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Monetary and Nonmonetary Causes of Urban Poverty in Sokoto Metropolis: A Descriptive Assessments

  • Farida Sani Nahuche
  • 1920-1927
  • Dec 23, 2023
  • Economics

Monetary and Nonmonetary Causes of Urban Poverty in Sokoto Metropolis: A Descriptive Assessments

Farida Sani Nahuche

Department of Sociology, Sokoto State University, Nigeria

DOI: https://dx.doi.org/10.47772/IJRISS.2023.7011152

Received: 27 October 2023; Revised: 08 November 2023; Accepted: 15 November 2023; Published: 22 December 2023

ABSTRACT

This study examines the monetary and non-monetary causes urban poverty in Sokoto metropolis using a survey dataset for a sample of four hundred and eight respondents. in the analysis, the study used a descriptive statistical technique in form of charts, mean and standard deviation. From the analysis on the monetary causes of poverty this study revealed that factors such as income inequality, persistent inflation, difficulties in accessing loan, macroeconomic shocks and lack of investment opportunities are the fundamental determinants of urban poverty in Sokoto Metropolis. Others include lack of savings and high rate of consumption, unemployment and underemployment, high debt burden, exchange rate depreciation, assets and income level of households and low rate of economic growth. On the non-monetary causes of urban poverty, this study however, attested those factors such as population growth, rural-urban migration, crime and violence, family size, low access to basic services, and level of education. Other non-monetary causes of urban poverty as indicated by this study are poor access to clean water, sanitation and hygiene, inadequate housing, lack of government support, diseases, climate change and corruption and political instability. Based on the findings, this study recommended that the government increase its spending in real sectors like manufacturing and agriculture. This is due to the sectors’ capacity to accommodate various worker types, which will lead to the creation of additional income-generating activities with a view to reducing poverty. The government and other relevant parties should invest more funding into human capital development programmes in the health, education, and, most importantly, entrepreneurial sectors. As a result, the productive capacity of the research region, the incidence of poverty, and the status of welfare will all improve. This will improve the availability of skilled employees in the real sectors. Finally, in order to improve the housing situation, the government should collaborate with financial institutions and wealthy individuals to construct new housing estates at subsidized rates.

Key words: monetary, non-monetary, urban poverty, Sokoto metropolis

INTRODUCTION

The rate of increase in poverty remains a major socioeconomic challenge in Nigeria despite the presence and abundance of productive human resources and natural resources such as crude oil, solid minerals, large water bodies, arable and cultivable land among others. In fact, there is no state in Nigeria that is not endowed with at least one productive natural resource in commercial quantity (Akinbode, 2013). But surprisingly, the country continues to record persistent episodes of poverty rate with majority of the populace living below poverty line (National Bureau of Statistic-NBS, 2020).

To address the poverty challenges government in Nigeria has introduced numerous programmes such as National Accelerated Food Production Programme and the Nigerian Agricultural and Co-operative Bank; Operation Feed the Nation; Green Revolution Programme; National Directorate of Employment (NDE), Directorate of Food, Roads and Rural Infrastructure (DFRRI); Family Support Programme and the Family Economic Advancement Programme. Others includes National Poverty Eradication Programme (NAPEP), Poverty Alleviation Program; Commercial Agricultural Development Project (CADP); Agricultural Transformation Agenda (ATA), which is a component of Transformation Agenda and AMCO borrowers among others. Regrettably, these programmes have failed to significantly reduce poverty in Nigeria owing to poor implementations and corrupt practices operation in the country.

However, the menace of poverty has been seen not only as a rural challenge but also an urban phenomenon. This due to the fact that, urban population is growing at a faster rate compared to the rural ones as a result of rural-urban migration and rising incidence of insecurity. It is estimated that, the growth rate of urban population will increase by almost twice the world’s population growth rate between 2003 and 2030 due to rural-urban migration (World Bank, 2004). The inflows of people from rural to urban areas is seen in developing countries like Nigeria as a helpful step needed to escape from poverty. Thus, the forgoing has negative consequences on few available social infrastructures. NBS (2011) added that poverty rate in the urban area rose to 61.8% in 2010 from 35.4% in 2004 in Nigeria. However, the recent report of National Bureau of Statistic release in 2020 shows that the urban poverty rose to 71.57%. Report further stated that Sokoto state is the poorest state in Nigeria with poverty headcount rate of 87.73% (NBS, 2020).

However, in analyzing the poverty situations, National Bureau of Statistic (2020) takes into cognizance the level of infrastructural development, economic base, literacy level, security and governance of the state. Furthermore, the few industrial establishment in Sokoto such as Cement Company of Northern Nigeria among others have a lot of problems that hinder them to provide employment opportunities for the urban population. These include high cost of production, lack of local material inputs, low productive capacity, interrupted power supply, nepotism among others. Thus, urban poverty is usually link with the problem of urban economic base and Sokoto experience is no exception.

However, there are few empirical studies (Shamaki, Rostman & Adamu, 2013; Dansabo, 2015; Mustapha, Yusuf & Abdullahi, 2019) concluded that are linked to poverty in Sokoto state. But the study of Shamaki, Rostman and Adamu (2013) focused on poverty and maternal health in Sokoto. Study of Dansabo (2015) focused on the assessment of developmental impact of poverty eradication programmes, while the study of Mustapha, Yusuf and Abdullahi (2019) focused on microfinance and rural poverty reduction. To the best knowledge of this study, there is no study that specifically investigated the causes of urban poverty in Sokoto metropolis. Thus, the objective of this study is to investigates the monetary and nonmonetary causes of urban poverty in Sokoto metropolis using a descriptive techniques of data analysis such as bar chart, pie chart, mean and standard deviation. However, understanding the causes of urban poverty in the state will help the government at all levels make sound policy decisions. As a result, the findings of this study will aid the government in developing policies that will address the root causes of poverty and reduce its prevalence. Given the aforementioned gaps, this study is divided into five sections. Following the introduction, section two presents a theoretical framework and review of related empirical studies. section three consists of data and methodology. Section four consists of results and discussions while section five comprises conclusions and recommendations.

LITERATURE REVIEW

There are two theories that underpin the conduct of this study. These are monetary and anthropometric theories of poverty. The monetary theory of poverty has been used by most economists and is the most frequently used measure of poverty developed by Booth and Rowntree in the 19th and early 20th centuries. The rationale behind the frequent adoption of this approach is that poverty is measured by looking at the income and utility-maximizing behavior of individuals (Laderchi, Saith, & Stewart, 2003). In addition, poverty is determined by looking at a deficiency in households’ income or consumption below a certain level of resources known as the poverty line and monetary indicator and a neutral derivation of a poverty line.

On the other hand, the anthropometric theory of poverty criticizes that income measures of poverty alone do not capture all dimensions of poverty. Thus, anthropometric measures represent more of people’s well-being because they measure the outcomes of income or consumption and check whether a person’s income is converted to its well-being. It has been argued that anthropometric measures are needed to adjust the conventional economic measures of poverty. This is because the economic measure is too narrow and does not adequately cover the facets of the standard of living captured by the anthropometric theory of poverty (Wakeyo & Derege, 2017). Therefore, the use of both monetary and anthropometric indices will capture more dimensions of people living standards that enable this study to cover adequate contents.

The related empirical studies were conducted by Esubalew (2006), Tesfaye (2006), Awan and Igbal (2010), Yonas et al, (2012), Etim and Udoh (2013) and Beshir (2017). These studies indicate that there are many factors that cause the incidence of urban poverty. For instance, Ebang (1986) examined the structure of urban poverty in Calaber metropolis Nigeria. He found that the people’s annual income, educational level, occupational distribution, residential status and psychological factors are the significant determinants of urban poverty. Furthermore, Esubalew (2006) investigates the causes of urban poverty in Amhara region of Ethiopia and found that average monthly income, family size, level of education and incidence of diseases as the significant determinants of urban poverty.

In additional development, Tesfaye (2006) conducted a study on urban poverty in Ethiopia and his results suggested that income growth and income redistribution are the useful instruments in reducing the poverty rate in the urban cities of Ethiopia. Similarly, Awan and Igbal (2010) estimated the causes of urban poverty in Pakistan using a sample of 330 households and found that employment in public sector, investment in human capital and access to public amenities reduces urban poverty while employment in the informal sector, greater household size and female dominated households increases the urban poverty incidence.

Yonas et al. (2012) added the volume of empirical findings by analyzing the causes of urban poverty in Ethiopia and their results suggested that households with history of poverty continue to perceive themselves as poor even if there is an improvement in their material consumption. Also, Beshir (2017) estimated the sources of urban poverty in Southern nations, Nationalities and Peoples’ region in Ethiopia. By applying a survey dataset of 5,015 urban households, found that marital status, family size, total dependence, education level, savings habit and energy sources as significant determinants of urban poverty in the region.

Ayoade and Adeola (2012) examined the effect of poverty on rural household welfare in Oyo state Nigeria. They found that the main causes of poverty are low-income level and lack of access to good health and house size. Also, Mustapha, Yusuf and Abdullahi (2019) investigate the effect of microfinance on rural poverty reduction in Goronyo Local Government Sokoto State. Their study suggested that microfinancing has significant positive effect on poverty reduction.

Apata, et al (2010) estimated the sources of rural poverty in southern states of Lagos, Ogun, Ondo, Osun and Ekiti Nigeria. Using a sample size of 500 small scale farmers, find that access to micro-credit, education, participation in agricultural workshops and seminars, livestock assets and access to extension services have significant influence on reducing poverty of the households. Finally, Dansabo (2015) assessed the developmental impact of poverty eradication programmes in Sokoto State using a survey dataset for a sample of 1888 households. His finding shows that poverty eradication programmes have insignificant impact on poverty reduction due to high level of poverty in the study area.

With case studies from North Sumatera, Novira et al. (2022) investigated the fundamental reasons of rice farmers’ poverty in Indonesia using qualitative research with in-depth interviews as the data collecting instrument. In the process, the authors interview agricultural office officials, rice farmers, and the head of the farmer union in the case study area The findings demonstrate that rice farmers, like all farmers in Indonesia, lack suitable facilities for processing and adding value to their grain. They also do not have market access and have no pricing control.

In addition, Gambo, Shafri, and Yusuf (2022) used an annual dataset from 1996 to 2019 to conduct a geographic study of Nigeria’s multidimensional poverty and to discover the geospatial distribution pattern of poverty in Jigawa State. According to the findings, physical and natural environmental resources play a key influence in the state’s high poverty rate. Natural drainage, good soil, flat geography, and plant patterns all help to reduce poverty in various sections of the state. Furthermore, using data from the National Bureau of Statistics (NBS) annual reports, Abubakar et al. (2023) investigated the factors responsible for the persistence of poverty in Nigeria. Using content analysis, their findings reveal that the persistence of poverty in Nigeria is linked to persistent negative economic, political, and social forces that have stymied progress in the fight against poverty.

DATA AND METHODOLOGY

The survey research design was used in this study to identify and analyse the monetary and non-monetary causes of urban poverty in Sokoto metropolis, Sokoto State, Nigeria. The survey analysed data from primary sources. A structured questionnaire was also used to obtain primary data. The population of this study is the entire households in Sokoto metropolis. The Sokoto metropolis is made up of Sokoto North, Sokoto South, and some parts of the local government units of Kware, Wamakko, and Dange Shuni. The target LGAs have a population of 1,265,400, according to the National Population Commission (NPC). The sample size is 427 given the population of the study. In addition, the sample size was generated using a Raosoft sample size calculator accessible at www.raosoft.com, the sample size was calculated with a margin of error of 5% (0.05) and a confidence level of 95%. Furthermore, the respondents for this study were chosen using a random sampling technique.

This study employed a Likert scale in the form of Strongly agree, Agree, Disagree, and Strongly disagree in the survey questionnaire. The decision rule states that an average of 2.5 or above is regarded agreed, while an average of 2.49 or lower is considered disagreed.  Yusuf, Gambari, Daramola, Badmus, and Isiaka (2018) determined the mean scores for four-point questions using a mean of 2.5 as a criterion. As a result, the mean criteria of 2.5 was computed by dividing the total of 4+3+2+1 by 4. Finally, the data was analysed descriptively utilizing data analysis techniques such as basic percentages, tables, charts, mean, and standard deviation.

RESULTS AND DISCUSSION

This section offers and analyses empirical findings from an investigation into the monetary and nonmonetary drivers of urban poverty in Sokoto metropolis. Four hundred and twenty-seven (427) questionnaires were distributed to respondents in the research region. However, only 408 questionnaires were returned to the responders, with the remaining 19 (19) missing. This accounts for 4.45% of all surveys received. This also suggests that the respondents responded at a rate of around 95.55%, which is more than acceptable for establishing broad generalizations for the research. As a result, the findings are separated into two sections: the first comprises biodata on the respondents, while the second discusses the monetary and non-monetary causes of urban poverty in Sokoto Metropolis. Starting with biodata, the results are summarized and reported in Figures 1–4.

 

         

Figure 1: Age of the Respondents.                           Figure 2: Gender of Respondents.

According to Figure 1, 204 (50%) of respondents are between the ages of 25 and 34, 123 (30.1%) are between the ages of 35 and 44, 40 (9.8%) are between the ages of 45 and 54, and 41 (10%) are between the ages of 55 and above. This suggests that the majority of responders are between the ages of 25 and 34. Furthermore, Figure 2 demonstrated that out of the 408 (100%) respondents in the sample survey, 60% (245) are male and 40% (163) are female. This means that a high percentage of the respondents in this survey are men.

 

                     

Figure 3: Level of Education of the Respondents.        Figure 4: Occupation of the Respondents. 

Figure 3 displays information about the respondents’ educational level. According to the findings, 82 (20.1%) of the respondents held senior secondary school certificates, 163 (40%) held a National Diploma (ND) or a Nigeria Certificate of Education (NCE), 122 (29.9%) held a degree or HND, and 41 (10.1%) held a Master’s degree or a PhD. As a result, the results suggest that the majority of respondents had an ND or NCE.  Furthermore, Figure 4 reveals that out of the 100% (408) sample survey of respondents’ occupations, 50% (204) are public employees, 40% (163) are in business, and 10% (40) are engaged in farming activities. As a result, out of the sample survey’s total respondents, 50% are public servants, making up the largest percentage of respondents. However, the results of the monetary and non-monetary causes of urban poverty in Sokoto metropolis is presented in Table 1 and 2 respectively.

Table 1: Monetary causes of Urban Poverty
S/N Statements Mean Std. Dev. Decision
1. Income inequality 2.70 0.78 Agree
2. High inflation 3.10 0.54 Agree
3. Difficulties in accessing loan due to high interest rate 3.20 0.75 Agree
4. Macroeconomic shocks and policy failure 3.30 0.46 Agree
5. Lack of investment and opportunities to generate income 3.40 0.49 Agree
6. Lack of savings and high rate of consumption 3.20 0.87 Agree
7. Unemployment and underemployment 3.50 0.50 Agree
8. Over indebtedness (high debt burden) 3.10 0.95 Agree
9. Exchange rate depreciation 3.30 0.46 Agree
10. Assets and income level of household 3.40 0.66 Agree
11. Nature (low) rate of economic growth 3.60 0.49 Agree
Cumulative Mean 3.25
Decision Mean 2.50
Source: Field survey, 2023.

In Table 1, the results show that monetary factors are among the causes of urban poverty in Sokoto metropolis. This is because the cumulative mean 3.25 is greater than the decision mean 2.5. This implies that income inequality, persistent inflation, difficulties in accessing loan, macroeconomic shocks and lack of investment opportunities are the fundamental drivers of urban poverty in Sokoto Metropolis. In addition, lack of savings and high rate of consumption, unemployment and underemployment, high debt burden, exchange rate depreciation, assets and income level of households and low rate of economic growth are the main monetary causes of urban poverty in the survey area. The foregoing findings are in agreement with works of Ruggeri et al., (2003), Ebang (1986), Tesfaye (2006), Bashir (2017) and Yusuf and Abdullahi (2019) who found that monetary factors such as household’s assets, income and among others are the main causes of poverty in their respective study areas.

Non-monetary causes of urban poverty, on the other hand, were investigated and the results are equally shown in Table 2.

Table 2: Non-Monetary causes of Urban Poverty
S/N Statements Mean Std. Dev. Decision
1. Population increases 3.20 0.87 Agree
2. Rural-urban migration 3.20 0.60 Agree
3. Crime and violence 3.40 0.49 Agree
4. Household composition and size 3.60 0.67 Agree
5. Poor access to basic social services such as school, hospital etc. 3.10 0.95 Agree
6. Household level of education 3.20 0.40 Agree
7. Poor access to clean water, sanitation and hygiene 3.30 0.64 Agree
8. Nature of occupation and inadequate housing services 3.40 0.80 Agree
9. Lack of government support and economic exclusion 3.20 0.87 Agree
10. Health/diseases and insufficient capability 3.20 0.60 Agree
11. Climate change and environmental degradation 3.60 0.80 Agree
12. Corruptions and political instability 3.60
Cumulative Mean 3.33
Decision Mean 2.50
Source: Field survey, 2023.

As reported in Table 2, non-monetary indicates constitute some of the causes of urban poverty in Sokoto metropolis. This is because the cumulative mean 3.33 is greater than the decision mean 2.50. This implies that increase in population, rural-urban migration, crime and violence, family size, low access to basic services, and level of education are the recognised causes of urban poverty in Sokoto metropolis. Additionally, poor access to clean water, sanitation and hygiene, inadequate housing, lack of government support, diseases, climate change and corruption and political instability are also the drivers of non-monetary causes of urban poverty in Sokoto metropolis. The findings in this study agreed with works of Wokeyo and Derege (2017), Esubalew (2006), Awan and Igbal (2010), Yonas et al., (2012) and Ayoade and Adeola (2012) who reported that non-monetary factors such as family size, low access to basic services, level of education and so on are the main causes of poverty. 

CONCLUSIONS AND RECOMMENDATIONS

From the results, this study concludes that both monetary and non-monetary factors are the causes of urban poverty in Sokoto metropolis. From the monetary side, the factors such as income inequality, persistent inflation, difficulties in accessing loan, macroeconomic shocks and lack of investment opportunities are the fundamental determinants of urban poverty in Sokoto Metropolis. Other monetary determinants of urban poverty according to the findings are lack of savings and high rate of consumption, unemployment and underemployment, high debt burden, exchange rate depreciation, assets and income level of households and low rate of economic growth. From the non-monetary causes of urban poverty this study concluded that factors such as population growth, rural-urban migration, crime and violence, family size, low access to basic services, and level of education. Other non-monetary causes of urban poverty as indicated by this study are poor access to clean water, sanitation and hygiene, inadequate housing, lack of government support, diseases, climate change and corruption and political instability. According to its conclusions, this research advised that the government increase its spending in real sectors like manufacturing and agriculture. This is due to the sectors’ capacity to accommodate various worker types, which will lead to the creation of additional income-generating activities with a view to reducing poverty. More funds should be channeled by the government and other relevant parties on human capital development initiatives in the health, education, and notably entrepreneurial sectors. As a result, the study area’s productive capacity, the prevalence of poverty, and the state of welfare will all improve. This will increase the amount of skilled labour available in the real sectors. Finally, the government should work with financial institutions and affluent individuals to build new housing estates at subsidized costs in order to ameliorate the housing situation. 

REFERENCES

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