Social Factors Associated with Insecurity in Nigerian Society

Abstract

The study examines the societal issues that contribute to the level of insecurity in Nigerian society using the Autoregressive Distributed Lag (ARDL) co-integration technique with data from 1991 to 2022. The variables used as independent and societal factors generating insecurity include the unemployment rate; the high cost of living in society; insufficient funds for education, community social services, healthcare services, and infrastructure; and agricultural development. Among the criteria evaluated, inadequate school financing and the unemployment rate appear to be the most significant sources of insecurity in society as a result of young people’s involvement in abduction, violence, and other societal issues. The study recognizes that government measures aimed at reorienting society towards a peaceful environment for habitation are critical. It is of the utmost importance to provide employment for young people and adequately support schools in order to lower the number of youngsters who are not in school. These out-of-school children are readily persuaded to join groups that make society untenable. Thus, free education is strongly suggested to engage and develop their thoughts in a constructive manner so that they can be valuable to society.

1. Introduction

The growth of insecurity in Nigeria has definitely left the population in an extreme condition of despair, with the majority of economic operations falling. The most important aspect of human existence is peace, and where there is a lack of peace, the implication is that social, economic, and political gains will be impossible to achieve [1]. All of the world’s countries strive to safeguard and enhance their fundamental values in order to enable their inhabitants to sustain their lives in safe and secure surroundings based on their shared fundamental beliefs while protecting their national concern, belonging, and autonomy [2]. Insecurity continues to be a danger to the Nigerian government and economic prosperity. Ethnic conflicts, religious divides, joblessness, and a variety of societal and governance issues are all fueling discontent in Nigeria, adding to events for criminal activity and instability [3]. Considering the leadership’s insufficient response or inactivity, it is believed that the Nigerian government is absolutely struggling to safeguard its population [4]. Regardless of the massive ongoing investment in internal stability at both the national and state levels, citizens in their numerous privileges, work places, and homes spend a considerable amount of money on providing protection for their family members and assets, yet the threat continues to grow unrestrained [4]. The Nigerian example appears to be exceptional since the Boko Haram terrorist team, which promotes insecurity, operates within a few northern regions where farming is still the backbone of the economy, making such regions less susceptible to instability [5].

According to [6], the root reasons of insecurity among so many others include a foundational lack of education, being without a job, weak leadership, the vulnerability of our borders, the increased availability of guns, and a failure to comply with the requirements of legislation. Underdevelopment, impoverishment, hunger, uprising, militant activities, youthful restiveness, abduction, violent burglary, panic, the misuse of drugs, governmental invasion and forceful takeover of power, and other negative consequences of insecurity have been noted [6]. Terrorist fatalities in Nigeria declined to 448 in 2021, the lowest figure since 2011, while terrorism-associated deaths fell by nearly half compared to the prior year [7]. Terrorist assaults, on the other hand, surged by 49% between 2020 and 2021, of which Islamic State in West Africa (ISWA) claimed responsibility for 36% of the assaults, Boko Haram for 8%, and the other 44% were not assigned to any organization [7]. The most recent and distressing terrorist assaults have been committed by the gang known as ‘unknown gunmen,’ who use weapons to take innocent civilians’ lives and vandalize government property. The occurrence of assaults by these unidentified shooters is widespread and suggestive of a weak state in which the authority of the government’s hold on power is under threat and discrimination, emergencies, and insecurity are common [8].

In agreement with empirical evidence, insecurity has a detrimental impact on the economy’s expansion [9,10,11,12,13,14,15,16,17]. Despite the harmful impacts of terrorist activity on economic growth in emerging nations, empirical research on the elements that promote insecurity in developing regions remains limited and underexplored. What is more striking is the lack of empirical study on the immediate and distant relationship between terrorism, poor governance, and the societal circumstances that make developing countries prone to terrorist strikes. According to the [7], Nigeria is the third most plagued nation in Sub-Saharan Africa and the sixth most afflicted country worldwide. As a result, this present research seeks to overcome the perceived emptiness by evaluating social factors and governance concerns that promote insurgency and other kinds of insecurity in Nigeria.

2. Literature Review

2.1. Conceptual Review

The nature of insecurity in Nigeria is very complex. Nigeria, widely regarded as the African continent’s giant, has experienced uncommon levels of insecurity, caused by herdsmen from the Fulani ethnic group operations, Boko Haram militant groups, equipped robbery assaults, abduction, political instability, religious catastrophe, assassination, devastation of petroleum resources by Niger Delta fighters, child abduction, trafficking, and so on [18]. Other acts of violence perpetrated by the Islamic group include automobile devastation; the destruction of worship centers, law enforcement facilities, educational institutions, healthcare facilities, stores, military barracks, and civilian residences; and the kidnapping of foreigners [18]. Furthermore, Fulani Herdsmen have attacked farmers and invaded farmlands, resulting in a shortage of appropriate food supplies.

The term “insecurity” has several implications. It represents peril, risk, unpredictability, an absence of safeguards, and a shortage of stability. According to [19], instability is “an emotional condition of dread or nervousness caused by an actual or imagined lack of protection”. It refers to a lack of or insufficient freedom from risk. Insecurity is defined as the absence of peace, order, and security. Insecurity is defined by [20] from two angles. To begin with, insecurity is a feeling of being vulnerable to harm or trauma, whereas risk is the state of being vulnerable to damage or hurt. Second, instability is the state of being vulnerable to danger or worry, where apprehension is an undefined undesirable sensation felt in expectation of some calamity.

Udoh et al. [21] opine that insecurity in Nigeria is best defined as a result of the “Resource Curse”, which describes how natural resources tend to lead to poor outcomes/civil unrest/war and a socioeconomic state in which a country receives a sufficient amount of money from the export of its mineral assets but suffers an economic loss in directing the revenues towards the development of its people. Nigeria is abundantly endowed with both people and resources from nature, but its human capital development is on the decline. Wojuade and Alayande [22] revealed that ethnic and religious disputes and a lack of jobs are among the causes of instability in Nigeria. The empirical studies of some scholars [9,23,24,25] suggest that poverty and inequality create conflict, ill will, and insecurity. Fighting insecurity requires more than weapons and drones; it requires promoting decent education, strong governance, and generating jobs for the countless youths who are angry and restless since their prospects for employment seem bleak [26]. Security issues produce a variety of effects on Nigeria’s socioeconomic growth, including social dislocations, the displacement of residents, and disruptions of family and social interactions [22].

2.2. Theoretical Foundations

The act of terrorism is an extremely horrifying form of insecurity that continually undermines worldwide stability and generally hinders the financial progress of many nations today. The prevalence and endurance of insecurity (terrorism) with its crippling consequences can be found in a variety of economic philosophies. For example, the “Relative Deprivation Theory” proposed by [27,28] contends that insecurity stems from public unhappiness produced by financial and societal hardship. In this study, the characteristics linked with insecurity in Nigeria that we uncover in our model include unemployment, inadequate education financing, high living costs, a lack of investment in agriculture, and inadequate infrastructure development. All of these causes of instability are the result of the country’s weak governance. According to [29], major security concerns for any nation include a dearth of freedom of information, toxic legislation and regulations, food shortages, poor governance, and leadership that is inept. According to [30], when the elite group in charge of the affairs of a nation becomes too powerful for the people to bring about change (lack of true democratic administration), the average man resorts to violence to show their displeasure with the country’s predicament.

The dissatisfaction–aggression postulation, which holds that discontent generates acts of violence, serves as the foundation for this notion. In the context of economics, the idea attempts to clarify the relationship between insecurity and impoverishment, stating that the existence of deprivation causes the formation of disputes, particularly in nations that are struggling. According to empirical findings from the research of [31,32,33], hunger is the primary driver of war in Africa. Awojobi [9] found that discontent, the absence of earnings, and the prospect of jobs drove Northern Nigerian youngsters to join the Boko Haram insurgency. According to [30], economic downturn in advanced economies has a substantial impact on transatlantic extremism.

In addition, the “Religious Fanaticism Theory” proposes that an association of religious extremists desire to impose an agenda or program with an established collection of doctrinal mandates [34]. The most serious function of extremism in religion is to facilitate the supply of human resources to terrorist groups. Terrorist groups gain from their capabilities, to the disadvantage of any nation’s prosperity since they are composed of well-informed persons who are religious fanatics, for instance, in Nigeria where the Boko Haram sect is anti-western-education due to religious extremism. According to [35], the perpetrators of suicide attacks are religious extremists and do not come from less fortunate backgrounds, as the notion of comparative deprivation hypothesis suggests. The detrimental impacts of beliefs (fanaticism) on economic progress, particularly the loss of intellectual property, have pushed most experts worldwide to present reasons and objections regarding the importance of negative religious beliefs today. According to this notion, terrorism stemming from religious fanaticism always seeks to modify or enforce an evolving program with a conventional array of political demands [34].

2.3. Empirical Review

2.3.1. Review of Effects of Insecurity on Economic Growth

Bilgel and Karahasan [10] used the method of causality to evaluate the financial implications of the Kurdistan Workers’ Party (PKK) insurgency in Turkey from 1988 to 2008. The study discovered that if Turkey had not been exposed to PKK terrorists’ attacks throughout these study years, its per capita GDP would ultimately have been greater than what was established in statistical terms. Nkwatoh and Hiikyaa [5] evaluated the impact of insecurity on Nigerian economic development from 2009Q1 to 2016Q4. The main findings revealed that during times of instability, economic development and investment activity tended to decrease. During moments of instability, the jobless rate also increased due to the unsafe business environment and closing down of firms that could not operate under unsafe surroundings. This suggested that, contrary to popular belief, uncertainty merely undermines economic activity and has a lot of detrimental impact on the economy as a whole. According to Onime [36], insecurity hampered the growth of the economy by reducing ventures, boosting joblessness, and reducing tax income, among other things. Regardless of these consequences, the country’s capital investment in domestic safety did not increase at a rate commensurate with the complex multifaceted security challenges.

Mukolu and Ogodor [37] discovered that armed conflicts and mismanagement significantly and adversely impacted Nigeria’s fiscal health. Using a panel of 50 nations from 2000 to 2016, Nikšić et al. [38] discovered that violent extremism does not influence FDI in the tourism industry. Ndubuisi-Okolo and Anigbuogu [18] disclosed that a lack of security is a major impediment to the expansion of industry and economic growth in Nigeria. Terrorism has a detrimental influence on tax revenue achievement, according to Cevik and Ricco [39], especially in nations where terrorism had become widespread, with numerous attacks and a high number of deaths compared to population. In a comparable manner, the analysis discovered substantial proof that terrorism is linked to a considerable rise in defense expenditures as a percentage of national revenue.

Manrique-de-Lara-Peate et al. [40] developed a global weight estimation system for visitors from abroad from 1995 to 2016 as well as an inter-country input–output framework for calculating the financial consequences of violence, graft, and unpredictability in economic policies. The study estimated changes in visitor arrivals and value added under multiple circumstances, which ranged from absolute safety to full insecurity and uncertainty values at the national and regional levels. According to the findings, the value added created by tourism would grow by 14.3% if insecurity and unrest in each country were reduced to their lowest level and would fall by 17.5% if they climbed to the highest possible point. Shavah [4] studied the impact of insecurity on Nigerian economic expansion between 2011 and 2020. The investigation revealed that the terrorist threat measure had a substantial negative influence on Nigeria’s economy, but the graft viewpoint indicator substantially contributed to growth.

Okoli et al. [41] discovered that a lack of security had a major influence on both public- and private-sector operations in Awka metropolis, as evidenced by the replies of the owners of private enterprises, high-ranking government officials, and employees chosen for the purpose of this research. According to the findings, unrest has had a negative impact on both public and private resources, manufacturing, revenue, job creation, and budgets in Awka metropolitan and Nigeria at large.

2.3.2. Evaluation of Causes of Insecurity in the Society

Okolie et al. [25] investigated the link between insecurity and economic hardship in Nigeria. The descriptive approach was used, and data were gathered by a survey of 600 people employing non-probabilistic sampling procedures. According to the findings from the data evaluation, poverty demonstrated a positive and substantial link with insecurity in Nigeria. Zubairu [2] analyzed the underlying factors and answers to Nigeria’s escalating insecurity. The findings found that the threats of joblessness and destitution, elites profiteering, cultural and theological divides, nepotism, an insufficient security system, insecure borders, discrimination and unfairness in the entire nation, and inadequate administration and poor management were the fundamental reasons for insecurity in Nigeria.

3. Methodology

The aim of this research is to examine the social factors associated with insecurity in Nigeria. The investigation covers the period 1991–2022. The dependent variable is the level of insecurity in Nigeria. The major social factors identified in this study as the independent variables include unemployment rate, infrastructure, health care facilities, education funding, agricultural development, community social services, and the high cost of living in the country. The Autoregressive Distributed Lag (ARDL) co-integration approach or bound co-integration technique was utilized in this research. The study used secondary data collected from the Central Bank of Nigeria Statistical Bulletin. In this study, the Augmented Dickey–Fuller Test unit root test and Phillip Perron were employed to examine the degree of integration. Thus, the variables’ operational definition is presented in

Table 1. Variables’ description and source.

Variable	Description	Data Measurement	Transformation Type	Data Collection Period	Source
$LNINSY$	Insecurity	Measured in national currency (Naira)	Natural logarithm	1991–2022	CBN Statistical Bulletin https://www.cbn.gov.ng/documents/Statbulletin.asp (accessed on 14 June 2023)
$LNUNMP$	Unemployment Rate	Measured in national currency (Naira)	Natural logarithm	1991–2022	CBN Statistical Bulletin https://www.cbn.gov.ng/documents/Statbulletin.asp (accessed on 14 June 2023)
$LNPNFR$	Infrastructure	Measured in local currency (Naira)	Natural logarithm	1991–2022	CBN Statistical Bulletin https://www.cbn.gov.ng/documents/Statbulletin.asp (accessed on 14 June 2023)
$LNPHLT$	Healthcare facilities	Measured in domestic currency (Naira)	Natural logarithm	1991–2022	CBN Statistical Bulletin https://www.cbn.gov.ng/documents/Statbulletin.asp (accessed on th June 2023)
$LNPFED$	Funding of Education	Measured in home currency (Naira)	Natural logarithm	1991–2022	CBN Statistical Bulletin https://www.cbn.gov.ng/documents/Statbulletin.asp (accessed on 14 June 2023)
$LNPAGR$	Agricultural Development	Measured in local currency (Naira)	Natural logarithm	1991–2022	CBN Statistical Bulletin https://www.cbn.gov.ng/documents/Statbulletin.asp (accessed on 14 June 2023)
$LNCSSS$	Community Social Services	Measured in domestic currency (Naira)	Natural logarithm	1991–2022	CBN Statistical Bulletin https://www.cbn.gov.ng/documents/Statbulletin.asp (accessed on 14 June 2023)
$LNHCOL$	High Cost of Living	Measured in national currency (Naira)	Natural logarithm	1991–2022	CBN Statistical Bulletin https://www.cbn.gov.ng/documents/Statbulletin.asp (accessed on 14 June 2023)

Source: Research information, 2024.

below.

Osberg [42] suggests that economic insecurity should be given greater emphasis because it has an impact on the well-being of people, their identity as individuals, and employment market activity, and since the social safety net was mainly driven by the need to reduce uncertainty. Thus, the selection of these variables is motivated by Sustainable Development Goals (SDGs) 1–11, which encourage all countries to eliminate poverty and hunger; improve healthcare services; and promote sound education, agriculture, infrastructure, the production of affordable goods and services, and the sustenance of cities and communities. The ongoing lack of these key social factors that foster livelihood in the country has resulted in a variety of social attacks and insecurity among youngsters.

The model developed for this inquiry is as follows:

$$Y={\beta }_0+\beta X_1+\beta X_2+\dots {\mu }_{it}$$

(1)

where,

Y = Insecurity

X = Social factors associated with insecurity

β = Coefficient

${\mu }_{it}$ = Error term

The above model is indisputably well-designed in this study, as presented in Equation (2) below:

$$LNINSY={\beta }_0+{\beta }_{1}LNUNMP+{\beta }_{2}LNPNFR+{\beta }_{3}LNPHLT+{\beta }_{4}LNPFED+{\beta }_{5}LNPAGR+{\beta }_{6}LNCSSS+{\beta }_{7}LNHCOL+{\mu }_{it}$$

(2)

where:

$LN$ represents the natural logarithm form of variables; $LNINSY$ indicates the level of insecurity in the country; $LNUNMP$ shows the degree of joblessness;$LNPNFR$ shows the amount of infrastructure in the country;$LNPHLT$ denotes the healthcare facilities; $LNPFED$ symbolizes the inadequate funding of education; $LNPAGR$ is agricultural development in the country; $LNCSSS$ represents the community social services that can enhance productivity of young people; $LNHCOL$ connotes the high cost of living; ${\beta }_0$ is the coefficient of the parameter estimate; ${\beta }_1$–${\beta }_7$ implies the intercept; and ${\mu }_{it}$ is the error term.

Since the F-statistic is bigger than the I(0) and I(1) limits at the 5% level of significance, the study employed a bounds-testing approach to co-integration (introduced by Pesaran et al., 2001) [43] to analyze the variables’ short and long-term associations. The bounds-test assumptions are illustrated in Equations (3) and (4) below; they test the presence or absence of a long-run link between the variables:

H₀: δ₁ = δ₂ = δ₃ = δ₄ = δ₅ = δ₆ = δ₇ = 0 (There is long-run relationship in the series)

(3)

H₁: δ₁ ≠ δ₂ ≠ δ₃ ≠ δ₄ ≠ δ₅ ≠ δ₆ ≠ δ₇ ≠ 0 (No long-run relationship exists in the series)

(4)

The ARDL model measurement is presented in Equation (5) below:

$$\begin{array}{c}∆LNINSYt ={\beta }_0+{\beta }_{1}LNINSYt-₁+{\beta }_{2}LNUNMPt-₁+{\beta }_{3}LNPNFRt-₁+\hfill \\ {\beta }_{4}LNPHLTt-₁+{\beta }_{5}LNPFEDt-₁+{\beta }_{6}LNPAGRt-₁+{\beta }_{7}LNCSSSt-₁+\hfill \\ {\beta }_{8}LNHCOLt-₁+{\sum }_{t=1}^qØ₁∆LNINSYt-₁+{\sum }_{t=1}^qØ₂∆LNUNMPt-₁+\hfill \\ {\sum }_{t=1}^qØ₃∆LNPNFRt-₁+{\sum }_{t=1}^qØ₄∆LNPHLTt-₁+{\sum }_{t=1}^qØ₅∆LNPFEDt-₁+\hfill \\ {\sum }_{t=1}^qØ₆∆LNPAGRt-₁+{\sum }_{t=1}^qØ₇∆LNCSSSt-₁+{\sum }_{t=1}^qØ₈∆LNHCOLt-₁+\mu t\hfill \end{array}$$

(5)

Equation (6) presents the error-correction model:

$$\begin{array}{c}∆LNINSYt ={\beta }_0+{\beta }_{1}LNINSYt-₁+{\beta }_{2}LNUNMPt-₁+{\beta }_{3}LNPNFRt-₁+\hfill \\ {\beta }_{4}LNPHLTt-₁+{\beta }_{5}LNPFEDt-₁+{\beta }_{6}LNPAGRt-₁+{\beta }_{7}LNCSSSt-₁+\hfill \\ {\beta }_{8}LNHCOLt-₁+{\sum }_{t=1}^qØ₁∆LNINSYt-₁+{\sum }_{t=1}^qØ₂∆LNUNMPt-₁+\hfill \\ {\sum }_{t=1}^qØ₃∆LNPNFRt-₁+{\sum }_{t=1}^qØ₄∆LNPHLTt-₁+{\sum }_{t=1}^qØ₅∆LNPFEDt-₁+\hfill \\ {\sum }_{t=1}^qØ₆∆LNPAGRt-₁+{\sum }_{t=1}^qØ₇∆LNCSSSt-₁+{\sum }_{t=1}^qØ₈∆LNHCOLt-₁+{\lambda ECM}_{t-₁}+\hfill \\ \mu t\hfill \end{array}$$

(6)

where $Ø indicates the short run coefficents,$∆ denotes the first differenced operator, t represents time, $ECMt-i$ represents the error correction term, $\lambda$ indicates the speed of adjustment in the long run from errors that occur in the short run, and ${\mu }_t$ implies the white-noise error term.

4. Result

Section 4 provides the analysis and interpretation of data applied for this research, including the trend analysis, descriptive statistics, analysis of the relationship between data, unit root test, ARDL bounds test, VAR lag-order selection criteria, and ARDL long-run and short-run estimation with ECM.

Figure 1 depicts the trend of data utilized in this investigation. The most noticeable issue is that the unemployment rate and insecurity appear to be at the same level, implying that young people’s unemployment is the most significant social element causing insecurity in the country. Other societal elements have increased but have not decreased insecurity, indicating that corruption is an intrinsic component that resists insecurity control. The yearly budget allocations for healthcare facilities, education, agriculture, community social services, and agriculture are insufficient to provide jobs for fresh graduates. As a result, a significant number of them get drawn into terrorism. The element of corruption in the Nigerian system has also created a vacuum for insecurity to grow as officials disbursing these funds always have a way of not applying the whole fund to the genuine societal concerns they are designed to solve at any point in time. Where communities lack basic infrastructure for young people to start enterprises, the youth in those places are more likely to cause societal problems.

The primary goal of the descriptive statistics given in

Table 2. Descriptive statistics.

	INSY	UNMP	PNFR	PHLT	PFED	PAGR	CSSS	HCOL
Mean	5.08	1.42	6.17	3.78	4.42	2.67	3.55	4.07
Median	5.42	1.36	6.39	4.27	4.85	3.22	3.31	4.22
Maximum	7.22	1.79	7.87	6.05	6.47	4.34	6.11	6.04
Minimum	2.12	1.31	3.33	0.14	0.23	0.16	0.48	1.00
Std. Dev.	1.71	0.14	1.17	1.88	1.77	1.44	2.08	1.29
Skewness	−0.53	1.66	−0.77	−0.54	−0.83	−0.56	−0.17	−0.60
Kurtosis	1.98	4.37	2.99	1.93	2.81	1.82	1.45	2.78
Jarque-Bera	2.85	17.2	3.19	3.06	3.69	3.49	3.34	2.01
Probability	0.24	0.18	0.20	0.22	0.16	0.17	0.19	0.36
Sum	162	45.4	197	121	141	85.4	113	130
Sum Sq. Dev.	90.2	0.63	42.9	109	97.2	64.7	134	51.7
Observations	32	32	32	32	32	32	32	32

Author’s calculation, 2024.

is to provide insight into the types of datasets used in this study. The fundamental goal is to produce a normal distribution of data. Thus, the Kurtosis and Jarque-Bera findings are quite important in this regard. According to Table 2, the Kurtosis is within acceptable ranges, and the JarqueBera p-values reveal that no variable has a p-value of less than 0.05 degree of materiality. As a result, the datasets are appropriately dispersed.

Table 3. Correlation analysis.

VARIABLE	INSY	UNMP	PNFR	PHLT	PFED	PAGR	CSSS	HCOL
INSY	1.00
UNMP	0.51	1.00
PNFR	0.74	0.50	1.00
PHLT	0.79	0.49	0.73	1.00
PFED	0.77	0.47	0.75	0.78	1.00
PAGR	0.75	0.46	0.72	0.75	0.73	1.00
CSSS	0.76	0.52	0.79	0.76	0.73	0.71	1.00
HCOL	0.77	0.57	0.77	0.77	0.78	0.70	0.72	1.00

Author’s calculation, 2024.

shows that insecurity is strongly associated with social characteristics. This is a clear sign that if social concerns are not properly addressed, societal insecurity will persist. Furthermore, unemployment is modestly connected with other social characteristics, confirming that these social elements are in low supply to reduce the enormous unemployment rate. Other social factors have a tight relationship with one another, showing that you cannot focus on one while ignoring the other. Nigerian society needs all social facilities to function properly and to eliminate unemployment and insecurity in its different regions.

A unit root test is performed to check the stability of the datasets employed in this investigation.

Table 4. Unit root test.

Variable	ADF T-Statistic	Critical Value @ 5%	p-Value	Order of Co-integration	PP T-Statistic	Critical Value @ 5%	p-Value	Order of Co-integration
LNINSY	−5.01	−2.99	0.00	I(0)	−7.26	−2.96	0.00	I(1)
LNUNMP	−3.52	−2.99	0.02	I(1)	−3.23	−2.96	0.03	I(1)
LNHCOL	−3.11	−2.97	0.03	I(1)	−3.27	−2.96	0.02	I(0)
LNPAGR	−4.07	−2.99	0.00	I(0)	−11.28	−2.96	0.00	I(1)
LNPNFR	6.68	−2.96	0.00	I(1)	−6.61	−2.96	0.00	I(0)
LNPHLT	−4.89	−2.99	0.00	I(0)	−8.82	−2.96	0.00	I(1)
LNPFED	−4.46	−2.98	0.00	I(0)	−4.08	−2.96	0.00	I(0)
LNCSSS	−8.26	−2.96	0.00	I(1)	−8.18	−2.96	0.00	I(1)

Author’s calculation, 2024.

shows the order of integration of the variables. We employed both ADF (Augmented Dickey-Fuller) t-statistics and Philip Perron (PP) to check each variable’s level of consistency. Table 4 shows that insecurity, unemployment, agriculture, health care facilities, and community social services are stable at the first difference, but the high cost of living, infrastructure, and education financing are stationary at the levels. Based on this finding, which is a mix of order one and zero, the ARDL model is the optimal analytical tool [43]. As recommended by [43] when series are stationary at order one and zero, ARDL is most appropriate in order to determine both the long and short-run relationships among the variables. The only limitation this method has is that it cannot be applied in a scenario where the series have a combination of order two and one or zero.

Table 5. ARDL bounds test result.

F-Statistic	Significance	I0 Bound	I1 Bound
6.02	10%	2.03	3.13
	5%	2.32	3.50
	2.5%	2.60	3.84
	1%	2.96	4.26

Author’s calculation, 2024.

displays the ARDL bounds test results. The goal is to establish whether the connection is long-term or not. Following the test results, the F-statistic value of (6.02) surpasses both the lower limitation (2.32) and the upper limit (3.50) at the five percentage point relevancy criterion defined by [43]. As a consequence, we have to disregard the null assumption, which asserts that there is no long-term relationship between the variables investigated, because one has been established.

Table 6. VAR lag-order selection criteria.

Lag	LogL	LR (Likelihood Ratio)	FPE (Final Predictor Error)	AIC (Akaike Information Criterion)	SC (Schwarz Information Criterion)	HQ (Hannan–Quinn Info Criterion)
0	20.44	NA	0.026	−0.829	−0.455	−0.709
1	20.72	0.402 *	0.027 *	−0.782 *	−0.361 *	−0.647 *
2	20.78	0.074	0.029	−0.719	−0.252	−0.569

* specifies interval direction designated by the benchmark. Author’s calculation, 2024.

displays the ARDL limited evaluation’s optimal latencies. Choosing the right lag results in a more reliable response while reducing serial reliance and ensuring an unbiased judgment. As indicated in Table 6, the optimal lag is one, which has been confirmed by all parameters.

Table 7. ARDL long-run estimation.

Dependent Variable: LNINSY
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	0.81	0.94	0.85	0.40
LNINSY(−1)	0.47	0.26	1.79	0.09 **
LNCSSS(−1)	−0.03	0.07	−0.48	0.63
LNHCOL(−1)	0.68	0.32	2.12	0.05 ***
LNPAGR(−1)	−0.13	0.13	−0.99	0.33
LNPFED(−1)	−0.47	0.19	−2.41	0.02 ***
LNPHLT(−1)	0.48	0.21	2.31	0.03 ***
LNPNFR(−1)	0.18	0.18	0.99	0.33
LNUNMP(−1)	−0.79	0.44	−1.82	0.08 **

Notes: R-Squared = 0.78; Adjusted R-Squared = 0.68; S.E. of regression = 0.21; F-statistic = 211.8; Prob. (F-statistic) = 0.000; Durbin–Watson = 2.2; AIC = 0.02; and SC = 0.43. *** and ** confirm significance levels at 5% and 10%, respectively. Author’s computation, 2024.

shows crucial evidence for the long-run influence of each social element. The findings indicate that unemployment has a negative impact on insecurity at the 10% level of significance, whereas education spending has a negative impact on insecurity at the 5% level. These two findings demonstrate that inadequate educational financing and a high unemployment rate both contribute considerably to a high level of insecurity over time. A temporary problem has little long-term impact, but if a problem persists and no remedy is found, it becomes a threat to the entire population. These findings are in agreement with the study of [2,41]. This is the scenario in Nigeria, where education spending is low and unemployment is consistently rising. In the long term, community social services and agriculture have no substantial negative influence on insecurity, but a positive impact on insecurity is discovered in the case of high living costs and inadequate healthcare facilities. This is really ridiculous since the more that healthcare institutions fail and the expense of living rises, the more insecurity grows in the country. This is exactly what is happening in the northeast of the country, where the Boko Haram cult has taken over extensive tracts of land and is preventing farmers from accessing and collecting their crops.

In

Table 8. ARDL short-run estimation and error-correction model.

Dependent Variable: D(LNINSY)
Method: Least Squares
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	0.034002	0.080298	0.423444	0.6765
D(LNINSY(−1))	0.375386	0.262375	1.430726	0.1679
D(LNCSSS(−1))	−0.043067	0.080737	−0.533428	0.5996
D(LNHCOL(−1))	0.803957	0.394329	2.038801	0.0549 **
D(LNPAGR(−1))	−0.117793	0.096009	−1.226892	0.2341
D(LNPFED(−1))	−0.661963	0.160354	−4.128144	0.0005 ***
D(LNPHLT(−1))	0.716182	0.183187	3.909560	0.0009 ***
D(LNPNFR(−1))	−0.082304	0.170818	−0.481823	0.6352
D(LNUNMP(−1))	−0.973583	1.163512	−0.836762	0.4126
ECM(−1)	−1.039294	0.279001	−3.725053	0.0013 ***

Notes: R-Squared = 0.66; Adjusted R-Squared = 0.51; S.E. of regression = 0.20; F-statistic = 4.32; Prob. (F-statistic) = 0.003; Durbin–Watson = 1.98; AIC = −0.12; and SC = 0.34. ***, **, and * confirm significance levels at 1%, 5% and 10%, respectively. Author’s computation, 2024.

, the study shows the result of the short run estimation and error-correction model. Thus, in the short run, the high cost of living and healthcare services had a significant positive impact on insecurity, while education had a significant negative influence on insecurity. Other factors were insignificant. As predicted, the error-correction model (ECM) is negative in value (−1.039) and of statistical importance at the 5% level. This finding supports the presence of a long-term link between the variables. According to the results, the ECM was set at −1.039, indicating that in the event of economic instability, the rate of transition back to normalcy is essentially 100%.

Diagnostic and stability evaluations using the Breusch–Godfrey serial correlation LM test and Breusch-Pagan-Godfrey heteroskedasticity test were performed to confirm the ARDL model findings, which are given in

Table 9. Breusch–Godfrey serial correlation LM test.

F-statistic	0.627	Prob. F(2,18)	0.545
Obs*R-squared	1.953	Prob. Chi-Square(2)	0.376

Author’s computation, 2024.

,

Table 10. Heteroskedasticity test: Breusch–Pagan–Godfrey.

F-statistic	1.864	Prob. F(9,20)	0.118
Obs*R-squared	13.68	Prob. Chi-Square(9)	0.134

Author’s computation, 2024. Note: Obs*R-square is the number of observation multiply to R-square while the proportion of the variation in the dependent variable.

, and Figure 2, respectively. The Breusch–Godfrey serial correlation LM test shown in Table 9 with a probability value above five percent indicates the absence of serial correlation. Similarly, the heteroskedasticity diagnostic test described in Table 10 with a value greater than 5% indicates the absence of heteroskedasticity. In addition, the cumulative sum of recursive residuals (CUSUM) was employed to assess the robustness of the model. Figure 2 shows that the equation plots are within the 5% significance threshold. We may thus conclude that the model is robust.

5. Conclusions

Insurgency in Nigeria is a major worry, prompting scholars and policymakers to examine a wide range of social, economic, and political factors that might be responsible for the recurring societal threat. In this study, we focused on the social elements that may have contributed to the ailing society as a result of the pervasive insecurity of lives and property over many years, with no clear guidance on how to mitigate the imminent threats to the economy and society as a whole. The study used the ARDL model, which demonstrated that in the long term, inadequate education financing and unemployment were the most important variables influencing young people’s involvement in abduction, violence, terrorism, and other social vices in the country. In the medium term, inadequate financing for education was seen as a key source of insecurity, whereas unemployment had only a slight adverse effect on the subject. Having established these realities, it is critical that the government revise its policies to address youthful joblessness and school financing as important concerns. Other social issues evaluated in this study were not as harsh as unemployment and inadequate support for education in society. As a result, policymakers must prioritize initiatives for reducing unemployment in society in order to restore the country’s dignity. It is essential to implement youth involvement programs and make significant investments in the nation’s educational system.