Phd Thesis

 "POVERTY, INEQUALITY AND NATURAL RESOURCE DEGRADATION:

AN INVESTIGATION INTO THE SMALL-SCALE FISHERY SECTOR OF

SOUTH KERALA". downloadable http://dyuthi.cusat.ac.in/dspace/handle/123456789/99

A. Research Problem

In many parts of the world the rural poor substantially depend on the freely available natural resources or ‘the commons’ for their livelihood. These resources provide them a range of goods for household use in various capacities, as consumer durables, production inputs, and capital assets. They also perform an important safety net function and guard against exogenous stresses and shocks. Even when the poor have access to other resources, these natural resources provide a cushion to them during periods when income from other sources decline or become unavailable; natural resources are sometimes the only asset to which the poor people has access  (Shyamsundar, 2002). The vulnerable and the marginal groups of our society are often the most dependent on the common resources of the community in which we live (Dasgupta, 1993, 1996). Hence it is these groups that are the most impacted due to the declining natural resource environment, especially in the absence of any successful process of regeneration. But the ways in which natural resource degradation affects the poor and the extent to which it affects individual groups depend to a large extent on the types of ‘poverty’ of such groups and their asset portfolios. In the present proposal an attempt is made to examine the behaviour of the poor small-scale fisher households in the situation of depletion of, and limited access to resources by examining the case of the coastal marine small-scale fishery sector of Kerala.

In Kerala, the marine fishery sector is de jure under state ownership but de facto, it is unregulated and open access in nature and is characterized by dualism in the form of co-existence of a small-scale sector the activities of which are concentrated in the inshore areas side by side with a large-scale sector. In the past decade there has been an enormous increase in fishing pressure as a result of increase in the number of fishing crafts, particularly in the number of motorised crafts in the small-scale sector. Nevertheless, the total annual fish production has remained stagnant around 5.9 lakh tonnes against the optimal sustainable yield of 5.7 lakh tonnes thus leading to a resource depletion crisis (GOK, 2002). Indications are that large potential resource rents are lost in fisheries because of overfishing. Under the open access regime, introduction of larger and faster vessels has meant a larger share of the common wealth of marine fishery. With about 50% of the fish output cornered by the large-scale sector and another 40% by operators of large seines in the motorised sector, the traditional fishermen especially those in the non-motorised sector find themselves to be marginalized (Yohannan et. al, 1999). It is believed that with modernization of fishing technology economic and social stratification and inequality in the fishing communities have increased. As more and more fishermen motorised their crafts, fishing pressure increased on the limited fishery resources which led to resource depletion. Individual catches and income began to level off and non-motorised operations lost ground.  At the same time increasing cost of operating motorised crafts reversed their initial advantage over the non-motorised.  For many a fisherfolk in the small-scale sector daily earnings from fisheries are low, fluctuating and often uncertain affecting their livelihood security. For them outward movement to non-fishing activities is difficult because of lack of knowledge of opportunities and skills.

Government polices in the past were aimed at creating conditions for increasing fish production through modernization of fishing crafts and methods.  The idea was that increased fish production would lead to higher earnings. Provisions for infrastructure, subsidies, and soft loans were part of the package.  Special assistance given to traditional fisher folk was in recognition of the fact that they themselves could not join the race unassisted. Further, to support the small-scale fishers from the consequence of resource depletion, Government imposed a ban on monsoon trawling. But even after all these Governmental efforts, a large section of the fishing community continues to be poor.

Kerala State with a coastline of 590 kms has plenty of marine resources with a predominance of oil sardines, mackerel, anchovies and prawns. The potential of marine fishery resources of the State within a depth of 200 m range is estimated at 7.51 lakh tonnes. (See Table 1.2)

Table 1.2 Marine resource potential of Kerala

Source: Dept. of Fisheries, GOK, 2002

 The fishing activity in the marine sector, however, is largely concentrated in the inshore areas within a depth range of 0-50 m. Against the optimum sustainable yield of 5.7 lakh tonnes, the fish landing from this inshore area is now around 6.0 lakh tonnes thus leading to a resource depletion crisis Govt. of Kerala (GOK, 2004). In Kerala, the marine fishery sector is de jure under state ownership, but de facto it is unregulated and is open access in nature. Against this background, the development programmes undertaken by the government in the sector, which included modernisation of country crafts, popularisation of new generation crafts, and subsidised distribution of suitable complements of fishing gear, have led to an enormous increase in fishing pressure. Increase in fish prices due to increased demand both in the domestic and the export markets, has also promoted large-scale investments in craft, engine and gear leading to over-capitalisation. High price and high demand for prawns in foreign market are responsible for the anarchic growth of the number of mechanized boats in Kerala (Rajasenan, 1987). The fishery resource forecast based on ‘auto regressive moving average’ (ARMA) shows stagnation with reference to most of species in Kerala (Rajasenan, 1987). The enormous increase in the number of fishing crafts especially in the number of motorised country crafts and the use of ring seine, a prohibited fishing gear, are considered to be the main causes of resource depletion.  Indications are that large potential resource rents are lost in fisheries because of over-fishing.

Marine fishing is a traditional activity of certain communities in the coastal area of the State. It is estimated that in Kerala about 8.4 lakh fisherfolk depend on marine resources for their livelihood[1]. Modernization ideologies in the early sixties aimed at increasing the extractive capacity of the fisheries sector and access to investment funds, led to a dualism in the form of coexistence of large-scale mechanized fisheries side-by-side with small-scale artisanal fisheries. In the years that followed the rapid expansion of the mechanized sector cut into the harvest of artisanal fishermen. The artisanal fishers responded to the new developments by going in for motorising their country crafts. The expansion of motorisation was very fast; and in order to cope with intensive competition new types of gears like ring seines were also introduced. Of the initial stages while these changes enabled the fishermen to fish more efficiently and to expand their activity space, the continuation of the process led to stagnation in fish production. Further, with about 50 percent of the fish output cornered by the large-scale sector and another 40 percent by operators of large seines in the motorised sector, traditional fishermen especially those in the non-motorised sector found themselves marginalized (Yohannan et al, 1999). As more and more fishermen motorised their crafts, fishing pressure increased on the limited fishery resources, which led to resource depletion. Individual catches and income began to level off and non-motorised operations lost ground.  At the same time, increasing cost of operating motorised crafts reversed their initial advantage over the non-motorised crafts. The income distribution has thus become highly skewed since the mechanized trawlers and those using large seines account for only a small percentage of active fishermen.

It is believed that with modernization of fishing technology, economic and social stratification and inequality in the fishing communities have increased. The costs of resource degradation are disproportionately borne by the poor who are the primary users of the commons and environmental resources. For many fisherfolk in the small-scale sector, daily earnings from fisheries are low, fluctuating and often uncertain, affecting their livelihood security. For them outward movement to non-fishing activities is difficult because of lack of knowledge of opportunities and lack of skills. To understand their plight, poverty has to be seen not only as income-poverty, but also in its wider sense to encompass low levels of achievement in education, health, sanitation and socio-political status. Some anecdotal evidence exists to show that fishing communities have above-average poverty rates, but few hard data and analyses are available on the nature and extent of poverty in these communities, and on the relative importance of different causes of poverty and on the most effective actions to alleviate poverty (FAO, 2001). The real benefits of fisheries development policies followed by Government and the general trends of economic growth do not seem to have reached the people in the lower strata of the fishing community. In order to evolve policy initiatives for sustainable improvement in the living conditions of the fisherfolk, it is essential to have a clear understanding of the nature and extent of poverty in all its different dimensions and also to find out its causes and consequences.

B. Study Goals           

The overall objective of the study is to understand the economic condition of fisherfolk in the small-scale sector in the context of change in access to and depletion of marine resources.

C. Research Questions

1.      What is the extent of income inequality among the small-scale fishing community? What are the causes of this inequality? Which are the groups in the lower strata?

2.      How poor are the small-scale fishery households and who are the poorer?

3.      What are the characteristics of the poor that distinguish them from the non-poor?

4.      What are the determinants of poverty? Depending on these factors, what is the risk of a household being poor?

E. Analytical Framework

The analysis starts with the perception that the coastal communities use natural resources primarily as an asset for income generation; it follows that increase in income from these resources are one of the principal factors of reducing poverty. It is recognized that environmental resources also provide life-supporting services and confer many intangible aesthetic and cultural benefits (Duraiappah, 2001). But we mainly confine our enquiry to the concept of economic use, i.e. the opportunities to convert resources for the purpose of production, consumption, and exchange.

Income differences between fishermen in the same locality arise mainly due to the differences in fish catch and its price. If prices are treated as ‘given’ catch can be explained on the basis of technology used, input combination, technical efficiency, and last but not the least by pure luck. (In the short-run, in a specific location, resource abundance may be assumed to be constant.) In order to test whether the catch differentials in the small-scale sector are due to the difference in production techniques and variable input use, an input-output relationship (referred as the ‘fishery production function’) may be formulated and applied to a cross-sectional data on a sample of fishery units in the study area. The results would give insight into the ways in which fishing income might be increased.

The next attempt is to understand the well-being of the people in the community. The standard of living is one of the most commonly used indicators of well-being and is represented by household income, from all sources and in all forms (i.e. cash as well as kind). Adjustments are to be made in the gross income for tax payments, receipts of subsidies, etc. to arrive at the disposable income. For comparison across households, age structure, household size etc. are also to be taken into account. Since it is difficult to get reliable data on household income, household consumption expenditure is often used as a proxy variable. While use of income as a measure of standard of living has its own advantage (e.g. extent of contribution of different source of income), consumption expenditure will be a better indicator for the following reasons. In the first place, it can be said that actual consumption is more closely related to a person’s well-being in the sense of having enough to meet current basic needs. Secondly, consumption can be better measured than income, especially in the case of poor households whose incomes keep fluctuating, and include non-monetized items (especially when consumption consists of own production goods also). Thirdly, since consumption expenditure reflects the household’s access to credit markets or savings at times when current income is low or almost nil or fluctuates widely. Whether income or consumption expenditure is chosen, it is necessary to adjust for differences in needs between households. The standard method is to use the per capita income/expenditure by dividing total household income/expenditure by the number of persons in the household. The implicit assumption is that no economies of scale in consumption exist.

Measuring inequality and poverty

Inequality of income can affect economic choice and political decisions. It is therefore desirable to assess the inequality in the levels of living of the households in the study area. The percentage of food items computed from household expenditure data is an indicator of the standard of living; the higher the ratio the poorer the household. Fractiles of income distribution Lorenz ratio, Gini coefficient, and Theil index are more refined indicators of inequality. Once the extent of inequality is assessed, we would like to get an insight into the contributing factors to inequality. If the inequality measure can be decomposed to explain the contribution of different groups with a particular characteristics it will give an insight into the structure of inequality and contributing factors. The Theil Index is amenable to decomposition of overall inequality into (i) a component of inequality between chosen groups and (ii) remaining inequality within groups. The percentage of inequality contributed by the between group inequality to the overall inequality can be considered as an indicator of the amount of inequality explained by the between groups with particular characteristics.

The conventional view is that a society’s welfare is contributed by two factors – income and the extent of inequality in the distribution of income. The notions of poverty and inequality are closely related; for a given mean income, the more unequal the income distribution the larger the percentage of people living in ‘income poverty’. In the case of fisher households the daily earnings are fluctuating and uncertain. There is some evidence that traditional work-sharing and output-sharing systems of fishing communities provide some insurance for these vulnerable groups against destitution and hunger. In spite of these traditional mechanisms there exists some anecdotal evidence that inequality has increased in fishing communities subsequent to motorisation; but little is known whether poverty has increased. In this context the cross-sectional data collected in the study can be used to assess the extent of poverty among the fisher households, and to assess the risk today of being in poverty.

Three ingredients are required in computing the poverty measure. First, relevant dimension and indicator of well-being has to be chosen. Second, is the selection of a poverty line, that is, a threshold below which a given household or individual is to be classified as poor; and finally a poverty measure to be used is to be chosen.

For the indicator of well-being we will continue the use of monthly percapita consumer expenditure (MPCE). For poverty line, we confine ourselves to the use an absolute measure based on the subjective perception of fisher households on poverty translated into a monetary measure. For measuring poverty, it is convenient to use FGT measure, because of its decomposability and simplicity of interpretation. In order to understand who are the poor and what are the differences between the poor and the non-poor, a poverty profile of different socio-economic groups would be developed[1]. The profile could include information on the identity of the poor in addition to their education, activity, etc.

 Determinants of poverty

When the determinants of poverty are identified from the data, their contribution to pushing a household into the poverty group will be assessed using a binary logistic regression model. The probability or risk of being poor in poverty or falling deeper into poverty is a key dimension of well-being. This vulnerability dimension affects individual’s behaviour and their perception of their own situation.

(1) log (p/1-p) = β₀ + β₁ X₁+ β₂ X₂ + ... β_i X_i

where, p is the probability of the responding         variable to the explanatory variables.

Factors influencing household income

Once an assessment of the level and disparity of standard of living is made, and the factors influencing well-being or the absence of it are identified, the next step is to assess how these factors influence the well-being of the households. In the fishing community, income is mainly from fishing and fish-related activities; and production depends on the ownership and utilisation of factors of production and access to natural resources. Non-utilisation or under-utilisation of productive resources or resource depletion affects resource rent.

A fishery household may receive income from non-fishing activities also. Non-fishing income is derived from ownership of or access to assets such as land, building and vehicles, in the form of rent; from financial resources in the form of interest; from employment in the agricultural, industrial or service sectors, in the form of wages/salaries; and from enterprises in form of profits. Income may also be obtained through government’s transfer payments, remittances, social sharing, etc. A suitable model linking household income and explanatory variables will be developed and the parameters will be estimated using the data from the household survey. Since fishery resource in a specified location may be assumed to be constant it can be eliminated from the model.