MSc

ABSTRACT
Risk is inevitable in agriculture as the farmers have very limited control over
the production and marketing process. The uncertainties in weather, yield, prices, and
government policies cause wide variations in farm income. Agrarian crises were
prevalent in Wayanad district due to fall in prices of commodities, indebtedness, flood,
drought, and instabilities in income. The present study estimated the agricultural risks
in Wayanad district, identified the sources of risks and risk preferences of farmers, and
assessed the types and determinants of coping mechanisms in the farm households of
Wayanad. The study was based on both primary and secondary data. The primary data
was collected from 100 respondents across four blocks in the district selected by the
proportionate random sampling method, using a pretested interview schedule.
There has been an increase in the Compound Annual Growth Rate (CAGR) of
area and production of coffee, arecanut, rubber and coconut from 1981-82 to 2018-19.
The decomposition analysis of production of crops showed positive effects of area in
coffee, arecanut, coconut and black pepper. The productivity effect was found to be
positive for coffee, rubber, coconut and paddy during the same period. Growth
accounting analysis showed positive influence of prices on the growth in revenue from
arecanut, rubber, coconut and black pepper.
The analysis of trend breaks in area and production of crops carried out using
Chow test showed significant trend break in area for coffee, arecanut, rubber, coconut,
black pepper and paddy. Except for coconut and paddy, a significant trend break was
also observed in the production of other crops. The estimation of climatic risks using
Just and Pope production and risk functions showed that standard deviation in
temperature and standard deviation in rainfall negatively influenced the production of
coffee and black pepper respectively. The mean annual temperature was found to
increase the production of coconut, while decrease the production of rubber. None of
the climatic factors were found to influence significantly the variability in yield of any
of the crops. The analysis of price instability using Cuddy-Della Valle index showed
highest instability in prices for black pepper, followed by coconut, arecanut and rubber.
The analysis of instability in income from the primary sector of Wayanad for
the period from 1982-83 to 2018-19 using chain index and link relatives showed high
income fluctuations. Compared to 1982-83, the income grew by 630 per cent in 2004-
05, which then decreased to 276 per cent in 2018-19. The district was found to have
very high levels of crop diversification (Herfindahl index < 0.33) during all the years
from 1981-82 to 2018-19.
The production risks in Wayanad were identified using primary data by
employing Just and Pope production and risk functions. Along with area, the other
factors accounting for significant variability in production were identified as cost of
human and machine labour for coffee, cost of machine labour and fertilizers for black
pepper, and cost of human labour for coconut. Crop loss was found to be the highest in
black pepper, both in terms of quantity (50 per cent) and number of respondents facing
the loss (43 per cent). Using Garret ranking technique, low price and price fluctuation
of products was identified as the major risk, followed by climate change and natural
calamity, and shortage of labourers. The major risk coping strategies adopted by the
respondents were identified as storage of produce, irrigation, employing family labour,
and chemical control of pests and diseases. Other risk coping strategies were
subscription of crop insurance, crop diversification (63 per cent respondents having
Herfindahl index less than 0.5), income diversification, availing credit, and sale of
assets. It was also found that 72 per cent of the respondents were beneficiaries of PMKISAN
programme implemented by Government of India.
The risk appetites of respondents were elicited using risk question and risk
game. When majority of the respondents (52 per cent) assessed themselves to be
moderately risk taking, risk game showed majority of them (35 per cent) to be
extremely risk averse. The significant factors influencing the risk appetite of
respondents were analysed using different regression models. Multiple regression
showed factors like experience in farming, education, land holding size, and net revenue
from agriculture to be significantly influencing the risk appetite. Logistic regression
identified factors like land holding size, net revenue from agriculture, and non-farm
income to be significantly influencing the classification of respondents as risk averse
or risk takers.