Adewunmi O. A.*
Entrepreneurs handle the establishment and expansion of a business. The process by which a person or group of people finds a business opportunity, gathers, and uses the resources needed to take advantage of it is known as entrepreneurship. Entrepreneurship is when someone acts on an idea they have, usually to provide a new product or service that disrupts the market. Although entrepreneurship typically begins as a tiny firm, the long-term goal is far bigger: to find a fresh and creative way to gain market share and make large profits. An entrepreneur is a person who owns, plans, and runs a business; in doing so, they take on the risk of either being profitable or losing their investment. Many people view entrepreneurship as the engine and steward of local and national economies. It is regarded as the most advantageous path to boost GDP and new job creation (Parker, 2004). According to Bello (2022), "as more countries move towards fostering entrepreneurship, the evidence is mounting that they represent an effective response for countries wanting to strengthen their economy's ability to create jobs when implemented comprehensively." According to Eze (2011) and Ade (2021), entrepreneurship has a favorable effect on economic development, and the notion that entrepreneurship and economic growth are favorably correlated has certainly existed since Schumpeter's early writings. According to Schumpeter (2016), entrepreneurship is about innovation since novel combinations of inputs of production, such as hired labor, are introduced by entrepreneurs, and as the number of entrepreneurs rises, economic growth also rises. Their abilities and capacity for innovation are the reason for this favorable outcome. For example, according to Balthelt (2019), entrepreneurs are able to effectively increase productivity by discovering new ways to combine current assets, market demands, and niches. Additionally, entrepreneurship, according to Acs and Audretsch (2019), promotes economic growth and diversity, fosters cooperation, creates new networks, facilitates more fluid information flow, and introduces significant innovations by breaking into markets with novel goods or production techniques. Scholars have recognized a variety of entrepreneurship features in the literature. According to [Kirzner, 2019; Schumpeter, 2016; Thompson et al, 2021], an entrepreneur is a planner, risk-taker, organizer, leader, and, as a result, an economic builder or developer, innovator, arbitrator, and problem-solving nature. His or her entrepreneurial activities are said to increase productivity and competitiveness, innovate and imitate, and prevent rent seeking, monopoly exploitation, and economic stagnation. Due to the belief that entrepreneurs must handle the most difficult business duties, entrepreneurship has historically been linked to the actions of private sector workers. The entrepreneur is ultimately in charge of ensuring that the work is completed, even though others may work for the company's manager and owner. However, with the majority of governments worldwide becoming more market-oriented, there is mounting evidence that the idea and practice of entrepreneurship have a place in public sector enterprises (Adams, 2022). In conclusion, entrepreneurship development is a transformational strategy that extends beyond creating a network of support for entrepreneurs. In order for people to benefit from entrepreneurship, it also involves transforming them and establishing entrepreneurial networks. In order to have a beneficial effect on the growth of the economy, it also entails supporting governmental policies that invest in the development of entrepreneurship (Markley, 2022). Because of its influence on economic growth and productivity, technical, vocational, and entrepreneurial education has been a crucial component of national development plans in many nations (Wenny, 2022). It is focused on gaining the information and abilities necessary for work and long-term financial stability. Vocational and technical education departments in secondary schools in developed countries help students get ready for the workforce; this was one of the reasons the then-education minister introduced the 6.3.3.4 educational system in 1983 (Fafunwa, 2022). Organizations in development-conscious countries invest billions of dollars annually on programs focused at skill upgrading and employee retention because trained personnel play a significant role in organizational growth and development. In order to create jobs in the modern, "knowledge-driven" global economy, educational programs must impart not just academic knowledge and job skills but also problem-solving abilities, critical and creative thinking, and socially conscious individuals (Ayo, 2022). Achieving full employment is one of every economy's main objectives. In emerging nations, especially those in Africa where there is extreme poverty and rising unemployment rates, achieving this macroeconomic goal has continued to be a topic of discussion. Numerous strategies, programs, and measures, including the National Economic Empowerment and Development Strategy (NEEDS), National Directorate of Employment (NDE), Structural Adjustment Programme (SAP), Seven-Points Agenda, Transformation Agenda, SURE-P, and Economic Recovery and Growth Plan (ERGP), have been proposed by previous and current administrations in an effort to address unemployment and increase job creation in Nigeria (Oni, 2023). Low or no income and, thus, low or bad living standards are the results of unemployment. For the individual, his home, and society as a whole, this has significant economic, social, and political ramifications (Peter, 2022). Adebayo (2019) investigated the effects of unemployment on postsecondary graduates in a range of fields, including the length of time they spent looking for work across states and regions and the suitability of the position held by those who had found their first job. Essentially, Nigeria's unemployment issue seems to be complex, which makes it historically distinct and open to a range of economic analysis. Along with the consequences for the labor market, this study will look at the uniqueness and multidimensional nature. According to Todaro and Smith (2018), the high rate of urban unemployment is caused by the ongoing migration of young people and economic activity from rural to urban areas. In Nigeria, as in the rest of Africa, unemployment is one of the most urgent social issues, both because it is presently significant and because it could get worse in the future. However, the majority of this unemployment occurs in metropolitan areas, and young people—especially those with some education—and young women bear a disproportionate amount of the burden. This is explained by a number of things. Demographics comes first. The overall population is growing quickly, but so is a situation that is uncommon in other parts of the world (African Employment Report, 2018). A second aspect is the massive growth in school enrollment, which has led to a rise in the number of school dropouts looking for employment. Due to their inexperience, recent school dropouts are the first to suffer during difficult employment circumstances. The degree to which policies influence the pattern of any development and its ability to create jobs is one of the other policy-related aspects. Because they either help or hinder the creation of jobs, policies pertaining to land ownership, taxes, salaries, education, technology, and a variety of other topics are crucial. High rates of population growth, slow economic growth, the failure of any growth to create a proportionate number of jobs, and the absence of fundamental economic transformation are all contributing factors to the greater unemployment issue. Any plan for resolving the unemployment issues must therefore take into consideration the forces that are at play on both the supply and demand sides of the labor market. This includes, at the very least, methods to quicken the pace of economic expansion. But it is now widely known that while growth is important, it is insufficient to increase employment. Stated differently, it must be a labor-intensive expansion. It is also necessary to implement policies that are expressly intended to support employment of women and youth, as well as the non-farm rural sector and the informal sector. Additionally, a thorough evaluation of the educational system is necessary, particularly in regards to curricula. Unemployment usually occurs when there is a greater supply of labor than there is demand for it at the going rate of pay. Thus, it is possible to examine the causes of unemployment from both the supply and demand sides of the labor market. On the supply side, Nigeria's urban labor force is expanding quickly due to rural-to-urban migration. According to Adebayo (2019), push-pull factors, such as the pressure caused by the man-to-land ratio in rural areas and the occurrence of severe underemployment due to seasonal climate fluctuations, are typically used to explain rural-urban migration. In Nigeria, the factors are exacerbated by the dearth of infrastructure, which deters people from choosing to live in rural areas. The pull factors include a large wealth gap between rural and urban areas that favors urban residents and a higher likelihood of finding profitable work in the metropolis. The concentration of social amenities in metropolitan areas is an additional factor. This suggests that rural areas are frequently overlooked when it comes to the distribution of social and economic possibilities. The economic slowdown in the 1990s and 2000s was the cause of the high and growing jobless rates during that time. In addition to discouraging new investment, the economic downturn compelled the government to enact stabilizing measures, such as import restrictions. Since the majority of manufacturing businesses rely heavily on imports, this import limitation forced many of them to run below installed capacity, which led to the closure of most of them or the layoff of a sizable section of their workforce. For example, according to the Manufactures Association of Nigeria (MAN) survey of manufacturing companies, 61.0 percent of the companies were short-staffed for varying durations of at least three months, and between 63.0 and 63.9 percent of the disengaged over 100 workers (CBN, 2003). Due to this development, it was quite difficult for recent school dropouts to find employment. According to Raheem (2007) and Ohiorhenuan (2018), government statistics exclusively publish reported open unemployment. Most persons who were dissatisfied with their job search or employment declined to register, which results in a glaring underestimation of the number of unemployed people. Additionally, Okigbo (2019) notes that a significant contributing cause to the underestimating of unemployment in Nigeria is the definition of labor force used in the Nigerian labor force statistical survey, which excluded those under the age of 15 and those over 55 who were still employed. As previously said, Nigeria's current focus on university education limits economic options for people who are more focused on the workforce than academia, which raises young unemployment. The public typically believes that students who enroll in vocational and technical schools are incapable of pursuing formal academic studies at higher education institutions. However, not everyone requires a college degree. Regretfully, a person's ability to develop in their career and gain social respect in Nigeria is heavily influenced by the number of degrees they have earned. Young people in society are not excited about technical and vocational schools due to negative public conceptions of blue-collar jobs. These institutions also lack trained lecturers, operational workshops, and hands-on application equipment. Because they lack the skills that companies and self-employed people need, youth unemployment in Nigeria has been on the rise. According to the Daily Trust (November 26, 2008), the federal government recently admitted that 80 percent of Nigeria's youth are unemployed and 10 percent are underemployed. Others have encouraged the kids to turn away from "social vices" and become "entrepreneurs" (Thisday, March 17, 2009). The low caliber of graduates from the country's educational institutions has occasionally been a source of concern for Dr. Sam Egwu, the previous minister of education. Without putting sensible policies into place to build a brighter future, the political leaders are adept at listing fixes for Nigeria's issues and forecasting the future. But according to business guru Peter Drucker, "if you want to predict the future, create it" (quoted in Wilson and Blumenthal, 2018:1). Without giving them the necessary tools and resources, it is sufficient to urge young people to avoid "social vices" and become productive citizens and "entrepreneurs." The creation of job possibilities for citizens is a key component of growth. Therefore, the presence of suitable and sufficient employment serves as an indicator of the health of an economy. But in Nigeria, unemployment is a recurring and expanding issue. In the past, protracted economic crises made matters more difficult. We use a variety of secondary data sources, including the Nigerian statistical fact sheet on economic and social development and the National Bureau of Statistics 2008, to analyze the current state of unemployment in Nigeria.
AIM OF THE STUDY
Analyzing the effect of entrepreneurial development on the youth employment rate in Abeokuta, Ogun State, Nigeria, is the aim of this study.
Specifically, this study aimed to do the following:
i. To determine how the youth empowerment program affects the rate of youth employment.
ii. To ascertain how youth training affects the rate of youth employment.
iii. To examine how technical and vocational education affects the rate of young employment.
iv. To look at the connection between the rate of innovation and the rate of young employment.
v. To evaluate the combined impact on the youth employment rate of youth empowerment programs, youth training, technical and vocational education, and innovation rate.
RESEARCH QUESTIONS
i. How does the youth empowerment program affect the rate of youth employment?
ii. Does the rate of youth employment increase with youth training?
iii. What was the relationship between the young employment rate and technical and vocational education?
iv. How does the rate of innovation affect the rate of young employment?
HYPOTHESES
H01: The rate of youth employment in Abeokuta is unrelated to youth empowerment programs.
H02: Abeokuta's young employment rate is not influenced by youth training.
H03: The rate of youth employment in Abeokuta is uncorrelated with technical & vocational education.
H04: The rate of innovation and the rate of youth employment are unrelated.
SCOPE OF THE STUDY
The youth population of Computer Village, Ibara, Abeokuta, served as the study's main source of information. They actively participated in the collection of primary data through questionnaires, interviews, and observations. Through direct interactions with the young people at the Computer Village, the study uses a strong primary data gathering methodology. In order to obtain firsthand knowledge about their experiences, difficulties, and viewpoints regarding employment and the growth of entrepreneurship, systematic interviews and surveys must be conducted. Furthermore, casual conversations and observations were used to enhance the qualitative components of the main data. Secondary data was widely used in conjunction with primary data collecting to give the study a historical and cultural backdrop. From 1980 to 2024, the study examined professional insights, scholarly assessments, and entrepreneurial viewpoints on youth employment and the growth of entrepreneurship in Nigeria.
LITERATURE REVIEW
Since Cantillon initially developed and proposed the concept of entrepreneurship in the middle of the 18th century, several authors have offered varying meanings of the term, according to Daur (2011). According to Ote (2009), the majority of these categories are predicated on how entrepreneurship is conceptualized across a range of academic fields, including economics, sociology, and psychology. As a result, various entrepreneurs have diverse definitions of entrepreneurship. The definitions of entrepreneurship that relate to the various theoretical frameworks and the empirical measurements that are relevant to the work are highlighted for the purposes of this study. In this context, the definition prioritized the role that entrepreneurship plays in fostering sustainable economic growth. Richard Cantillon divided economic agents into three groups in the 18th century: wage earners, landowners, and financiers. This is when the idea of entrepreneurship first emerged. In contrast to wage and rent earners, he initially viewed entrepreneurs as a factor of production who are in charge of the exchange and circulation of goods and services within the economy and who also generate an uncertain profit. Stough (2016) defines entrepreneurship as a process of information revelations that provide a dynamic externality that provides market information to potential future market entrants, outside firms, and lenders. For the majority of African countries, entrepreneurship is a veritable channel of reducing poverty. The impact of information technology on entrepreneurship has also shed additional light on the definition of entrepreneurship. According to Schumpeter's definition, which is adopted in this study, entrepreneurship is the act of spotting and seizing opportunities through ongoing initiative and innovation in the face of risk and uncertainty in order to either create or reorganize the available resources in a way that can create jobs for long-term economic growth. Bello (2022) asserts that the core of entrepreneurship is innovation, as entrepreneurs create new combinations of production variables, such as hired labor, which boost economic growth. Balthelt (2019) goes on to show how entrepreneurs innovate by finding new markets and niches, combining preexisting assets in novel ways, and increasing productivity. According to Ayo and Adam (2021), entrepreneurship stimulates economic growth and diversity, makes it easier to build networks, fosters collaboration, enables the flow of information, and provides crucial innovations through the introduction of new goods or manufacturing techniques. One essential element is entrepreneurship training, which is given to people who want to start their own businesses with the goal of making money. According to Odah (2019), entrepreneurship is defined as practical creativity that combines opportunities and resources in new ways to succeed in the economic world. Similar to this, Emmanuel (2022) emphasizes opportunity creation and social requirements by defining entrepreneurship as the readiness and capacity to recognize investment possibilities, launch businesses based on them, and effectively manage them. In order to stimulate employment, accelerate the implementation of universal primary education, reduce poverty, and advance gender equality, Shane and Venkataraman (2022) stress that entrepreneurship training entails identifying sources of opportunities as well as processes of discovery, evaluation, and exploitation. The ability to recognize environmental resources and impart new ideas to improve creativity, invention, beliefs, and recombination skills are among the results of entrepreneurship education.
(i) Entrepreneurship Development
The process of improving entrepreneurs' knowledge and abilities in the areas of business venture development, management, and organization while taking associated risks into consideration is known as entrepreneurship development (UNESCO & ILO, 2022). This is accomplished by emphasizing entrepreneurial aptitude through training sessions and initiatives. If you choose to pursue this career path, you will be helping aspiring company owners develop their skills and overcome the challenges they face in starting their enterprises (UNESCO & ILO, 2022). The process of improving entrepreneurial knowledge and abilities through a structured training program is known as entrepreneurship development. It covers the study of business dynamics, entrepreneurial behavior, and the growth and development of businesses. Increasing the knowledge and expertise of current entrepreneurs and inspiring others to start their own business are the goals of entrepreneurship development programs. In the end, it contributes to the growth of such individuals within an economy (UNESCO & ILO, 2022). Training those who want to start their own business or grow their current one is the main goal of entrepreneur development. Additionally, it focuses more on promoting innovation and assessing an organization's potential for growth. New businesses benefit from this development process by performing better, achieving their objectives, and growing. Consequently, a country's economy likewise gets better. Additionally, it helps business owners better manage and grow their company while overcoming the financial risks involved. An economy's unemployment issue is lessened as the rate of entrepreneurial venture creation rises. It also improves market competition and lessens the problem of stagnation. The goal of such a process is to increase an entrepreneur's and his or her venture's competency. As a result, it raises the bar for entrepreneurship and inspires more people to pursue it. The strategic process of entrepreneurship development uses a variety of instruments that focus on the individual's skill development in a number of ways (UNESCO & ILO, 2022).
(ii) Employment
According to Merriam-Webster (n.d.), employment is the act of hiring someone or something, or the state of having a job. Full-time According to the World Bank (2018), employment is any job, or combination of jobs, where a person does the entire regular work week as required by the governing authority or receives the full salary for the position. Part-time Employment is defined as a job in which a worker completes half or less of the typical workweek and receives no more than half of the rate that is appropriate for the position if it is part of a graded salary schedule (World Bank, 2018). In order to help people with disabilities find and keep jobs in competitive or customized employment environments, supported employment entails giving them continuous assistance, making sure the work is integrated, and paying at least the minimum wage (World Bank, 2018). People with severe disabilities who might not have historically been able to find competitive employment are the focus of this strategy (World Bank, 2018). According to the World Bank (2018), customized employment is a strategy that involves individualized job tasks and reasonable adjustments in order to tailor the employment relationship to the needs of the employer and employee. Rehabilitative employment does not include full-time performance of all the responsibilities of a regular vocation, but it does include work for which a person's education, training, or experience is properly fit, subject to clearance by a doctor or qualified specialist (World Bank, 2018). Temporary Employment and Transfer: Temporary employment is defined as hourly, limited-duration positions that do not require permanent status, whereas a transfer is the movement of a permanent employee to a position that is within the same pay range (World Bank, 2018). By strengthening business settings, boosting educational and vocational training, and encouraging entrepreneurship and equal opportunities, youth employment initiatives seek to solve youth unemployment (Okigbo, 2019). Economic stability and development are significantly impacted by youth unemployment worldwide, with young women frequently experiencing more obstacles (Okigbo, 2019).
METHODOLOGY
By dividing the entire "Abeokuta" region into a few local governments and then into settlements inside those local government areas as geographical clusters, the researchers employed area sampling. Because the researchers lacked a list of the people in question, they decided to use area sampling (Sam, 2018).
Data Reliability Test
The dependability or consistency of the data used and the events in this research project were tested using Cronbach's Alpha. The findings indicate that 82% of the data utilized in this investigation is consistent. As a result, the study's data is highly trustworthy.
Model Specification
Important macroeconomic factors and indicators are included in the model to support the investigation's emphasis. The logit regression model used in the analytical framework is shown as follows:
LogYER=β0+β1LogYEMP+β2LogYTRN+β3LogTVED+β4LogINOR+μ __(1)
Where:
YER=Youth employment rate
YEMP = Youth empowerment programme
YTRN = Youth training
TVED = Technical and vocational education
INOR = Innovation rate
β0 = Intercept
β1, β2, β3, and β4 = Partial slopes of the regression model
µ = Stochastic error term.
A thorough investigation of the connection between Nigeria's young employment rates and the growth of entrepreneurship is made possible by this model framework. A comprehensive understanding of the factors impacting young employment in Nigeria is ensured by the inclusion of government spending and innovation rates. While the stochastic error term (μ) takes into consideration unobserved factors influencing the young employment rate, the model's coefficients (β1 to β4) shed light on the individual effects of each variable. This exacting model specification serves as the cornerstone for a thorough examination of the study hypotheses and advances a sophisticated comprehension of the complex connections between youth employment and entrepreneurial development in Nigeria.
Logit Regression Model
Logit regression (more precisely, logistic regression) is often used in medicine with the aim of, for example, testing a certain drug (predictor) for its effectiveness (outcome variable - 1 / effective; 0 / ineffective), and also in natural sciences (Sufahani & Jun 2020). However, it is very rarely used in education sciences, especially in pedagogy, although there are justifications for its application (Joyami & Salmani, 2019; Andegiorgis, 2020; Niu, 2020). The truth is that we frequently only have categorical or dichotomous dependent variables in our research designs, which prevents us from using tests for complex relationships between variables (chi square is typically the only test used when the dependent variable is categorical). But logistic regression in this case allows us to investigate the predictive role even though the dependent variable is categorical (Kim, Song, Kim, Lee & Cheon, 2018; Ozvurmaz, 2016). By fitting data to a logistic curve, logistic regression calculates the likelihood that an event will occur by analyzing the relationship between several independent variables and a categorical dependent variable. Logit regression is actually a nonlinear regression (Kim et al., 2018). Binary logit, which is used when the dependent variable has only two categories, and multinomial logit, which is used when the dependent variable has more than two categories, are the two basic categories into which logistic regression can be separated. The maximum likelihood is the basis for logit regression, not residuals (OLS), a regression line that minimizes the sum of squares, or R2. In a normal distribution, the maximum likelihood of σ is the normal distribution's standard deviation (curve width), and the maximum likelihood of µ is the location of the normal distribution's center. The log-likelihood is based on summing the probabilities associated with the predicted and actual outcomes (Said, Salman & Elnazer, 2019), that is, the goal is to find the best linear combination of predictors to maximize the likelihood of obtaining the observed outcome frequencies. Said et al. (2019) indicates that log likelihood is analogous to the residual sum of squares in multiple regression due to the fact that it is an indicator of how much unexplained variance remains after the model is set (this is evident from LL values which if high indicate a poorly fitting model). Since -2LL has a chi square distribution that is better suited for comparison (χ2 = -2 (Constant –LLfull model), LL is typically multiplied by -2. The fundamentals of computing Logit requires knowledge of probability, odds, and log odds, among other statistical processes. Probability is the ratio of something happening (event occurring) to everything that could happen (occurs), and odds are the ratio of something happening to something not happening (p / 1-p).
Binary Logit Regression Model
If the dependent variable is binary (dichotomous) and we want to examine the relative impact of continuous and/or categorical independent variables on the dependent variable as well as evaluate the interaction effects between the independent variables, binary logit regression is the preferred method. The impact of independent variables is typically described in terms of odds since logistic regression computes the probability of an event occurring over the probability of an event not occurring. The mean of the response variable "y" in terms of an explanatory variable x is modeled in relation to p and x using the logistic regression equation.
y= α+βx _ (2)
Unfortunately, extreme values of x will result in values α+βx that do not fall between 0 and 1, making this a poor model. The logistic regression solution to this problem is to transform the odds using the natural logarithm (Peng, 2002). The natural log odds are modeled using logistic regression as a linear function of the explanatory variable.
Logit y=lnodds
= Inp(y=1)1-p(y=1)= α+ βx __ (3)
That is,
ln p-In1-p=logit (y) _(4)
Where x is the explanatory variable and p is the probability of the desired outcome. "α" and "β" are the logistic regression's parameters. The basic logistic model is this. By taking the antilog of equation (5) on both sides, the following equation can be used to predict the likelihood that an outcome of interest will occur:
p = P (Y = desired result / X = χ, a particular value)
= ea+βx1 + ea+βx = 11 + e-(a+βx) _(5)
A complex logistic regression can be created by applying the reasoning of the simple logistic regression to multiple predictors, as follows:
logit y = InP1-P
=α+β1X1+β2X2+…+βkXk __ (6)
Therefore, p = P (Y = desired result / X1=χ1,X2=χ2,…,Xk=χk )
= eα+β1X1+β2X2+…+βkXk1 + eα+β1X1+β2X2+…+βkXk
= 11 + e-(α+β1X1+β2X2+…+βkXk) _(7)
Log Odds and the Odds R
10.5281/zenodo.15715528