The study investigated the Effects of Poverty on the Risk Attitudes of Farmers in Benue State, Nigeria. Nigeria has remained one of the poorest countries in the world and Benue State in particular was ranked the eight poorest of the thirty-six states of the Federation. The dominance of the oil sector and the consequent neglect of agricultural sector is one of the major precursors of poverty in Nigeria. Small-scale farmers who operate in an environment characterized by risk and uncertainty produce the bulk of Nigeria’s food andfibre. Presently, the Nigerian agriculture is characterized by low productivity, low level of technological adoption, and use of inefficient production techniques. The present poor state of the Nigerian agriculture is related to farmers1 attitudes towards risks in the production and socioeconomic environment.
Based on the above problems the specific objectives of the study were to: determine the extent of poverty among farmers in Benue State; identify the various risk situations faced and risk aversion strategies employed by farmers with differing poverty levels; assess the risk attitudes of farmers; and determine the effect of poverty and socioeconomic variables on risk attitudes of the farmers.
A multistage random sampling technique was used for selecting the respondents. One hundred and twenty (120) farm households were used for the study. The data were collected during the 200312004 farming season. The data were analyzed using the Foster Greer Thorbercke poverty measures, descriptive statistics, Likert scale, safety-first model and multiple regression analysis.
.Results of the study showed that the households on the average contained about 7.6 persons, with annual per capita income of 4432,491 and had a total land holding of 4.8 hectares. The household head was about 44 years and had spent about 5.5 years in school. Using the international poverty line of US$1 per day per person, the result revealed that 78.3% of the respondents were poor and that the depth of poverty, that is the mean distance of the income of the poor from the poverty line was 42.5% which is approximately 8119,800 below the poverty line (0546,519 per annum). Majority of the respondents lived in thatched mud houses (51.7%), fetched water from unsafe sources such as wells and rivers (96.7%), had no toilet facilities (49.2%), and no access to electricity (85%). The degree of poverty was found to be related to farmers’ socioeconomic characteristics.
The study identified the following types of risk situations faced by farmers: changes in crop yieldllivestock production (16.7%), cropllivestock prices (8.3%), technology (4.2%), cost of inputs (9.2%), credit availability (11.7%), labour scarcitylavailability (9.2%), weather (15%) etc. Analysis showed that risk situations faced by farmers were independent of their poverty levels. The risk management strategies used by the farmers included among others: combination of different cropsllivestock (14.2%), combination of crop and livestock enterprises (8.3%), replanting of crops (7.5%), use of .improved varieties (10.8%), use of pesticideslherbicides (9.2%), spreading of saleslharvest (6.7%), engagement in non farm income activities (10.8%) etc. Result showed that the risk management strategies employed were independent of farmers’ poverty levels.
The result of the assessment of farmers’ attitudestoward price risk showed that 86.7% were risk averse, 11.7% were risk seeking and 1.7% were risk neutral using scale 1 classification, whereas all farmers were classified as risk averse under scale 2. Using the safety first model to assess respondents attitude towards yield risk, it was found that 71.7% were high risk averse, 25.8% were intermediate risk averse, 1.7% were low risk averse and only 0.8% was risk preferring. Regression analysis showed that age, household size, educational level, extension contact, membership in a solidarity group and degrees of poverty were significant determinants of risk attitudes.
.Based on the findings of the study there is need to consider socio-economic and poverty variables of farmers when designing new farm technologies and other agricultural policies in Benue state. Policies to improve the literacy level of the people, and access to agricultural inputs were recommended. Also the use of social protection practices such as income insurance, price-support schemes, credit insurance, etc, which may be helpful strategies in mitigating the effects of poverty on risk attitudes of farmers were recommended.
1.I Background Information
Nigeria, though endowed with abundant human, capital and natural resources and in spite of her oil revenue has remained one of the poorest countries in the world. Various national and international bodies have documented this high incidence of poverty. The Federal Offce of Statistics (FOS, 1999) and the United Nations Development Programmes (UNDP, 1998) asserted that despite a remarkable decrease in poverty in the 1980s’the dramatic increase in the 1990s was discouraging.
Over two decades ago, the country enjoyed relative prosperity but progressively saw 40% of the population slide into poverty (Adegbite and Akintola, 2002). The proportion of Nigeria’s population in abject poverty gradually increased from 40% to 70.2% between 1992 and 2002. As at the end of 1997, nearly 49% of the population were living in poverty. FOS (1999) reports that prior to the end of 1997, Nigeria’s poverty level was 65.6% and she was ranked among the twenty-five poorest countries of the world (table 1. I)
The Human Poverty Index (HPI) was 41.6% implying that one out of every two Nigerians was poor. Life expectancy has gradually declined to a little above 50 years (FOS, 1999); whereas UNDP (1998) put it at 52 years. The percentage of adult literates was 55% and only 49% had access to portable water and health services. The Gini coefficient of poverty increased from 0.38 to 0.43 within the same period and became worse at 0.52 by the end of the 1990s (UNDP, 1999).
As at December, 1999, 54% of the world’s population were considered to be poor by the United Nations, on the basis of each country’s score on an index of human income and human suffering. The percentage is far higher in some countries such as Sri Lanka, Burma where 90% of the people are below poverty line, and Nigeria where about 67.1 million of the people are below poverty line. It was estimated that only 50% of Nigerians have access to safe water; 50% have never attended any school at all; demand for food increases by about 3% annually while the annual growth rate of food production was
between 1-1.5% (Olaitan et al, 2000). Moreover, UNDP (2004) noted that the Human Development Index (HDI), a composite measure of income and access to education and health services, ranked Nigeria 152″ out of 175 countries in 2000. This low HDI reflects the situation with regard to poor access to basic social services in the country. Further the reports indicate that in 2001 over 70% of the population lived below the international income poverty line of $1 per day. Specifically in Benue State, FOS (2001) report showed that the household economic situation worsened by 27.6% compared to the previous year, access to safe water was 25.6%, adult literacy was 58%, 59.9% had access to primary school, 35.7% had access to secondary school and 32% had access to health services.
Agriculture plays a vital role in the economic development of Nigerian economy. It employs about 70 percent of the labour force and contributes about 41% to the GRP (World Bank, 2004). In Nigeria, over 80 percent of the agricultural population are smallholder farmers with fragmented farm holdings. The smallholder farmers are poor and dwell in the rural areas and are characterized by low income, large family size, lack of formal education, low savings and investment, lack of access to credit facilities and use crude farm production technologies (Olayide et al 1980).
A fundamental problem for all decision makers is the absence of complete information about the decision environment. If all possible actions, events and conditional outcomes could be predicted with complete certainty, then decision-making would be the simple mechanical exercise of calculating the optimal action according to some predetermined criteria. In practice, of course, the decision environment is characterized by uncertainty or the absence of perfect and complete information. Actions are undertaken in anticipation of future benefits that may not be realized. Thus all decisions contain some element of risk because of the unpredictability of outcomes, which imposes an opportunity cost on the decision-making (Hill, 1989). Furthermore, risk arises because uncertainty impacts directly on the decision process through the decision-maker’s attitude towards risk. Theprudent or cautious manager may well choose different actions from the decision-maker who has confidence (or resources) to take greater risk (Hill, 1989).
Over their lifetime, all men and women are subject to a wide variety of risks. Some of these risks affect their well being in the most direct manner: illness, accident, and death. Others affect their ability to support and feed themselves, either temporarily – unemployment, crop failure, loss of property – or permanently – disability, business failure, skill obsolescence (Fafchamps, 1999). According to Adegeye and Dittoh (1985), most agricultural decisions are taken in the environment of risks and uncertainty. Farmers will have to make decisions now, which will affect their production later. The farmers are not sure of weather, government policies, and new changes in technology – factors which make it difficult for them to predict the future with certainty.