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Insurgency and Economic Growth in Nigeria

Peverga, Kator

, Aye-Agele, Freeman

, Udele, Isaiah Aondosoo

, Iorliam, Stephen A.

1,2

Department of Economics, Federal University of Lafia, Nasarawa State, Nigeria.

Registry Department, Fidei Polytechnic, Gboko, Benue State, Nigeria.

Catholic Education Services, Catholic Diocese of Gboko, Benue State, Nigeria. Corresponding

DOI:

https://dx.doi.org/10.47772/IJRISS.2025.910000571

Received: 19 October 2025; Accepted: 25 October 2025; Published: 18 November 2025

ABSTRACT

This study investigates the impact of insurgency on economic growth in Nigeria within the context of the

country’s persistent insecurity challenges. Using time series data from 1999 to 2024 sourced from the Central

Bank of Nigeria (CBN), National Bureau of Statistics (NBS), Global Terrorism Database, and Index Mundi, the

study employed descriptive statistics, Augmented Dickey-Fuller (ADF) unit root test, Johansen co-integration,

and Vector Error Correction Model (VECM) to examine the short-run and long-run dynamics between

insurgency, discomfort index, terrorism risk index, and real gross domestic product (RGDP). The findings reveal

that insurgency exerts a positive but temporary effect on economic growth in the short-run, possibly due to

increased emergency-related expenditures, but significantly undermines growth in the long-run. Similarly, the

discomfort index exhibited a short-run positive effect but a long-run negative and significant influence on

RGDP, reflecting the adverse role of socioeconomic stressors on growth. The terrorism risk index also

demonstrated a statistically significant negative effect on economic growth both in the short-run and long-run,

with a 1% change in TRI reducing RGDP by approximately 0.66%. These results confirm that insurgency and

terrorism pose substantial constraints on Nigeria’s long-term economic development by discouraging

investments, displacing populations, and weakening productive capacity. The study concludes that effective

counter-insurgency measures, socioeconomic reforms to reduce unemployment and poverty, and community-

based peace-building initiatives are critical to mitigating the adverse effects of insecurity on Nigeria’s economic

growth.

Keywords: Economic growth, insurgency, insecurity, terrorism, Nigeria.

JEL Classification codes: O47, F52, H56.

INTRODUCTION

Nations experiencing persistent security challenges are often associated with weak or negative economic growth

indices. This relationship between insecurity and economic underperformance has been widely discussed in the

literature as one of the most pressing threats to national development (Ali, 2013; Ewetan & Urhie, 2014; Onime,

2018; Ezeajughu, 2021). Empirical evidence from Abadie and Gardeazabal (2013) and corroborating case

studies by Achumba, Ighomereho, and Akpan (2013), Ajibola (2016), and Aghaulor (2020) further confirm that

insecurity undermines productive capacity and limits growth potential. In Nigeria, the situation has reached an

alarming proportion, manifesting in loss of lives, population displacements, collapsing businesses, dwindling

investments, relocation of multinationals, rising unemployment, and widespread fear among citizens (Onime,

2018). Such conditions threaten governance and economic stability, consistent with Stewart’s (2004) assertion

that the economic costs of insecurity are immense, ranging from the destruction of schools, roads, and power

stations to the displacement of labour and decline in export capacity.

The Nigerian state continues to grapple with the menace of insecurity despite increasing government

expenditure on security at both the federal and state levels. Individuals and communities also invest heavily in

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private security to protect lives and property, yet the problem persists (Onime, 2018). In almost every region of

the country, distinct patterns of insecurity can be identified: ethnic clashes in the North, kidnapping across the

country (but prominent in the South-South and South-West), militancy and pipeline vandalism in the Niger

Delta, terrorism and religious extremism by Boko Haram in the North-East, secessionist agitations by IPOB and

MASSOB in the South-East, herdsmen–farmer conflicts in the North and North-Central, ritual killings in the

South-West and East, and diverse political and economic disturbances (Onime, 2018).

These crises have had visible impacts on regional and national economies. In the North-East, Boko Haram

insurgency has devastated communities, displaced millions into IDP camps, reduced employment opportunities,

collapsed informal businesses, and eroded state revenues. Similarly, militancy and vandalism in the Niger Delta

have forced multinational corporations to shut down or relocate operations, reduced Nigeria’s oil production,

triggered foreign exchange shortages, increased unemployment, and raised the cost of doing business.

Comparable disruptions are evident in other conflict-prone regions, creating a national pattern where insecurity

suppresses economic activities. The gravity of this situation underscores the need to systematically examine the

relationship between insurgency and economic growth in Nigeria. Against this backdrop, this study investigates

insurgency and economic growth in Nigeria, situating the analysis within the country’s democratic dispensation

where the dynamics of insecurity have intensified.

LITERATURE REVIEW

Conceptual Review

Economic Growth

Economic growth generally, can be described as a positive change in the level of production of goods and

services by a country over a certain period of time. In other words, economic growth is the increase in the value

of goods and services produced by an economy. It can also be referred to as the increase in the gross domestic

product. It is a relatively straight forward measure of output and gives an idea of how well off a country is,

compared with competitors and past performance. It is a beacon that helps policy makers steer the economy

towards key economic objectives. Finally, it is a measure of the wellbeing of a State; usually in real terms, all

other things being equal (Enu, 2009).

According to Haller (2012), economic growth is, in a limited sense, an increase of the national income per

capita, and it involves the analysis, especially in quantitative terms, of this process, with a focus on the functional

relations between the endogenous variables; in a wider sense, it involves the increase of the GDP, GNP and NI,

therefore of the national wealth, including the production capacity, expressed in both absolute and relative size,

per capita, encompassing also the structural modifications of the economy. In other words, economic growth is

the process of increasing the sizes of national economies, the macro-economic indications, especially the GDP

per capita, in an ascendant but not necessarily linear direction, with positive effects on the economic-social

sector. Haller (2012) also concludes that economic growth is obtained by an efficient use of the available

resources and by increasing the capacity of production of a country. It facilitates the redistribution of incomes

between population and society. The cumulative effects, the small differences of the increase rates, become big

for periods of one decade or more. It is easier to redistribute the income in a dynamic, growing society, than in

a static one. When the rate of economic growth is big, the production of goods and services rises and,

consequently, unemployment rate decreases, the number of job opportunities rises, as well as the population’s

standard of life. We shall, for the purpose of this study, employ the definition of economic growth by Haller

(2012) as the working definition because it is broad-based and by far more encompassing in explaining

economic growth than others.

Insurgency

Insurgency has been defined as an organized movement aimed at the overthrow of a constituted government

with subversion and armed conflict (Haviland, 2012). The Counter-Insurgency Initiative (2009) has defined

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insurgency as the organized use of subversion and violence to seize, nullify, or challenge political control of a

region. Insurgents seek to subvert or displace the government and completely or partially control the resources

and population of a given territory. They do so with force (including guerrilla warfare, terrorism, coercion or

intimidation, propaganda, subversion, and political mobilization).

Boko Haram which in general terms, simply means “western education is forbidden” was founded in 2002 in

Maiduguri in northeastern Nigeria by a charismatic Muslim cleric, Ustaz Mohammed Yusuf. The sect’s

philosophy is rooted in the practice of orthodox Islam, and the group’s official name in Arabic, Jama’atu

Ahlissunahlidda ’awatiwal Jihad, translates to “people committed to the propagation of the Prophet’s teachings

and Jihad” (Chothia, 2012). Boko Haram is an Islamist movement that is tied to Al-Qaeda and its followers

forbid Muslims or its groups to be involved in any political or social activity that is related to western education

or ideology. The Islamic sect beliefs that Nigerian society is so corrupt that it is necessary for a devoted Muslim

to migrate to a society that is free from deprivation. Akanji (2009) observes that the goals of Boko Haram are

to overthrow the Nigerian government, incite religious tensions by acts of terror and eventually declare an

Islamic state in Nigeria.

Insurgency is a condition of revolt against a government that is less than an organised revolution and that is not

recognised as belligerency (Peter, 1964). It is the rising up against what is believed to be a constituted or

legitimate authority. The term "insurgency" is used in describing a movement's unlawfulness and capacity to

pose a threat to a state or seen as such by another authority, especially when viewed from the backdrop of its

not being authorised, and therefore executing a cause that is illegitimate (Shafer, 1988). Those causing the

uprising (insurgence) are seen as rebels, whereas those rising up will see the authority itself as being illegitimate.

Insurgency is an act of rebellion against a legitimate authority. However, such an authority would have acquired

the recognition by an international body such as the United Nations, while those taking part in the rebellion are

not recognised as belligerents. It becomes deduced from the foregoing that if there is a rebellion against the

authority (for example the United Nations) and those taking part in the rebellion are not recognised as

belligerents, the rebellion is an insurgency. The United States Department of Defence [DOD] (2007) defines

insurgency as an organised movement aimed at the overthrow of a constituted government through the use of

subversion and armed conflict. The threats of insurgency has intensified and assumed global dimension in recent

times. However, not all rebellions are insurgencies. A rebellion may not be viewed as an insurgency if a state of

belligerency exists between one or more sovereign states and rebel forces, even if the revolt takes the form of

armed rebellion.

THEORETICAL REVIEW

Social Structure-Anomie Theory

The social structure-anomie is a contemporary theory developed by Robert K. Merton, in social sciences that

illustrates the active roles of deviant behaviour in criminality (Halliru, 2012). Merton focuses mainly on the

“broad patterns of norm-violating behavior rather than in the behavior of individual deviants”, using cultural

goals, institutional norms and social structures of the society. Merton analyzes how people situated in certain

segments of the society are predisposed to environmental pressures and how it could encourage deviant

behaviours. According the thinking of Merton, all sections of the society are expected to struggle for the cultural

goal of physical accomplishment which includes money and the impressive possessions it can afford within its

institution or structure.

Nevertheless, the society that places high emphasis on cultural environment for success attainment and social

ascent for all its members ought to make adequate provisions for their accomplishments. Quite unfortunately,

society emphasizes less on the means for members of the society to attain this goal and it predisposes them to

criminality. Thus, the serious inconsistency between cultural goals and structural certainties does not only

destabilizes social support for the established norms but also for the promotion of defilements of those norms

(Merton, 1957). When persons are choked in their pursuit of economic success in the society, they are forced to

acclimatize in deviant ways to this exasperating environmental condition. How people adjust to the

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environmental burdens is therefore the vital contribution to the anomie tradition. This is illustrated in an

analytical typology of how individuals adjust to the discrepancy between culture and social structure in the

society, shown in Table 2.1.

Table 1: Typology of Individual Adaptations to Environmental Pressure

S/No.

Types of Adaptation

Cultural Goals

Institutionalized means

Conformity

Innovation

Ritualists

Retreatism

Rebellion

Source: (Halliru, 2012).

Note: + means acceptance while - means rejection. The symbol for rejection of the existing goal or means and

substitution of new goal is ±

As indicated in Table 2.1, adaptations define the types of social roles which persons engage in their reaction to

cultural and structural pressures. Hence, conformity connotes a non-deviant adaptation where persons keep on

engaging genuine work related or educational roles in-spite of the prevailing environmental pressures toward

criminality. Thus, the conformists are persons who accept and strive for the cultural goal of material success (+)

by following structural provisions (+).

On the other hand, innovation is an adaptation style for accepting the cultural goal (+) and discarding the

legitimate institutionalized means (-) of achieving the goal, which propels innovators to engage in criminality

via illegal means to obtain material success. The ritualist in the above typology is an over conformist. His or

her quest hunts for the main cultural goal of economic success is avoided (-) in favour of the compulsive

conformity to structural norms (+). The retreatism typology indicates the rejection of both cultural goals (-) and

institutionalized means (+) in order to avoid the pressures and demands of organized society. In the final

adaptation in the above table, rebellion, is specified by dissimilar symbolization than the other adaptations. The

two ± signs show that the rebel does not only rejects the institutional goal and its means of accomplishment but

actively attempts to replace them with new goals and means.

Harrod-Domar Growth Model

The Harrod-Domar models are based on the assumptions of full employment, absence of government

interventions, open economy, equality between average propensity to save APS and marginal propensity to save

MPS, savings and investment relates to income of the same year and constant ratio of capital stock to income.

Based on these assumptions, Domar’s model tries to explain the rate of growth in investment that would cause

income to rise by a size equal to the rise in productive capacity, so that full employment is maintained.

The growth models propounded by Harrod and Domar are based on the experiences of the advanced capitalist

economies. They both emphasize the role of investment in economic growth based on the dual characteristics

of investment. Firstly, it creates income and secondly, it augments the productive capacity of the economy by

increasing its capital stock. The former is regarded as the ‘demand effect’ while the later is the ‘supply effect’

of investment. In his work titled “The Theory of Economic Growth” (1957), Domar’s Model as cited by Jhingan

(2003), was given as Δ/I =α∂

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Where I= Investment,

Δ = Change in I,

∂= Net potentials social average productivity of investment (=DY/I)

α =MPS

His model shows that to maintain full employment, the growth rate of net autonomous investment (Δ/I) must

equal α∂ (the MPS times the productivity of capital). This is the rate at which investment most grow to ensure

the use of potential capacity in order to maintain a steady growth rate of the economy at full employment.

According to Domar, any divergence between the two will lead to cyclical fluctuations. When Δ/I is greater than

∂, the economy would experience boom and when Δ/I is less than ∂, it would suffer from depression.

Professor Harrod tries to show how steady growth may occur in the economy. Once the steady growth rate is

interrupted, and the economy falls into disequilibrium, cumulative forces tend to perpetuate this divergence

thereby leading to either secular deflation or secular inflation. Harrod’s model is based upon three growth rates;

the actual growth rate (G) which is determined by the savings ratio and the capital output ratio. The actual is

given as G=S/C where G is the rate of growth of output in a given period of time, C is the net addition to capital

and its given as the ratio if investment to the increase in income (I/DY) and S is the average propensity to save,

APS. The second is the warranted growth rate GW which is given as GW=S/Cr where Cr = the capital

requirement needed to maintain GW. This equation shows that if the economy is to grow at the steady rate of G

what will fully utilize its capital; income must grow at the rate of S/Cr per year. The third is the natural growth

rate. This is the rate of increase in output at full employment as determined by a growing population and the

rate of technological progress, Jhingan (2003). Harrod’s equation for the national growth rate is Gn. Cr = or ≠

S where Gn is the natural full-employment rate of growth. For full employment equilibrium growth,

Gn=GW=G. Any divergence between the three rates of growth would cause condition of secular stagnation or

inflation in the economy.

The Harrod- Domar growth models were criticized on the ground of their unrealistic assumptions such as the

existence of full-employment, non-government intervention in the economy, constancy of MPS (s) and the

capital output ratio (∂) Jhingan (2003).

Romar’s Model of Endogenous Growth

Romar’s Model of endogenous growth addresses technological spillovers (in which one firm’s or industry’s gain

lead to productivity gains in other firms or industries) that may be present during industrialization (Todaro,

2009). It is valuable to think of each firm’s capital stock as including its knowledge. The knowledge part of the

firm’s stock is essentially a public good that is spilling over instantly to the other firm in the economy. As a

result, this model treats learning by doing as “learning by investment”.

According to the neo-classical theories of economic growth the prevailing low capital – labour ratio of

developing countries is an impetus for high investment which in turn enhances growth. But the situation in these

countries leaves more to desired. It is based on this abnormal behavior of developing countries that the concept

of endogenous growth theory or more simply, the new growth theory was developed. This theory provides a

theoretical framework for analyzing endogenous growth, that is determined by the system governing the

production process rather than by forces outside that system. The modern growth theory seems to explain the

factors that determine the size of the GDP growth rate that is unexplained in the Solow’s neo-classical growth

model. Prof. Romer, in his Endogenous Growth Theory Model, includes the technical spillovers which are

attached with industrialization. Therefore, this model not only represents endogenous growth but it is closely

linked with developing countries also. Moreover, in Romer’s model, just the technological spillovers are

considered ignoring the determinants of savings and the problems of general equilibrium.

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Empirical Review

Illo, Akanmu and Osman (2023) investigated the impact of the Boko Haram insurgency in Nigeria on human

security. To this end, responses were collected through a qualitative approach using in-depth interviews.

Findings indicate that the terror activities of Boko Haram have led to the death of thousands of lives, loss of

properties, shortage of food supply, and an increase in number of internally displaced people in the affected

regions. Also, the study revealed that education has been drastically affected and small businesses have

collapsed, thus increasing the poverty level in the country. The paper concluded that the insurgency has an

adverse effect on indispensable factors that constitute human security such as health, education, food and

nutrition, small business enterprises, and human rights and liberty.

Ezeajughu (2021) examined the relevant issue of insecurity in Nigeria and its effect in socioeconomic

development; and noted that the continuous rise in Insecurity and deterioration in the economic development in

Nigeria call for a concern among researchers and policy makers over the years. However, these two hydraheaded

problems remain the greatest challenges facing nations all over the world. Since the past decade or more,

Nigeria has witnessed an unprecedented security challenge occasioned by the activities of militants in the

SouthSouth region, kidnappers in the south east, violent armed robbery in almost parts of the country, political

assassination, ritual killings and more recently activities of Boko Haram in some parts of the northern region

especially north east. These social menaces, when put together impinge on the security of lives and property of

both Nigerian citizens and foreigners living or even trying to invest in the country. To ensure economic

development in Nigeria therefore, the study recommends various measures of curbing insecurity including

preventive community policing, human development centered growth perspective, equitable distribution of

resources as well as channeling of resources to frontline sectors of the economy among others. This has become

worrisome in the face of Nigeria’s preparedness to be ranked among the twenty (20) developed countries of the

world by the year 2020. These social menace triggers off a worrisome sense of insecurity that challenges

Nigeria’s efforts towards national economic development and consequently its vision. It also scares the

attraction of foreign investment and their contributions to economic development in Nigeria. This paper

recommends effective leadership and good governance as a panacea to solving problems of insecurity,

unemployment, poverty, hunger, disease, among other negative indices.

Aghaulor (2020) conducted a study on growth impact of insecurity on the Nigerian economy and investigated

restructuring national security for economic growth in Nigeria for the period 1981 to 2017. In a bid to actualize

the main objective of the study, literature materials were reviewed and data were collected from secondary

sources such as the various editions of CBN Statistical Bulletin. The data were analyzed using Augmented

Dickey-Fuller (ADF) Unit Root test, Johansen co-integration test, Error Correction Model. The selected

variables (i.e. Gross Domestic product, Life expectancy at birth, terrorism risk index, discomfort index, adult

literacy rate, corruption perception index and unemployment rate) had a co- integrating relationship indicating

long-run relationship among the variables. The result of the Error Correction Model (ECM) had the expected

negative sign and statistically significant at the 0.05 level, an indication that any disequilibrium in the system

will be adjusted. Based on the conclusion made, it is recommended that government should restructure and

decentralize security architecture, increase capital expenditure on security and provide the enabling environment

for people to work especially in the area of security of lives and property. This is against the back-drop that no

meaningful economic activity can thrive in the face of insecurity.

Ebipre and Wilson (2020) examined the impact of national insecurity on economic growth using the case of

Nigeria. The study aimed at addressing the challenges of kidnapping, robbery, and herdsmen-farmers’ conflict,

ethno-religious crisis and terrorism, and proffer solutions to the attendant impacts that negatively affect the

economy. Descriptive analysis was adopted as a method of the study. It was discovered that national insecurity

has not only impeded the attainment of sustainable economic growth but that there has been a drastic decline in

economic activities in all geo-political zones in the country. The paper recommends that government should

develop strategies to enhance good governance, increase recurrent and especially capital expenditures on

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internal security, workable anti-terrorism measures, build strong and legitimate institutions that can safely curb

the menace of insecurity.

Onime (2018) examined the effect of insecurity on economic growth in Nigeria and noted that apart from its

direct effect on the populace, it also affects the economy. Using elements of descriptive qualitative analysis and

data from secondary sources, the study analyzed its effect on some economic parameters. The analysis showed

that insecurity affects economic growth by drying-out investments, increases unemployment and dwindles

government revenue, amongst others. Despite these effects, government capital expenditure on internal security

did not grow astronomically to match the hydra-headed problem. The study therefore recommended an increase

in capital expenditure on internal security and concludes with a discussion of some policies to be designed and

targeted at addressing the economic effects of insecurity.

Ukpong-Umo (2016) carried out a study on insurgency in Nigeria and the challenge of nationhood and stressed

that insurgency in Nigeria has become an endemic social ill taking toll on all categories of members of the

Nigerian society as terror is unleashed with a corresponding incidence on the various classes of people in the

society (the wealthy and poor; young and old; male and female; Indigenes and aliens almost alike). This condition

which poses a serious security challenge to national integration is enthroned through the perpetuation of

kidnappings, terrorism, etc. The study used the library research data collection method and data were collected

using secondary sources with rapid appraisal assessment. The study was framed on the basis of conflict theory

of post-colonial states. The study suggested that true federalism, liberal democracy and improved political

structure among other measures should be adopted to strengthen our internal democracy; installation of youth

mobilization programme through massive job creation for all categories of the working class youth as well as

resolution of internal grievances.

Ajibola (2016) conducted a study on economic growth amidst insecurity in Nigeria. Time series data were

collected from 1981 to 2014 on Real Gross Domestic Product, Total Expenditure on security, Gross Fixed Capital

Formation, Total Labour Force, corruption perception index and poverty index to show the relationship

empirically with the use of multiple regressions (OLS) method. It was found out that 90% systematic variation

in Real GDP is caused by variation in total labour force, total expenditure on security, corruption perception

index, poverty index, unemployment rate, inflation rate and gross fixed capital formation. The study showed that

security and other related variables do not only contribute positively to economic growth in Nigeria, but its

impact on economic growth is strong and statistically significant. Also, Nigeria potential GDP growth rate is

11% while the actual growth rate is 6%, which implies that Nigeria economy if efficient due the level of

insecurity, corruption, unemployment, and poverty. Therefore, based on the findings, the study concluded that

the structure and trend of allocation to security is still inadequate to face the challenges of boko haram. Security

funding and reduction in unemployment rate has to treated as matter of urgency in Nigeria i.e. increase in security

funding will lead to increase in economic growth. The study therefore recommended that government should as

a matter of priority implement the policy of EFCC in order to reduce the level of corruption in the country. The

donor agencies like the World Bank, UNDP, UNESCO, etc. should also be encouraged to inject funds into the

security sector.

METHODOLOGY

Data Needs and Sources

This study used data secondary data which were collected from published data in textbooks, journal and

Statistical Bulletin such as CBN statistical bulletin, Annual Reports and Statements of Accounts, and National

Bureau of Statistics (NBS) publications as well as global terrorism database and index mundi. The collected data

covered a period from 1999 – 2024. The quantitative research design was employed in the study using time series

data. This approach is adopted because it enabled the study to obtain data-driven and evidence-based findings;

it also enabled the research objectives of this study to be achieved. This research design is also selected because

it enables impact analysis to be carried out among variables in a study and it enables causality to be tested among

or between variables used in the study.

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Model Specification

Aghaulor (2020) while examining the impact of insecurity on the Nigerian economy, adopted the pro-poor

growth model by Mahbub (1997) stated in implicit form as:

𝐺𝐷𝑃 = 𝑓(𝐷𝐶𝐼, 𝑇𝑅𝐼) … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … (1)

Equation (3.1) was stated explicitly as:

𝐺𝐷𝑃 = 𝛼

+ 𝛼

𝐷𝐶𝐼 + 𝛼

𝑇𝑅𝐼 + 𝜀

𝑖

… … … … … … … … … … … … … … … . . … … … … … … … … (2)

Where GDP is gross domestic product, DCI is discomfort index and TRI is terrorism risk index, 𝛼

is intercept,

𝛼

& 𝛼

are estimated parameters.

The model was slightly modified by adding Adult Literacy Rate and Corruption Perception Index. The researcher

(Aghaulor, 2020), then formulated model one as:

𝐺𝐷𝑃 = 𝑓(𝑇𝑅𝐼, 𝐷𝐶𝐼, 𝐴𝐷𝐿𝐼𝑇, 𝐶𝑈𝑃𝐼) … … … … … … … … … … … … … … … … … … … … … … … (3)

Linearizing the function, the author arrived at a multiple regression equation below:

𝐺𝐷𝑃 = 𝑎

+ 𝑎

𝑇𝑅𝐼

𝑡

+ 𝑎

𝐷𝐶𝐼

𝑡

+ 𝑎

𝐴𝐷𝐿𝐼𝑇

𝑡

+ 𝑎

𝐶𝑈𝑃𝐼

𝑡

+ 𝑈

𝑡

… . . … … … … … … … … … … (4)

Where, GDP is Gross Domestic Product, TRI is terrorism risk index, DCI is discomfort index (addition of

unemployment and inflation rates), ADLIT is adult literacy rate CUPI is corruption perception index 𝑎

constant, 𝑎

− 𝑎

are parameters t is the time trend and Ut is error term.

Model two was formulated implicitly as:

𝐿𝐸𝑋 = 𝑓(𝑇𝑅𝐼, 𝐶𝑈𝑃𝐼, 𝐴𝐷𝐿𝐼𝑇, 𝑈𝑀𝑅) … … … … … … … … … … … … … … … … … … … … … . . (5)

𝐿𝐸𝑋 = 𝑏

+ 𝑏

𝑇𝑅𝐼

𝑡

+ 𝑏

𝐶𝑈𝑃𝐼

𝑡

+ 𝑏

𝐴𝐷𝐿𝐼𝑇

𝑡

+ 𝑏

𝑈𝑀𝑅

𝑡

+ 𝑈

𝑡

… … … . … … … … … … (6)

TRI, CUPI, ADLIT are as defined above UMR = Unemployment Rate b0 = Constant and b1-b4 are parameters

t = is the time trend and U

is the error term.

Following Aghaulor (2020), the model for this study is formulated as stated below taking into cognizance the

specific objectives of the study:

𝑅𝐺𝐷𝑃 = 𝑓(𝐼𝑆𝐺, 𝐷𝐶𝐼, 𝑇𝑅𝐼, 𝐶𝑈𝑃𝐼, 𝐺𝐹𝐶𝐹, 𝐹𝐼𝑆𝐸) … … … … … … … … … … … … … … … … … . . (7)

If Equation (7) is explicitly stated, we have:

𝑅𝐺𝐷𝑃 = 𝛽

+ 𝛽

𝐼𝑆𝐺 + 𝛽

𝐷𝐶𝐼 + 𝛽

𝑇𝑅𝐼 + 𝛽

𝐶𝑈𝑃𝐼 + 𝛽

𝐺𝐹𝐶𝐹 + 𝛽

𝐹𝐼𝑆𝐸 + 𝜇 … … … … (8)

Where, RGDP is real gross domestic product, ISG is insurgency measured as number of terrorist attacks in

Nigeria in a year, DCI is discomfort index, TRI is terrorism risk index, CUPI is corruption perception index,

GFCF is gross fixed capital formation and FISE is federal government security expenditure. 𝛽

is the intercept,

𝛽

− 𝛽

are estimated parameters and 𝜇 is the error term.

The a priori expectation of the study’s model involves the expected sign and significance of the values of the

coefficient of the parameter between dependent and independent variables. Thus, the study expects to have 𝛽

𝛽

> 0 and 𝛽

, 𝛽

< 0.

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Data were analyzed using descriptive statistics and econometric analytical tools. The descriptive statistical tools

that were used are tables, charts, ratios and percentages while the econometric analytical tools include the unit

root test of stationarity that was conducted on each variable before the estimation of the equation. If the variables

are stationary, the ordinary least square technique of estimation might be employed in estimating the equation.

If the variables are differenced to be stationary, the Johanson co-integration test comes in handy to ascertain the

existence of long run relationship between the variables. If there exist a long run relationship, the error correction

model for the short run will be estimated (Engle and Granger, 1988, 1991). If there is no long run relationship

among the variables, the differenced ordinary least square will be used to estimate the relationship between the

variables. Granger causality test will be tested to determine the causal relationship among the variables. The

statistical package to use is E-view 12 software.

The methodology adopted in this study is deemed appropriate because the series of this study failed to be

stationary at level. The error correlation mechanism account for the short-run dynamics of the study variables

and also reveals how long it variables takes to randomly walk back to equilibrium.

RESULTS AND DISCUSSIONS

Descriptive Statistics

The data on the study's variables were calculated using descriptive statistics. Among the statistics are mean,

median, maximum, minimum, standard deviation, skewness, kurtosis, Jarque-Bera, sum, and sum-squared

deviation. To evaluate the statistical properties of the important research variables, these statistics were

computed. The results are presented in Table 2.

Table 2: Summary Statistics of the Variables used in the Study

Statistic

RGDP

ISG

DCI

TRI

CUPI

GFCF

FISE

Mean

42520.33

246.7813

23.34281

6.833438

23.84781

7.70E+12

200.3747

Median

38735.23

238.0000

17.43000

7.150000

25.00000

6.39E+12

107.9000

Maximum

73060.06

588.0000

76.87000

9.310000

30.00000

2.46E+13

728.8300

Minimum

19199.06

12.00000

9.180000

3.210000

12.88000

2.63E+11

2.390000

Std. Dev.

20480.17

192.1571

16.21602

1.806979

4.187426

6.96E+12

218.5513

Skewness

0.237650

0.243945

2.019838

-0.564179

-1.142313

0.876416

1.035580

Kurtosis

1.423188

1.596766

6.230721

2.139697

3.878135

2.945026

3.045471

Jarque-Bera

3.616330

2.942803

35.67539

2.684419

7.987513

4.100593

5.722360

Probability

0.163955

0.229603

0.000000

0.261268

0.018430

0.128697

0.057201

Sum

1360651.

7897.000

746.9700

218.6700

763.1300

2.46E+14

6411.990

Sum Sq. Dev.

1.30E+10

1144655

8151.740

101.2203

543.5707

1.50E+27

1480705.

Observations

Source: Researcher’s Computations from Eviews 12

Skewness and kurtosis measurements were provided by Jarque & Bera (1987); the Jarque-Bera test is widely

used to judge the normality of distributions. The study performed a normality test on the series employed in the

investigation using the Jarque-Bera, skewness, and kurtosis statistics. The conventional value of skewness for

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the normal distribution, which distributes data along its mean, is zero. The majority of the study’s series have

skewnesses that differ noticeably from those that are commonly believed to have a normal distribution. The left

(negatively) or right (positively) of these series are not, however, noticeably distorted. This demonstrates that

these series’ distributions resemble the normal distribution. The kurtosis statistic of a normal distribution is 3. It

measures how peaked and flat a normal curve is. The kurtosis gauges how peaky a distribution is, which is

typically taken to be about normal. Leptokurtic (k>3) distributions with a high peak and "fat tails" are what the

series DCI, CUPI and FISE typically display. However, RGDP, ISG, TRI and GFCF have platykurtic (k<3),

thinner tails, and somewhat flat-topped curves.

Unit Root Tests

In order to avoid spurious regression results, stationarity properties of the series used in this study were subjected

to tests using the ADF. The results obtained are presented in Table 3.

Table 3: Stationarity Test Results

Variable

t-Statistic

Critical value @ 5%

Order of Integration

Decision

RGDP

-4.878664

-3.587527

I(1)

Reject H

ISG

-6.925622

-3.568379

I(1)

Reject H

DCI

-4.504278

-2.963972

I(1)

Reject H

TRI

-5.113333

-2.967767

I(1)

Reject H

CUPI

-3.874789

-2.991853

I(1)

Reject H

GFCF

-4.137075

-2.991878

I(1)

Reject H

FISE

-3.843825

-3.622033

I(1)

Reject H

Source: Researchers’ Computations from Eviews 12

Table 3 shows the stationarity test results. The results show that most of the series failed to attain stationarity at

levels, except GFCF, which was stationary at level. The series RGDP, ISG, DCI, TRI, CUPI and FISE attained

stationarity at their first logarithmic differences. Thus, the null hypotheses of the series having unit roots were

rejected as indicated in the fifth column of Table 4.

Cointegration Results

Unit root results showed that all the variables used in the study to establish a long-run relationship among the

variables were stationary at the first difference. Based on this, the long-run relationship that existed among the

variables used in the VAR system have been established. The study made use of the Johansen Cointegration

technique as it is required of series whose order of integration is I(1). The Johansen Tests were conducted and

the results are shown in Table 4.

Table 4: Results of Unrestricted Cointegration Rank Tests (Trace and Max-Eigen Statistic)

Hypothesized

no. of CE(s)

Eigen

value

Trace

Statistic

0.05

Critical

Value

Prob.**

Eigen

Value

Max-Eigen

Statistic

0.05

Critical

Value

Prob.**

None*

0.876029

188.3221

111.7805

0.0000

0.876029*

62.63117

42.77219

0.0001

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At most 1*

0.718723

125.6909

83.93712

0.0000

0.718723*

38.05250

36.63019

0.0339

At most 2*

0.690924

87.63843

60.06141

0.0001

0.690924*

35.22503

30.43961

0.0117

At most 3*

0.604688

52.41340

40.17493

0.0019

0.604688*

27.84242

24.15921

0.0152

At most 4*

0.379069

24.57098

24.27596

0.0459

0.379069

14.29606

17.79730

0.1558

At most 5

0.276470

10.27492

12.32090

0.1076

0.276470

9.708382

11.22480

0.0913

At most 6

0.018707

0.566539

4.129906

0.5136

0.018707

0.566539

4.129906

0.5136

Source: Researchers’ Computations from Eviews 12.

Trace test and Max-Eigen tests indicates 5 & 4 Co-integrating Equation(s), respectively at the 0.05 level.

* denotes rejection of the hypotheses at the 0.05 level using the MacKinnon-Haug-Michelis (1999) p-values

denoted by **.

Table 4 presents the Johansen Cointegration results. The results show that the Trace test has indicated five

cointegrating equations while the Max-Eigen test has indicated four cointegrating equations. This is because the

Trace statistics of 188.3221, 125.6909, 87.63843, 52.41340 and 24.57098 are greater than their respective critical

values of 111.7805, 83.93712, 60.06141, 40.17493 and 24.27596 at 5% level of significance. Thus, we reject the

null hypotheses of None*, At most 1*, At most 2*, At most 3*, and At most 4* of the hypothesized number of

cointegrating equations. For the remaining hypothesized number cointegrating equations (for At Most 5 and At

Most 6), we cannot reject the null hypotheses as their Trace statistics are less than their respective 0.05 critical

values.

The table also shows that the Max-Eigen test has indicated four cointegrating equations at 0.05 critical value.

This is because the Max-Eigen statistics of 62.63117, 38.05250, 35.22503 and 27.84242 are respectively greater

than their critical values of 42.77219, 36.63019, 30.43961 and 24.15921 at 5% level of significance. Therefore,

we reject the null hypotheses of none*, At most 1*, At most 2* and At most 3* of the hypothesized number of

cointegrating equations for the Max-Eigen statistic. The remaining hypothesized number of cointegrating

equations (ranging from At most 4 to At most 6), we cannot reject the null hypotheses as their Max-Eigen

statistics are less than their respective 0.05 critical values.

Long-Run Impact of Insurgency on Economic Growth in Nigeria

The presence of five and four cointegrating equations for the Trace and Max-Eigen Statistics depict that

cointegrating relationship among variables used in the VAR system had been established. The nature of the

longrun relationship between insurgency and economic growth in Nigeria using the cointegrating coefficients

normalized by b

*s11*b=1 (the inverse matrix) was estimated and the results are presented in Equation 4.1.

lnRGDP = − 0.2938

∗

lnISG − 0.6300

∗

lnDCI − 0.6617

∗

lnTRI − 2.2147

∗

lnCUPI + 0.7347

∗

lnGFCF + 0.0355lnFIS

(0.0932) (0.1125) (0.1895) (0.4202) (0.0539) (0.0577)

Note: Standard error in parentheses.

* denotes that the coefficient is significant at 5% level.

Equation 9 shows estimates that were obtained from the model to establish a long-run relationship between

insurgency and economic growth in Nigeria. The estimates in the regression were treated as elasticities of RGDP

with respect to the independent variables in the equation, since all other variables are held constant in each case

when a particular variable is being treated. As shown in equation 4.1a, coefficients of variables in the long-run

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are significant at 5% level of significance, with the exception of FISE – which was not statistically significant at

5% level of significance.

The results show that, a one percent increase in insurgency (ISG) is associated with 0.2938% decrease in the

growth of RGDP (real gross domestic product) – the size of the economy in the long-run. This means that when

there is increase in ISG, the growth of real gross domestic product will fall quickly in the long-run. This finding

is in line with that of Ajibola (2016) who reported that insurgency has a negative influence on economic growth

in Nigeria. The results of equation 9 shows that the impact of insurgency on economic growth is statistically

significant at 5% level, thus, the null hypothesis one, which state that insurgency has no significant impact on

economic growth in Nigeria is rejected and its alternative accepted.

The results also show that discomfort index (DCI) is associated with a coefficient of 0.6300, which implies that

a one percent increase in DCI leads to 0.6300% decrease in RGDP and vice versa, in the long-run. This means

that increases (decreases) in discomfort index precipitate decreases (increases) in economic growth in Nigeria in

the long-run. This relationship is statistically significant at 5% level of significance, suggesting rejection of null

hypothesis two, which states that discomfort index does not have a significant impact on economic growth in

Nigeria, and thus its alternative is accepted. Therefore, discomfort index has significant impact on economic

growth in Nigeria. The finding of a negative and significant relationship between DCI and RGDP corroborates

that of Aghaulor (2020), who found that discomfort index has a negative but insignificant effect on economic

growth of Nigeria. However, this was a short-run dynamic.

Terrorism risk index (TRI) shows a negative influence on economic growth as expected. The coefficient of

0.6617 indicates that a one percent change in TRI leads to 0.6617% negative change in economic growth, in the

long-run. The relationship between TRI and RGDP is statistically significant at 5% level of significance, which

means that the null hypothesis three – that terrorism risk index has no significant impact on economic growth in

Nigeria – is rejected, and its alternative accepted. This finding is in line with that of Aghaulor (2020) who

reported a short-run negative relationship between terrorism risk index and economic growth in Nigeria.

The results of Equation 9 also show that corruption perception index (CUPI) has a coefficient of –2.2147. This

implies that a 1% increase in CUPI leads to 2.3147% decrease in real GDP in the long-run and vice versa, this

relationship is statistically significant at 5% level. The results also show that gross fixed capital formation

(GFCF) and federal insecurity expenditure (FISE), individually exerted positive influences on real GDP in

Nigeria in the long-run, in line with a priori expectations. However, FISE was found to be statistically

insignificant at 5% level.

Error Correction Model

Before the estimation of the model, an appropriate lag length was chosen and the results are presented in Table

4.4.

Table 5: Lag Order Selection Criteria for model of Life Expectancy

Lag

Log L

FPE

AIC

76.55047

0.001495

-3.669255

-3.455978

-3.592733

138.4388

104.7342*

6.59e-05*

-6.791735*

-6.535802*

-6.699909*

138.5871

0.243330

6.90e-05

-6.748057

-6.449469

-6.640926

*indicates lag order selected by the criterion

LR: sequential modified LR test statistic (each test at 5% level)

FPE: Final prediction error

AIC: Akaike information criterion

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SC: Schwarz information criterion

HQ: Hannan-Quinn information criterion

Source: Researchers’ Computation, 2025

On the basis of the results presented in Table 4.4, the lag length of 1 was selected as the optimum lag that best

explain how backwards to go in a bid to capture the dynamic behaviour of the variables in the VAR system

regarding the models that explain the effect of insurgency on economic growth in Nigeria. The first year was

selected as the optimum, having produced the minimum AIC, SC, HQ and FPE. The results for the leading

models in their first logarithmic differences on the short-run relationship between insurgency and economic

growth in Nigeria are presented in Table 4.5.

Table 6: Vector Error Correction Estimates

Variables

Coefficient

Std. Errors

t-statistic

RGDP (-1)

0.711915

0.13488

5.27808*

ISG(-1)

0.211245

0.01131

4.99386*

DCI(-1)

0.190292

0.01514

3.27414*

TRI(-1)

-0.219263

0.02016

-3.65436*

CUPI(-1)

-0.035624

0.05128

-0.69475

GFCF(-1)

0.037364

0.03265

1.14427

FISE(-1)

0.013047

0.01775

0.73510

ECM(-1)

-0.256541

0.00713

-4.72812*

0.004562

0.00934

0.48823

R-Squared =

Adj. R-squared =

Sum Sq. Resids =

S.E. equation =

F-statistic =

Log likelihood =

Akaike AIC =

Schwarz SC =

Mean dependent =

S.D. dependent =

0.605583

0.573241

0.013941

0.025766

4.030396

-72.54328

-4.236219

-3.815859

0.044667

0.034912

Source: Researcher’s Computations from Eviews 12

Rgdp is dependent variable

* denotes significance at the 5% level.

Table 6 shows the short-run VEC estimates. The results show that in the short-run, the growth of RGDP in the

current year is positively influenced by the growth of insurgency (ISG (-1)) in the previous year. This implies

that a one percent increase in ISG (-1) is associated with 0.211245% increase in RGDP. The result also show that

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discomfort index (DCI (-1)) had a positive influence on RGDP in the current year. These are contrary to

expectations and may be attributed to increase in budgetary provisions for social security and emergencies arising

from insurgency. The result show that terrorism risk index (TRI (-1)) exerted negative influence on the growth

of RGDP in the short-run. In line with expectations, corruption perception index (CUPI (-1)), exerts negative

influence on economic growth (RGDP) in the short-run. The results also show that, in line with expectations,

gross fixed capital formation (GFCF (-1)) and federal security expenditure FISE (-1), all collectively exert

positive influence on the growth of RGDP in the short-run.

The Adjusted R-squared of 0.605583 shows that even with adjustments in the model, the explanatory variables

included in the model can still explain 60.56% of changes in the RGDP in the short-run. The ECM (-1) value of

-0.256541, with the standard error of 0.00713 and a corresponding t-statistic of -4.72812, show that the speed of

adjustment is significant. This implies that variables included in the model have the ability of returning to their

long-run equilibrium values after experiencing short-run perturbations at a speed of adjustment of 25.65%. The

F-statistic value of 4.030396 reports the synergy effect of explanatory variables on the dependent variable. This

means that explanatory variables included in the study model are collectively significant determinants of

economic growth in Nigeria in the short-run.

DISCUSSION

The first objective of this study was to examine the impact of insurgency on economic growth in Nigeria. The

results of the descriptive statistics show that insurgency is not normally distributed, just as the unit root results

show that the series – insurgency (ISG) failed to attained stationarity at level, however, became stationary after

it was differenced once. The results of the short-run model show that insurgency in the first year lag exerted

positive influence on economic growth in Nigeria. However, in the long-run, as expected, insurgency exhibited

a negative and significant influence on economic growth in Nigeria. On empirical basis, there are strong

evidences for expecting insurgency to exert negative influence on economic growth. This is because, rising

security issues, discourage investments, leads to loss of jobs, lives and properties. Daura (2014) assert that,

“Developing nations like Nigeria in particular experience pervasive risk of devastation, human and property loss

resulting from human and natural disasters. In addition, According to Henderson (2004) “This level of risk was

attributed to socio- economic stress, aging, and inadequate physical infrastructure, weak education and

preparedness for disasters and in sufficient fiscal and economic resources to carefully implement the

preparedness, response, mitigation, and recovery components of emergency management.”

The second objective of this study was to evaluate the impact of discomfort index on economic growth of

Nigeria. Descriptive statistics show that discomfort index exhibit characteristics far from those considered to be

normally distributed. Equally, the series (discomfort index) failed to attain stationarity at level, however, it

became stationary after it was differenced once. The short-run results of the error correction model show that

discomfort index’s relationship with economic growth, was positive and contrary to expectations. However, in

the long-run, the results show that discomfort index has a negative and statistically significant relationship with

economic growth. This called for the rejection of null hypothesis two and the acceptance of its alternative, thus

implying that discomfort index has a significant impact on economic growth in Nigeria. The finding of a negative

and significant relationship between DCI and RGDP corroborates that of Aghaulor (2020), who found that

discomfort index has a negative but insignificant effect on economic growth of Nigeria. However, this was a

short-run dynamic. The results suggest that since the turn of the new millennium, which was the period of clear

comparison and computation of the discomfort index, Nigeria had always record disturbing record in the index

which is attributable to security issues.

The last objective of this study was to analyse the impact of terrorism risk index on economic growth of Nigeria.

Results of descriptive statistics of terrorism risk index revealed that terrorism risk index was not normally

distributed. The unit root test conducted to determine the stationarity property of this series (TRI) showed that

the series became stationary after it was differenced once. The short-run results revealed that, the series drifted

away from its equilibrium value, however, have the tendency of randomly walking back to its equilibrium value

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in the long-run. The long-run results showed that terrorism risk index has a negative and statistically significant

impact on economic growth in Nigeria. The null hypothesis number three—that the terrorist risk index has no

meaningful impact on economic growth in Nigeria—is rejected in favour of its alternative since there is a

statistically significant association between TRI and RGDP at the 5% level of significance. This means that

terrorism risk index has significant negative impact on economic growth in Nigeria. According to the coefficient

of 0.6617, a one percent change in TRI over time results in a negative change in economic growth of 0.6617

percent. This result is consistent with that of Aghaulor (2020), who found a short-term inverse link between

Nigeria's economic development and the terrorist risk index.

CONCLUSION AND POLICY RECOMMENDATIONS

Based on the findings of this research work, it can be concluded that insurgency has negatively influenced the

long-run economic growth process in Nigeria. It can also be concluded that insecurity occasioned by the activities

of militants, kidnappers, violent armed robbers and more especially Boko Haram in the country can truncate the

country’s goal of achieving economic development, if not tackled or checked by the government. Overall, a

nation replete with insecurity can never attract investments nor grow its economy.

The study therefore, recommended based on its findings that since insurgency and terrorism risk indices have

significant long-run negative impacts on economic growth, Nigeria must prioritize strengthening its security

framework. This includes investing in modern surveillance technologies, enhancing intelligence gathering and

sharing, and improving the capacity of security agencies through adequate funding, training, and accountability

mechanisms. Proactive intelligence-led operations can help prevent insurgent attacks, reduce terrorism-related

risks, and restore investor confidence in the Nigerian economy.

The findings show that insurgency, terrorism, and the discomfort index are linked to socioeconomic stressors

such as poverty, unemployment, weak infrastructure, and inequality. Government policies should therefore focus

on inclusive economic growth by expanding job opportunities, particularly for youths, through skill acquisition

programs, agricultural development, and MSME support. Investment in education, healthcare, and social welfare

can also reduce grievances that fuel radicalization, while improving resilience against insecurity.

Finally, it is Given that terrorism risk and insurgency negatively affect economic growth across regions, Nigeria

should complement military responses with regional stabilization programs and community-driven peace

initiatives. Government should engage local leaders, traditional rulers, religious institutions, and civil society in

dialogue and reconciliation processes, particularly in insurgency-prone areas such as the North-East and Niger

Delta. Strengthening social cohesion, rebuilding destroyed infrastructure, and supporting internally displaced

persons (IDPs) with livelihood opportunities will help stabilize communities, reduce insurgent recruitment, and

stimulate local economic recovery.

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