POVERTY ANALYSIS OF DISPLACED BAKASSI RETURNEES IN URUAN LOCAL GOVERNMENT AREA, AKWA IBOM STATE

POVERTY ANALYSIS OF DISPLACED BAKASSI RETURNEES IN URUAN LOCAL GOVERNMENT AREA, AKWA IBOM STATE ABSTRACT Udondian 1, N. and Ogbanga 2, M. M. 1 Department of Agricultural Economics and Extension, University of Uyo, udondiann@yahoo.com 2Faculty of Social Sciences, University of Port Harcourt, Port Harcourt, Nigeria This paper examined the poverty status of Bakassi returnees in Uruan Local Government Area, Akwa Ibom State. This was necessitated by a massive influx of persons fleeing the Bakassi Peninsular into Akwa Ibom State following the handing over of the administration of the Peninsular to Cameroon on the 14 th of August 28. Integrated Regional Information Network IRIN (28), reports that Akwa Ibom State received 15 returnees in just the last two weeks of August. This paper therefore documents the poverty profile of these persons two years after their migration. Uruan Local Government Area was chosen because it is one of the few Local Government Areas in custody of a majority of the returnees. To achieve this, the following specific objectives were analysed: Socio economic characteristics of displaced Bakassi Returnees in Uruan Local Government Area; incidence, depth and severity of poverty as well as determinants of poverty in the study area. Information was obtained from a total of 9 respondents through the use of structured questionnaire and personal interview. Their responses were analysed using frequency distribution and percentages tables, Foster Greer Thorbecke (FGT) weighted poverty index and Tobit regression. It was observed that 74.5% of the respondents were between the ages of 31 and 5; 66.7% were married; 36.7% had primary education as their highest level of education; 56.7% did not own mobile phones and 63.3% used firewood/charcoal as their major source of energy for cooking. The FGT analysis showed 7.8% of the respondents as core poor and 48.9% as moderately poor while non-poor was 43.3%.Tobit regression result showed household size, primary earnings, secondary earnings and other working members as determinants of poverty in the study area. Keywords; Poverty status, Displaced persons, Bakassi returnees, Socioeconomic characteristics, INTRODUCTION Nigeria, despite its many resources and oil wealth suffers from great poverty. The situation has worsened since the late 196s to the extent that the country is now considered one of the poorest countries in the world. Over 7 percent of the population is classified as poor, with 35 percent living in absolute poverty (IFAD, 26). Report by World Bank shows Nigeria as the 12 th poorest nation in the world, ranking 146 out of 174 in the human Development Index (Nwogu, 28). The displacement of Nigerians from Bakassi Peninsular following the 14 th August 28 ceremony, which officially handed over the administration of Bakassi Peninsular to Cameroon, seems to have escalated the situation. According to Adewale (28), Over 3, inhabitants of Bakassi are now refugees being made to live like criminals in primary schools not fit for learning, let alone habitation. Integrated Regional Information Network IRIN (28), reports that tens of thousands claiming to be from Bakassi fled about 12km away into the neighboring Nigeria. The number of displaced reported in local media does not, according to the same source, represent people who fled violence on the Peninsula. The figures are said to be inflated for several reasons, one of which could be a deliberate attempt on the part of Nigerian authorities to get more funding from the Federal Government. However, the greater bulk of the displaced fled to the neighboring Cross River and Akwa Ibom State. In all this, the nature and determinants of poverty facing these displaced persons are yet to be determined, even whilst it is obvious that this trend is such that requires urgent attention. This study is therefore intended to provide the necessary information for economic planners to base their recommendations towards poverty reduction and eradication. It will also serve as the basis for further empirical research on poverty among displaced persons in Uruan Local Government Area and in other parts of the world. It has been observed that in spite of abundant natural, physical and human resources that Nigeria is endowed with, there is still high incidence rate of poverty in Nigeria especially in the rural areas (Imoh, Isaac, Nwachukwu 29). In Akwa Ibom State, recent poverty data desegregation shows poverty varying from a low rate of 27% in a few local government areas to about 9% in several others (Akwa Ibom State Economic and Development Strategy AKSEEDS, 24). The handover of the Bakassi peninsular to Cameroon without provision by the Nigerian central government to resettle persons who have been displaced by that development has led to situations where the already strained resources available to states are further stretched to accommodate these refugees. This has worsened the poverty situation of the states saddled with the greater bulk of the returnees to the point where the Government of Akwa Ibom State has had to call on the federal government for help (IRIN 28). In order to effectively resettle these returnees and tackle their poverty problems, it is important to establish their socio-economic characteristics, ascertain their poverty status and determinants without which meaningful interventions cannot be obtained. The general objective of this NJAFE VOL. 1 No. 1, 214 1

study is to estimate the poverty status of displaced Bakassi returnees in Uruan Local Government Area, Akwa Ibom State. The specific objectives are to; Examine the socio-economic characteristics of the displaced Bakassi returnees in Uruan Local Government Area. Ascertain the poverty status of the displaced Bakassi returnees in Uruan Local Government Area. Estimate the determinants of poverty among the displaced Bakassi returnees in Uruan Local Government Area. METHODOLOGY The study was conducted in Uruan Local Government Area of Akwa Ibom State. The study area has Idu as its administrative headquarters. It is bounded by Uyo, Itu, Nsit Atai, Okobo and Oron Local Government Areas. Geographically, Uruan is located between latitude 5 6 North and longitude 7 59 East. It has an estimated population of 118,3 out of which 62,897 are males and 55,43 are females (NPC, 26). The climate is tropical with two distinct seasons, the rainy season (April to October) and dry season (November to March). The people of Uruan are majorly Christians and the dialects spoken are Efik and Ibibio. Farming is the major occupation of the people though the area has been noted to possess relatively untapped fisheries potential. The commonly cultivated crops are cassava, oil palm, yam, and cocoyam. Micro livestock usually raised as supplement includes poultry and goatry. The study population comprised of all displaced Bakassi returnees in Uruan Local Government Area. The displaced Bakassi returnees in Uruan Local Government Area are settled in three camps; Adadia, Idu and Ikototoinye. Simple random sampling technique was used to select 3 respondents from each of the camps making a total of 9 respondents. Primary source of data was used for this study to obtain information from the 9 respondents through the use of structured questionnaire and personal interview. The questionnaire contained analytical questions on the objectives of the study. Objective one was analysed using frequency distribution and percentages. Objective two was analysed using the Foster, Greer and Thorbecke (FGT) weighted poverty index. The model was preferred as it helps estimate poverty at different levels. The model is given as; For α=, index P ai becomes: P = q / n This stands for Head Count or incidence of poverty. It counts the number of households with expenditure below the poverty line. For α =, index P ai becomes; This stands for depth of poverty. It shows the percentage of expenditure required to bring each household below the poverty line up to the poverty line. For α = 2, index P ai becomes; This represents the severity of poverty. It indicates severity of poverty by giving weight to the extremely (core) poor; Where: Z = the poverty line, Z i= the expenditure or income of the 1 st poor household or individual, n = the total number of households, q = the number of households whose consumption are below the poverty line, α = Degree of poverty aversion which can be (P, P 1, and P 2), P ai = weighted poverty index. The poverty line for the study was constructed using the Mean Per Capita Household Expenditure (MPCHHE) method. Here, two poverty lines were obtained; the core poverty line equivalent to one-third ( 1 / 3) of the MPCHHE and the moderate poverty line equivalent to the two-third ( 2 / 3) of MPCHHE. From the set poverty lines, the respondents were grouped into core poor, moderately poor and non-poor categories. For objective three, the Tobit regression model, a hybrid of the discrete and continuous dependent variable was used to determine the impact of the explanatory variables on the probability of being poor. The model expressed based on Tobin (1958) is given as; q:p i = + if P i > P i* O = + if P i P i* NJAFE VOL. 1 No. 1, 214 2

i = 1, 2 9 Where: q = the dependent variable. It is discrete when the households are not poor and continuous when they are poor. P ai = the poverty depth/intensity defined as, P i* = the poverty depth when the poverty line (z) equals the mean per capita household expenditure (MPCHHE), X i = A vector of explanatory co-efficient, B = A vector of unknown co-efficient, = independently distributed error term. The explanatory variables that served as determinants or factors responsible for poverty in the area are specified below: X 1= Age of the respondents (in years), X 2 = Marital status (Dummy 1 if married, if otherwise), X 3 = Household size (number of people living and feeding from the respondent), X 4= Primary occupation (Dummy 1 for farming, for other occupations), X 5= Income from primary occupation (in naira), X 6= Income from secondary occupation (in naira), X 7 = Education level (years of formal schooling), X 8= Access to extension services (Dummy 1 if yes, if otherwise), X 9= Distance from source of water (in km), X 1= Distance to clinic (in km), X 11= Ownership of assets (Dummy 1 if yes, if otherwise), X 12= Expenditure on food and non-food items (in naira) and X 13= Access to government aid (Dummy 1 if yes, if otherwise). Based on the objectives of the study, the socio-economic characteristics of the farmers were measured on a variety of characteristics as follows: Age: This was measured by asking respondents to state their ages in years Marital Status: This was measured by asking the respondents to indicate whether they were single, married, divorced, widowed or separated, etc. Education Level: This was measured by asking the respondents to state their highest educational level attained Household Size: This was measured by asking the respondents to state the number of people in their households that were dependent Occupation: This was measured by asking the respondents to state their primary and secondary occupation Other Working Member(s): Respondents were asked to state the number of other working member(s) of the family (if any) Income Level: Respondents were requested to estimate the actual income they earned on monthly basis from the primary and secondary occupations Total Expenditure on Food and Non-food Items: Respondents were requested to give an estimate of total expenditure on food and non-food items. Ownership of Assets: This was measured by asking the respondents whether they owned assets or not Distance to Source of Health Care: This was measured by asking the respondents to state the distance to their source of healthcare in kilometers Distance to Source of Domestic Water: This was measured by asking the respondents to state the distance to their source of domestic water in kilometers Access to Government Aid: This was measured by asking the respondents to state if they received aid from government and how often they did (if they did). RESULT AND DISCUSSIONS The table 1 shows that they were more males (57.8%) than females (42.2%) among the returnees. 5% were within the age bracket of 31-4 years, suggesting youth and vigor to work should opportunities present themselves. 6% were married, increasing the likelihood for them to increase their household sizes. 36.7% had primary school education as their highest educational qualification whilst 35.6% had no formal education. This is in line with IRIN (28) report which stated that the 1 square kilometer Bakassi republic had no roads and no schools. 53.3% had household sizes between 4 and 6 and 51.1% had no other working member in their households. 31.1% had fishing as their major occupation; this is probably due to the fact that most of the respondents were originally fishermen before their return. This is in line with the report from Wikipedia (28) that most of the Bakassi populations make their living through fishing. 8% of the returnees were monogamist. NJAFE VOL. 1 No. 1, 214 3

Table 1: Distribution of respondents based on socioeconomic characteristics Variables Frequency Percentages (%) Sex: Male Female AGE: 2 3 31 4 41 5 >5 Marital status Single Married Divorced Separated Widowed Level of education No Formal Education Primary Education Secondary Education Adult Literacy Education Tertiary Education Household size 1 3 4 6 7 9 Other working members 1 2 3 Primary occupation: Farming Fishing Trading Artisan Civil service Secondary occupation Farming Trading Artisan None Type of marriage Monogamy Polygamy 38 52 19 45 22 4 11 6 1 6 12 32 33 23 2 27 48 15 46 25 18 1 22 28 25 15 6 13 2 69 8 1 42.2 57.8 21.1 5. 24.5 4.4 12.2 66.7 1.1 6.7 13.3 35.6 36.7 5.6 2.2 3 53.3 16.7 51.1 27.8 2.1 1.1 24.4 31.1 27.8 16.7 6.7 14.4 2.2 76.7 88.9 11.1 Source: Field report 29 NJAFE VOL. 1 No. 1, 214 4

Incidence, depth and severity of poverty of displaced Bakassi returnees in Uruan Local Government Area The poverty line Table 2: Mean per capita household expenditure Items Amount (N) Percentage Clothing Housing Food and drinks Water Transportation Electricity Health services Phone call/recharge card Education Others 333.8889 2112.2222 11448.8889 634.4444 2281.1111 583.779 277.7778 1864.4444 13.59 8.69 47.1 2.61 9.38 2.4 8.55 7.67 Total MPCHHE 2 /3 MPCHHE 1 /3 MPCHHE Source: Field report 29 2436.48 7451.85 4967.89 2483.95 The first step in this analysis is the determination of the poverty line. The Mean Per Capita Household Expenditure (MPCHHE) was used to determine the poverty line. Table 4.17 shows the mean amount expended by the displaced Bakassi returnees in the consumption of some basic items. The major items of consumption taking up the greater percentage of income are food and drinks. The Mean Per Capita Household Expenditure is N7,451.85. Poverty classification Table 3: Displaced Bakassi returnee s poverty classification Income Poverty line Frequency Percentage (%) Core poor ( 1 /3 MPCHHE) < 2483.95 7 7.8 Moderately poor ( 2 /3 MPCHHE) 2483.95 Z 4967.89 > 4967.89 44 48.9 Non poor 39 43.3 Total 9 1 Source: Field report 29 Expenditure data was used in this analysis. The total expenditure per capita was obtained by summing up all expenditure on food and non-food items and dividing by the number of people living in each household as proxy for standard of living. This figure was used as poverty line. The Mean Per Capita Household Expenditure was N7,451.85 monthly. The moderate poverty line which is 2 / 3 of the MPCHHE was N4,967.89 and the core poverty line which is 1 / 3 of the MPCHHE was N2,483.95. This is in line with the approach adopted by FERT (21). On the basis of the above, displaced Bakassi returnees were regarded as poor if their per capita household expenditure was below the poverty line. Thus 56.7% were found to be poor and the non-poor were 43.3%. Among the poor, 48.9% were moderately poor while 7.8% were classified as core poor. Measurement of poverty Table 4: Incidence, depth and severity of poverty among the displaced Bakassi returnees in Uruan Local Government Area Group P P P 1 /3 MPCHHE (Core poor) 2 /3 MPCHHE (Moderately poor) Source: Field Report, 29.7.49.17.31 The incidence of poverty which indicates the number of households with expenditure below the poverty line is 7% for the core poor and 49% for the moderately poor. The depth of poverty which shows the percentage of expenditure required to bring each households below the poverty line up to the poverty line is 17% for the core.6.13 NJAFE VOL. 1 No. 1, 214 5

poor and 31% for the moderately poor. The severity of poverty among displaced Bakassi returnees in Uruan Local Government Area is 6% for the core poor and 13% for the moderately poor. The severity of poverty shows the spread of the poor around the average poor. Determinants of poverty among displaced Bakassi returnees in Uruan Local Government Area of Akwa Ibom State This section presents the results of the Tobit regression on the determinants of poverty among displaced Bakassi returnees in Uruan Local Government Area. The regression parameter and diagnostic statistics were estimated using the Maximum Likelihood Estimation (MLE). In estimating the determinants of poverty among displaced Bakassi returnees in the area, censored regression model made up of 1 regresses was specified. From the maximum livelihood estimates of the Tobit regression, the results show that Sigma (σ) is 1.7482 at P <.1. This indicates that the model has a good fit to the data. Also 4 out of 1 parameters estimated in the model were statistically significant. The intercept is 1.7934 and this represents the autonomous poverty depth among displaced Bakassi returnees in the study area. The result of Tobit regression is shown in Table 5. Table 5: Maximum likelihood estimates of tobit regression of poverty among displaced Bakassi returnees in Uruan Local Government Area Variable Parameter value Standard error t-ratio Gender Age Marital status Education Household size Primary earnings Secondary earnings Distance from source of water Distance from source of health care Other working members Constant Sigma.128 -.1146 -.3468 -.457.17139 -.4 -.9 -.5739 -.515 -.3535 1.79339 1.7482.3685.23.12395.16911.7796.2.5.29729.1153.3923 1.5572.8842 Source: Computed from Tobit regression results, 29. *denotes significance at 1%, ** denotes significance at 5%, *** denotes significance at 1%. -.56 -.28 -.27 2.2 ** -2.3 ** -1.82 * -.19 -.5-3.35*** 1.7 * 13.28 *** From the result of the analysis, household size is significant at 5% and carries a positive sign. This implies that the higher the household size, the higher the likelihood and the intensity of poverty in the study area. The co-efficient of regression was.17139, implying that a unit increase in the household size will lead to an increase in the probability of poverty by.17139. This is likely due to the fact that a high household size will increase dependence of members on those working. This is in line with the findings of Omonona (27) that a unit increase in household size will raise depth of poverty because more resources are needed to keep a relatively larger household size. Primary earning has a co-efficient of -.4 and is significant at 5%. This shows that the higher the primary earnings, the lower the likelihood and intensity of poverty in the study area. The co-efficient -.4 implies that a unit increase in primary earnings will reduce the probability of poverty by.4. This is probably due to the fact that increased earnings increases availability of funds to meet household expenses. Secondary earnings with co-efficient of -.9 is found to be significant at 5%. This implies that the higher the secondary earnings, the lower the likelihood and intensity of poverty in the study area. The co-efficient of.9 implies that a unit increase in secondary earnings will decrease probability of poverty by.9. This is likely due to the fact that secondary earnings provide additional income to meet household expenses. The co-efficient of other working members was estimated at -.3535. This was significant at 1% implying that the higher the number of working members in the household, the lower the intensity of poverty in the study area. The co-efficient of -.3535 indicates that a unit increase in the number of other working members will lead to a decrease in the probability of poverty by.3535. This is probably due to the fact that increased number of working members implies more household income and less dependence on working members. This agrees with Omonona (27) who stated that the presence of other working members in the household increases the level of income in such households. Gender, age, marital status, education, distance from source of health were not significant. This implies that alterations in any of these factors will neither increase nor decrease the likelihood and intensity of poverty in the study area. NJAFE VOL. 1 No. 1, 214 6

CONCLUSION From the results of this study, it is apparent that poverty is endemic amongst these displaced persons. This level of poverty therefore requires that the government, non-governmental organizations and other international organizations pay attention to salvaging this people of poverty in their quest to wipe out poverty globally. POLICY RECOMMENDATIONS The government should organize population study to teach the returnees on the need for population control. Birth control measures should also be encouraged. Social safety nets should be provided for those already running large household sizes. This would be useful as poverty increases with increase in household size. The National Directorate of Employment should develop a special program just for the displaced Bakassi returnees. This program should aim at providing employment opportunities for the returnees. The government, NGOs and other development agencies should encourage the displaced Bakassi returnees to engage in as many income generating activities as possible as this will help increase their income level and reduce dependence on those working. REFERENCES Adewale, P. 28. Bakassi Controversy is a scramble for oil not the people s interest. A scholarly article for democratic socialist movement, Lagos. http://www.socialistnigeria.org/page.php?article=1364 Foundation for Economic Research and Training (FERT). 21. Poverty profile of Akwa Ibom State, Office of the Governor, Life Enhancement Programme, Uyo. Foster, J., Greer, J. and Thorbecke, E. 1984. A class of decomposable poverty measure, Econometrica 52: 761-765 International Fund for Agricultural Development (IFAD). 1992. The state of World Rural Poverty: An enquiry into Cause and Consequences, Oxford Press, New York. Imoh A.N., Isaac U. J. and Nwachukwu E. O. 29. Comparative Analysis of Poverty Status of Community Participation in Rural Development Projects of Akwa Ibom State, Nigeria. http://www.sciencepub.net/newyork. Integrated Regional Information Networks (IRIN). 28. Cameroon Nigeria Bakassi Returnees Overwhelm Authorities. http://www.unhcr.org. National Population Census (NPC). 26. Population census of the Federal Republic of Nigeria, Analytical Report at the National Level, National Population Commission, Lagos. Nworgu E. C. 28. Estimation of Poverty Status of Women Headed Households in Ini Local Government Area of Akwa Ibom State. Unpublished B.Sc. Research Findings, Department of Agricultural Economics and Extension, University of Uyo, Uyo. Omonona B. T., Udoh, E. J. and Owicho, M. I. 27. Urban People s Perception and Causes of Poverty, Nigeria Agricultural Development Studies, Vol.1 No.1 pp. 8 96. Ukpong, E. A. 24. Akwa Ibom State Economic Empowerment and Development Strategy The Abridged Version. Wikipedia (28): poverty http://www.wikipedia/poverty/org. NJAFE VOL. 1 No. 1, 214 7