SMALL SCALE FARMERS’ WILLINGNESS TO TAKE AGRICULTURAL INSURANCE IN PAIKORO LOCAL GOVERNMENT AREA OF NIGER STATE Nmadu, J.N. (
[email protected]) and J. Peter (
[email protected]) Dept. of Agric. Economics and Extension Tech., Federal University of Tech., Minna, Nigeria ABSTRACT This study examined the attitude and constraints of small scale farmers in Paikoro Local Government Area towards agricultural insurance-taking in the past and their willingness in the future. The data collected from 75 farmers, were analysed using descriptive statistics and chi-square. The findings indicate that about 65% of the respondents had more than 5 years of farming experience, a good development but which has made the respondents to abandon education at secondary level. It was also found that most of the farmers (84%) did not insure their farms with NAIC voluntarily. About 60% of the farmers claim ignorance as the constraints to insurance-taking, a situation which was likely attributable to the low level of education of the respondents. It was also found that the extent of awareness is a very important factor to successful insurance-taking. It is recommended that stakeholder sessions on confidence building on agricultural insurance as well as sensitizing the respondents of the benefits of well-educated farming population be undertaken. It is also recommended that farmers should be merged to 20-30ha for economy of scale. There is also need to establish a continuing education system to assist in transformation from traditional to commercial level, making insurance-taking imperative. KEYWORDS Insurance-taking, economy of scale, continuing education system, decision-maker, commercialisation INTRODUCTION Annual agricultural production is subjected to large variations due to risk and uncertain factors completely beyond the farmer’s control. This is the reason why the management of farm enterprise is much more complex than the management of industries. These factors complicate management decisions in agricultural production and affect farmer’s decision in production and marketing (Hardaker et al 1997). Some of the key factors accounting for these variations in Nigerian agriculture are such hazards like vagaries of nature, inclement weather conditions and the effect of natural hazards like flood, erosion, drought, pests and diseases outbreak, fire outbreak, windstorm (Kiari, 2003, Aminu, 2001); hampering past efforts to promote food production and encourage small scale farmers to commercialise their production processes. According to Heintz (2010) the shift from traditional to modern farming could only be done with specialisation and investment in technology. And this will definitely lead to accumulation of capital, necessitating the need for transfer of production risks to the insurance company. These eventualities impact very seriously on failure of agricultural enterprises and tend to keep farmers away from the business since there is no protection of capital against these risky and uncertain situations. It is the realisation of these negative impacts on Nigeria Agriculture that the Federal Government launched the Nigerian Agricultural Insurance Scheme (NAIS) and established a company to drive the Scheme i.e. Nigerian Agricultural Insurance Corporation (NAIC) on the 15th December, 1987. The Scheme has been in operation for over 25 years now and no
appreciable progress towards commercialisation of Nigerian agriculture has been achieved, rather the food situation in Nigeria suggests a decline in agricultural production. Farmers in Niger State are basically subsistence in nature with the objectives of providing food for their family and little for sale. A survey of the farmers in the state by Ministry of Agriculture showed that 80% of farmers are small, 13% are medium farm holder and 7% are large scale farm holders. Kiari (2003) reported that 73% of farmers from Bosso, Chanchaga and Lapai Local Government Areas of Niger State are aware of the insurance scheme but that only 30.1% who are aware of the scheme accepted it. He also indicated that 54.6% were forced to take the insurance cover while 45.4% voluntarily took insurance cover. In addition, 19.6% of the farmers refused to take insurance cover because they were not indemnified when they had claims previously and 58.8% could not afford the policy. Lajidu (1987) observed that an average Nigerian with some degree of justification sees the scheme as a one way traffic that led to the booming of the bank account of the agencies. It is a general belief that NAIC for example like any other conventional insurance companies is interested in collecting premium but reluctant at settling claims in an event of loss. Ndanitsa (1995) and Erima (2005) stressed that available evidence suggests that negative attitude which exists towards the scheme is caused by the official of agencies which are expected to assist in the implementation of the scheme consequently impeding the performance of the
NAAE 2010 scheme and that of the target beneficiaries. Ajayi (1990) revealed that there is lack of enthusiasm on the part of the consumers to learn much about the insurance business. He pointed out that many of those who manage to adopt the policy do not seek clarifications and therefore sometimes end up with false expections. They do end up with wrong ideas of false security which consequently leading to controversy and confusion. According to Ikpelue (1995) Ndanitsa (1995) the premium remitted to NAIC was only been used to offset staff salaries. However, NAIC (2005) claimed that with more awareness coming into the system, the level of adoption of the scheme is increasing year in year out. The evidence of this was because of the increasing number of branches opened across Nigeria by the corporation. For example, in year 2000, the number of farmers insured was 636 and the premium generated was N2.9million. In 2005, 2,503 farmers were insured and N5.3 million was generated. This, according to NAIC, implies that the level of the adoption of the scheme rose from 16.1% in 2000 to 20.7% in 2003 and 63.2% in 2005. The goal of this present study is to find out the level of readiness of the farmers in Paikoro Local Government Area in Niger State to accept agricultural insurance cover. The specific objectives of the study are to: i. examine the extent of farmers awareness of agricultural insurance-taking; ii. examine the past attitude of farmers towards insurance taking; iii. determine the willingness of farmers to accept insurance for agriculture in future; and iv. examine the factors/constraints that may discourage farmers’ confidence in taking agricultural insurance.
include Nupe, Hausa, Fulani, Igbo, Yoruba, Tiv, Igala. The climate, soil nature and hydrology permits the cultivation of most of Nigerians staple crops and still leaves ample areas for grazing, fresh water fisheries and forestry. Farming is the major occupation of the inhabitants of Paikoro L.G.A, as about 85% of the active labour force is engaged in agricultural production, while the remaining 15% are engaged in other vocations such as white collar jobs, businesses, arts and crafts. Similarly, there are natural resources such as gold, marble, dolomite, granite, limestone, potash, clay, and iron ore (Paikoro LGA, 2010) In order to obtain the sample for the study, three districts were randomly chosen and in each district three villages were randomly selected. The villages selected were Tungan-Mallam, Danduru, Paiko, Baida, Kwakuti, Chimbi, Muye, Kafin-Koro, Kurchi, Adunu, Tungan-Barau, Tungan-Garba, Dakolo Amale. Finally five farmers were randomly selected from each of the villages for the survey marking a sample size of 75 respondents. The survey was carried out between March and August, 2009. The primary data was collected using structured questionnaire directly from the respondents. Supporting secondary data were collected from Nigeria Agricultural Insurance Corporation (NAIC) Minna Zonal Office and Nigerian Agricultural Cooperative and Rural Development Bank (NACRDB) in Minna. The data collected from farmers include demographic factors, knowledge on insurance taking, willingness to take insurance in future and constraints of farmers in taking agricultural insurance in the study area. The data were analysed using descriptive statistics (Tables, frequencies, percentages) and inferential statistics (chi-square).
METHODOLOGY This research, carried out in Paikoro Local Government Area of Niger State, Nigeria which has five districts namely: Paiko, Kaffin Koro, Kwakuti, Adunu and Ishau. Paiko. The Headquarters of the Local Government is located at Paiko, about 22 km South of Minna, the Niger State capital. It is bordered by Chanchaga, Munya, Gurara, Agaie, and Lapai Local Government Areas of Niger State and Kachia Local Government Area of Kaduna State. The entire area is generally situated in the Southern Guinea Savannah Region with the population of 158,086 (NPC, 2006). The area experiences distinct dry and wet seasons with annual rainfall varying from 1300mm in the North to 1600 mm in the South. The wet season ranges from 170 days or more in the Northern part to 210 days or more in the Southern part. The major indigenous ethnic groups that make up the L.G.A are the Gbagyi, Kadara and Koro, with Gbagyi representing the majority tribe. Other inhabitants
RESULTS AND DISCUSSION The age distribution of the respondents is shown on Table 1 while Table 2 shows the marital status of the respondents. Table 3 indicates number of children of respondents while Table 4 shows the educational background of respondents. Table 5 sets out the distribution of respondents based on their years of farming experience while Table 6 shows the distribution of the respondents with respect to farm size. Table 7 sets out the distribution of respondents based on awareness of existence of agricultural insurance while Table 8 shows the distribution of respondents based on attitude towards insurance-taking in the past. Table 9 is the distribution of respondent based on reason for patronising NAIC in the past while Table 10 shows the distribution of respondents based on
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Commercial Agricultural and Banking reforms
constraints to insurance-taking. Table 11 shows the distribution of respondent based on willingness to accept insurance in future and Table 12 sets out the relationship between some socio-economic factors and willingness to accept insurance from NAIC. Results show that 16% of the respondents were female and 84% were males. In addition, 56% were full-time farmers while 44% were farming on parttime basis. It is a clear indication that there are less women farmers in the area. In addition, majority of the farmers are on full-time. The result on Table 1 shows that the mean age of the farmers in the study area is 29 years and majority of the farmers (86%) were between the 18-40 years bracket. This is quite contrary to earlier findings by Nmadu, 1995; Nmadu and Ibiejemite. 2007, Nmadu et.al., 2008, Nmadu et.al., 2008a. However, the findings compare favourably to the findings of Nmadu and Chindo (2009); FAO (2001); Eze (2002) and Asumugha (2005). According to FAO (2001); Eze (2002) and Asumugha (2005), the age of the decision-maker is an important factor influencing change and enhancing adoption of improved agricultural production technologies. It is expected that younger farmers will accept innovation more easily than the older ones as they are higher risk-takers. But this is contrary to the situation among these farmers where only 13% (Table 9) of the respondents voluntarily took agricultural insurance. Table 1: Age distribution of respondents Age Frequency Percentage 18-20yrs 19 25.3 21-30yrs 28 37.3 31-40yrs 18 24.0 41-50yrs 7 9.3 51-60yrs 3 4.0 Total 75 100 Mean 29.3 Source: Field survey, 2009. Table 2: Marital status of respondents Status Frequency Percentage Single 14 18.7 Married 53 70.7 Divorced 1 1.3 Separated 1 1.3 Widow 6 8.0 Total 75 100 Source: field survey,2009 Table 3: Distribution of respondents based on number of children Number of Frequency Percentage children 0 2 2.7 1-5 47 62.7
6-10 18 11-15 4 16-20 3 >20 1 Total 75 Mean Source :field survey, 2009
24.0 5.3 4.0 1.3 100 5.5
Table 4: Educational background of Educational Frequency Non-formal 27 Primary 13 Secondary 20 Tertiary 15 Total 75 Source: field survey,2009
respondents Percentage 36.0 17.3 26.7 20.0 100
Table 5: Distribution of respondent of farming experience Farming Frequency 1-5yrs 11 6-10yrs 39 11-15yrs 10 16-20yrs 12 >20yrs 3 Total 75 Mean Source field survey, 2009
based on years percentage 14.7 52.0 13.3 16.0 4.0 100 10.1
Table 6: Distribution of respondents based on their farm size (ha) Farm size Frequency Percentage 0.1-0.9ha 1 1.3 1-2.9ha 23 30.7 3-4.9ha 21 28 5-6.9ha 14 18.7 7ha and above 16 21.3 Total 75 100 Mean 4.6 Source: Field survey, 2009 Table 7: Distribution of respondents based on awareness of existence of agricultural insurance Level of awareness Frequency Percentage No response 36 48 Strongly aware 8 10.7 Partially aware 27 36 Fairly aware 4 5.3 Total 75 100 Source field survey,2009 Table 8: Distribution of respondents based on attitude towards insurance-taking in the past Status frequency percentage Positive 25 33.3 Negative 20 26.7 Neutral 30 40.0 Total 75 100 Source field survey,2009
NAAE 2010 higher than earlier findings (e.g. Nmadu, 1995, Nmadu and and Ibiejemite, 2007, Ojo, 2008, Onemolease and Alakpa, 2009, , Baiyegunhi et. al., 2010) and compares favourably with Sebopetji and Belete, (2009) but none of the farmers are operating at commercial level. It is likely that the low level of patronage of agricultural insurance might be attributed to small size of farms and other factors as shall be elaborated shortly. The necessary ingredient for take-off of commercialisation of farms include farm size expansion, high level of education, mechanisation, high-yielding varieties, experience and good management skills and capital inputs. In addition, Heintz (2010) also indicated that specialisation and investment in technology are also key factors enhancing commercialisation. It is therefore not very surprising that there is no commercialisation given the low level of education (Table 4) and small farm size.
Table 9: Distribution of respondent based on reason for patronising NAIC in the past Status Frequency Percentage No response 50 66.7 Voluntary 10 13.3 Persuasion 3 4.0 Compulsory 12 16 Total 75 100 Source field survey, 2009 Table 10: Distribution of respondents based on constraints to insurance-taking Problems Frequency Percentage Problem of fund 19 17.9 Ignorance 64 60.4 Attitude of NAIC 18 17 Beliefs and value 5 4.7 Total 106 100 *=multiple response Source field survey, 2009
The results on Table 5 shows that only 15% of the respondents had less than 5 years farming experience while the rest of the respondents had above 5 years experience, about 20% even had over 15 years experience. This is a good development as the more experience a farmer is the better the management skills and the better the farm enterprises would be managed. However, this trend had a negative impact on the educational background of the respondents (Table 4). It was observed that there is positive correlation between more years of farming experience and low level of education as 80% of the respondents did not have more than secondary education, suggesting that many of them finish only secondary education and then take to farming. Various studies have indicated that a more educated farmer is preferred as with the case of age, as he is more likely to adopt innovations and improvements much more easily. Given this scenario, there is likely to be apathy towards new technologies among this farmers. This might have contributed to the low level of adoption of insurance-taking by the farmers as shown on Tables 8 and 9; and even the high level of apathy towards awareness of the existence of agricultural insurance claimed by the respondents (Table 7). This assertions are further confirmed by most respondents (60.4%) claiming ignorance as the constraint to insurance-taking on Table 10. This is more worrisome because only extent of awareness affected the willingness of the farmers to adopt agricultural insurance significantly (Table 12). However, since 67% (Table 11) of the respondents show willingness to accept agricultural insurance in the future, there seems to be a light at the end of the tunnel.
Table 11: Distribution of respondent based on willingness to accept insurance in future Status Frequency percentage Very willing 9 12.0 Willing 41 54.7 Not willing 25 33.3 Total 75 100 Source: field survey,2009 Table 12: Relationship between some socioeconomic factors and willingness to accept insurance from NAIC Variable Chi-square Degree of value (X2) freedom (df) Age VS Willingness to 4.454ns 8 accept NAIC Education level VS 14.046ns 8 Willingness to accept NAIC Household size VS 12.003ns 10 willingness to accept NAIC Extent of awareness of 38.887* 6 NAIC VS Willingness to accept NAIC *P = 0.05 Source field survey, 2009 The results on Table 2 shows that 71% of the respondents are married with majority of them (87% on Table 3) having between 5 and 15 children. This is likely an indication of low level of awareness of family planning and reproductive health issues among the respondents.
SUMMARY AND CONCLUSION This study examined the attitude of small scale farmers in Paikoro Local Government Area
The results on Table 6 shows that the mean farm size of the respondents is 4.6ha which is slightly
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Commercial Agricultural and Banking reforms
towards agricultural insurance-taking in the past and their willingness to accept agricultural insurance in the future. The study also examined the constraints to insurance-taking by the respondents. A sample of 75 farmers were interviewed to achieve the stated objectives of the study from nine villages. The data were collected using structured questionnaire. The data were analysed using descriptive statistics and chi-square. The findings indicate that about 65% of the respondents had more than 5 years of farming experience, a good development but which has made the respondents to abandon education at secondary level. It was also found that most of the farmers (84%) did not practice the art of insuring their farms against natural disasters in the past through NAIC voluntarily. About 60% of the farmers claim ignorance as the constraints to insurance-taking, a situation which was likely attributable to the low level of education of the respondents. It was also found that the extent of awareness is a very important factor to successful insurance-taking. Finally, it was discovered that many more of the respondents are willing to patronise agricultural insurance in future which gives a ray of hope. In view of the above findings, it is recommended that stakeholder sessions on confidence building on agricultural insurance as well as sensitizing the respondents of the benefits of well-educated farming population be undertaken. It is also recommended that farmers should be merged to larger size of between 20-30ha so that they can enjoin economy of scale. There is also need to establish a continuing education system where farmers are given formal training as well as training on new innovations and improved technologies so that our farmers can move from the traditional level of production to commercial level which will make insurance-taking imperative. REFERENCES Ajayi, L. (1990) ‘’Barrier to Marketing Insurance Services in Competitive Environment‘’ Insurance News volume 4 P 32-35. Baiyegunhi, L. J. S., D. O. Chikwendu and G. C. G. Fraser (2010). Resource use efficiency in sole sorghum production in three villages of Kaduna State Nigeria. African Journal of Agricultural Research Vol. 5(3), pp. 172-177, 4 February Erima, C.O (2005). ‘’The level of Awareness and Patronage of Nigerian Agricultural Insurance Scheme by farmers in Markudi Local Government Area of Benue state’’ Unpublished FAO (2001). Production, Accessibility, Marketing and Consumption Patterns of Freshwater Aquaculture Products in Asia: A Cross-
Country Comparison. FAO Fisheries Circular No. 973 Pp 283. http://www.fao.org/docrep/004/Y2876E/y 2876e0j.htm retrieved 21st August, 2010. Food and Agricultural Organization (FAO). 1991 Annual Report on Land Use for Agricultural Production. Food and Agricultural Organization New York, USA. Hardaker, J. B. Raud, B.M.H and Jack, R.A(‘1977). ‘’Coping with Risk in Agriculture’’ New York. AB International Oxford, P 5-7. Kiari, A. (2003). ‘’Agriculture and Food Security ’’ National Programme for Food Security (NPFS),Expansion Phase Project, 2003,2006,2010. Federal Government of Nigeria pp5-13. Lijadu, O. (1987). ‘The Insurance Industry : An Imperative Need for Poor Resource Marketing Africa’ A Paper Presented at a Workshop on Insurance Industry in Lagos , May/June P 10. National Population Commission, NPC (2009). Census 2006 Result, Federal Government of Nigeria P 5. Ndanitsa , M.A (2005) Economics of Fadama Crop Production in Niger state, Nigeria. M.Sc Thesis Department of Agricultural Economics and Farm Management, University of Ilorin, Ilorin Nigeria P 147. Ndanitsa, M.A (1994). Nigeria Agricultural Insurance Cooperation, N.Y.S.C Performance Report Award Winner, NAIC. Headquarter Abuja P 2. Ndanitsa, M.A (1995). Problems , Forces, Fluxes and Flash Flosses in Nigeria’s Agricultural Insurance Scheme, NAIC. Headquarters Abuja, P 18. Nigeria Agricultural Insurance Scheme Lecture note (2005) Delivered by the Manager Nigerian Agricultural Insurance Cooperation , Minna Zonal Office. Nmadu J. N (1995). The Socio-economic Characteristics of Farmers in Patti, Lavun Local Government Area of Niger state. A Paper Presented at the 3rd Annual Conference of the Agricultural Society of Nigeria at Edo state University, Ekpoma between 5-8th November. Nmadu J. N., E.P.O Egwa And A. Ogaji 2008a. Factors affecting loan acquisition among small scale farmers in Otukpo Local Government Area of Benue State, Nigeria. In the Proceedings of the 10th Annual Conference of the Nigerian Association of Agricultural Economists held at 750 Seater Lecture Theatre, University of Abuja Permanent Site (Opposite Nmandi Azikiwe International Airport), Abuja. October 7th – 10th, 2008.
NAAE 2010 Nmadu J.N. and G.L. Chindo, (2009). Willingness to adopt improved technology among maize farmers in Shiroro Local Government Area of Niger State, Nigeria. A paper presented at the 2009 National Conference of the Agricultural Extension Society of Nigeria (AESON) held at the Federal University of Technology, Minna between 21st and 24th of April. Nmadu, J.N. and J.O. Ibiejemite. 2007. Economic analysis of fertilizer use on yam production in Kabba Bunu local government area of Kogi State, Nigeria. In: U. Haruna, S.A. Jibril, Y.P. Mancha and M. Nasiru (eds). Consolidation of Growth and Development of Agricultural Sector. Proceedings of the 9th Annual National Conference of the Nigerian Association of Agricultural Economists held at ATBU, Bauchi, 5th – 8th November. Nmadu, J.N., A. Haruna and O. Jiya. 2008. Socioeconomic structure of farmers displaced by the establishment of large-scale farming in Edu local government of Kwara State, Nigeria. Proceedings of the 2008 SOGARD Conference held at University of Agriculture, Markurdi, May 25th to 28th. Onemolease, E. A. and S. O. Alakpa (2009). Determinants of Adoption Decisions of Rural Youths in the Niger Delta Region of Nigeria. Journal of Social Science 20(1): 61-66. Sebopetji T.O. and A. Belete (2009). An application of probit analysis to factors affecting small-scale farmers’ decision to take credit: a case study of the Greater Letaba Local Municipality in South Africa. African Journal of Agricultural Research Vol. 4 (8), pp. 718-723, August.
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