Adis Israngkura and Sombat Sae-Hae
Natural Resources and Environment Program
Thailand Development Research Institute
Israngkura, A., and S. Sae-Hae. 2002. A review of the economic impacts of aquatic animal disease. p. 253-286. In: J.R. Arthur, M.J. Phillips, R.P. Subasinghe, M.B. Reantaso and I.H. MacRae. (eds.) Primary Aquatic Animal Health Care in Rural, Small-scale, Aquaculture Development. FAO Fish. Tech. Pap. No. 406.
Quantifying the economic costs of aquatic animal disease is important in determining the optimal investment in aquatic disease control. This study develops three approaches in studying the economic impact of aquatic animal disease: (i) measuring the economic costs of aquatic animal disease at the farm level and (ii) at the national level, and (iii) via the farmer's investment decision in disease control. At the farm level, the conceptual model illustrates that measuring the economic loss of aquatic animal disease by using the output forgone (volume of dead animals) times the market price will lead to an overestimation of the economic loss. The correct concept of economic loss to the farmers is to measure the difference between the profit when the animal is fully grown and the actual profit received when some (or all) the animals died. The empirical results show that the economic costs of aquatic disease at the farm level decrease with time, as expected. Farmers who are able to keep their aquatic animals alive longer will experience a smaller economic loss compared to farmers whose animals die at an earlier stage of the cropping period. This result contradicts the belief that if disease strikes when the animals are fully grown, then the economic loss will be large. At the national level, the Sri Lankan secondary data for 1995-97 reveal that shrimp processing and exporting companies are able to guard themselves from economic loss better than the farmers. As a nation suffers economic loss due to an aquatic animal disease, shrimp processing and exporting companies take a smaller share of the national economic loss as compared to that of the the farmers. Based on the farmer's investment decision model, it was found that Thai farmers invest rather optimally (i.e, in a profit-maximising manner) with regard to disease control investment in shrimp farming.
Aquaculture is important to the international economies in many ways. To many producing countries, it is an important income earner for local farmers and upstream-downstream industries. Often, it also contributes to the country's export earning and generates employment in rural areas. In the case of Thailand, fishery production contributed 2.73% to GDP in 1998 (Office of the National Economic and Social Development Board 1999), and in 1999, fishery exports earned US$1,877 million in foreign exchange (Bank of Thailand 2000), resulting in it being classified among the country's major export items.
The volume and value of international trade derived from aquaculture products have risen steadily from US$35.8 billion in 1990 to $47 billion in 1994 (FAO 1996). While the major importers of cultured fish and shellfish are developed countries such as the members of the European Union (EU), Japan and the United States, the major exporters are mainly developing countries. FAO (1996) reports that this trade represents a significant source of foreign exchange earnings for many developing countries. Between 1985-94, the net receipts from foreign exchange in developing countries increased from US$5.1 billion to $16 billion.
Despite the important role aquaculture has played in determining economic well being, the success and sustainability of the sector evolve around the issue of disease management. Often, the success or failure of aquaculture enterprises rests on how effectively the producers and researchers are able to manage aquatic diseases. Records show that success in managing disease results in high profits for producers and increased benefits for consumers.
Table 1 shows some estimates of the magnitude of losses resulting from shrimp disease. During the first half of the 1990s, it is reported that the losses due to disease totalled about 541 mt and were valued at around US$3,019 million (based on a price of US$5/kg). In interpreting the numbers reported in Table 1, it is essential that one adopt a correct method of calculating these economic losses. If these values are calculated using an incorrect concept of economic loss, then the values report will be misleading, either too large or too small. If the miscalculated numbers are then used by the concerned agencies as a benchmark for allocating investment funds for aquatic disease control, this can lead to an over-investment or under-investment in disease control.
Table 1. Some estimated losses due to shrimp disease (source: unpublished World Bank report prepared by C.G. Lundin in 1998).
Economic losses associated with aquatic animal disease also have international implications. As aquaculture products are traded internationally, diseases can lead to two types of economic losses. Firstly, internationally traded products can be subject to disease and/or quarantine control. Failure to comply with the quarantine standards imposed by an importing country can result in a total ban on importation. This will lead to economic losses deriving from a decline in export earnings, and also, losses derived from a decline in consumer welfare in importing countries. Secondly, infected products derived from aquaculture can transmit diseases to other countries, resulting in production and consumption losses in the recipient countries.
Aquatic animal disease management is crucial to aquaculture, and thus, investment in disease control is vital to success and sustainability. Investments in aquatic animal disease control can take place at the international, regional, national and farm levels. Just as aquatic animal diseases are costly to the economy, so is investment in aquatic disease control. The question that challenges policy makers is whether the saving to be realised from reducing economic losses due to aquatic diseases is worth the investment in disease control. For this reason, it is important that the economic losses resulting from aquatic animal disease are correctly evaluated, so that investment funds for disease control can be allocated in an optimal manner. An over-estimation of economic loss due to aquatic animal disease can lead to an over-investment in disease control efforts, while an under-estimation can lead to an under-investment. In other words, too little investment funding for disease control is considered as sub-optimal as too much.
Another concern in aquatic disease management is the hypothesis that the farmers may not invest sufficiently in disease management. Subsequently, this insufficient investment on the part of the farmers may result in an economic loss. This study will examine whether the farmers are investing optimally with regards to disease control. In this study, a farmer profit maximising model is developed to examine the net economic benefit of the farmers' aquatic disease control strategies. This model will help explain the farmers' investment behaviour in disease management and will indicate the extent to which the farmers are optimising their disease control investment.
The aim of this study is: 1) to develop a systematic assessment of the economic losses due to aquatic diseases; and 2) to construct a profit maximising model to examine the farmers' investment behaviour in aquatic disease control strategy. Such analyses will be useful for international and regional organisations, national governments and the private sector when calculating the economic loss from aquatic animal disease and for understanding the farmers' investment behaviour in disease control.
Disease problems are serious in many areas where more intensive farms have been operating. Diseases are commonly caused by viruses, bacteria, fungi, protozoa and toxins (Patmasiriwat et al. 1996). Bacterial and viral infections are among the most common diseases encountered in shrimp farms, and are usually associated with poor management or environmental conditions. In the past few years, viruses have been the most significant cause of serious losses in Thai shrimp production (Chanratchakool 1999). Among the viral diseases, yellowhead disease and white spot disease are most common. Other serious diseases include vibriosis caused by Vibrio harveyi.
Yellowhead disease (YHD), caused by yellowhead virus (YHV), is one of the most serious diseases affecting cultured shrimp. This disease was first reported on the east coast of the Gulf of Thailand in 1990, although the causative agent was not identified until years later (Alday-Sanz and Flegel 1997). Widespread epizootics have led to significant economic losses in Thailand and other Asian countries. Infected shrimp will die within three to five days (Panasont and Viwatchaisert 1996). Its name comes from the gross signs of the disease, which include a light yellow coloration of the dorsal cephalothorax due to the underlying yellowish and often swollen hepatopancreas showing through the translucent carapace in moribund shrimp (Alday-Sanz and Flegel 1997).
Outbreaks of this disease appear to be triggered by environmental factors, such as sub-optimal or unstable water condition and deteriorated pond bottom (Chanratchakool 1994). YHD infects several penaeid species, including those from the western hemisphere. This virus also infects planktonic shrimp species that are common residents of shrimp ponds, and these thus become viral carriers (Alday-Sanz and Flegel 1997).
There are currently no chemical treatments effective against this virus. However, on-farm sanitation should be regarded as a priority, and stocking densities should be kept within manageable limits in order to maintain a healthy, stress-free environment for the shrimp (Briggs 1993).
White spot disease, caused by white spot syndrome virus (WSSV), has caused the most severe production losses in Thailand since 1993, and is widespread throughout culture areas along the Gulf of Thailand and the Andaman Sea (Chanratchakool 1994). This virus is able to enter culture ponds through many vectors, such as various crustaceans, including shrimp postlarvae and wild shrimp entering the ponds during water exchange. Birds, land animals and workers are also possible vectors (Chanratchakool 1999). White spot disease can also be transmitted from adjacent affected ponds with poorly managed water exchange (Limsuwan 1997).
Affected shrimp show reddish to pinkish-red discoloration of the body, which is often accompanied by white patches on the inside surface of the carapace. Mortality can reach 100% within seven to ten days (Kasornchandra et al. 1995).
Currently, there is no effective drug or chemical to control the virus. Therefore, prevention is often recommended. Since shrimp farmers have reduced the amount of water exchange by adopting closed or semi-closed systems and have implemented proper pond management, the severity of infection has been reduced (Limsuwan 1997). However, WSSV still has the ability to cause problems in shrimp culture through out the country, due to its presence in postlarvae (Limsuwan 1997).
Vibrio harveyi is an important pathogen causing mortalities in shrimp hatcheries and farms. The disease usually occurs one month after stocking of postlarvae in the pond. Mortalities usually range from 5-80% within a few days (Kasornchandra et al. 1995). Good pond and hatchery management can help to avoid contamination and minimise the risk of disease. Water exchange management is recommended, because it can maintain the right concentration of phytoplankton in the pond. Treatment with oxytetracycline and other antibiotics has also been widely used for controlling the disease, however, their excessive use can lead to the development of drug-resistant populations of bacteria (Primavera 1993).
Expenditures and investment in disease control take place at many levels: internationally, regionally, nationally and at the farm level.
Shrimp disease problems have attracted much attention at the international level. In terms of health management, there have been vast efforts carried out in Ecuador, Taiwan Province of China, Thailand and the United States to promote sustainable shrimp farming through better management practices. Much of this effort has been directed towards improving health management by coming to terms with the ecology of aquaculture systems, namely, water exchange systems, farm densities, soil composition and intensity of farming practices.
C.G. Lundin, in an unpublished World Bank report prepared in 1998, indicated that, for medium-term solution of shrimp disease problems, investment in research should be on the order of US$31 million/yr for the first two years, $91 million/yr during years three to seven, and $90 million/yr during years eight to fifteen. Thus, a research effort totalling US$1,237 million is needed to help control disease problems. Table 2 provides a breakdown of this proposed research investment.
Table 2. Proposed annual funding requirements for shrimp disease research during the next 15 years (source: unpublished World Bank report prepared by C.G. Lundin in 1998).
In Asia, lack co-ordination has hindered progress in aquatic research. FAO/NACA (1997) reports that technical constraints include lack of technologies for nutrition and feed development, genetic improvement, breeding and seed production, health and environmental management, and integrated and intensive fish-farming systems. FAO/NACA (1997) recognised that the non-technological issues and constraints to effective aquatic research in Asia include weak interagency and institutional linkages, poor co-ordination among agencies, ineffective technology transfer and utilisation, ineffective information exchange, lack of skilled personnel, lack of understanding of impacts and implications of aquaculture development policies and plans, inadequate legislation and regulations specific to aquaculture, weak enforcement of regulations, low support for aquaculture in general and lack of support for aquaculture research.
Recent efforts in mobilising resources for research and development have resulted from the workshop held in Hawaii on diseases of cultured penaeid shrimp in Asia and United States. Also, some collaborative efforts have been made through the Asian Fisheries Society and the American Fisheries Society. The Network for Aquaculture Centres in Asia-Pacific (NACA) is a regional intergovernmental organisation promoting co-operation in research, information exchange and training and education in aquaculture development in Asia. NACA is actively involved in all aspects of aquaculture development, but in recent years has been giving particular attention to regional co-operation in aquatic animal disease control. The reason for such co-operation is that aquatic animal diseases are a common problem in Asia and can spread rapidly between countries through movement of live aquatic animals. Therefore, a common regional approach and technical co-operation have proved useful in assisting countries in solving such problems. Recently, in co-operation with the Food and Agriculture Organization of the United Nations (FAO), a regional agreement on a set of technical guidelines on health management for the responsible movement of live aquatic animals was reached among Asian governments. This represents an important step and a platform for development of common policy and actions for aquatic animal disease control in Asia (FAO/NACA 2000).
Governments of developing countries faces limited budgets; hence, research efforts towards shrimp disease control in some countries are very low. The private sector of some developing countries has devoted funding to some applied research on improvement of feed quality, use of probiotics, and the search for natural products to enhance shrimp health. However, lack of sufficient knowledge has been a bottleneck for these efforts. An unpublished World Bank report claims that the private-sector spending on shrimp research in developing countries only accounts for 0.5% of a total production loss estimated at around US$3,000 million. One reason for the lack of financial support to developing aquatic research capacity is the difficulty associated with quantifying the economic returns from investment in research effort.
Thrustfield (1995) illustrates that animal disease affects economic well being in two ways: (1) disease leads to disease control expenditure (increase in production costs), and (2) disease decreases output and hence, consumption (loss in producer and consumer economic welfare). This study follows the concept of economic losses as suggested by Thrustfield (1995), but has made adaptations to fit phenomena specific to aquaculture, namely, diseased shrimp harvested before fully matured and revenue derived from the sale of dead or premature shrimp.
Disease outbreaks result in economic losses to the farmers in terms of income reduction. These losses can be divided into two components: reduction in revenue and increase in disease control costs. The reduction in income is measured as the difference between the income that the farmers actually receive after they experience a disease outbreak and the income they would have received if the animals were fully grown without disease. This income reduction includes reduction resulting from the sale of young (premature) or dead animals or the total loss when infected animals are too small and cannot be marketed. The cost of disease control is another component that reduces the profit a farmer would otherwise receive. This includes expenditure on disease prevention, such as lime and pond preparation costs, and additional disease-control costs when the farmer experiences a disease outbreak and more disease control inputs (e.g., chemicals) have to be used.
In addition to classifying these losses, it is sometimes essential when conducting the calculation to take into account the time dimension. For instance, a loss which takes place five days after stocking will be less detrimental to the farmer as compared to another case where the loss takes place at the 100th day after stocking and the animals are nearly full grown. To take into account the time dimension, the revenue and cost stream will be discounted by the interest rate at the beginning day of each crop, to derive what is called the "present value of economic losses."
Lastly, small occurrences of production losses due to disease outbreaks will have a different economic impact than production losses that occur at a large scale. This is because small occurrences of loss will have little impact on consumer welfare, while large losses will have a substantial impact. This type of consumer welfare loss is detected by observing the change in the market price of the product resulting from reduced production due to disease outbreak. When production losses are small, they will probably have no impact on the market price. On the other hand, if disease is widespread and results in a large volume of production loss, this may have an impact on market price (making the price increase). Therefore, valuation of production losses should also take into account the size of loss volume, as well as how it will affect the market price, and hence, consumer welfare.
Measuring the total value of economic loss resulting from aquatic animal disease is a complex exercise, as it involves measuring the welfare loss on the part of both the consumers and the producers (farmers and upstream industries). Studying these losses in detail requires intense data analysis and modeling. However, a type of economic loss from aquatic animal disease can be more conveniently measured by examining the reduction in farmers' income. A mistake that is often seen is when economic loss is calculated simply by measuring reduction in aquatic animal output (volume of dead animals) and multiplying it by the market price. This method of calculation tends both to over-estimate and under-estimate the true magnitude of economic loss for the following reasons. Firstly, measuring the economic loss as the quantity of dead animal times the market price only represents the loss of revenue to the farmer. But the economic well being of the farmers is not measured by revenue, but rather by the profit realised from each crop. Therefore, a more correct method to measure economic loss is to examine the profit foregone, not the reduction in revenue. Secondly, using the amount of dead animal times the market price is misleading in the situation where farmers can derive income from the sale of dead animals. Furthermore, there are situations where disease is detected and the farmers can harvest the animals prematurely. In this case, there may not be any animal reported as "dead," but an economic loss will have taken place. Thirdly, basing the economic loss on the reduction in farm revenue ignores the fact that aquatic animal disease also increases the cost of production, as the farmers have to spend money on disease control substances/inputs. Expenditures on disease control substances/inputs essentially constitute part of the reduction in the well-being of the farmers, and as it leads to a decline in farm profit, it should be counted as part of the economic loss.
For these reasons, this study shall develop an approach that can be used to accurately measure the economic loss due to aquatic animal disease on the part of the farmers. Figure 1 represents the economic loss when a disease occurs and the animals (either still alive or already dead) have to be harvested prematurely. R(t) represents the revenue function of the sale at different stages of cultivation. It is assumed that a particular animal will not be large enough for the market before 50 days of cultivation. After the 50th day, it will begin to capture some market value, as it can either be sold as dead or premature shrimp (not fully grown). The price and the size of shrimp will increase as the number of cultivation days increases, and hence R(t) is an increasing function of time, t. C(t) represents the costs of shrimp cultivation, which is also an increasing function of time, t.
Economic loss occurs when a disease causes the farmer to sell his product before it is fully grown. The economic loss in this case will be the difference between the profit the farmer would obtain if the animals were fully grown (cultivated for at least 120 days) and the profit (or losses) he actually obtains when the animals are sold (or discarded) prematurely. Equation 1 shows how this component of economic loss is calculated. Figure 1 shows that economic loss, EL(t), is the sum of the decrease in farmers' profit and disease control expenditure, DE(t). It is expected that the economic loss, EL(t), diminishes as the number of cultivation days increases.
Economic loss at tth day
EL(t) = [Profit/rai at 120th day] - [Profit/rai
at tth day] + DE(t) (1)
where t = Time when harvest or sale takes place.
DE(t) = Disease control expenditure at time t.
Figure 1 and the following examples show how the economic loss is calculated
when disease occurs at different stages of cultivation.
Disease occurs at 120th day:
Economic Loss = (a-b) - (a-b) + DE(t)
= 0 + DE(t)
Disease occurs at 100th day:
Economic Loss = (a-b) - (c-d) + DE(t)
= (a-e) + DE(t)
Disease occurs at 80th day:
Economic Loss = (a-b) - (f-f) + DE(t)
= (a-b) + DE(t)
Disease occurs at 60th day:
Economic Loss = (a-b) - (g-h) + DE(t)
= (a-b) + (h-g) + DE(t)
Disease occurs at 30th day:
Economic Loss = (a-b) - (0-i) + DE(t)
= (a-b) + i + DE(t)
When a disease takes place that may result in total death or premature harvest, the revenue and cost streams should be valued based on a particular point in time. This concept is known as economic discounting. For instance, a farmer who experiences a disease outbreak on day 80 and obtains a profit of $100 will be better off than another farmer who experiences a disease outbreak on day 110 and obtains a profit of $100. This is because the profit that occurs later in the process will cost more to the farmer due to interest foregone. Putting it differently, a farmer who suffers the loss sooner can reinvest sooner compared to another farmer who suffers the same magnitude of economic loss, but at the later stage of the cycle. When taking into consideration the discounting factor valued at a given interest rate, the economic loss function can be represented by equation (2).
Economic loss function
EL(t) = [(R(120)-C(120))/(1+r)120] - [(R(t)-C(t))/(1+r)t] + DE(t) /(1+r)t (2)
For small losses (marginal), the amount of dead shrimp will not affect the market price, hence P = Pw, where Pw is the world price of shrimp. The revenue of shrimp sale is:
R(td) = Pw Qh (3)
As for large losses (non-marginal), the amount of shrimp losses will affect
the market price, and hence P = f(Q, GDP; ...), which is the inverse demand
function of shrimp. The revenue of shrimp becomes:
R(td) = P(Q, GDP; ...)Qh (4)
Equations (3) or (4) will be used to calculate the revenue in equation (2), depending on the magnitude of disease outbreak and its impact on the market price.
To illustrate the calculation of economic loss experienced by the farmers, this study uses the Thailand Development Research Institute survey (TDRI 1996) to compute the revenue, R(t), as a function of time. The calculation of the farmer's economic loss will be based on equation (1) as shown above, and it will be assumed that the impact of the disease is small and hence, will not affect the market price of the aquatic animal. The discounting effect and the market price effect as discussed in equations (2) and (4) will not be included in the empirical analysis below. This revenue is measured on a per rai basis. The cost of cultivation, C(t), is the cost per rai, and is also measured as a function of time. Table 3 shows the variables used in estimating the cost of disease faced by the farmers. These costs are divided into three categories: preparation cost, fixed cost and operation cost.
Table 4 shows summary data of the cost structure of the farms classified by number of cultivating days. Farms surveyed are classified into nine categories depending on the number of cultivating days. For each category, the average pond preparation costs, average fixed costs and average operating costs are calculated on a per rai basis. The results are as expected, in that both preparation costs and fixed costs do not vary with cultivating days. The only type of cost that varies with cultivating days is operating cost. For instance, farms that experience disease during the first 30 days of cultivation will only lose 61,270 Baht per rai in terms of cost incurred. Farms which carry their stock longer, such as 90-119 days, and experience disease will lose as much as 117,621 Baht per rai in terms of costs incurred.
1 The Thailand Development Research Initute (TDRI) conducted a shrimp farm
survey in 1996. The survey collected farm-level data from 348 shrimp farmers
in eight coastal provinces. The survey data include farmers' information regarding
their shrimp output, factor of production, culturing system, costs, revenue
and frequency of disease occurance.
1 rai = 0.16 ha.
Table 3. List of variables of production cost.
Table 4. Structure of production costs by culturing day (source: calculated by author and TDRI 1996 survey data).
Table 5 corresponds to Table 4, but presents the costs of farms in percentage terms. Table 5 indicates that, on average, preparation costs will account for 3.9% of farm total costs, fixed costs will account for another 17.4%, and that most of the costs are operating costs of 78.7%. So the cost structure of an average shrimp farm surveyed shows that most of the production cost is in operating costs. As the number of cultivating days increases, the proportion of preparation costs to the total costs declines from 8.3% to 2.0%. This similar trend is also observed for the fixed costs.
Table 5. Structure of production costs by cultivating days (source: calculated by author and TDRI 1996 survey data).
Table 6 shows the calculation of equation (1) (repeated below), that is, economic loss which occurs at tth day is represented by:
EL(t) = [Profit/rai at 120th day] - [Profit/rai
at tth day] + DE(t) (1)
In calculating the economic loss incurred by a shrimp farmer, it is assumed that the shrimp are fully grown at 120 cultivating days. Hence, the profit obtained at 120 cultivating days will be used as the bench mark for calculating economic losses of a farmer. In Table 6, farms are again classified into nine types according to the number of cultivating days. The total cost of an average farm, C(t), is simply the sum of average pond preparation costs, average fixed costs and average operating costs as shown in Table 5. The revenue stream, R(t), is calculated from the total revenue an average farmer in each category obtains. This revenue includes sales of farm products in all forms. For instance, R(t) includes sale of fully grown shrimp (for those belonging to categories 120 culturing days and more), and sale of premature and dead shrimp (for those belonging to categories 90-119 days and less). Based on this survey data, the bench-mark profit that an average farmer expects is the profit at 120 cultivating days, which is equal to 41,390 Baht/rai (177,345 Baht/rai minus 135,395 Baht/rai]. For the farmers who experience disease but still obtain some revenue, their economic loss will be the bench-mark profit of 41,390 minus the profit they actually obtain plus the cost of disease control, DE(t). Disease control costs, DE(t), are the costs that all farmers must face whether disease strikes or not, and hence, are included as a component of economic loss, EL(t) (see equation 1).
Table 6. Cost, revenue and economic loss of shrimp per area (unit: Baht/rai) (source: calculated by author and TDRI 1996 survey data).
Figure 2 is based on calculations from data presented in Table 6. The cost of production, C(t), starts from 61,270 Baht/rai and is an increasing function, as expected. This means that an average farmer will face an initial start-up cost of 61,270 Baht/rai (Table 6). On the revenue side, an average farmer whose cultivating days is less than 30 days will not be able to market his product if disease occurs. However, after 30 days of cultivation, the size of shrimp will be large enough for market. An average farmer can obtain revenue from selling 30-day shrimp of only 3,080 Baht/rai (Table 6). As the number of cultivating days increases and the shrimp become larger, the revenue continues to increase. At around 90 days, an average farmer will break even, as the cost of production is about equal to the revenue, even though the shrimp are not fully grown. After 90 days of cultivation the farmers will begin to earn profit.
Figure 2. Analysis of economic losses per area of shrimp farming by culturing day.
Based on equation (1), the economic loss function is depicted by EL(t), which is decreasing as expected. This phenomenon leads to the following conclusions:
Numerous disease-control devices are currently employed by the farmers to help reduce disease risks. Such disease-control devices include, for instance, application of lime during pond preparation, and during stocking to help reduce acidity, application of fertilisers and medicines, and the use of aerators to increase oxygen levels in the pond. This section examines the farmers' behaviour towards disease control activities by calculating the returns to the use of disease control inputs or the value of marginal product (VMP) with respect to each disease control input. The benefits of calculating the value of marginal product of each disease control input are:
For instance, the calculation of VMP for lime application during pond preparation may equal 2.50 Baht. This means that a kilogram of lime used generates an additional revenue of 2.50 Baht to the farmer. Suppose that a kilogram of lime costs the farmer 2.00 Baht; hence, every 2.00 Baht spent on lime during pond preparation increases the net benefit to the farmer by 0.50 Baht. This leads to two conclusions: 1) lime application during pond preparation is beneficial to the farmer, and 2) economically, the farmers did not overuse lime, that is, the return of 2.50 Baht is greater than the cost of lime, which is 2.00 Baht.
The following shows the formal derivation of the concept of VMP. Assume that a farmer selects input levels (feed, seed and disease control inputs) such that his/her profit is maximised.
p =p*Q(SXi, SXj, SXk) - Sci*Xi - Scj*Xj - Sck*Xk (5)
Where p = farmer profit
P = price of shrimp
Q = quantity of shrimp sold
Xi = quantity of primary inputs i (feed and seed)
Xj = quantity of disease control input j
Xk = quantity of fixed input k
ci = unit cost of primary input i
cj = unit cost of disease control input j
ck = unit cost of fixed input k
Equation (5) shows that the farmers profit (p) is obtained by revenue (P*Q) minus costs. The revenue component is composed of price (P) times quantity of output (Q), where Q is a function of all inputs used (Xi, Xj and Xk). The cost to a farmer is comprised of three components: costs of primary inputs, feed and seed (Sci*Xi), costs of disease control inputs (Scj*Xj) and costs of fixed inputs (Sck*Xk).
A rational farmer optimises his/her input used by choosing the level of variable inputs Xi and Xj until profit is maximised. As Xk are fixed inputs, they will not vary in the short run, and hence, will not enter the farmer's optimisation process in the short run. To maximise profit, partially differentiate the profit function with respect to Xi and Xj and set the first partial derivatives equal to zero.
/Xi = P*MPi(SXi)
- ci = 0
VMPi = P*MPi(SXi)
VMPi = ci (6)
= P*MPj(SXj) - cj
VMPj = P*MPj(SXj)
VMPj = cj(7)
Equations (6) and (7) are the first order conditions indicating that a farmer will maximise profit when the quantity of inputs is used at the level where VMP = unit cost of inputs, c.
However, due to the restriction in the definition of the Thai data set, many of the important inputs (Xi and Xj) are defined in value terms. For example, medicine application is given in expenditure, and not in quantity terms. For this reason, arguments in the production function will be redefined as expenditure on inputs used (ci*Xi and cj*Xj) instead of quantity of input used (Xi and Xj). Using expenditure instead of quantity should not affect the estimation of the production function or marginal product of inputs. Given that this study uses cross-sectional data where most farms are facing the same input prices (ci and cj), using expenditure of inputs instead of quantity of inputs simply means scaling the inputs to the same factor, that is, input prices (ci and cj).
For this reason, the production function Q(SXi, SXj, SXk) and the objective function of the farmer will be rewritten as equations (8) and (9), respectively.
P*Q = f(Sci*Xi, Scj*Xj) (8)
p = P*Q(Sci*Xi, Scj*Xj, Sck*Xk) - Sci*Xi - Scj*Xj - Sck*Xk (9)
Differentiating (9) with respect to input costs ci*Xi and cj*Xj obtains:
= P*MPi(Sci*Xi) - 1 = 0
VMPi = P*MPi(Sci*Xi)
VMPcixi = 1 (10)
= P*MPj(Scj*Xj) - 1 = 0
VMPj = P*MPj(Scj*Xj)
VMPcjxj = 1 (11)
hence, VMPcixi = VMPcjxj = 1 (12)
Equation (12) indicates that a farmer's use of inputs will be optimal (maximise profit) if the last Baht spent on each input yields equal returns, and these returns are equal to one.
Figure 3 shows the relationship between VMP and quantity of input. Point
A, where VMP equals to 1 and quantity of input is Q*, is a point that the
farmer's use of input is optimal. Point B is a point where the quantity of
input is decreased to Q1 and value of VMP is greater than 1. Thus, at this
point, the use of input is not optimal. At point C, the quantity of input
is increased to Q2 and the value of VMP is less than 1. Therefore, at this
point, the use of input is not optimal. This indicates that the farmer will
experience profit maximisation if VMP is equal to 1.
To examine if this phenomenon prevails in reality, this study tests the model using three different data sets: the Thai shrimp data collected by TDRI, the Bangladesh carp data set and the Indian carp data set.
To obtain equation (12), the study first estimates the revenue function (8), where farm revenue is a function of expenditure on each input. In this study, equation (8) will be specified linearly as shown in equation (13).
P*Q = a + Sb i(ci*Xi) + Sbj(cj*Xj) (13)
The first partial derivatives of equation (13) with respect to ci*Xi and cj*Xj represent the VMPcixi and VMPcjxj, respectively.
Based on the TDRI survey, important disease control devices have been selected and are shown in Table 7. Table 8 shows the coefficient estimates of equation (13), the t-test of each variable. As expected, nearly all the disease control devices estimated have positive signs. This shows that all these disease control inputs are making positive contribution to farm revenue. However, due to limited observations and the fact that the estimation is carried out with cross-section data, only some coefficients are significant at the 95% level. Based on 95% significant level it is found that expenditure on dry feed (TFEEDO) and oil & electrical (TENERGY) have positive impact on the revenue of the farmer.
The resulting VMPcixi and VMPcjxj show the change in farm revenue from the
last Baht spent on these disease control devices. For instance, the last Baht
spent on dry feed increases the revenue of an average farmer by 0.4744 Baht.
This, therefore, constitutes an economic loss of 0.5256 Baht. On the other
hand, the last Baht spent on seed raises the revenue of an average farmer
by 2.1040 Baht, hence, the economic value of seed is 1.1040 Baht.
Table 7. Variable description and property related to diseases (source: calculated by author and TDRI 1996 survey data)
The results given in Table 8 show that out of the 12 disease-control inputs selected, as many as 11 have positive coefficients. This means that application of these 11 disease-control inputs contributes positively to farm revenue - the value of marginal product exceeds zero. However, when we consider the economic value of these disease-control inputs, the value of marginal product minus one, eight disease-control inputs have positive economic value. These disease-control inputs are seed, medicine, teaseed cake, vitamin, chlorine, lime, oil and electricity, and lime used during pond preparation. Although 11 inputs contributed positively to the farmers' revenue, economically, there are two inputs that the farmers have overused, and hence, their economic value is negative. They are dry feed (-0.5256) and chlorine during pond preparation (-0.1278). The results presented in Table 8 suggest the following:
Table 8. Estimated value of marginal product (VMP) with respect to each input for Thai shrimp (source: calculated by author and TDRI 1996 survey data).1
In terms of future aquatic research, the results of this study lead to the following recommendations:
Data collection on a continuous basis will be essential for future research. Annex I provides an example of a questionnaire format which may be adopted for long-term data collection. This data format will allow a researcher to trace the economic performance of shrimp farms with reference to disease outbreaks and ecological constraints.
Equation (12) developed above is also tested using carp data from India. In addition to feed and seed (Xi), there are six disease control inputs (Xj) chosen from the survey data. The total number of observations included in this test is 560. Due to the difference in data format, some variables are measured in value (Rupee) and some are measured in quantity (kg). Coefficients of variables that are measured in Rupees will be interpreted as the value of output when an input used is increased by one Rupee (VMPcixi). Equation (12) suggests that, at optimum, these coefficients should be equal to one. Coefficients of variables that are measured in quantity will be interpreted as value of output when an input used is increased by one kg (VMPi). Equations (6) and (7) suggest that, at optimum, these VMPi and VMPj should equal their input prices ci and cj, respectively.
Table 9 shows that the important variables, feed and seed, are statistically significant and have positive sign, as expected. Their values are also close to one, as expected. This shows that the use of feed and seed by the Indian farmers is optimal, as equation (12) suggests. Disease-control inputs do not perform well. From six disease-control inputs selected, only three have positive signs as expected. The coefficient of fertiliser is positive and significant, and is close to one, as expected. This means that an increase in the farmers' expenditure on fertiliser will increase farm revenue. As for the other disease control inputs, the results are mixed. VCHEM is negative but its statistic is not significant. As for QLIME, QTEAS, QWATT and QFILL, which are measured in kg and not Rupee, their VMP will then be based on the value of applying an additional kilogram of input and not an additional Rupee in terms of expenditure. For this reason, their economic values cannot be calculated here. These four variables are, however, included in the model in the attempt to avoid model misspecification. It is believed that the reason that might explain the poor statistical performance of the disease-control inputs is the data availability. From the total of 1,004 observations, there are many observations that have missing data on harvested area, production, feed and seed. The number of observations available for the statistical analysis is only 560. Even within these 560 observations, there are some missing data for disease-control inputs. It is, therefore, difficult to judge whether these missing data on disease control inputs indicate that these inputs are not used, or that the results are due to survey error.
Table 9. Estimated value of marginal product with respect to each input for Indian carp (number of observations = 560) (source: estimated by author and NACA (1996) survey data).
From a total of 626 observations, only 74 observations were used in this statistical analysis. The remaining observations were deleted, due to the absence of important variables, such as harvested area, production, feed and seed. Variable definition for this Bangladesh case is the same as for the Indian case. The results of the estimated value of marginal products are reported in Table 10.
VFEED, VSEED, VFERT and VCHEM have positive signs as expected, although the t-scores on VFEED and VFERT are not statistically significant. Their VMPcixi and VMPcjxj vary from 1.5953, in the case of VFEED, to 17.2305, in the case of VCHEM. This outcome, together with the quality of data, suggests that the results presented in Table 10 may be unreliable and that more effort should be devoted to improving the quality of data collection.
Table 10. Estimated Value of Marginal Product with respect to each input for Bangladesh carp (number of observations = 74) (source: estimated by author and NACA (1996) survey data).
Shrimp culture in Sri Lanka did not begin until the early 1980s. Having recognised the availability of coastal resources (unpolluted brackish water and unused coastal areas), the Government of Sri Lanka began stimulating private-sector involvement in shrimp culture through investment incentive packages, such as exemption from import taxes on machinery and income tax holiday. During the 1980s, shrimp farming expanded at a moderate rate, with a total of only 60 farms in operation covering an area of around 400 ha. Shrimp farming took off in the 1990s, the total number of farms growing to 960 by 1996. Out of the 960 farms in operation, as many as 589 were unauthorised. The total farm area in 1996 was 2,400 ha, of which 1600 ha were shrimp ponds (Siriwardena 1998).
Shrimp culture benefits the Sri Lankan economy mainly through foreign exchange earnings. In addition, it contributes through linkages with downstream industries, employment generation and income distribution. Table 11 shows that the quantity of shrimp exported rose three-fold from 1992 to 1996. The total export volume in 1996 was 3,555 mt, of which about 90% was derived from cultured shrimp. In terms of export earnings, the total export value rose from 613 million Rupees in 1992 to 2,365 million Rupees in 1996. The expansion in shrimp aquaculture has exceeded that for other fishery products. This is seen from the increase in the contribution of shrimp export earning to the total fishery export, which rose from 42.3% in 1992 to 51.6% in 1996. Furthermore, shrimp culture also expanded at a faster rate as compared to the average growth rate of all other exports from Sri Lanka. The contribution of shrimp exports to the total export value rose from 0.6% in 1992 to 1.0% in 1996.
Table 11. Shrimp export data for Sri Lanka, 1992-1996.
Major inputs into shrimp farming that have to be imported include feed, aerators, water pumps and electrical generators. Tables 12 and 13 show the value of these imports during 1992-96. In 1996, the value of feed imports into Sri Lanka for use in shrimp farming was 460.70 million Rupees. From 1992 to 1996, these feed imports totalled 1,352.92 million Rupees. This amount constitutes about 73% of the total value of material imported for shrimp farming. Other imported items account for the remaining 27% (see Table 13).
Table 12. Import of feed used in shrimp production in Sri Lanka, 1992-1996 (source: Siriwardena 1998).
Considering the total export value from the shrimp sector from 1992 to 1996 of 7,589 million Rupees (not taking into account economic discounting), together with the total import volume during the same period of 1,855 million Rupees, shrimp culture brought a net foreign exchange earning of 5,734 million Rupees into the country over this period.
Table 13. Import of feed and equipment used in shrimp farming from 1992-1996 (source: Siriwardena 1998).
In addition, shrimp culture in Sri Lanka generates both direct and indirect employment. Siriwardena (1998) reports that direct employment in the shrimp sector is approximately 20,000 jobs. Another 20,000 indirect employment opportunities are also reported in supporting industries and part-time labour, such as work in construction of ponds and other infrastructure facilities on shrimp farms. The shrimp culture industry pays about 984 million Rupees in wages and salaries annually for direct employment. The total direct and indirect employment accounts for about 11% of the total employment in the fishery sector of Sri Lanka.
Having recognised that shrimp farming is an important foreign exchange earner, the Board of Investment (BOI) of Sri Lanka has granted a tax holiday package for licensed shrimp farms as a means to encourage exports. BOI privileges include: 1) a five-year full exemption on income tax, 2) a concessionaire tax period at 15% for another 15 years after full income tax exemption, 3) exemption from import duties on imported farm machinery, 4) exemption from turnover tax on sales, 5) exchange control exemption and 6) concessionaire tax for expatriates at 15% for five years. These privileges benefit mainly the large shrimp farms and shrimp processing factories with licenses. In 1998, there were about 65 licensed shrimp farms. Small farms without licenses were not entitled to these benefits.
Besides the direct economic impacts discussed above, the shrimp sector also generates social and environmental impacts on the community. The co-existence of large-scale and small-scale farms has led to conflicts in resource utilisation, such as access to land and to water from canals. During the last decade, suitable shrimp land was leased to large-scale or "licensed farmers," while small-scale farmers were labelled as "intruders." Conflicts often occur when both types of farmers' extract and release water from the same water source, as this increases the likelihood of spreading disease. There are also conflicts between shrimp farmers and other farmers, as the salt water used in shrimp ponds may damage agricultural areas and grazing lands used for traditional animal husbandry. Hatcheries and farms which extend their water intake pipes into the sea to obtain sea water also create conflicts with coastal fisherman who operate their vessels in the area.
Clearing of mangroves for shrimp ponds has also had a great impact on local environments. For instance, reduction in nursery grounds for juvenile fish, loss of storm protection function, and loss of fuel wood supply have been outcomes of the expansion of shrimp ponds into mangrove areas. Lastly, many shrimp-farm owners extract groundwater to control the salinity level in their ponds. This practise could lead to reduced groundwater levels that could affect other water users in the vicinity.
Shrimp disease outbreaks took place in Sri Lanka during the second half of 1996. While some economic impacts were felt towards the end of 1996, most of the impacts were carried on to the 1997 crop. Table 14 shows the potential and actual shrimp outputs in Sri Lanka during 1995-97. Based on a postlarval capacity of 598 mt in 1995 and 849 mt in 1996 and 1997, the potential shrimp export volumes in 1995, and 1996 and 1997, were 2,781.00 and 3,948.28 mt, respectively. However, due to the disease outbreaks that occurred towards the second half of 1996, the actual shrimp export volumes in 1996 and 1997 were 3,155 and 1,228 mt, respectively. This translated into a production loss of 793.28 mt in 1996 and as much as 2,720.28 mt in 1997. Based on the average selling prices of shrimp exports in 1996 and 1997, this reduction led to a reduction in the value of exports of 594.64 million Rupees in 1996 and as much as 2,006.94 million Rupees in 1997.
Table 14. Shrimp production and exports for Sri Lanka, 1995-1999.
Based on the total loss of 2,601.62 million Rupees, or US$43.36 million, Table 15 shows the breakdown of this economic loss by sector. The three sectors considered are the shrimp-processing sector, the shrimp-farming sector and the hatchery sector. The breakdown of the total economic loss in 1996 and 1997 is based on the price of shrimp sold at each stage. These are the price of postlarvae sold to shrimp farms, the price of fresh shrimp sold as inputs to shrimp processors, and the export price of processed shrimp. For instance, if a shrimp processor received, on average, US$12/kg of processed shrimp being exported, and the price paid for fresh shrimp from the farmers was US$9/kg, then processing adds US$3/kg to the value of shrimp. In other words, this US$3/kg represents the value added by the processing industry. This value added encompasses returns to the processing owners, wages of the workers, interest income and returns to capital, and the opportunity cost of land used during shrimp processing. As a result of disease outbreaks, this US$3/kg becomes an economic loss faced by all the stakeholders of the processing sector. A similar argument is used to calculate the breakdown for the shrimp-farming sector and the hatchery sector.
Table 15 shows that out of the total economic loss of 2006.98 million Rupees in 1997, about 25% were felt by the processing sector, 69% was absorbed by the farming sector and only 6% were shared by the hatchery sector. The farming sector absorbs most of the impact of disease outbreaks, as most of the value added by shrimp farming is located in this sector. A similar picture is also seen in 1996, when 33% of the impact was felt by the processing sector, 62% by the farming sector and the remaining 5% by the hatcheries.
Table 15. Economic loss of shrimp farming due to disease measured as reduction
in exports (US$ 1 = Rs 60) (calculated by author based on Table 14).
In summary, the disease outbreak that took place in Sri Lanka in the second half of 1996 cost the country a total of about 2,601.62 million Rs (US$43.36 million) in terms of decline in export value. Due to the lack of data on feed imports, this study cannot calculate the net loss in terms of foreign exchange earnings resulting from this disease outbreak.
Besides the reduction in export income, the disease outbreak that took place in Sri Lanka towards the second half of 1996 also caused a liquidity problem among farm operators. Many shrimp farms and shrimp processing factories could not make bank payments on their loans. This led lenders, especially the commercial banks such as the Development Finance Corporation of Ceylon (DFCC), to come up with a loan rescheduling programme for shrimp farmers. This loan rescheduling programme includes 1) differed instalments up to 15 months, 2) a rescheduled loan repayment for another five years at, 3) an interest rate reduction by 5% and 4) capitalisation of accumulated interest payments. This programme was extended to about 125 bank borrowers, and it constitutes another type of cost Sri Lanka had to face as a result of shrimp disease outbreaks.
This study conducted a survey in Sri Lanka during April 1998 to examine the extent of economic loss at the farm level. An interview survey was carried out with government officials and farm owners in Chilaw in the North Western Provinces. The following reports how shrimp disease outbreaks affected farmers in the Chilaw area.
The interview with government officials at the North Western Provincial Council (NWPC) showed that the disease outbreak that took place in the second half of 1996 had severely affected shrimp farms in this area. This disease outbreak affected two crops: the second crop of 1996 and the first crop of 1997. From the provincial statistics, it was shown that about 4,600 acres of land in the province were used as shrimp ponds, from which 15,000 mt of shrimp were produced in 1995. In 1996, the provincial statistics show that the disease outbreak had led to about 60% reduction (of 1995 output level) in farm output and another 80% reduction (of 1995 output level) in 1997.
As a consequence of this disease outbreak, many farmers had to forego two additional crops after the disease outbreak. This loss of potential economic gains from abandoning the farms for two crops also represented an additional economic loss to the local economy as income that would have been generated.
In addition to the above losses, the local farmers and the government made some investment towards disease control. Through the Dutch Canal User Group, some shrimp farmers contributed labour in cleaning the canal, and the local government made some small financial contribution. Statistics on the amount of this investment were not available, but officials from the NWPC revealed that the investment was small.
In addition to interviewing government officials, visits were made to some shrimp farms, processing factories and hatcheries in Chilaw. Information on economic losses resulting from shrimp disease outbreaks was obtained through personal interviews. The following provides some baseline information on how this disease outbreak affected the farmers in Chilaw.
Thus, it is concluded that the disease outbreak in Sri Lanka affected the local farmers through 1) reduction in expected profits; 2) foregone benefit for another crop, as ponds were generally put to rest for one crop cycle; and 3) expenses for maintaining workers (union workers who are generally on large, licensed farms) when ponds were not stocking during the resting period. There were also benefits associated with the shrimp disease outbreak: 1) release of some workers to other economic activities, such as fishery, and 2) reduction in shrimp feed imports into the country.
Due to limited observations, this study could not apply the economic loss concept and the economic value of disease-control estimation procedure to Sri Lanka. In order to implement such economic methodology, a large data set is required. This data set should contain information on the breakdown of cost and revenue stream, information as to when the disease takes place, and the bio-physical characteristics of the farms. An example of a full questionnaire is given in Annex I for future research activities in Sri Lanka. This study recommends that the aquaculture authority in Sri Lanka should develop a consistent data collection mechanism. This database will be useful for assessing the impact of disease outbreaks and will help determine appropriate investment in disease control expenditures.
This study recognises the importance of quantifying the economic loss caused by aquatic animal disease. The magnitude of economic loss can be used as a guideline for determining optimal investment in aquatic animal disease control. The study shows that measuring economic loss by using the volume of dead animals multiplied by the market price tends to result in overestimation of the loss. Use of this method can result in an over-investment in aquatic animal disease control. A more accurate method is to measure the farmers' economic loss by examining the difference between the expected income when the animal is fully grown and the actual income realised, and the farmers' expenditure on disease control inputs. The empirical results show that the economic loss of the farmers decreases as cultivating time increases.
In examining the economic loss caused by aquatic animal disease at the national level, it is found that the processing and exporting industries are better able to protect themselves from losses than are the farmers. During disease outbreaks, these sectors took a smaller share of economic loss as compared to the farmers.
To investigate farmers' investment behaviour, this study developed a profit maximising model to examine how well shrimp farmers are able to cope with aquatic animal disease. The calculated Value of Marginal Products for applying aquatic disease control inputs showed that Thai farmers tend to invest rather optimally in this regard.
Alday-Sanz, V., and T.W. Flegel. 1997. The risk of introducing yellow-head and white spot viral infections from Asia to the Americas. CD-ROM Paper No. 1, IV Congreso Ecuatoriano de Acuicutura, 22-27 October, 1997, Guayaquil, Ecuador, 9 p.
Bank of Thailand. 2000. Monthly Bulletin, September 2000, p. 66-67.
Briggs, M.R.P. 1993. Status, problems and solutions for a sustainable shrimp culture industry with special reference to Thailand. Report submitted to the Overseas Development Administration (ODA) under the project "Development of Strategies for Sustainable Shrimp Farming," Project No. R4751, Institute of Aquaculture. University of Stirling, 41 p.
Chanratchakool, P. 1994. Shrimp pond management - how to keep the feeding area clean. AAHRI Newsl. 3(2): 2-3.
Chanratchakool, P. 1999. Key technical and farm management issues in Thailand. p. 27-29. In: Proceedings of the workshop "Toward Sustainable Shrimp Culture in Thailand and the Region," 28 October - 1 November 1996, Songkhla Province, Thailand. Sponsored by the Australian Center for International Agricultural Research (ACIAR), the Network of Aquaculture Centres in Asia-Pacific (NACA) and the Asian Development Bank (ADB).
FAO. 1996. The state of world fisheries and aquaculture. FAO Fisheries Department, FAO Fish. Circ. No. 886, Rev. 1, 125 p.
FAO/NACA. 1997. Survey and analysis of aquaculture development research priorities and capacities in Asia. FAO Fish. Circ. No. 930, 263 p.
FAO/NACA. 2000. Asia technical guidelines on health management for the responsible movement of live aquatic animals and the Beijing consensus and implementation strategy. FAO Fish. Tech. Pap. No. 402, 53 p.
Kasornchandra, J., S. Boonyaratpalin, U. Aekpatithanpong and R. Khongpradit. 1995. Mass mortality caused by systemic bacilliform virus in cultured penaeid shrimp, Penaeus monodon, in Thailand. Asian Shrimp News, 5(2): 2-3.
Limsuwan, C. 1997. Reducing the effects of white-spot baculovirus using PCR screening and stressors. AAHRI Newsl., 6(1): 2.
NACA. 1996. A survey project for the source of water pollution from coastal fishery. A research report submitted to the Department of Pollution Control, Ministry of Science, Technology, and Environment, Bangkok, 382 p. (in Thai).
Office of the National Economic and Social Development Board. 1999. National Income of Thailand. Bangkok, 49 p. (in Thai).
Panasont, S., and Y. Viwatchaisert. 1996. Tiger prawn farmers seminar of Songkla Province. Thai Fish. Gazette, 49: 256-262. (in Thai).
Patmasiriwat, D., M. Bennis and S. Pednekar. 1996. Shrimp farming in Thailand: assessing environmental economic and trade-related impacts: a review of literature. Draft working paper for environmentally sensitive sector: a case study of shrimp aquaculture in Thailand. Thailand Development Research Institute. Bangkok, 50 p.
Primavera, J.H. 1993. A critical review of shrimp pond culture in the Philippines. Rev. Fish. Sci. 1: 151-201.
Siriwardena, P. 1998. Shrimp culture in Sri Lanka: the benefits, problems and constraints associated with the development and management and responses to address problems. National Aquatic Resources Research and Development Agency (NARA), Colombo, 17 p.
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1. Name of data collector : ...........................................................
2. Date of survey: Day ......... Month ................... Year 19..........
3. Location of farm: City...........................Country.....................
4. Year this farm began operation in 19........
5. Crop duration being interviewed:
From Day ......... Month ................... Year 19 ..........
To Day ......... Month ................... Year 19..........
6. Total farm area of crop in Question (5) .................. acre.
7. Total pond area of crop in Question (5) .................. acre.
8. Number of ponds cultivated in crop in Question (5) ........................
9. Treatment pond area used during crop in Question (5) .................acre.
10. Source of water supply:
o 1. Sea water
o 2. Channel/rivers
o 3. Ground water o 4. Recycle from treatment pond
11. Water discharge/exchange:
o 1. into channel
o 2. into treatment pond
12. Expected harvest amount ...................... tons.
13. Actual amount harvested ....................... tons.
14. Expected number of cultivation days ..................... days.
15. Actual number of cultivation days........................... days.
16. Survival rate .................... percent. [100*(13)/(12)]
16. Size of shrimp when harvested .................... cm.
17. Price of shrimp when sold ................ Rs/kg.
18. Total REVENUE (not profit) obtained .................... Rs.
Section IV : Disease During Crop in Question (5)
52. Did your farm experience disease during crop in Question (5)?
o 1. Yes
o 2. No, then go to Section V Question (58)
53. If Yes, how many days after stocking did the disease occur? ...............
54. Why type of disease did you experience?
o 1. White spot
o 2. Yellow spot
o 3. others, please specify ................................................
55. How much did this disease cost you in terms of additional inputs required
to cope with the disease?............................Rs.
56. At the beginning of crop, how much PROFIT did you expected from this crop (not counting initial fixed investment costs) ...................... Rs?
57. At end of this crop, how much PROFIT did you actually obtain ... ....¼¼....Rs?
58. Age of the farmer .............. years.
59. Numbers of years practised shrimp farming .................. years.
60. Type of training received:
o 1. Training from Govt.
o 2. Learned from friends
o 3. Training by private companies (e.g., fertiliser company)
o 1. Primary
o 2. Secondary
o 3. Technical diploma
o 4. Bachelor
o 5. Graduate studies o 6. No education
Section VI Quality of this Interview
62. What is the interviewer opinion about the quality of this interview?
o 1. Very Reliable
o 2. Reliable
o 3. Rather unreliable
********** END OF QUESTIONNAIRE **********
Following are the definitions and clarification of some of the technical terms used in the questionnaire.
5. Crop duration being interviewed:
From Day ......... Month ................... Year 19 ..........
To Day ......... Month ................... Year 19..........
You are required to ask the farmer about the situation of his/her farm only DURING ONE PARTICULAR CROP, and not the situation of his/her farm through out the year. This question directs you to the particular crop that you are asking. If you want to ask the farmer about the situation during other crops, you have to use more than one questionnaire. For instance, a farmer supplies information about the past three crops, then you will need three questionnaires to collect all the data - one questionnaire for each crop.
9. Treatment pond area USED during crop in Question (5) ....................acre.
If the farmer practices extensive farming and discharges all the wastewater into the canal, put zero. This question applies mainly to large farms that practice water exchange or intensive farming. Make sure that the number you put in is the area of treatment ponds that were USED during that crop and NOT the total area of treatment pond the farmer HAS on his/her farm.
16. Size of shrimp when harvested .................... cm.
If shrimp are sold at different age, then use the average size.
17. Price of shrimp when sold ................ Rs/kg.
If shrimp are sold at different prices, then use average price.
Market Price (Rs)
This refers to the market price DURING THE CROPPING PERIOD BEING INTERVIEWED. For instance, a farmer bought an aerator for 10,000 Rs five years ago, but this aerator is WORTH only 4,000 during the cropping period being interviewed. In this case, you would put 4,000 Rs in the appropriate column, not 10,000 Rs. that he paid for five years ago.
Costs (Rs) (quantity * price)
You have to do some calculation along with the farmer to double check that the total cost of each input is approximately correct with the farmer's own calculation.