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Chapter 7 - Costs and earnings analysis - the impact on industry profits


7.1. The profit and loss account and the classification matrix

In the chapter above, we discussed various issues regarding the assessment of different types of fisheries subsidies. Approaches and methodologies were suggested for how to calculate their cost - or revenue - to the government and their value to the industry. In this chapter, we will look closer at the latter aspect and see how we can analyse the impact of fisheries subsidies on the profits of the industry in more detail.

The classification of subsidies into four categories gives us a good idea of their modalities and general characteristics. However, to analyse their impact on the profits of the fisheries industry, we would like to know more precisely in what way they influence the industry's financial situation. Do revenues increase? Do variable costs decrease? Or are capital costs influenced? It is suggested that we add another dimension to the subsidies classification system that will give us information on which revenues and costs that are being affected. Table 1 shows how the different subsidy examples cited earlier could fit into a classification matrix based on revenue and cost types in addition to the categories from chapter 5.

As we can see, the structure of a profit and loss account has been used as a model according to which the influence on profits has been divided into revenue-enhancing (or reducing, if a profit-decreasing subsidy) and cost-reducing (increasing) subsidies. The latter have been further divided into subsidies influencing mainly running costs, labour expenses, fixed costs or capital and financial expenses in order to give an indication of the type of cost that is affected and whether the subsidy affects profits immediately or in the medium-term: a subsidy implying a change in capital is likely to have a longer-term direct impact than a subsidy affecting running costs[16]. The definitions of the different revenue and cost groups are:

TABLE 1
Fisheries subsidies classification matrix

Reference to profit/
loss account

Category 1

Category 2

Category 3

Category 4

REVENUES





SALES REVENUES
(AND OTHER INCOME)

Price support
Direct export incentives
Vessel decommissioning programmes

Indirect export promotion support
Inspection and certification for exports
International cooperation and negotiations

Import quotas
Direct foreign investment restrictions
Fisheries management

Lack of management measures

OPERATING COSTS





RUNNING
(VARIABLE) COSTS

Import/export duties*

Fuel tax exemptions
Port and landing site facilities
Provision of bait services

Chemical and drugs regulations*

Non implementation of existing regulations

LABOUR COSTS

Income guarantee schemes
Disaster relief payments

Special income tax deductions
Specialized training
Extension



FIXED COSTS

Grants for safety equipment
Taxes and fees *

Special insurance schemes for vessels and gear
Payments to foreign governments to secure access to fishing grounds
Government R & D programmes

Environmental protection programmes*
Gear regulations*

Free access to fishing grounds
Lack of pollution controls

GROSS CASH FLOW





CAPITAL AND FINANCIAL EXPENSES




DEPRECIATION AND
INTEREST COSTS

Investment grants
Equity infusions

Investment loans on favourable terms
Loan guarantees
Investment tax credits



PROFIT OR LOSS BEFORE TAX




TAX





CORPORATE
INCOME TAX


Deferred tax programmes



PROFIT OR LOSS AFTER TAX




* = Commonly profit-decreasing (revenue-reducing or cost-increasing) in the short-term.

As we noted with regard to the classification of subsidies in the four main categories, there may be subsidies that appear to suit equally well into several different groups and sometimes it can be difficult to decide whether a certain measure affects, for example, variable or fixed costs - or both. We should try to determine the most direct, immediate and significant impact and classify the subsidy accordingly but it is recognized that this may be unsatisfactory and it may be felt that longer-term effects should be accounted for. However, as was explained in section 6.6 above, this is often difficult and the Guide's focus is on short-term effects. For the costs and earnings analysis, we generally focus our attention on one year as we will see below.

7.2. Information requirements

With the subsidies classified and assessed so that we have estimates of their values to the industry with regard to revenues and different types of costs, we can proceed to look at these estimates in the context of a costs and earnings analysis. This will require that we have access to income statements of the relevant parts of the industry. In some cases, we may be able to use officially published statements or use financial statistics made available through other surveys or research. However, in most cases we need to consult with the private sector directly. This direct contact is generally recommended as it will also give us the opportunity to verify our findings and ensure that we have understood the impact of subsidies on the particular industry correctly. It should be remembered, though, that it is likely to be a time consuming task, both for our study team and for the respondents. We may also encounter one or several of difficulties common to data collection in this field. Particularly in the informal sector, written accounts are not always kept and income statement as such do thus not exist but have to be estimated through discussions. Moreover, financial information on commercial activities is often considered confidential and operators may be hesitant to cooperate for this reason. Businesses might also fear that the purpose of the study is to set the stage for removing subsidies and hence be unwilling to cooperate. Our fisheries subsidies study may already be limited to a certain segment of the fisheries sector, e.g. the harvesting subsector or one type of aquaculture, but for this part of the study we should probably consider to limit our focus even further given the data requirements. If our study as a whole covers the entire sector, we are likely to want to choose one or a limited number of subsectors for the costs and earnings analysis. Still, we may need to use assumptions and extrapolations to compensate from lack of precise data.

Already in section 4.4, it was explained how we need to include an extensive survey of the fisheries industry in order to correctly identify and assess fisheries subsidies. It was suggested that we make an inventory of all the operators of the fisheries sector and their activities. This type of information is needed also for the costs and earnings analysis. Firstly, such an inventory would help us to select and sample the segment of the sector that we would like to include in the analysis. Secondly, we need to estimate to what extent different operators are affected by the various subsidies. Depending on the type and scope of their activities, different operators' revenues and costs may be influenced in different ways and at different degrees by the same subsidy. In our assessment of the subsidies, we probably calculated aggregated costs and values but in our more detailed analysis, we need to know how much of this aggregated value that should be apportioned to each segment or to each type of operator. For example, in Box 6, we saw that, in our invented country Seidisbus, the government operated an investment grants scheme for improving fresh fish storage and transport in the aquaculture subsector at a total value of US$ 2 300 000 in 2000. But there are many different types of aquaculturists in the country and some may have benefited more than others from the subsidy. If the main part of the grants were applied for by the export-oriented brackishwater shrimp producers and our costs and earnings analysis covers only the small-scale rural aquaculture, only a small portion of the total value of the grants scheme is likely to be of relevance to us.

Depending on the data available, this division of the total value of the subsidy among different groups of beneficiaries or subsectors may be done in different ways. In some cases, we may have detailed information on, for example, exactly who has received a certain grant. In other cases, we need to construct a distribution index to allocate the aggregated value in a more approximate way. We may need to use a sample population and make assumptions about how the results can be extrapolated. If we have a clear view of the economic structure of the sector, this work is greatly facilitated.

BOX 22
Structure of the fisheries sector - An example

An inventory and description of the fisheries industry in our country Seidisbus gave the following summary information:

Type of commercial activity

Total
sales
volume

Unit

Sales
value
(M US$)

Number of
operators/
firms

Number
of
employees

Remarks

INPUT AND SUPPORT INDUSTRY:






Boat builders (private)

30

Artisanal craft

1.5

3

20


Ship wharf (state-owned)

2

Fishing vessels

20

1

200


Fishing gear importers
(nets, engines, etc)

n/a

n/a

10

25

55


Repair workshops/artisanal

n/a

n/a

5

20

30


Repair workshops/major

n/a

n/a

10

2

15


Shrimp hatchery

60 million

postlarvae

0.5

1

20

3 hatcheries

Fish feed producers

5 000 000

tonnes

10

2

20


Various support services
(informal sector)





200

Estimate

TOTAL SUBSECTOR



57

54

560


CAPTURE FISHERIES (MARINE):






Artisanal fishers

20 000

tonnes

30

500

3 500

800 boats

Semi-industrial fleet

10 000

tonnes

10

20

250

30 boats, mainly
small pelagics

Shrimp trawlers

5 000

tonnes

35

6

120

8 boats

TOTAL SUBSECTOR

35 000

tonnes

75

526

3 870


AQUACULTURE:







Small-scale farmers
(fresh water, < 3 ha/pond)

20 000

tonnes

20

5 000

10 000

Often household
based; carps

Prawn farmers

1 000

tonnes

8

12

30


TOTAL SUBSECTOR

21 000

tonnes

28

5 072

10 030


PROCESSING:







Small artisanal plants

25 000

tonnes

75

200

400


Industrial plants

30 000

tonnes

300

10

500


TOTAL SUBSECTOR

55 000

tonnes

375

270

900


MARKETING AND DISTRIBUTION:






Exporters

10 000

tonnes

150

3

20


Retailers in local markets

15 000

tonnes

75

1 000

1 200

Estimates

TOTAL SUBSECTOR

25 000

tonnes

225

1 003

1 220


GRAND TOTAL




6 805

16 580


N.B.: All figures are fictitious and may not correspond to real market prices or values.

7.3. Income statement with and without fisheries subsidies

Once we have the information - by operator or sector segment depending on how we have selected the focus of our analysis - we should organize the subsidy values and income statement data into a format allowing us to calculate a profit and loss account with subsides, i.e. representing the actual or current situation, and one in which we have removed the subsidies.

Regarding revenues and the variable, labour and fixed costs - if following the structure proposed above for the subsidy classification - there is not likely to be much difficulty once we have obtained the relevant figures from the industry. However, with regard to depreciation and interest costs, we may want to standardize our values.

In the fishing industry, depreciation costs are commonly an important item in the financial accounts owing to the importance of vessel investments. Tax regulations for how to account for these depreciation costs vary considerably between different countries. Interest is another highly variable cost in a profit and loss account as it depends on the level of loans and does not include the capital opportunity cost. If we would like to compare the results of the analysis, and the effect of subsidies, between different operators or groups of operators, a standardized method for valuing depreciation and interest costs would be needed. This would also assist us in understanding the economic performance of the industry better. It is hence suggested that the actual or current income statements are recalculated, using standardized methods for valuating depreciation and interest costs[17].

With regard to calculating the depreciation cost for a fishing vessel, the basis is the factual replacement value of the vessel. This could equal the current building costs of a similar new vessel or be the price of a second-hand vessel, if this is the most likely scenario for replacing vessels according to local commercial practices. The annual depreciation value is then calculated as the replacement value divided by the expected economic life span. The expected economic life span should also be calculated based on knowledge of local conditions.

With regard to the interest cost, the replacement value of the vessel - calculated in accordance with the above-described methodology - should be used as the value on which to impute interest cost. The interest rate used can be the rate for government bonds adjusted for inflation or any other measurement considered being an appropriate measurement of real interest rates.

So far we have only mentioned depreciation and interest costs related to vessels. However, the Guide suggests that the same principles are applied to other subsectors and that profit and loss accounts including adjusted depreciation and interest costs are calculated - to the extent possible - also for companies with other activities involving important capital investments, e.g. processing plants.

An example of a costs and earnings analysis is presented in Box 23. It is based on the information given on our invented country Seidisbus in the various examples from section 6.5 and the sample sector inventory in Box 22.


[16] 16 This aspect is, however, not discussed further in the Guide but could be an important input into a more in-depth analysis. It should also be noted that the notion "longer-term" in this context is somewhat different from when talking about the long-term impact in chapter 6.2. Here the impact is noticed directly in the profit and loss account (from the beginning and for a number of subsequent years).
[17] The methodology for uniform depreciation and interest cost calculations for fishing vessels was developed by the Department of Fisheries of the Agriculture Economics Research Institute in the Hague (Davidse et al. 1993) and has also been used in cost and earnings analyses of fishing units carried out by FAO (Lery, Prado and Tietze 1999 and Tietze et al. 2001).

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