multisectoral Model of the Australian Economy. Amsterdam: North-Holland. Heien, D., and.Wessells, C. (1990) Demand Systems Estimation with Microdata: a Censored Regression Approach. Journal of Business & Economic Statistics, 8, 365-371. Horridge, J., Parmenter, B., and Pearson, K. (1993) ORANI-F: A General Equilibrium Model of the Australian Economy. Economic and Financial Computing 3(2): 71140. Huang, J., and Chen, C. (1999) Effects of Trade Liberalization on Agriculture in China: Commodity Aspects. Working Paper No. 43. Coarse Grains, Pulses, Roots and Tuber Crops in the Humid Tropics of Asia and the Pacific. Kirkley, J., Strand, I. (1988) The Technology and Management of Multi-Species Fisheries. Applied Economics 20, 1279-1292. Pinstrup-Andersen, P., and Pandya-Lorch, R. (1999) Achieving Food Security For All: Key Policy Issues for Developing Countries. Fisheries Policy Research in Developing Countries: Issues, Priorities and Needs (eds. M. Ahmed, C. Delgado, S. Sverdrup-Jensen and R.V. Santos), 13-20. International Center for Living Aquatic Resources Management (ICLARM) Conference Proceedings 60. Sadoulet, E., and de Janvry, A.(1994). Quantitative Development Policy Analysis. Baltimore: Johns Hopkins University Press. Shumway, R., Jegasothy, K., and Alexander, W. (1987) Production Interrelationships in Sri Lankan Peasant Agriculture. Australian Journal of Agricultural Economics 31, 16-28. Squires, Dale (1987) Long-run Profit Functions for Multiproduct Firms. American Journal of Agricultural Economics 69, 558-569. Westlund, L. (1995) Apparent Historical Consumption and Future Demand for Fish and Fishery Products – Exploratory Calculation. Paper presented for the International

10 Conference on the Sustainable Contribution of Fisheries to Food Security, Kyoto, Japan, 4-9 December. Williams, M. (1999) Factoring Fish into Food Security: Policy Issues. Fisheries Policy Research in Developing Countries: Issues, Priorities and Needs (eds. M. Ahmed, C. Delgado, S. Sverdrup-Jensen and R.V. Santos), 13-20. International Center for Living Aquatic Resources Management (ICLARM) Conference Proceedings 60.

11 Tables Table 1. Simulation Results, Aquaculture Supply Shock: China (Percent From Baseline) Production

Exports

Imports

Carps (average)

13.5

16.9

a

Tilapia

9.7

10.1

9.5

Other finfish culture

4.7

11.7

0.6

Other culture

8.5

10.9

6.6

Yellow croaker capture

-3.4

-5.4

-0.2

Hairtail capture

-1.1

-7.8

3.4

Other capture

0.6

-0.9

4.6

a/ Non-traded

12 Table 2. Simulation Results, Capture Supply Shock (-10%): India (Percentage From Baseline) Production Consumption

Consumer prices

Shrimp

-3.4

-2.0

1.3

High value pelagic finfish

-7.5

-5.1

4.7

Low value pelagic finfish

-7.0

-7.0

6.8

High value demersal finfish

-8.2

-4.5

4.1

Low value demersal finfish

-6.9

-6.9

6.9

Molluscs

-8.1

-3.9

4.3

Indian Major Carp

-0.2

-0.2

-0.5

Other freshwater fish

-0.2

-0.2

-0.5

13 Table 3. Simulation results, export price shock (-5%): Thailand (Percent From Baseline) Exports Production

Consumption

Tilapia

-5.2

-0.3

-0.1

Shrimp

-2.0

-0.7

1.5

High value marine

2.9

2.9

1.5

Low value marine

-4.1

-0.2

-0.1

Cephalopods

6.8

6.7

5.5

Processed freshwater fish

-4.5

-0.2

0.9

Processed marine fish

4.5

5.0

1.0