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Measurement of economic impacts of fishery management decisions - model-based approaches in specific fleet sectors.

Objective

A simulation model has been developed for measuring the economic impacts of fishery management decisions.
The simulation model developed and applied in this project is a Mixed Integer Programming optimisation model maximising the gross margin. The model is a deterministic approach, containing deterministic data without uncertainties, developed with GAMS. Except from this deterministic character of the model, most of the limitations of the present model structure can be overcome with further development.

Based on an accurate allocation of variable costs to fishing activities and on a model configuration reflecting the economic interrelations in a proper way, first simulation runs and a great number of feasibility tests (including adjustments) were carried out. As main criteria for testing the feasibility of the model configuration and the plausibility of the model solution, specific outputs (e.g. catches, proceeds, number and length of trips, days at sea, gross margin) were considered and compared with the empirical results observed in practice.

In general, the differences between the model solutions and results in reality may be caused by deficiencies of data and by the behaviour of fishermen, not always being directed to maximising the economic result, and only to a small extent by model-inherent reasons. After extensive tuning and implementation of several reasonable and useful adaptations a set of so-called "BASIC solutions" was produced that simulates the reality acceptably well. These "BASIC solutions" are considered as the standards of comparison for all simulation procedures.

Finally, the application of the developed simulation model is demonstrated by simulating different scenarios dealing with different regulatory measures (e.g. quotas, reduction of time at sea) and changing economic and biological parameters (e.g. prices, costs, catch rates). Furthermore, some individual management strategies (additional target species and fishing areas, different fish prices in landing ports, landings only in homeports, temporary lay ups, etc.) have been considered.

In the majority of the simulated examples, the above mentioned measures and parameters have been introduced separately in the model; but in some cases several factors were simulated simultaneously with regard to their impact on the gross margin. The presented model applications were quite successful and demonstrate that the model is well able to measure the impacts of various planning decisions of the vessel owners as well as to assess future political measures on the national and EU level.
This project, largely funded by the EU FAIR programme, was a co-operation of research institutes from three countries: Germany, the Netherlands and Spain.
Based on detailed investigations of costs & earnings, operational (activity) data from logbook records and other databases (e.g. price statistics) in the participating countries, this model-based approach enables political institutions and fishing industries to assess the economic consequences of political and individual measures concerning quotas, time restrictions, closure of fishing areas, decreasing catch rates, prices, etc. on the economic results of particular fleet segments.

The study can be classified as an empirical investigation, analysing and calculating the impacts of specific decisions (measures) in quantitative terms. The scope of the project is restricted to a selection of so-called "standard vessels" representing important fleet segments of the fishing fleets in Germany, the Netherlands and Spain (Mediterranean Sea). But the extension to other types of vessels and fisheries will not pose a great problem to knowledgeable experts.

In general, the selection of fleet segments in this study was determined by and depending on the importance of the fleet sector within the national fishery, the necessity of fairly homogeneous groups and the availability of data. According to these criteria in Germany two groups - Baltic cutters (located in Saenitz/Ruegen) and North Sea cutters (situated in Cuxhaven) - were selected, while in the Netherlands the segment of the 300 HP beamers (so-called "Eurocutters") and 2000 HP beamers were chosen for this investigation. In Spain, the selection was focussed on two important Mediterranean ports, Barcelona and Castellon where different fleet segments (trawlers and purse seiners) have been investigated.

As the model was meant not only to estimate changes in costs and earnings but also to simulate changes in operational behaviour, very detailed data were required as inputs. The evaluation of existing databases, the collection and/or updating of necessary data and data comparison, harmonisation and preparation for model use were very time-consuming tasks. The data records were amplified by personal communications of fishermen, managers of producer organisations and accountants, together with scientific knowledge based on special investigations and experiences. For the project, the year 1995 (or 1996) has been chosen as the basic year according to the availability of a full set of data.

The data set on fishing activities is resulting from concrete operating figures recorded in the logbooks in detail (Germany and the Netherlands) or from enquiries in Spain and includes the time spent for fishing activities and the catch quantities by species on the different fishing grounds.

Fishing boats generally change their fishing grounds seasonally and sometimes even from trip to trip according to the available fish stocks and the expected catch rates. So for an adequate simulation of operational behaviour, data on the short-term evolution of fish stocks and catchabilities by fishing grounds are required. Such data are generally not available, so we had to construct them ourselves, putting a lot of effort in the process.

Monthly average catch rates per hour by fishing ground were derived from the logbook data of the sampled vessels in the German and Dutch cases and from the landings statistics in the Spanish case. The resulting data sets proved to be quite useful, although they were certainly not flawless. For some grounds very small numbers of trips made the resulting catch rates unreliable; in the Dutch case, time on the grounds had to be estimated by reducing trip duration by estimated steaming times, and similarly in the Spanish case.

Another important task was the preparation of fleet activities with respect to time input. A distinction is made between active and inactive time. The active time contains the steaming time from port to grounds and back, the so-called effort time for fishing and searching on the fishing grounds and some additional time which is directly combined with fishing activities like unloading, reparation, holidays and bad weather days.

These operating (activity) data were confronted with the (variable) cost data in such a way that cost allocations and calculations of cost units were possible which form a crucial part of the data inputs for the model.

For measurement of economic impacts an interim result, the so-called "gross margin" has been selected, representing the surplus of proceeds minus variable costs. The selected term "gross margin" only contains operating costs, which are depending on fishing activities so that impacts of the introduction of alternatives and modifications of existent management measures and strategies (regulatory and individual) can be quantified. The resulting "gross margin" will not disclose the economic performance of the selected fleet segment in total, because fixed costs and depreciation are not taken into account.

Funding Scheme

CSC - Cost-sharing contracts

Coordinator

Bundesforschungsanstalt fur Landwirtschaft
Address
Bundesallee 50
38116 Braunschweig
Germany

Participants (3)

Bundesforschungsanstalt fur Fischerei
Germany
Address
9,Palmaille, 9
22767 Hamburg
LANDBOUW ECONOMISCH INSTITUUT
Netherlands
Address
Burgemeester Patijnlaan 19
Den Haag
Universidad de Barcelona
Spain
Address
Gran De Gracia, 229
08012 Barcelona