Journal of Contemporary Accounting and Finance

Affiliated with: Department of Accounting, Federal University Dutsin-Ma, Katsina State, Nigeria

ISSN: 3115-6606

ORIGINAL RESEARCH ARTICLE

Importation, unemployment and poverty levels in Nigeria: A structural vector auto-regression (SVAR) model approach

Abubakar Orlando Ijoko¹, Oluwaseun Oluwadamilare Oluwasanmi², Ali Muhammad³, Salam S. Mohammed³

¹Department of Economics, School of Management and Social Sciences, Miva Open University, Abuja, Nigeria.

²Department of Business Management, School of Management and Social Sciences, Miva Open University, Abuja, Nigeria

³Department of Economics, Faculty of Social Sciences, Prince Abubakar Audu University, Anyigba, Kogi State, Nigeria

Corresponding Author: Abubakar Orlando Ijoko abubakar.ijoko@miva.university

Abstract

Nigeria's heavy reliance on imports has worsened unemployment and poverty in the nation. In view of this, this study empirically investigated the impact of importation on unemployment and poverty, with a view to drawing the attention of policymakers to the challenge and to proffering policy recommendations. Using time series data spanning 1991 to 2023, the study employed a Structural Vector Autoregression (SVAR) Model with impulse response functions (IRFs) and forecast error variance decomposition (FEVD) to examine the nexus among the variables of interest. The findings revealed that importation creates indirect employment, though this relationship is weak and not sustainable, suggesting a more significant and sustainable nexus between local production and job creation. On the other hand, importation increases poverty levels by eroding local initiatives that could lead to greater wealth creation and, hence, poverty reduction. The findings, among others, suggest the need to adopt trade policies that balance external objectives with domestic economic stability.

Keywords: Importation, Poverty, SVAR, Unemployment

1. INTRODUCTION

Unemployment and poverty persistently remain a challenge in Nigeria, with significant effects on the nation’s socio-economic progress (Ijoko et al., 2020). Nigeria’s unemployment rate, which reached 38.9% in recent years, and poverty affecting over 40% of the population (NBS, 2023 & World Bank, 2022) pose a significant challenge to socio-economic stability. The interaction between foreign trade policies, particularly as they relate to importation, and these socio-economic issues has become of interest to policymakers and researchers. According to CBN (2023), Nigeria depends mainly on imports to meet the growing demand of its citizens for essential goods, such as machinery, food, and industrial inputs. This dependency has serious implications for local producers, who struggle to compete with cheaper imported goods. While it is argued that importation fosters economic growth by making diverse goods and services available, it has an adverse impact on local production, potentially leading to job losses and heightened poverty levels (Adegoriola & Ben-obi, 2024).

The industrial sector in Nigeria contributes less than 10% to the Gross Domestic Product (GDP), a decline attributable to limited investment, poor infrastructure, and competition from imported products (NBS, 2023). This has led to job losses and reduced income for local producers. Over the past few decades, Nigeria has adopted various trade liberalization policies to boost economic growth through importation. However, these policies have also exposed local industries to unfair competition, contributing to rising unemployment and poverty (Adegoriola & Ben-obi, 2024). The Nigerian economy is highly vulnerable to external shocks, such as fluctuations in global oil prices and exchange rate volatility, which significantly impact import costs, inflation, and economic stability (IMF, 2023).

Empirical studies have shown that importation results in unemployment, with increased importation often leading to job displacement in local industries, aggravating poverty levels (Adekunle, 2025). To examine the dynamic relationship among importation, unemployment, and poverty, this study employs the Vector Autoregression (VAR) model, a robust econometric tool that captures the interdependence among multiple time-series variables (Stock & Watson, 2018). By analyzing historical data, this study aims to identify causal linkages and the magnitude of importation’s impact on Nigeria’s unemployment and poverty levels. Understanding these relationships is crucial for policymakers seeking to strike a balance between trade liberalization and domestic economic stability. The results of this study are expected to provide empirical insights into how importation affects unemployment and poverty in Nigeria, offering actionable recommendations for mitigating adverse impacts while fostering sustainable economic development.

2. EMPIRICAL REVIEW AND HYPOTHESES DEVELOPMENT

Empirical studies have shown mixed results regarding the impact of importation on unemployment. In contributing to this debate, Bisiriyu et al. (2020) and Ijoko et al. (2025) examined the effect of import penetration on employment in Nigeria’s manufacturing sector and found that increased imports significantly displaced local production, leading to job losses. Similarly, Adekunle (2025) highlighted the vulnerability of Nigeria’s labour market to foreign competition, showing that sectors reliant on imported goods experienced higher unemployment rates. Also, Komal and Madan (2020) applied a VAR model to examine the impact of trade liberalization on Nigeria’s labour market. Their findings revealed significant short-run and long-run interactions between importation, unemployment, and poverty. Conversely, Adegoriola et al. (2024) argued that importation could create indirect employment opportunities through supply chain activities, albeit at a lower scale than the job losses incurred.

Additionally, informal cross-border trade (ICBT) in African economies, particularly along the Nigeria-Benin border, has been identified as a significant economic activity driven by pervasive unemployment and poverty (Dzawanda et al., 2025). This form of trade, while providing livelihoods for many, especially women, often involves the importation of cheap goods. However, it also exposes participants to various risks and can undermine formal economic structures. The study underscores that high unemployment rates push individuals into the informal sector, perpetuating a cycle of vulnerability and hindering formal economic growth that could otherwise contribute to poverty reduction.

In analyzing the relationship between importation and poverty, Olarinde and Bello (2021) found that high levels of importation negatively affect the Nigerian government's poverty-reduction efforts. The study found that reliance on imported goods undermines domestic industries, reduces income levels, and increases poverty rates. On the other hand, Afolabi and Ndamsa (2024) discovered that access to affordable imported goods can improve living standards by reducing the cost of essential commodities in Nigeria. The study emphasized that the net effect of importation on poverty depends on the structure of the economy and the inclusivity of trade policies.

A look at unemployment and poverty nexus reveals that unemployment has been consistently identified as a significant driver of poverty. For instance, Komal et al. (2020) found a strong positive correlation between unemployment rates and poverty levels in Nigeria, with each percentage increase in unemployment contributing to a 0.8% rise in poverty. This relationship is particularly pronounced in rural areas, where employment opportunities are scarce, and social safety nets are weak. Similarly, Ibrahim et al. (2024) argued that unemployment perpetuates inter-generational poverty by limiting access to education, healthcare, and other basic needs. Onwuemeka (2024) examined the nexus among inflation, unemployment, and poverty in Nigeria using an Autoregressive Distributed Lag (ARDL) model. The study concluded that income inequality stands as a primary driver of poverty in Nigeria. While inflation and unemployment were found to have significant relationships with poverty, the absence of a causal link between unemployment and poverty in some contexts suggests that other structural factors, such as income distribution, play a more dominant role. Onwuemeka (2024) advocates redistributive fiscal policies and increased public spending on essential services, such as education and health, to improve access for low-income families, thereby reducing income inequality and, consequently, poverty levels.

Furthermore, studies that have directly examined the interactions among importation, unemployment, and poverty include Chinedu et al. (2022), who employed a simultaneous equations model to analyze these linkages in Nigeria and found that importation exacerbates unemployment, which in turn drives poverty levels. The study also highlighted the feedback effect, in which poverty influences demand for imported goods due to a lack of capacity to produce them, often creating a cycle of economic dependence. Similarly, research by Kamara and Orlando (2025) utilized a Granger causality framework and confirmed bidirectional causality between importation and unemployment, and between unemployment and poverty.

Drawing on the empirical literature review, this study tests two hypotheses stated in null form: (i). Structural shocks to importation (specifically finished goods) do not have a significant impact on Nigeria's unemployment rate. (ii). Importation shocks do not exert an indirect impact on poverty levels through the unemployment channel.

2.1 Theoretical Framework

The Dependency Theory posits that the economic development of less developed countries (LDCs) is hindered by their reliance on developed countries for imports, which creates a cycle of dependency that perpetuates poverty and underdevelopment (Cardoso et al., 1979). In the context of Nigeria, this theory can help explain how heavy importation of goods, especially consumer and capital goods, impedes local production, stifles job creation, and ultimately contributes to rising unemployment and poverty levels (Ijoko et al. 2025). The framework highlights the consequences of import dependency, including the erosion of local industries, limited economic diversification, and ongoing poverty (Ake and Claude, 1981; Onimode and Bade, 1973).

As explained, dependency theory suggests that Nigeria’s reliance on developed countries for imports creates a cycle of dependency that perpetuates poverty and underdevelopment. This theory can help explain how heavy importation of goods impedes local production, stifles job creation, and ultimately contributes to rising unemployment and poverty levels in Nigeria. Therefore, dependency theory is the most relevant theoretical framework for investigating the effects of importation on unemployment and poverty in Nigeria. It can be mathematically written as: Pov = f (UMPL, IMP); UMPL = f (IMP)…………………………………………………..…..………..(1)

3. METHODOLOGY

i. Data and Measurements

ii. Technique of Analysis

This study adopts a quantitative research design to examine the dynamic relationships between importation, unemployment, and poverty. Specifically, a time-series econometric approach is employed to capture the inter-dependencies and causal relationships among the variables. To explore the relationships among the variables, the study first employs the Augmented Dickey-Fuller (ADF) unit root test to assess the stationarity of the variables, understand their properties, and ascertain their validity for the Structural Vector Auto-regression (SVAR) model. Since we would be interested in long-run restrictions (that is, permanent changes in the importation have no long-run effect on unemployment and poverty rate), it is expected that the unit root test would return at least one variable as stationary at first difference, I(1) and the variables would be in their natural logarithm forms.

The SVAR model allows the explicit modelling of contemporaneous interdependence among the left-hand-side variables. Hence, these models aim to overcome the shortcomings of VAR models. We use the SVAR model, as it can be used to interpret the effects of structural shocks in importation on unemployment and the poverty rate. The purpose of applying SVAR models is to determine the dynamic responses of unemployment and the poverty rate to an independent external shock, Importation. We apply the following SVAR model, as demonstrated in the Akinbobola and Saibu (2004) study.

\(y_{t} = \sum_{n = 1}^{k}{Ay}_{t - n} + \sum_{n = 0}^{k}{Cx}_{t - n} + \varepsilon_{t}\)……………………………………………………………(2)

where A and C are the structural coefficients of the variables, and the ε_t are the orthonormal unobserved structural innovations. y_t = \((y_{t}^{d},y_{t}^{f})\), x_t = \((x_{t}^{d},x_{t}^{f})\), are vectors of variables representing the endogenous factors, as well as exogenous factors of the domestic and external variables respectively, and ε_t = \((\varepsilon_{t}^{d}{,\varepsilon}_{t}^{f})\), is the vector of structural shocks with domestic \((\varepsilon_{t}^{d})\) and external \((\varepsilon_{t}^{f})\) origin. The vector of internal variables is represented by the series of unemployment and poverty rate, and the vector of external variables contains importation. Hence, we estimate the following models for our objectives:

\({logUMPL}_{t} = \sum_{n = 1}^{2}{{A(logUMPL}_{t - n})} + \sum_{n = 0}^{2}{{C(logPOVR}_{t - n})} + \sum_{n = 0}^{2}{{C(logIMP}_{t - n})} + \sum_{n = 0}^{2}{{C(logINFL}_{t - n})} + \varepsilon_{t}\)……………………………………………………………………….(3)

\({logPOVR}_{t} = \sum_{n = 1}^{2}{{A(logPOVR}_{t - n})} + \sum_{n = 0}^{2}{{C(logUMPL}_{t - n})} + \sum_{n = 0}^{2}{{C(logIMP}_{t - n})} + \sum_{n = 0}^{2}{{C(logINFL}_{t - n})} + \varepsilon_{t}\) …………………………………………………………….……(4)

Where logPOVR is Poverty, logUMPL represents Unemployment, logIMP stands for Importation, and logINFL is Inflation Rate. The \(\varepsilon_{t}\) is the error term, while A and C are the coefficients. All variables are in their natural logarithm form (log)

Therefore, the estimation of SVAR models provides important information on the dynamic responses of unemployment and the poverty rate to structural shocks and on the variance explained by the dynamics of importation. The empirical results can provide important guidance on possible measures to manage (or reduce) unemployment and the poverty rate during periods of decline, taking into account their sensitivity to importation.

Moreover, the shocks will be illustrated using the generated impulse response functions (IRFs) and forecast error variance decompositions (FEVDs). While the IRFs trace the direction and size of the effect of a one-standard-deviation shock to one variable on other system variables over time, the FEVD shows the percentage of each variable's forecast error variance that may be attributed to its own dynamics and to fluctuations in other variables in the system. Since model variables are converted to first differences prior to estimation, the IRFs and FEVD reported indicate the effects of a shock to the changes in unemployment and the poverty rate on changes in importation.

4. RESULTS AND DISCUSSION

Table 1: Stationarity Test

Note: ***,**, * indicate 1%, 5% and 10% respectively.

Table 1 shows the Augmented Dickey-Fuller (ADF) unit root test results for determining the stationarity of the variables. Three of the four variables; UMPL, IMP, and INFL, are found to be non-stationary at levels but are stationary at first difference I(1). However, only POVR is stationary at level I(0). This result is valid for the use of the SVAR model, as there must be stationarity at the first difference of at least one variable.

Table 2: Lag Order Selection Criteria

Note: * indicates lag order selected by the criterion. Where LR: sequential modified LR test statistic (each test at 5% level), FPE: Final prediction error, AIC: Akaike information criterion, SC: Schwarz information criterion, HQ: Hannan-Quinn information criterion.

To carry out SVAR analyses, the need to determine the accurate lag length. Thus, Table 2 presents the results of all lag selection criteria for determining the lag length using LR. SC and HQ indicate a one-lag, while PPE and AIC select two-lags. Therefore, we select a one-lag length for the analysis rather than two lags.

Figure 1: Impulse Response Functions (IRFs)

Figure 1 illustrates the responses of the dependent variables (that is, unemployment and poverty rates) to different structural shocks for each exogenous variable. We would concentrate on the first two rows, which explain our objectives. From the first row, the figure shows that unemployment responds negatively to the unemployment shock (shock 1), the import shock (shock 3), and the inflation shock (shock 4). This suggests that increases (or decreases) in these shocks will have an indirect, inverse impact on unemployment. Also, a positive response of unemployment to a poverty shock (shock 2) is observed, suggesting that poverty and unemployment move in the same direction. However, in the long run, the shocks all vanish (or decrease). This supports the long-run restriction imposed in the model, which does not reveal long-run unemployment responses. The results of the indirect impact of importation (Shock 3) on unemployment suggest that importation creates indirect employment. However, this empirical finding is relatively weak and the impact is short-lived, implying that domestic production could have had a more significant negative impact on unemployment. However, the finding of a negative impact of importation on unemployment supports the study by Adegoriola et al. (2024), who argued that importation could create indirect employment opportunities.

Secondly, we discuss the second row, which shows the responses of the poverty rate to shocks in other variables (domestic and foreign). The responses of the poverty rate to the fluctuations of the unemployment shock (shock 1) and the import shock (shock 3) are positive in periods 1-2, before it permanently vanishes. It implies that both import and unemployment shocks lead to higher poverty in the short run. However, POVR responds negatively to shock 2 (poverty rate shock) and shock 4 (inflation shock) in years 1-2, then shows a slight increase and permanently clears. These findings simply indicate that there is no shock that has the capacity to permanently impact the poverty rate. The results conform with the study of Chinedu et al. (2022).

Table 3: Forecast error variance decomposition (FEVD)

To complement the IRF results, we discuss the result of the variance decomposition shown in Table 3. From Table 3, the variation in unemployment (UMPL) for the first quarter (period 3) is attributed to 86.8%, 6.66%, 2.41%, and 4.16% for UMPL, poverty rate (POVR), importation (IMP), and inflation (INFL), respectively. For the second quarter (period 6), the variation in UMPL is explained by 86.82% in UMPL itself, 6.48% in POVR, 2.71% in IMP, and 3.99% in INFL. Similarly, in the third quarter (period 9), the variation in UMPL is accounted for at 86.17%, 6.83%, 2.85%, and 4.15% for UMPL, POVR, IMP, and INFL, respectively. Lastly, in the fourth quarter (period 12), changes in UMPL are caused by 86.07%, 6.90%, 2.86%, and 4.18% variations in UMPL, POVR, IMP, and INFL, respectively.

The poverty shock explains almost 86% of the variation in POVR in the fourth quarter. Followed by the INFL shock, which accounts for about 10.8% of the variation in POVR in the fourth quarter. While the shock of Importation (IMP) contributes to the variation in POVR by 1.84%, 1.88%, 1.94%, and 2.01% in quarters 1, 2, 3 and 4, respectively, the shock of unemployment (UMPL) accounts for the least variation in POVR at about 1.18% at the end of the 12^th period (or 4^th quarter). The findings generally reveal that the variation in the shocks to importation on unemployment and poverty increases over time across the four quarters covered by the findings.

5. CONCLUSION

The study has empirically examined how unemployment and poverty respond to importation in the Nigerian economy. It is observed that importation creates indirect employment but this empirical nexus is weak and not sustainable hence it persists for a very short period before it vanishes. This suggests that domestic production could have had more significant and sustainable employment creation if allowed to thrive in the Nigerian economy through deliberate policies aimed at boosting local productivity. Importation, on the other hand, results in higher poverty levels in the country, suggesting that as the country imports more products, local initiatives are destroyed, culminating in a shrinking domestic investment base that could absorb more of the labour force, thereby resulting in higher poverty levels in the country. In addition, it is observed that poverty and unemployment are mutually reinforcing, suggesting that the variables move in the same direction. The findings suggest the need to adopt trade policies that could significantly reduce the importation of commodities that can be produced locally, ensure local content, and balance domestic economic stability with trade liberalization. Also, the government should make concerted efforts to bridge the infrastructure gap and improve the financial system's contribution to industrial productivity.

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