1. Introduction
From 1992 to 2021, Afghanistan’s longest war, which resulted in the overthrow of several political regimes and governments, had severe impacts on socioeconomic indicators. Extreme poverty, the highest unemployment rate, extreme income disparities, forced migration, loss of millions of people, physical and mental disabilities, loss of social and economic infrastructure, human capital flight, and trillions of dollars of outcome-free expenditure are the ultimate results of the civil wars in Afghanistan [
1,
2]. It is well documented by the existing literature (see, inter alia, refs. [
3,
4,
5]) that civil wars destroy economic and social institutions, plunge a country into poverty, foster extremism, erode social norms, and increase unemployment rate, all of which return as a cyclical effect to war intensification. Nonetheless, there is no general agreement on the speed of a nation’s post-conflict recovery, but it is literally obvious that it takes longer than expected due to the prevalence of social exclusion, extreme poverty, and reconstruction of devasted infrastructure in war-torn societies—Afghanistan being at the top of the list of such societies, assuming that long-run civil wars have concurrent and long-term negative effects, specifically on the high unemployment rate. Thus, this study turns its focus to analyzing one of the sensitive strands of the socioeconomic predictors—that is, the labor market effects of the long-run war on the unemployment rate, which is assumed to have significant causality in intensifying the war in Afghanistan.
From an economic point of view, civil wars disrupt the balance of demand and supply of manpower in an economy, causing the supply (demand) curves to shift upward (downward), resulting in an excess of manpower supply, which significantly heightens the unemployment rate [
6,
7]. The short-run consequences of war-driven unemployment may simultaneously swallow per capita savings and decrease per capita real income and aggregate consumption, which can be adjusted by effective interference [
8], while the long-run consequences of war-driven unemployment have far more serious social impacts on the economy, inflicting severe negativity and inconceivable human suffering [
9], which will take an unexpectedly long time to recover to its pre-war state. Moreover, it is also well evident that war-driven unemployment is a significant driver of plunging nations into severe poverty and unemployment, further enhancing the propensity for prolonged civil wars. Therefore, the emerging term “war-driven unemployment” should still be used with caution because several empirical studies show an inverse trend—that is, unemployment-driven civil wars [
5,
10]. Such claims are plausible but are likely to provide only half an explanation. Therefore, one way or another, each war-torn society will, perhaps, require a context-specific analysis to gain a wider and deeper insight into the causes, effects, and causality direction of the civil wars with the socioeconomic indicators. The principal conclusions of recent studies have also urged empirical works to focus on context-specific questions, sophisticated empirical models, and a wide range of predictors to offer comprehensive results on the social and economic consequences of civil wars (see, inter alia, refs. [
11,
12]). From a sustainability viewpoint, only when output growth exceeds the economy’s aggregate productivity of human capital can it decrease the unemployment rate. As a result, growth moves closer to sustainability if the gradual economic growth promotes a rapid decline in unemployment [
13]. Again, such a theoretical expectation is disrupted by the consequences of prolonged civil wars in a country.
Even though a vast body of literature exists on the legacies of civil wars and their effects on different indicators, such as mental health, human displacement, growth, poverty, and income disparities, the missing gaps in the literature can be highlighted in two key areas. First, the scarcity of empirical studies to analyze the effects of long-run civil war on the unemployment rate—that is, one of the sensitive labor-market strands and an important component of the sustainable development goals (SDGs) for developing and post-conflict economies, using sophisticated models to offer consistent, accurate, and comprehensive results. Second, the non-existence of such studies examining the effects of the longest civil war on the unemployment rate in Afghanistan, which has been a war-torn society for the last four decades, provides ample room and significant justification for the present study to fill the gaps. To that end, it is important to direct the study by formulating three key questions, among all others. First, does the long-run civil war have positive (negative) asymmetric effects that increase (decrease) the unemployment rate? Second, as aimed by the United Nations, does financial inclusion effectively intermediate to squeeze the asymmetries of civil war on the unemployment rate? Third, do the negative (positive) components of the civil war cause any negativity (positivity) in the unemployment rate?
The key objective of this study is to provide statistical evidence on the effects of the long-run civil war on the unemployment rate in Afghanistan by taking a new step in the existing literature and using non-linear autoregressive distributed lags (NARDL) and asymmetric causality techniques to uncover the effects and establish a foundational literature. Though the study focuses on Afghanistan, its outcome can be generalized to all war-torn societies that share a common nature. Thus, this paper is a novel study in the literature of war-driven unemployment analysis in Afghanistan and, therefore, its contribution can be outlined as follows: First and foremost, to the best of the authors’ knowledge, this is the first ever study in the existing literature for Afghanistan examining the effects of long-run civil war on the unemployment rate. Second, this paper builds a comprehensive composite financial inclusion index for Afghanistan, using widely accepted predictors that explain financial inclusion outreach and are incorporated into the model to explain its intermediating role in reducing unemployability during wartime. Third, unlike most recent studies, this paper employs sophisticated models that allow asymmetric characteristics of the predictors in assessing the effects of civil war on the unemployment rate, using the most recent and updated datasets from 2004Q3 to 2020Q4 to reflect new statistical evidence. Fourth, it enables a broad range of control predictors in the modeling process to provide deeper analysis by considering the intermediating effects of relevant macroeconomic indicators on the unemployment rate.
The remaining sections of the study are structured as follows.
Section 2 reviews the relevant literature about the concept of civil war and its effects on various socioeconomic indicators, specifically the unemployment rate.
Section 3 presents the methodology, explaining the empirical models, estimation strategy, data, and variables used in the study to test the competing hypotheses.
Section 4 presents the results of the estimations and discussion about the findings.
Section 5 provides the concluding remarks and some relevant policy recommendations.
2. Literature Review
There are various definitions of war in the existing literature, but all definitions give the impression of similar content. McNeill and Mueller [
14] define war as a state of armed conflict within or between two or more nations seeking political, economic, and/or other beneficial hegemonies. Gersovitz and Kriger [
15] define civil wars as politically organized, sustained, large-scale, and armed conflicts within or between important groups of a country’s inhabitants over the monopoly of political and economic powers. Kalyvas [
16] and Farrell [
17] define war as instances of organized and sustained conflicts between political parties, groups of inhabitants, two or more nations, or countries that are subject to a common authority at the onset of aggression. Although various definitions and theories have been developed to define civil war and its destructive effects on nations, it is evident that war is a great tragedy and a societal catastrophe [
18], whether it is executed by one country against another or imagined to be waged by humanity as a whole [
19].
The basic concept of war is not uncommon to the nations; it is stated that, if not all, almost a large proportion of all nations have witnessed either intense or trifling conflicts. In the common sense, an armed conflict between political groups is linked by aggressions of extensive duration and magnitude [
20]. Though advances in technology have changed the mechanics of war from those of 1945, the concept has remained unchanged. On the one hand, the empirical literature widely documents the effects of long-term war on socioeconomic indicators, reporting the customary measurement of war effects in terms of money, cost of war, effects of war on the economy, lost productivity, psychological effects of war, and the number of people killed, wounded, and displaced; while on the other hand, it does not report a standard measurement method to ascertain the scale and magnitude of the effects of war on specific socioeconomic indicators. Moreover, the trend of global war has been gradually declining in the past two centuries, but the trend of civil war shows a rapid upward shift in the last four decades [
21]. It shows that civil war is most likely to impact the working population; therefore, the human capital and their active engagement in an affected economy [
22]. In a general theoretical sense, using plausible assumptions, unemployment is based on the excessive supply of manpower viz-a-viz demand for labor in an economy. A supply that is higher than the numbers demanded or does not match the skills, knowledge, and technicalities is likely to influence the rate of unemployment [
23]. However, these assumptions become invalid in an economy bearing the brunt of massive destruction due to prolonged civil wars, where war is assumed to be the main cause of the unemployment onset and unemployment is the outset cause of the intensified civil wars. Though the existing literature mainly documents the civil wars that are outright linked to unemployment, this study proceeds to review the available ones.
For instance, Raphael and Winter-Ebmer [
24] investigated the empirical relationship between the unemployment rate and the level of crime, using datasets for US states. The authors employed a wide range of control variables for state-level demographic and economic factors, prime defense contracts, state-effects, time-trend, and year-effects in their estimations. They found that there was a significant link between the decline in crime and the unemployment rate during the 1990s, implying that the decline in the unemployment rate was associated with a reduction in the crime rate. This requires testing the following hypothesis in the context of the long-term war in Afghanistan:
H1. There is an asymmetric relationship between civil war and unemployment in Afghanistan.
Rabiile [
25] examined the effects of civil wars on the unemployment rate in Mogadishu, Somalia, aiming to test the effectiveness of the Somalian government’s policies to increase job creation in an affected war economy. The author used a self-administered questionnaire and collected primary data from 171 out of 300 respondents and employed descriptive statistics and correlation analysis. The author concluded that there was a significant link between civil war and unemployment, emphasizing the importance of policy changes to encourage foreign investment and sound international projects to reduce unemployment in Mogadishu, Somalia. Hamilton [
26] examined the impact of unemployment on civil conflict in 184 countries based on the North Ireland case. The author used both social and economic factors, with a specific focus on civil conflict in ethnically heterogeneous nations. Using logit regression models, the author found that rising unemployment rates are linked with the onset of civil wars.
Miguel and Roland [
27] investigated the impact of US bombing on the persistence of local poverty and unemployability in Vietnam, using a set of unique data relevant to the US military, comprising bombing intensity at district levels, which bears a massive humanitarian cost. The estimation was based on comparative analysis of the districts bombed with other districts, while the authors controlled for demographic and geographic characteristics. The authors conclude that there were no significant effects of bombing on the outcome variables, though it has been the most intensified bombing in the history of Vietnam (see, also, ref. [
28]).
Berman et al. [
29] argued for the notion of the opportunity cost, relevant to government spending to bring social and political order, assuming that gainful employment of young men reduces their propensity to participate in armed conflicts. The authors used their assumptions in Afghanistan, Iran, and the Philippines, employing a set of survey data comprising unemployment, attacks against governments and their allied forces, and civilian deaths. The estimation results of their study conclude that there is no significantly positive link between the predictors. Specifically, no evidence was found to support the relationship between unemployment and the number of attacks killing civilians in all three countries. Furthermore, the authors found potential explanations, presenting the notion that insurgent meticulousness to arbitrate between the potentials of predation on one hand and security measures and information costs on the other would be the negative association between the unemployment rate and civil wars.
Kecmanovic [
30] evaluated the effects of war in Croatia on unemployment, education, and earnings lines of men born in 1971, using the Croatian and Slovenian Labor Force Survey datasets and the Difference in Difference (DiD) method to analyze their data in comparison with Slovenia, a neighboring country that experienced no war. The authors found that the war is negatively associated with education and positively associated with the unemployment rate and earning outcomes of men born in 1971. The author argues that Croatia’s victory explains the observed preferential treatment of draftees in the labor market. Moreover, Galdo [
12] investigated the effects of armed conflicts on the labor market in Peru, using datasets spanning from 1980 to 1995. The author discovered that the first 36 months of life are the most vulnerable period of early life exposure to civil war, and that one standard deviation increase in war causes a 5% decrease in adult monthly earnings, a significant decrease in the recruitment of female job seekers, and a 6% decrease in the possibility of men working in large companies. Thus, the author emphasizes the positive association of unemployment with the civil war in Peru. This leads this study to develop the following hypothesis:
H2. Civil war has non-monotonic negative effects on the rapidly rising unemployment rate in both the short and long runs.
Shemyakina [
31] explored the effects of armed conflicts on the outcomes of the labor market in Tajikistan, focusing on school-age cohorts during wartime, from 1992 to 1998. The author controlled for district-level exposures to civil war and employed regression analysis. The author found that younger women who lived in war-effected regions were more affected by conflict than men and were 10% more likely to be employed compared to older women from less affected districts. These results show a changing pattern in the employment of women induced by civil war.
Vincent de Paul et al. [
32] evaluated the long-run effects of conflict exposure throughout various stages of life on the outcomes of the labor market in Sierra Leone using datasets from the Sierra Leone Integrated Household Survey (2011) and other sources on human-rights violations and loss of assets during war. The authors found negative effects of conflict exposures throughout primary schooling time and long-run labor market involvement and employment, implying that long-run effects of war reduce labor market participation, e.g., employment, by 3% in Sierra Leone.
Mansoor [
33], which is a leading study of the war-unemployment rate nexus in Afghanistan, attempted to explain the principal reasons for unemployment in Afghanistan. The author employed secondary datasets collected from a nationally representative household survey and augmented the variables of his study with age, gender, marital status, the level of education, educational attainment, sector-wise employment, and insecurity perception. The author employed logit regression models to test the effects of the war and the youth protuberance on total labor market failure in Afghanistan and found that the high unemployment rate is not statistically significant enough to impact the war and the insecurity in Afghanistan and concluded that the rapidly rising unemployment rate is not necessarily the cause of the prolonged war in the country, while age, gender, education, marital status, geographical constraints, and sector-wise employment are statistically significant enough to impact the unemployment in Afghanistan. Assuming the feedback effects, it is important to develop and test the following two competing hypotheses:
H3. In a country-specific context—for example, in Afghanistan—asymmetric causality runs from civil war to unemployment rate with no feedback response.
H4. The current study assumes that the expansion of financial inclusion outreach intertwines with the civil war and reduces the direct effects of the civil war on the unemployment rate.
Although the existing literature is limited in reporting empirical studies focusing on testing the effects of civil wars on unemployment rate or using sophisticated models to provide accurate and consistent results, the literature reports no study analyzing the effects of long-term civil wars on the unemployment rate in Afghanistan, a country where most of the population lives below the poverty line with an extremely high unemployment rate. Thus, it encourages the present study to overcome these empirical shortcomings.
5. Conclusions
It is assumed that civil war not only destroys a country’s infrastructure but also has serious negative effects on the socioeconomic indicators of an economy, both during wartime and as residual effects afterward. The results of the empirical analysis using an asymmetric approach to test the effects of civil war and relevant control predictors on the unemployment rate in Afghanistan suggest that both the positive and negative asymmetric shocks from civil war, which is the key variable of interest in this study, significantly increase and decrease the unemployment rate in the short and long runs, respectively. The results clearly reflect that an increase in the cost of war causes the unemployment rate to increase, while a percentage decrease in the cost of war causes the unemployment rate to decrease in the runs. This implies that the occurrence of war allocates specific employments for the military sector, while it causes a massive unemployability in Afghanistan. Innovatively, this article incorporated the composite financial inclusion index into the model. The results demonstrate that enhancing the outreach of financial services intermediately reduces the unemployment rate during wartime in Afghanistan, while the exclusion of financial services increases the unemployment rate both in the short and long runs. Consistent with Okun’s law, the findings support that an asymmetric positive change in the GDP growth rate increases employability, whereas its negative asymmetric change reduces employability in the short and long runs. Moreover, the findings provide significant evidence that positive (negative) partial changes in government expenditure, foreign direct investment, and the rule of law decrease (increase) the unemployment rate in the short and long runs. The findings show that an asymmetric positive change in the inflation rate reduces the unemployment rate, while a negative partial sum change in the inflation rate reduces the unemployment rate. The population growth rate is also found to have significantly asymmetric effects on the unemployment rate both in the short and long runs, implying that positive (negative) changes in the population growth rate increase (decrease) the unemployment rate in Afghanistan. Finally, as the results suggested, the study examined the asymmetric causality relationship between the unemployment rate, the cost of war, and the control variables. The results indicate that except for the final government expenditure and the secondary school enrollment rate, asymmetric causality runs from both the positive and negative asymmetric components of the cost of war, the composite financial inclusion index, GDP growth, foreign direct investment, inflation rate, population growth, and the rule of law to the unemployment rate.
These results highlight several important policy implications. First, the government needs to bring in significant orders in the relevant policies concerning the labor market to adjust to the excessive supply of unskilled and deficient labor that has emerged as a direct and indirect consequence of the long-running war in Afghanistan. Second, improving regional and provincial occupational mobility would be an effective policy tool to reduce the unemployment rate, with a specific focus on the regions most affected by war. Third, as an act of post-war economic recovery, though it takes longer, the government needs to support the engagement of private sector actors to generate jobs. Fourth, improvement of policies that attract innovative and technological projects to create new job opportunities. Fifth, it is found that financial inclusion is an effective tool to reduce the long-run effects of war on unemployability. As a result, assisting financial institutions in extending the outreach of financial inclusion would engage newly banked people in the creation of new job opportunities.
Limitations of the Study
The present study suffers from one major limitation, which is the unavailability of datasets for the cost of war in Afghanistan for a longer period. Since there has been war in Afghanistan for more than four decades, the datasets are only available from 2004 to 2020. Upon availability, future studies may augment higher-frequency datasets to explore additional insights into the effects of war on the unemployment rate in Afghanistan.