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Conditions of Farmers in West Bengal

This paper is a part of the Indian Council of Social Science Research (ICSSR) Project, and the author is thankful to ICSSR, New Delhi for providing him with financial assistance to conduct this research work. The author is also thankful to Sridev Adak and Animesh Kundu, former research assistants, ICSSR Research Project for helping him in data collection, data entry, and tabulation works.

The income and poverty conditions of farmers’ households in four sample districts of West Bengal are brought out. The main crops grown in the study areas are paddy, wheat, jute, pulses, potato, and vegetables. Farmers mostly suffered from losses in cultivating these crops, except for fruits and vegetables. Their main source of income is received from wages and salaries, which constituted 45.76% of their total income. In the study area, around 70% of the incomes of farmers’ households come from non-farm sources and this reflects the picture of a relative collapse of agriculture as the primary source of rural livelihood. Farm sector becomes increasingly non-viable as income earned from the farm sector is not sufficient to meet farmers’ daily requirement. As per the poverty estimation based on the Rangarajan Expert Committee report, about 35% of the farmers’ households may be regarded as poor in the study areas of West Bengal.

Farmers’ conditions in West Bengal are very deplorable. Their source of income is highly volatile because they are facing double risks, that is, production and marketing risks. Further, from the early 1990s, neo-liberal policies entailed the reduction of public investments in agriculture, withdrawal of subsidies, weakening of institutional support, including institutional credit and extension, and the lowering of tariff protection on agricultural trade (Mahendradev 2000; Rao 2003; Ramachandran 2011). This leads to increasing dependency of farmers on moneylenders for credit, traders for sale of their crop output and agricultural input dealers for crop advice, etc. Thus, the middlepersons, traders, input sellers, etc, have an increased scope to exploit them, while they are deprived of getting fair returns from the selling of output. About 90% of farmers in West Bengal are small and marginal farmers. High population pressure on land leads to subdivisions and fragmentation of landholdings, making it difficult for them to meet ends. Moreover, increase in the price of agricultural inputs, uncertain price of perishable agricultural produce, inadequate market infrastructure, and distress sale of produce by small and marginal farmers are additional problems that pose serious challenges to sustainability of the farm sector in the state (Goswami et al 2014). The socio-economic condition of the farming community is declining in the absence of appropriate technical, social, financial, and market interventions (NABCONS 2009; Goswami et al 2014). Now the income of a farmer increases at a lower rate as compared to the income earned by an agricultural labour and a non-agricultural worker (Chand et al 2015).

The objective of the study is to bring out the conditions of income and poverty of farmers’ households in West Bengal. The average rate of return or profitability per hectare has also been calculated by deducting the cost of cultivation per hectare from the value of farm product per hectare of farmers.

This paper is based on the primary data collected from four sample districts (Burdwan, Purulia, Uttar Dinajpur, and Jalpaiguri) of West Bengal along with the existing literature. West Bengal is divided into two parts—North and South Bengal. From North Bengal, one agriculturally developed district (Uttar Dinajpur) and one agriculturally less developed district (Jalpaiguri) have been selected. Similarly, from South Bengal, one agriculturally developed district (Burdwan) and other agriculturally less developed district (Purulia) have been selected for the purpose of this study. To measure the agricultural development of districts, three indicators have been used: (i) foodgrains productivity per hectare; (ii) cropping intensity; and (iii) the share of rural agricultural workers to total rural workers. The composite index for each district has been prepared using these indicators. Subsequently, two blocks (one, agriculturally developed and the other, agriculturally backward) have been selected from each district by preparing a composite index. Two villages have been selected from each sample district for this study. The total sample size is of 240 farmers’ households and selected 30 farmers’ households from each sample village. Data have been collected on agricultural production, cost, prices, sources of income, consumption expenditure, etc, of farmers’ households during 2017–18 from eight sample villages of West Bengal.

Farmers’ Conditions—Farmers’ Income

Farmers’ conditions depend upon the income of farmers that comes from different sources. However, the appropriate estimates of farmers’ income are not available in our country. Some individual researchers have tried to estimate the farmers’ income on the basis of the National Sample Survey Office (NSSO) and Central Statistical Office data. Narayanamoorthy (2006) estimated the farmers’ income on the basis of the Situational Assessment of Survey (2005) of the NSSO and got a very gloomy picture of the farmers’ income. Chand et al (2015) estimated derived farm income during 1983–84 to 2011–12 from the gross domestic product (GDP) (agriculture and allied) using the following approach: farm income = GDP in agriculture and allied sectors, less capital consumption, less wage for hired labour employed in bill agriculture or derived farm income from net domestic product agriculture and allied sectors less wage bill for hired labour. They assumed that, as producers, farmers get wholesale prices and as consumers, they pay retail or consumer prices. This assumption exaggerated the farm income. They argued that the farm income per cultivator deflated by the consumer price index for agricultural labourers (base year 2004–05) rose 2.7 times, from `16,103 to `42,781 during 1983–84 to 2011–12. However, farmers are not wholesalers and the price received by them is far lower than the wholesale prices. Most of the farmers are small and marginal and their marketable surplus is also small. They generally have to
accept prices offered by the middlepersons. According to Narayanmoorthy (2017),

the wholesale cost of inputs at macro level used in the estimate would be much lower than the retail price of inputs. For instance, the retail price of fertilisers sold in the district headquarter is lower than the price of fertilisers prevailing in the retail shop located at a village or block. The managerial cost (the Commission for Agricultural Cost and Prices [CACP] considers 10 percent of C2 as managerial cost) is another big cost which may not have been included in the macro level cost used by Chand et al (2015). If these costs are included in the estimate, then there is a possibility that the farm income estimated by them would exhibit a declining trend.

Narayanamoorthy (2013) made an attempt to find the trends in profitability of different crops over a period. He utilises data from the cost of cultivation survey of six important crops from 1975–76 to 2006–07. He argued that farmers have suffered substantial losses by cultivating different crops for the analysis. In cases where profit was earned, it was less than 30% of the cost of cultivation. It is found that farmers suffer losses both due to increased cost of cultivation in some crops and reduction in the value of output in other crops. Continued suffering of losses or earning only a low margin of profit from crop cultivation will definitely discourage farmers from engaging in agriculture (Narayanamoorthy 2013).

Here an attempt is made to estimate the farm income using field-level data collected from selected sample districts of West Bengal. First, to estimate the farm’s income, the return or profitability per hectare over the cost of production of different crops is estimated across four sample districts as shown in Table 2 (p 61). It is done by taking the concept from the Government of India (2007 and others).

Cost A1 = All actual expenses in cash and kind incurred by owner

Cost A2 = Cost A1 + rent paid for leased-in land

Cost B1 = Cost A1 + interest on value of owned capital assets (excluding land)

Cost B2 = Cost B1 + rental value of owned land (net of land revenue) functions performed by farmers

Cost C1 = Cost B1 + imputed value of family labour

Cost C2 = Cost B2 + imputed value of family labour

Cost C*2 = Cost C2 estimated by taking into account statutory minimum or actual wage, whichever is higher

Cost C3 = Cost C*2 + 10% of Cost C*2 on account for managerial input of farmer

The return or profitability per hectare of different crops = value of total product (main + by-product) – C2

The major crops studied are paddy, wheat, jutes, pulses, maize, potato, and vegetables. Paddy is an important foodgrain crop, predominantly cultivated in the districts under study. Burdwan district is known as the “rice bowl” of West Bengal. The area under paddy accounts for 69% of the total gross cropped areas of Burdwan (Table 1). It was expected that farmers would earn high profits from the paddy cultivation. But, field-level analysis brings out a dismal picture. Paddy farmers of the two agriculturally developed districts (Burdwan and Uttar Dinajpur) were able to earn moderate profits. However, those of the other two agriculturally less developed districts (Purulia and Jalpaiguri) suffered losses (Table 2) as farmers were unable to recover the cost of cultivation from the value of output of paddy. The per hectare loss of paddy cultivation in Purulia district was `4,133.84; it was `1,882.77 for Jalpaiguri district. Paddy is generally cultivated in irrigated land, but Purulia is a drought-prone district. This leads to high cost of production and low productivity of paddy. Farm income, especially from paddy crops, is found to be very low or negative in all those states (for example, West Bengal and Odisha) where procurement level is pathetically low. Procurement arrangements are also very poor for non-foodgrain crops, such as oilseeds and pulses, which is clearly evident from the statistical analysis system data as well. This has allowed private market agents to scrupulously exploit the farmers and the consumers (Narayanamoorthy 2017).

In West Bengal, the cropping pattern is dominated by paddy. The sale of paddy by farmers in West Bengal is largely confined to rice mills controlled by local monopolies (of ex-landlords), which are protected and supported by cheap credit by the state government, and that have achieved higher profit margins through exploiting poor peasants who are tied to them in credit relations. (Harriss–White 2008; Kannan 2015)

Wheat is the second most important foodgrain crop that accounted for about 7% of the total gross cropped areas of the sample districts (Table 1). It is cultivated only in three sample districts—Uttar Dinajpur, Burdwan, and Jalpaiguri. However, wheat farmers have incurred huge losses due to crop loss caused by disease and crop depredation by elephants in the Jalpaiguri district. To avoid disaster due to diseases, as a preventive control, the Indian Council of Agricultural Research (ICAR) has implemented a temporary “wheat holiday” for nine districts (Darjeeling, Jalpaiguri, North 24 Parganas, Cooch Behar, Uttar Dinajpur, Dakshin Dinajpur, Maldah, Murshidabad, and Nadia) of West Bengal for three years. These districts share borders with Bangladesh. The ICAR has suggested legumes and oilseeds in place of wheat (Mottaleb 2019). Maize is another foodgrain crop cultivated only in Uttar Dinajpur and Jalpaiguri districts. However, maize farmers of only Uttar Dinajpur were able to make profit. Those of Jalpaiguri suffered from losses due to crop depredation by elephants. Frequently, herds of elephants enter human settlements and crop fields to eat wheat and maize, damaging the crops and attacking the people, as reported by farmers. Thus, we see human–wildlife conflicts happening in this district. Pulses were cultivated predominately in three sample districts: Burdwan, Purulia, and Jalpaiguri. Together it accounted for less than 1% of the total gross areas of the sample districts. However, pulse farmers of sample three districts have incurred huge losses due to low productivity.

Potato is an important non-foodgrain and a commercial crop predominately cultivated in all four sample districts. Together it accounted for 10% of the total gross cropped area of the sample districts. Potato farmers of only Burdwan district were able to earn profits, while those of the other three sample districts have incurred huge losses due to the low harvesting prices of potato. Generally, the potato farmers kept the potatoes in cold storage after harvesting to get better prices. Even after keeping potatoes in cold storage for three months during the survey (2017–18), the market prices did not increase.
Instead they remained so low that it could not even cover the rent of cold storage, as reported by the farmers. The low prices of potatoes will deepen the agrarian crisis. The cultivation of potatoes is highly cost-intensive and farmers make huge investments for the cultivation by taking loans from private moneylenders and others at a high rate of interest. In 2017–18, most of the potato farmers were not able to repay their loans due to the low prices of potatoes. The sharp fall in prices of crops like potato and the failure of crops like wheat and paddy created the situation of shock, vulnerability, and agrarian crisis in the study areas. It was only in the cultivation of fruits and vegetables that farmers earned positive profits in all the sample districts (Burdwan, Purulia, and Jalpaiguri districts). The fall in crop profitability is worrisome and causes distress among farmers. It is likely to have contributed to farmers’ suicides (Reddy and Mishra 2009; Deshpande and Arora 2010).

In West Bengal, the main reasons for low returns from agriculture are defective marketing system, low prices of agricultural products, fluctuation of prices of agricultural products, and crop loss due to disease/crop depredation by elephants/flood/heavy rains. To make the farming operations remunerative for high-value crops (HVCs), particularly fruits, vegetables, and other cash crops, it is essential to have an efficient agricultural marketing system that is missing in West Bengal. Most of the agricultural markets, including wholesale markets, did not have adequate infrastructure with no particular system of price fixation. Farmers accept the prices offered by middlepersons. The whole marketing system is operating under a vicious cycle of large numbers of small producers producing low marketable surplus resulting in low bargaining power and low profit (Mandal 2015). “The nature of capitalist development of agriculture and accumulation of agro-commercial capital in West Bengal is not so beneficial for agricultural growth as compared to that of the capitalist development witnessed in Punjab” (Lerche 2011; Kannan 2015). This is due to the marginalisation and fragmentation of landholding along with the underdeveloped market structure.

Sources of Income

Farm sector becomes increasingly non-viable as income earned through it is not sufficient to meet the daily requirements. Farmers mostly suffered losses due to low prices of agricultural products and high cost of production. The insufficient income earned from the farm sector compelled them to diversify their income sources to non-farm sectors. Table 3 and Figure 1 show the average monthly income per farm household from different sources. From these it is clear that the average monthly income per farmer household from all sources is `8,270.27. Out of this, the average monthly income per household from the farms is `2,486.85. This constitutes only 30.07% of the total income of the farmer’s households. Their main source of income is the income received from wages and salaries, which constituted 45.76% of their total income.

But, the average monthly income per farmer household varies across sample districts. On the basis of the share of income from the farm sector, three types of farming systems are found in the study areas. Foodgrain-based farming system (more than 50% of the share of farm income comes from foodgrain cultivation) is found in Uttar Dinajpur and Burdwan districts; non-foodgrain, especially vegetable-based farming system, is found in Jalpaiguri district; and livestock-based farming system is found in Purulia district. The incomes earned by farmers’ households depend upon the farming system followed by them. Horticulture crops like fruits and vegetable farming ensure higher returns compared to food crop-based farming. Mithiya et al (2018) argue that diversification towards horticulture crops would generate considerable income and employment opportunities for farmers, particularly smallholders in West Bengal. The highest income (average monthly income per farmer’s household) was earned by farmers’ households of Jalpaiguri district (`12,476.17). It is an agriculturally less developed district but practices vegetable-based farming. Jalpaiguri is followed by Burdwan district (`7,892 per month), which is agriculturally developed. Purulia district (`6,576.66 per month), an agriculturally less developed district, came next. The lowest income was earned by farmers’ households of Uttar Dinajpur district (`6,136.25 per month). It is an agriculturally developed district but follows foodgrain-based farming. In the case of Jalpaiguri, farmers diversified through the cultivation of HVCs like vegetable crops, which ensured higher and positive returns. The gross cropped areas for vegetable crops in this district constituted around 34% of the total gross cropped area. The cultivation of vegetable crops are highly labour-intensive as compared to other crops. The farmers with large average family size enjoy the comparative advantage of cultivating vegetable crops in this district. State-level awards were acquired by some of the farmers as recognition for successfully producing HVCs, that is, vegetables. The share of net income receipt from farming constituted 37.50% of the total income, the second highest source of income after net income receipt from wages and salaries (39.12%) of farmers’ households of this district.

In the agriculturally developed district of Burdwan, farmers diversified in the cultivation of vegetable crops, especially potato cultivation that accounted for around 23% of the gross cropped areas of the sample farmers’ households. This district recorded the second highest average monthly income per farmer household, and the share of income from farms constituted 25.41% of the total income. However, the low potato prices bring down the average monthly income from farms as well as the average total income of the farmers’ households of this district. The income from wages and salaries (that constituted around 51.42% of the total income) is the major source of income of farmers’ households in this district. Farmers of Purulia district, agriculturally less developed in a rain-fed district, diversified in livestock farming, which emerged as an important source of income. The average monthly income per farmer household is very low in this district, and the share of farm income to the total income is only 16.46%. The major share of income comes from wages and salaries that constituted 63.52% of the total income. Farmers of Uttar Dinajpur district mainly concentrated on the production of foodgrains like paddy, wheat, and maize. It constituted 95% of the total gross cropped area (Table 1). Their major source of income is the income from farms that constitutes around 35% of the total income. From the above, it is clear that diversification to horticulture, especially of vegetable crops, helps in increasing the income levels of farmers’ households. But, this diversification is limited by the level of market prices. Though farmers of Burdwan diversify their crop production to include vegetable crops, especially potato cultivation, their share of income from the farm sector is low because of the low market prices of potatoes.

The average monthly income of farmers’ households also depends upon the farm sizes. As farm sizes increase, the average monthly income of farmers’ households also increases as shown in Table 5. Thus, farmers’ income is positively correlated to the land size. Farmers’ households with more land specialised in cultivation and were less dependent on non-farm sources. But for farmers’ households with less land, the major source of income is from non-farm sources/off farm sources. Table 5 shows that marginal farmers received about 86% of their income from non-farm sources, and medium farmers received about 63% of their income from non-farm sources. The question that then arises is whether a higher percentage of diversification to non-farm sources leads to higher levels of income too? From Table 4, it is clear that marginal farmers (below 1 hectare) constitute 77.08% of the total farmers’ households in all four sample districts. The average monthly income of medium farmers’ households comprising around 3% of the total farmers’ households is `34,985.83. This is four times more than that of marginal farmers’ households, three times more than that of small farmers’ households, and nearly double of semi-medium farmer’s households. Thus, we can conclude that specialisation ensures higher levels of income for farmers’ households. The type of livelihood activities that individuals and households are engaged in is an important determinant of their income than diversity of those activities (Anderson and Deshingkar 2005).

Rural Livelihood Diversification

According to Ellis (2005), rural livelihood diversification describes the phenomenon by which small farm households take up non-farm activities or rely on non-farm income transfers for the overall standard of living they are able to achieve. The extent of such diversification away from agriculture is an indicator of the degree to which farming operations on their own can provide a secure and improving livelihood (Ellis 2005). In the study area, around 70% of the incomes of farmers’ households come from non-farm sources. This reflects on the relative collapse of agriculture as the primary source of rural livelihood. The diversity of income sources has also happened across farm sizes, but the nature of diversification varies across farm sizes. The semi-medium and medium farm households diversify their income sources in the form of non-farm business activities (trade, transport, and shopkeeping) and salaried employment, while marginal farmers diversify in the form of casual work. In the case of marginal farmers’ households, the share of non-farm sources constitutes around 78%. The average monthly per capita income of marginal farmers’ households is lowest at `7,256.79. Here, the higher percentage of diversification to non-farm sources leads to lower levels of income. This indicates the distress diversification of marginal farmers’ households to non-farm sources.

But in the Livelihoods and Diversification Directions Explored by Research (LADDER) project, the positive correlation between per capita household income and share of income obtained from non-farm sources was strongly affirmed. For example, in Tanzania, the relative dependence on agriculture declines across the income ranges from 68% for the poorest quartile to 43% for the richest quartile. (Ellis 2005)

The dependence on agriculture declines with the increase in income levels, and farmers tend to diversify their income sources to non-farm activities. Thus, the higher percentage of diversification to non-farm sources leads to higher levels of income in Sub-Saharan Africa (SSA) countries under the LADDER project. This is a paradoxical finding of diversification with respect to the study areas.

Poverty among Farmers’ Households

In order to examine the poverty levels among farmers’ households, sample farmers’ households have been classified by taking concepts from the Rangarajan Expert Committee report (Planning Commission, Government of India 2014) as extremely poor, poor, marginal, vulnerable, middle income, and high income on the basis of daily per capita consumption expenditure. The sample farmers’ households who have been classified as extremely poor had an average daily per capita consumption expenditure (DPCE) of about `23; the poor had a DPCE of about `23–`31; the marginal household had a DPCE of `31–`39; and the vulnerable household had a DPCE of `39–`47. The middle-income group is identified as people with an average DPCE of `47–`93 and the high-income group as those with an average DPCE of `93 and above. From Table 6, it is clear that 15.83% of farmers’ households fall into the category of extremely poor and 20% of farmers’ households fall into the category of poor. In the study areas, about 35% of farmers’ households may be regarded as poor as per the poverty estimation based on the Rangarajan Expert Committee report. However, it varies across sample districts. Agriculturally less developed districts like Purulia recorded the highest percentage of poverty level (extremely poor and poor = 71.66%) and the lowest (18.33%) in Burdwan, which is an agriculturally developed district. Thus, better agricultural performance of a district leads to lower levels of poverty. There have been many studies that explain the direct linkage between agricultural growth and poverty (World Development Report 2008; Gulati and Roy 2021).

There are many ways agricultural growth can lead to the betterment of a country’s population. First, improved agriculture can directly result in increased farm income. Second, the availability of cheaper food will have a positive effect on nutrition. Third, agriculture creates an opportunity for the non-farm sector as well. (World Development Report 2008; Gulati and Roy 2021)

Agricultural performance, non-farm employment, literacy rate, and infrastructure have a significant negative relation with poverty (Gulati and Roy 2021). In Jalpaiguri, an agriculturally less developed district, the incidence of poverty is low (extremely poor and poor = 25%) among farmers’ households, which cultivated HVCs, that is, vegetables crops. Birthal et al (2015) also found lower incidences of poverty among those households that grow HVCs (Birthal et al 2017).


The farmers’ conditions depend upon their income from different sources. Despite agriculture being their primary source of income, wages and salaries were seen as the main source of income in the study areas. This indicates the de-peseantisation or de-agrarianisation of agriculture in West Bengal. The main crops grown in the study areas are paddy, wheat, jute, pulses, potato, and vegetables. However, farmers mostly suffered losses while cultivating these crops, except for the cultivation of fruits and vegetables. The poor return over the cost of production is one of the important reasons for the agrarian crisis in West Bengal. Farm sector becomes increasingly non-viable as income earned from this sector is not sufficient to meet farmers’ daily requirements.

The average monthly income per farmer household from all sources is `8,270.27, out of which the average monthly income per household from farms is `2,486.85, which constitutes only 30.07% of the total income of the farmers’ households in the study areas of West Bengal. Farmers increasingly diversified their income sources to meet their basic needs. About 35% of the farmers’ households can be regarded as poor as per the poverty estimation based on the Rangarajan Expert Committee report. Thus, a large number of farmers’ households live below the poverty line. There is a need to ensure living income to farmers’ households so that they can live comfortably.

The “living income” is defined as sufficient income to afford decent standard of living for all household members, including nutritious diet, clean water, decent housing, education, healthcare and other essential needs, plus extra for emergencies and savings, after farm costs are covered (Fair Trade 2019; Living Income Community of Practice 2019). The income of the farmers can be increased adequately if procurement arrangements and other non-price (technology, credit and irrigation) incentives are packaged and sequenced appropriately along with revision of the minimum support price in consonance with the cost of cultivation (Narayanamoorthy 2017).


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Updated On : 4th Jun, 2022
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