Baseline Survey of Prevalence and Distribution of Unemployment and Poverty in Kaduna State

KADUNA JOURNAL OF POSTGRADUATE RESEARCH Vol 2. No:2. December, 2019 AFANG HELEN ANDOW AND IBRAHIM GERARH UMARU Department of Business Administration, Faculty of Management Sciences, Kaduna State University [email protected]

Abstract: Unemployment and poverty are two of the socio-economic problems the Nasiru El-Rufai’s administration targeted and planned to tackle in Kaduna state. However, the necessary data to support such a laudable macroeconomic objective is either scanty or unreliable. Thus, undertaking a study that will provide disaggregated and comprehensive data for the state becomes imperative. This study is an attempt to do so. Three poverty measurement approaches and one inequality measure - the relative poverty measurement approach, absolute (objective) or food energy in-take measurement approach, the dollar per day measurement approach and the Gini Inequality Coefficient were used to compute the poverty measure using the expenditure approach. For unemployment, the Nigeria’s National Bureau of Statistics (2012) framework for the measurement of unemployment and underemployment was adopted. The survey method was used to collect data from 16 local government of the state between 21 March and 12 April 2017. The study found that the poverty incidence for the entire state as of 2017 was 64.4, meaning that more than two-thirds of people in the state lived below the poverty line. The breakdown of poverty figures by zone indicated that northern and central zone were home to the most of the ‘extreme poor’ in the State as they reportedly had ratios higher the State average of 36.1. The study also shows that the unemployment rate for the period ended 2017 was 21.3 per cent of the labour force in the state with Chikun LGA having the highest computed figure for 2017, whereas Ikara was had the lowest rate (14.3). The analysis further revealed that the highest incidence of unemployment was more pronounced in the central and southern Senatorial district, all of which had rates higher than the State average. As of 2017, 476,087 of urban dwellers within the labor force were unemployed and unemployed when compared with 165,869 persons of rural counterparts. The unemployment figures equally exhibited serious gender bias in the state - 9.4 per cent of males were reported as unemployed, about 15 per cent of their female counterparts were jobless. Underemployment was predominantly an urban affair. The Gini coefficient for the entire state showed more than half of the population share all or some of the state’s income, while the other 46 per cent possessed the remainder or have nothing. Kauru LG in the Southern zone had the lowest coefficient, while the greatest inequality was reported for Kaduna North. The survey findings also showed that 7.4 per cent of women within the labor force (age 15-64 and willing, able and actively seeking work) were unemployed, compared with 4.9 per cent of men within the same period. Keywords: Prevalence, Unemployment, Poverty, Gini coefficient, Kaduna

Introduction

There is no denying the fact that three socio-economic problems confronting contemporary Nigeria are insecurity, unemployment, and poverty. However, of the three, the last two have been on the front burner in public discourse and development studies for quite a while now, because as it is argued, the prevalence of unemployment in any society often leads income inequality, disproportionate distribution and access to national wealth, underutilization of resources for development, worsens the poverty situation and ultimately the insecurity of lives and poverty. Unemployment in Nigeria has generally been measured as that part of the labour force that is available for work but cannot find work in the week preceding the survey period for at least 39 hours. The figures released by the National Bureau of Statistics in 2010 put the number of the unemployed at 23.9 per cent. After some adjustments consistent with the World Bank’s methodology, the rate was re-estimated at and came down to 8.1 per cent in 2014. It rose to 10.4 per cent by the first quarter of 2015. It further rose 9.92 per cent in the third quarter of the same year. By the end of the fourth quarter of 2015, it had risen to 10.040 per cent of the labour force. Disaggregated figures on unemployment in Nigeria are often difficult to come by, and where available, they are not only scanty but are often not computed on a regular basis. In fact, the most recent disaggregated unemployment figures available are those released by Nigeria’s National Bureau of Statistics 2010 report. The report put the unemployment rate by state of Oyo, Lagos, Yobe, Zamfara and Kaduna at 8.8 per cent, 7.6 per cent, 39.0 per cent, 33.4 per cent and 25.7 per cent, respectively. The report also gives the breakdown of unemployment by gender. For example, while the breakdown for Oyo State is given as 8.9 per cent (male) and 8.8 per cent that of Zamfara State is 22.2 per cent (male) and 48.6 per cent (female). As for Kaduna State, the figures are 18.7 per cent (male) and36.2 per cent (female). However, the report came short to providing disaggregated data beyond the state level. Aside from the fact that the unavailability of such data at those levels may limit any indepth analysis of the unemployment situation at the state level, it is perhaps the greatest threat to the realization of current government determination to reduce the unacceptable levels of unemployment in the state. The situation with poverty statistics situation is neither too different. The National Bureau of Statistics’ the Harmonized Nigeria Living Standard Statistics (HNLSS) and General Household Survey put the rate of poverty at 62.2 per cent in the 2009/2010 period. The poverty situation seemed to have worsened when compared to estimates of subsequent periods of 2010/2011 (35.2 per cent) and 2012/2013 (33.1 per cent). The implication of all this is that at the national level, about 60 per cent of the Nigerian population lived below 140 per cent of the poverty line which is close to two dollar per day. What is more, it has already been speculated that by 2015 an additional 40 million people would have been added to the already 60 million Nigerians already trapped below the poverty line as insinuated by theVice President, Professor Yemi Osinbajo (Vanguard Newspaper, August 20, 2015). The Oxford Poverty and Human Development Initiative (OPHI) survey findings released in 2015 seems to corroborate the above statement. The report revealed that 26.6 per cent of Nigeria’s 170 million people were destitute, while 68.0 per cent and 84.5 per cent of the Nigerian population lived below 1.25 dollar per day and 2 dollar per day, respectively. It is instructive to point out the fact that national figures appear to mask the true picture of the poverty situation at regional, state, and local levels. For instance, a World Bank study in 2012/2013 showed that there was a higher rate of poverty in northern parts of Nigeria than

39 there was in the southern parts: the number of poor Nigerians remained 58 million, of which more than half lived in the North East or North West of the country. Also, while the South and North Central experienced declines in the poverty rate between 2011 and 2012 to 2013, the poverty rate increased in the North East and remained almost unchanged in the North West. A 2015 United Nation’s Global Dimensional Poverty Index (GDPI) report which was based on the data collected in years between 2004 and 2014 gives a regional and state-wide breakdown of the poverty situation in Nigeria. Against the national average of 46 per cent, the report states that the three geopolitical zones of southern Nigeria had poverty rates well below the national average of 46.0 per cent: South West (19.3 per cent); South South (25.2 per cent) and South East (27.36 per cent). All the northern zones had rates above the national average, except North Central - [North East (76.8 per cent); North West (80.9 per cent); and North Central (45.0 per cent)]. The 2015 report of National Bureau of Statistics provides the state-by-state breakdown of the poverty situation in the country. The report shows that Osun, Ondo, Bayelsa and Lagos states had the lowest rates with following below-the-national averages of 37.9 per cent, 45.7 per cent, 47.0 per cent and 48.6 per cent, respectively. The same report identified ten states, all within the North East and North West zones, except Ebonyi from the South South zone, had rates far above the national average. Specifically, Sokoto State with 81.2 per cent had the highest; then followed by Katsina State (74.5 per cent), Adamawa (74.2 per cent), Gombe (74.2 per cent), Jigawa (74.1 per cent), Plateau (74.1 per cent), Bauchi (73.0 per cent), Kebbi (72.0 per cent) and Zamfara (70.8 per cent). For Benue, Nasarawa and Kaduna States, the rates were 59.2 per cent, 52.4 per cent and 56.5 per cent, respectively. Though Kaduna State is not in the category of states with the lowest or highest incidence, the fact that its poverty rate is well above the national average is well enough reason to qualify poverty reduction or eradication policy targeting. This becomes even more relevant considering the close relationship between poverty and unemployment especially at the regional and local levels of the state. However, any policy measure or policy targeting against poverty or unemployment by the state government that is not founded on available and reliable data is bound to perform abysmally. Unfortunately, such data are hardly available at those levels now; and where available, they are stubbornly inconsistent, aggregative, and unreliable for any serious policy formulation and implementation. Now that government policy at both federal and state levels are essentially targeted at tackling the twin problem of unemployment andpoverty but the necessary data to support it is scanty or unreliable, undertaking a study that will make such data available (disaggregated and comprehensive) becomes imperative. Based on the above research questions, the following research objectives will be used to guide the survey: 1. Determine the number of unemployed and poor people in the state and how they are distributed across region, local government area and economic/productive sectors in the state. 2. Ascertain the scale and depth of unemployment and poverty in the state. 3. Ascertain the manifestation of unemployment and poverty as well as their relationship with other socio-economic characteristics in the state. 4. Investigate the remote and immediate causes of unemployment and poverty in the state. 5. Identify the groups or subgroups of the poor and the unemployed in the state that require policy targeting?

Methodology In the study the definitions of unemployment and underemployment used in the 2012 by Nigeria’s National Bureau of Statistics, which corresponds with that of the International Labour

Organization (ILO) will be adopted as a working definition. Here, unemployment is defined as the proportion of those in the labour force (not in the entire economic active population, nor the entire Nigerian population) who were actively looking for work but could not find work for at least 20 hours during the reference period to the total active (labour force) population, while unemployment will be taken to mean if a person works less than full time which is 40 hours but work at least 20 hours on average a week and/or if the person works full time but is engaged in an activity that underutilises his/her skills, time and educational qualification (NBS, 2015). Similarly, the United Nation’s definition states that poverty occurs when a family is unable to meet a federally or globally established threshold need, often measured in income terms. Typically, it is measured with respect to families and not the individual and is adjusted for the number of persons in a family. Generally, the computation of poverty rates is simply an attempt by economists to identify the families whose economic position (defined as command over resources) falls below some minimally acceptable level. In the same vein, the international standard of extreme poverty is set to the possession of less than one dollar a day (Smelser & Baltes, 2001). Poverty is a complex phenomenon influenced by a large of factors and which can be studied from many different perspectives. Depending on the point of view adopted and the aspects that are required to be stressed, different poverty analysis can be carried out. Among the available approaches, one classification refers to the type of base information used, and which can be referred to as objective and subjective poverty. Similarly, one can speak of absolute and relative poverty, depending of course on the scale or reference used to set the thresholds. By applying an objective focus, an analysis of both absolute poverty and relative poverty can be carried out. Absolute poverty is defined as a situation in which the individual’s basic needs (lack of basic goods and services) are covered. The goods and services are normally related to food, housing, and clothes. In this regard, the concept of poverty is strongly linked to destitution and can be applied to all countries and societies. An individual who is considered poor under this criterion can be classified as such throughout the world. An attempt was made to measure absolute poverty in the study. Relative poverty locates the phenomenon within the context of specific location. disadvantaged situation, either financially or socially, with regards to other people in their environment. This definition of poverty is intricately linked to the notion of inequality. In this study, the focus was on to compute relative poverty. To do that, the so-called poverty lines were employed as bases to classify people in the State as poor or as not poor depending on the side of the line of barrier they are placed. Monetary values were assigned these indicators. Another useful indicator used to describe poverty in the State in this study was Incidence of Poverty often computed as:

P Poverty _rate (PR)  (1) n where p is the number of poor people and n is the total number of people, poor or not, in the group within which the poverty rate is being calculated. The incidence of poverty measure, sometimes called the headcount ratio, provides information on the extent of the problem. In other words, it provides data on the quantity of people or households that are affected. It is normally expressed as a percentage of the population. In the study, the measure was calculated across the whole population of the State and in all the subgroups (sectors, senatorial zones and LGAs).

Yet two other indicators used in the study to describe the poverty situation in the State were the Poverty Distribution and the Intensity of Poverty measures. One of the greatest influences on the seriousness of the poverty phenomenon is its intensity. Using relative measure alone does not provide information on the degree of poverty suffered by poor people. It is therefore important to use indicator of the depth of poverty alongside the relative measure get information on the financial situation of poor people and the differences with the rest of the population. In the study, the poverty intensity or gap was computed as: p

Poverty_intensity/ gap (PG)  (u xi ) (2) i1 Where u represents the poverty threshold (line), xi is the equivalent income of person i and p is the number of poor people in the population. The measure was used in this study to indicate how poor people are distributed in the State and the characteristics they share. The second measure allowed us to analyse up to what point poverty affected the population, as it focused on the degree of poverty suffered by the people (extremely or moderately) rather than the number of individuals considered to be poor. Three poverty measurement approaches and one inequality measure were used in this study namely, the relative poverty measurement approach, absolute (objective) or food energy in- take measurement approach, the dollar per day measurement approach and the Gini Inequality Coefficient. The techniques used in this study highlighted the poor and vulnerable groups in the State. The main component used in the computation of relative poverty measure was the household expenditure. For measuring poverty in the survey conducted, expenditure was defined as ‘all household outlay on goods and services for use which include all monetary transactions including transfers and savings.’ The importance of determining and estimating household expenditure cannot be overemphasized. This is because it shed some insights into the consumption patterns of the poor. In calculating household expenditure, the expenditure aggregates compute all individual member household expenditure into their primary headings for the purpose of poverty profile. In addition, it includes some non-monetary measures such as consumption from own produce, uses value of owned assets and inputted owner-occupied rents. This explains why household aggregate is commonly expressed in terms of per capita expenditure (the household expenditure divided by the household size). The ‘expenditure share of household’ is also another technique used to measure price change in a household. In this study, the items listed as part of expenditure share of household were food purchase, food own consumption, total food expenditure, education expenses, health expenses, rent, non-food expenses, total expenditure share and per capita expenditure. The importance of this measure is that it indicates the nature of the State expenditure profile and the areas that may require intervention to mitigate the impact of poverty on households. Poverty line as a measure that divides the poor from the non-poor was also computed. One- third of the mean per capita household expenditure was used to separate the ‘extreme poor’ or ‘core poor’ from the rest of the population, while two-thirds of the mean per capita expenditure to define the group, ‘moderate poor’ from the rest of the population. The NBS (2010) figures for poverty lines were adjusted using official yearly inflation rates and adopted as benchmarks for the computation of poverty thresholds for the State. The September 2017 exchange rate of N361.5 to one dollar was used to determine the Dollar per day poverty threshold for the State. The poverty lines for food poverty, Absolute poverty, Relative poverty, and Dollar per day poverty for the State for 2017 were computed and summarized in Table 3.1.

The figures on ‘core poor’ and the ‘moderate poor’ were combined to get the population of the poor in the State. The ‘non-poor’ group was determined as that population with mean per capita expenditure greater than that of two-thirds of the population. In the study, the Gini Coefficient was used to determine spread of income/expenditure or income/expenditure inequality. The coefficient was computed as: n 1 i1 (n  1- i)x i G  (n  12 n ) (6) n i1 xi where for a population with income/expenditure values xi, and i = 1 to n, are the points with non-decreasing order .

For this study, the Nigeria’s National Bureau of Statistics (NBS, 2012) framework for the measurement of unemployment and underemployment was adopted. The framework defines labour force as employed persons plus underemployed persons. Similarly, people outside the labour force will be defined as persons within the working age population who are neither employed nor unemployed, while the labour force participation rate (LFPR) will be defined as percentage of labour force in the working age population measured as

Labour force LFPR   100 (3) Working age population

The unemployed was defined as number of persons not in employment in the reference period and are available for employment, while the unemployment rate (U) was measured as:

Unemployed persons U   100 (4) Labour force

Underemployment rate (UFR) was defined as the number of persons in employment who are working fewer hours than they would like to or engaged in employment not commensurate with their occupational skill (training and working experience). Underemployment is two types - visible and invisible. It was measured as

Number of underemployed persons UFR  100 (5) Number of persons in the Labour force

In computing the unemployment rate for the Kaduna State, the total working population was divided into labour force (currently active) and non-labour force (not currently active). The former covered all persons reported to be between the ages of 15 and 64 who indicated their willingness and ability irrespective of whether they had a job or otherwise. Our working definition of unemployment in the State was therefore those persons (aged 15 - 64) who during the period referred to during the survey were the available for work, actively seeking work but were without any. The persons considered not in the labour force included those fell under those age cohorts outside the economically active population (15-64) group, not actively seeking work or deliberately preferred not to work/and or were not available for work (the economically inactive group). Under the second category were voluntary full-time housewives, underage children between the age of 14 and below, adults above 64 (‘Senior citizens), full- time students, those in active military service and physically/mentally challenged persons. For the most part of the study, primary data was used. Micro data from household survey was utilized for the computation of unemployment in the State. Similarly, primary data was used to

43 measure poverty in the State. The main instrument used to collect the primary data was survey questionnaire. Data from secondary sources was used to compare the results of the study with similar national and global surveys conducted in the past. The study involved a state-level survey intended to cover the 23 local government areas (LGAs) of Kaduna State. It was designed to also shed some light on the nature of poverty in both the urban and rural sectors of the State. The main of the study was to generate detailed, multi- sector and policy relevant data using the welfare and expenditure approach. In particular, the survey focused on agricultural assets, household food and non-food expenditure and transfer receipts and payments. The sample frame for all the 23 LGAs used wards and polling units demarcated by Kaduna State Independent Electoral Commission (KAD-SIECOM, 2012) Guide used for conducting elections in the State. The entire State was divided into three zones namely, the northern, central and southern. The existing geo-political arrangement were the State is divided into three senatorial districts was used as a basis for the classification of the State into three enumeration zones. Seven, four and five enumeration areas were systematically selected in northern, central and southern zones to ensure that those predominantly rural and urban local governments are equally represented in the selection. A total of 16 enumeration areas were delineated for the study. From each of the EA, ten PSUs were again systematically selected, giving a total of ten selected in all. Each of the 10 PSU was divided into four quadrants, and two households were randomly selected using a random number table for settlements in the urban area where houses were organized and arranged along streets or along the road or/and the ‘spine-bottle’ method – a statistical method where the enumerator goes to the centre of the location and spins and allow a bottle to settle and point to a particular direction. The enumerator then selects the first household which the tip of the bottle points at. At the end of the second stage, a total of 320 households were covered in the State (Table 3.2). Table 3.2: Number Northern zone Central Southern Total zone zone Enumeration area (EA) 7 4 5 16 Primary sampling unit (PSU) 10 10 10 30 Households selected in each PSU 2 2 2 6 Total respondents interviewed 140 80 100 320 The enumeration was conducted between 21 March 2017 and 12 April 2017. Copies of questionnaire were administered by research assistants coordinated by supervisors. Based on the research instrument (questionnaire) designed (Appendix, Table 1), codes were developed for easy processing and analysis using SPSS, Version 21. All the relevant ratios were computed, cross tabulation, tables and graphs generated, and analysis carried out using both SPSS Version 21 and Microsoft Excel softwares.

Empirical results and discussion Poverty incidence is one of the indicators used to measure absolute poverty in a population. It is simply defined as the proportion of the population with per capita income less than the per capita poverty threshold. Analysis of the data collected from our survey showed that the thresholds of food poverty and absolute poverty in the State were N96,912.1 and N135,133.9, respectively. N192,967 was the reference value for relative poverty. Going by the exchange rate of Naira to Dollar as of September 2017 of N361.5, the Dollar per day poverty for the State was determined to be N134,496.5 (Table 3.1).

Table 3.1: Poverty line for food poverty, absolute poverty, relative poverty and Dollar per day poverty for Kaduna State, 2017

Type Poverty line for Nigeria in Naira Poverty threshold for Kaduna (NBS, 2010) State in Naira (2017) Food poverty 39,759.49 96,912.1 Absolute poverty 54,401.16 135,133.9 Relative poverty 66,802.2 192,967 Dollar per day poverty 54,750 134,496.5* * An exchange of 24 September 2017 (N361.5 = $1) was used to compute the dollar per day poverty

The poverty incidence for the entire State as of 2017 was 64.4, meaning that more than two-thirds of people in the state live below the poverty line. If this ratio is translated to the actual proportion of the entire population of the State, we can state that out 8.3 million people projected to be in the State as of 2017, 5.3 million live below the poverty line. From Table 3.2, it is not difficult to observe that Kudan, Ikara and Kaduna North were the LGAs were the bulk of the poor people stay, while Kajuru and Soba are reported to the lowest incidence of poverty.

Table 3.2: Poverty numbers for Kaduna State by local government, zone, and sector, 2017 Estimated Population in Incidence of population poverty poverty (%) (million) (million) Ikara 72.3 262,800 190,004 Kubau 69.2 378,900 262,199 Kudan 76.2 187,600 142,951 Lere 62.1 458,600 284,791 Sabon Gari 64.5 393,300 253,679 Soba 51.2 393,00 201,216 Zaria 70.1 549,400 385,129 Chikun 62.8 502,500 315,570 Kaduna North 76.2 492,100 374,980 Kaduna South 71.8 543,600 390,305 Kajuru 50.8 148,200 75,286 Jaba 62.1 210,500 130,721 Jema’a 64.5 375,500 242,198 Kachia 57.3 340,900 195,336 Kagarko 60.3 322,700 194,88 Kauru 59.1 298,700 176,532 State average 64.4 8,252,400 5,315,061 Source: Field survey (2017)

The average incidence for both northern and central zone of the State recorded incidence slightly higher than the State average of 64.4, while the southern zone recorded 60.7. As for the distribution by sector, it would seem poverty is more prevalent in the urban than rural sector.

Poverty incidence in Kaduna State , 2017

Rural, 62.50% Urban, 69.50%

Southern , 60.70% Central , 65.40% Northern , 66.50%

Source: Field survey (2017)

Figure 3.1: Poverty incidence by sector and zone in Kaduna State , 2017 As pointed in the preceding section, relative poverty is the condition in which people lack the minimum amount, often expressed in monetary terms, needed to maintain the average standard of living in the society in which they live. In computing the relative poverty for the State, the various expenses of the household were summed up. Table 3.3 shows the breakdown of the individual household expenses and the per capita expenditure for the State. Table 3.3: Household expenditure share by item in Kaduna State, 2017 Item Per cent share Food purchase 42.9 Food own consumption 28.3 Total food share 68.2 Education share 6.8 Health share 12.3 Rent share 15.1 Non-food share 49.2 Total food and non-food share 347.3 Per capita expenditure 98.5 Source: Field survey (2017)

The households with expenditure greater than two-thirds of the total household per capita expenditure were classified as ‘non-poor’, whereas those with per capita expenditure below it were regarded as ‘poor’. Further disaggregation was done: households with less than one-thirds of total household per capita expenditure were further classified as ‘core-poor’ or ‘extreme poor’ while those with reported with per capita expenditure greater than one-third but less than two-thirds were classified as ‘moderate poor’. Table 3.4 shows the results of the classification of the poor in the State into the three categories defined previously namely, ‘non-poor’, ‘moderately poor’ and ‘extremely poor’. Ikara, Kudan, Zaria, Kaduna South and Kaduna North were the LGAsreported to host some of the most moderately poor people in the State, while Kajuru and Soba had the lowest figures. The geo-political analysis indicated that northern and central zone were home to the most ‘extreme poor’ in the State as they reportedly had ratios higher the State average of 36.1 (Table 3.4).

Table 3.4: Relative poverty: the non-poor, the moderately poor and the extremely poor in Kaduna State, 2017 Non-poor Moderately poor Extreme poor Ikara 27.7 31.7 40.6 Kubau 30.8 30.4 38.8 Kudan 23.8 33.5 42.7 Lere 37.9 27.3 34.8 Sabon Gari 35.5 28.3 36.2 Soba 48.8 22.5 28.7 Zaria 28.9 30.8 39.3 Chikun 37.2 27.6 35.2 Kaduna North 23.8 33.5 42.7 Kaduna South 28.2 31.5 40.3 Kajuru 49.2 22.3 28.5 Jaba 37.9 27.3 34.8 Jema’a 35.5 28.3 36.2 Kachia 42.7 25.2 32.1 Kagarko 39.7 26.5 33.8 Kauru 40.9 26.0 33.1 State average 35.5 28.3 36.1 Senatorial district

Food Poverty Relative Poverty Dollar per day Absolute Poverty

Senatorial district Poor Non Poor Non Poor Non Poor Non poor poor poor poor

Northern 35.6 64.5 61.4 38.6 66.5 33.3 59.0 41.0 Central 28.4 71.6 56.1 51.4 65.4 34.6 58.7 41.3 Southern 32.2 67.8 64.5 37.5 60.7 39.3 55.7 44.3 Sector Urban 38.3 61.7 48.9 51.1 69.2 30.8 63.6 36.4 Rural 43.2 56.8 56.7 43.3 62.5 37.5 72.4 27.6 Northern 33.3 29.2 37.3 Central 34.6 28.7 36.7 Southern 39.3 26.7 34.0 Sector Urban 30.2 30.7 38.1 Rural 37.5 27.4 35.1 Source: Field survey (2017)

Table 3.5 shows the breakdown of the poor in the state according to the classifications, ‘food poverty’, ‘absolute poverty’, ‘relative poverty’ and ‘dollar per day poverty’. It is not too difficult to notice that a positive correlation in the cross-sectional trends of absolute poverty and relative poverty and the conclusion that about two-thirds of people in the State and across location, zone and sector fell within the ‘poor’ category. The figures on food poverty show that only about one-third of the population in the State could not afford to live above the designated poverty line (Table 3.6). But for Dollar per day poverty, the situation was slightly better at the state level, because average percentage of the ‘poor’ who were living below the stipulated threshold was slightly above 50 per cent. When disaggregated along sectoral divide, it however turned out that higher number of people might have been living below the poverty line (Table 3.6). Table 3.5: Poverty numbers for Kaduna State by local government, zone and sector, 2017 Food Poverty Relative Poverty Dollar per day Absolute Poverty Location/region Local government Poor Non Poor Non Poor Non Poor Non poor poor poor poor Ikara 39.7 60.3 60 40 72.3 27.7 62.1 37.9 Kubau 31.2 68.8 67.8 32.2 69.2 30.8 59.3 40.7 Kudan 42.4 57.6 73.2 26.8 76.2 23.8 63.2 36.8 Lere 25.4 74.6 59.1 40.9 62.1 37.9 59.2 40.8 Sabon Gari 34.8 65.2 58.9 41.1 64.5 35.5 58.4 41.6 Soba 37.6 62.4 48.9 51.1 51.2 48.8 42.3 57.7 Zaria 38.1 62.9 62.1 37.9 70.1 28.9 68.3 31.7 Chikun 32.8 67.2 58.7 41.3 62.8 37.2 56.7 43.3 Kaduna North 21.8 78.2 54.3 45.7 76.2 23.8 69.2 30.8 Kaduna South 24.9 75.1 51.2 48.8 71.8 28.2 60.6 39.4 Kajuru 34.1 65.9 60.3 69.7 50.8 49.2 48.3 51.7 Jaba 25.8 74.2 61.5 38.5 62.1 37.9 57.8 42.2 Jema’a 26.7 73.3 62.1 37.9 64.5 35.5 56.4 43.6 Kachia 35.8 64.2 53.2 46.8 57.3 42.7 50.9 49.1 Kagarko 40.3 59.7 82.7 27.3 60.3 39.7 58.9 41.1 Kauru 32.5 67.5 62.8 37.2 59.1 40.9 54.3 45.7 State average 32.7 67.3 61.1 41.5 64.4 35.5 57.9 42.1

Table 3.6: Poverty numbers for Kaduna State by zone and sector, 2017 Table 3.6: Poverty numbers for Kaduna State by zone and sector, 2017

Source: Field survey (2017)

As there is yet no reliable and disaggregated data on the extent of inequality across the State, an attempt was made to provide a baseline by measuring the Gini Coefficient for each LGA in the sample designed for this study and on the basis of that extrapolate for the entire State and across it’s geo-political districts and sectors. The summary of the findings is presented in Table 3.7. The computed coefficient for all the LGAs ranged between 0.43 and 0.69. While Kauru in the Southern zone had the lowest coefficient, meaning that it in 2017 it had the lowest gap between the rich and the poor, while the greatest inequality was reported for Kaduna North. Overall, nine LGAs recorded Gini coefficient higher than the State average of 0.56.

Table 3.7: Income inequality in Kaduna State by local government, zone and sector, 2017

Location/region Gini coefficient, 2017 Local government Ikara 0.45 Kubau 0.53 Kudan 0.51 Lere 0.65 Sabon Gari 0.62 Soba 0.49 Zaria 0.52 Chikun 0.63 Kaduna North 0.69 Kaduna South 0.68 Kajuru 0.59 Jaba 0.49 Jema’a 0.54 Kachia 0.63 Kagarko 0.53 Kauru 0.43 State average 0.56 Source: Field survey (2017)

Figure 3.2 and Figure 3.3 show the distribution of inequality across senatorial districts and sectors in the State. The inequality in northern and southern zones was not as dramatically marked as in the central zone of the State. Differentials in income distribution appeared to be more profound when the analysis is carried out along sectoral lines. The Gini coefficients for urban and rural sectors were reportedly 0.67 and 0.52, respectively.

Gini coefficient for Kaduna State by sector, 2017

0.7 0.6 0.5 0.4 0.3 Gini coefficient 0.2 0.1 0 State Urban Rural average

Source: Field survey (2017) Figure 3.2: Gini coefficient for Kaduna State by sector, 2017

Gini coefficient for Kaduna State by zone, 2017

Southern

Central

Northern Gini coefficient, 2018

Senatorial district

State average

0 0.2 0.4 0.6 0.8

Source: Field survey (2017) Figure 3.3: Gini coefficient for Kaduna State by zone, 2017

The NBS (2016) projected population of 8,252,400 and breakdown by LGAs for Kaduna State were used as basis for the analysis of unemployment in this study. To arrive at the working population in the State, the total number and characteristics of persons in the 345 households sampled were first determined. 2,610 persons were reportedly counted as the total members of all the household’s members covered in the survey. Out of this number 79.8 per cent were within the economically active population in the study area. During the survey, respondents were required to indicate the availability of their household members for active work. Based on their responses, the population of those who were reportedly willing and able to work or were working was determined. They constituted 40.8 per cent of the working population. Those who indicated being engaged in any form of legal economic activities in the last 40 hours before the survey were classified as fully employed while those working for between 20 and 30 hours within the reference time period were classified as under-employed. Household members who worked either for between 1 and 19 hours in the last three weeks or doing nothing as at the time of the survey were classified as the unemployed. Table 3.8 presents the State-wide summary figures while Table 3.9 shows the breakdown by LGA, zone, sector and gender.

While Chikun and Kaduna South LGAs played host to the largest number of the employed in the State, Kagarko and Chikun had the two highest unemployment rates (Table 3.8). As of 2017, the State had 388 thousand people who were willing and able to work but could not find jobs. This number translates to an unemployment rate of about 21.3 per cent.

AGE GROUP POPULATION UNEMPLOYMENT Local 15-35 36-50 51-64 Total 2016 Working Labour Number Rate government Projected Population Force Ikara 35.7 10.6 3.5 49.8 262,800 130,874 53,134 7,598 14.3 Kubau 38.7 7.7 1.9 48.3 378,900 183,009 72,106 11,393 15.8 Kudan 38.8 8.1 2.9 49.8 187,600 93,425 38,491 8,891 23.1 Lere 37 11.4 3.2 51.6 458,600 236,638 79,534 12,885 16.2 Sabon Gari 36.3 10.9 4.7 51.9 393,300 204,123 86,956 18,522 21.3 Soba 35.1 9.3 2 46.4 393,000 182,352 68,564 11,930 17.4 Zaria 36.8 12.9 2.8 52.5 549,400 288,435 118,258 22,114 18.7 Chikun 39.7 15.4 5.4 60.5 502,500 304,013 136,502 38,903 28.5 Kaduna North 41.4 12.2 4.7 58.3 492,100 286,894 104,429 26,003 24.9 Kaduna South 38.8 13.2 6.7 58.7 543,600 319,093 140,401 30,607 21.8 Kajuru 40 12.6 4.1 56.7 148,200 84,029 27,141 4,967 18.3 Jaba 36.1 17.5 5.2 58.8 210,500 123,774 50,747 11,469 22.6 Jema’a 42.5 13.6 7.9 64 375,500 240,320 92,043 21,538 23.4 Kachia 40.2 12.7 3.3 56.2 340,900 191,586 82,382 19,607 23.8 Kagarko 39.2 12.9 2.9 55 322,700 177,485 72,059 19,528 27.1 Kauru 33.5 14.8 5.6 53.9 298,700 160,999 59,879 12,934 21.6 State 38.2 11.8 4.1 54.1 8,252,400 4,464,548 1,821,536 387,987 21.3 Senatorial district Northern 36.6 10.2 2.9 49.7 2,821,500 1,402,286 572,133 103,638 18.1 Central 39.1 11.6 4.3 55 3,011,600 1,656,380 675803 157,969 23.4 Southern 39.2 14.0 5.4 58.6 2,419,300 1,417,710 578,426 137,087 23.7 Gender Female 40.8 10.9 3.5 55.2 4035424 2,227,554 908,842 135,417 14.9 Male 35.6 12.6 4.7 55.2 4216976 2,327,771 949,731 89,275 9.4 Source: Field survey (2017)

Table 3.9: Breakdown of labour statistics by educational attainment and age groups in Kaduna State, 2017

LABOR FORCE Work 40 Hrs+ Work 20- Work 1-19 Work 0 Hr Total unemployed POPULATION 30 Hrs Hrs (Did nothing) Fully Under- Unemployed Unemployed Numbers Per cent employed employed All groups 1,821,536 1,362,509 310,714 74,683 313,304 387,987 21.3 Educational Group Never attended 540,996 327,322 91,821 14,019 107,834 121,853 22.5 Below primary 14,572 208,880 15 1,603 1,457 3,060 21.0 Primary 353,378 254,785 36,398 12,368 46,293 58,661 16.6 Secondary 633,894 412,665 142,626 38,668 39,935 78,603 12.4 Post-secondary 278,695 158,856 39,853 22,296 57,690 79,985 28.7 Age group 15-24 375,236 112,571 136,961 63,790 61914 125,704 33.5 25-34 539,175 336,984 35,046 11,862 155282 167,144 31.0 35-44 431,704 331,549 71,663 22,449 6044 28,492 6.6 45-54 302,375 237,969 21,166 10,361 32879 43,240 14.3 55-64 173,046 129,957 10,556 3,288 29245 32,533 18.8 Place of residence Urban 1,249,573 773,486 221,174 68,727 186,186 254,913 20.4 Rural 571,962 406,093 38,321 18,303 109,245 127,548 22.3

It is of interest to note that NBS (2010) put the unemployment figure for Kaduna State was 12.4 per cent. Thought it fluctuated substantially in previous years, it tended to increase through the 2001 – 2010 period. It may seem that the official for subsequent years after the 2010 were unavailability, however, this findings may lend credence to the conclusion reached by the United Nations Multi-dimensional Poverty Study (2015) which ranked Kaduna State, along with Zamfara, Bauchi, Niger, Gombe, Nasarawa, Jigawa, Edo, Yobe and Adamawa, as the ten states in the country with the highest unemployment numbers. Underemployed persons in the labour force (those working but doing menial jobs not commensurate with their qualifications or those in fulltime work and merely working for few hours) numbered 310,714 in the State. When disaggregated by zone, the analysis shows that the highest incidence of unemployment was more pronounced in the central and southern Senatorial district, all of which had rates higher than the State average. The rate for the northern zone was 18.1 per cent. As for the sectoral distribution, it would seem, unemployment was higher in the rural areas than in the urban sector. Table 3.8 also shows that unemployment exhibited serious gender bias in favour of the female household members in the State. While 9.4 per cent of males was reported as unemployed, about 15 per cent of their female counterparts were jobless. Further break down of the unemployment figures in the State revealed some fascinating feature of the situation. For the educational groups, those household members without formal education and those with post-secondary educational attainment constituted more than half of the unemployed population in the State. As for the age groups, the youngest of the economically active cohorts (15 - 24 years) was the hardest hit by joblessness in the State. It is also obvious that under-employment was a predominant phenomenon in the rural sector of the State’s economy within the reference period of the study (Table 3.9).

Concluding remarks The poverty incidence for the entire State as at 2017 was 64.4, meaning that more than two-thirds of people in the state lived below the poverty line. The breakdown of poverty figures by zone indicated that northern and central zone were home to the most of the ‘extreme poor’ in the State as they reportedly had ratios higher the State average of 36.1. The study also revealed that only about one-third of the population in the State could not afford to live above the designated poverty line. But as for Dollar per day poverty, the situation was slightly better at the state level, because average percentage of the ‘poor’ who were living below the stipulated threshold was slightly above 50 per cent. When disaggregated along sectoral divide, it however turned out that higher number of people might have been living below the poverty line. The average Gini Coefficient for the State as at 2017 was 0.56, meaning the income concentration among residents in the State was 56 per cent or otherwise interpreted as more than half of the population in the share all or some of the state’s income while the rest (46 per cent) possessed the rest or have nothing. The economically active or working age population (15 – 64 years of age) in the State as of 2017 was 4.5 million, with the northern and central zones playing host to 1,402,286 and 1,656,380 persons either working or actively seeking work. The Southern zone had a working population of 1.4 million.

The total number of persons in full-time employment (at least 40 hours a week) in the State was 1,362,509. While 8.3 per cent of that number represents person within the youngest working age group (15-24), 11.7 per cent was workers with post-secondary school qualification. The unemployment rate for the period ended 2017 was 21.3 per cent of the labour force in the State. With a rate of 28.5, Chikun Local Government Area had the highest computed figure for 2017, whereas Ikara was the LGA with the lowest rate (14.3). While 387,987 persons in the State were unemployed and 310,714 were classified as underemployed within the period under review, the total number for the two combined was 698,701. The survey findings also showed that 7.4 per cent of women within the labor force (age 15-64 and willing, able and actively seeking work) were unemployed, compared with 4.9 per cent of men within the same period. Underemployment was predominantly in the urban area (17.7 per cent of urban residents within the labor force) were underemployed (engaged in work for less than 20 hours a week), compared to 6.7 per cent of rural residents within the same period. As at 2017, 476,087 of urban dwellers within the labor force were unemployed and unemployed when compared with 165,869 persons of rural counterparts. The study also found that for the period under review, the unemployment rate for young people stood at 33.5 per cent for those aged 15 to 24, and 31.0 per cent for those aged 25 to 34. Similarly, unemployment tended to be higher for people within the labor force that have post-secondary school qualifications (79,985 persons as unemployed and 219,838 as combined unemployed and underemployed person in the State as at 2017).

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