Asymmetry Impact of Economic Policy Uncertainty on Economic Growth in Nigeria

Asymmetry Impact of Economic Policy Uncertainty on Economic Growth in Nigeria

Aina, Abiola Lydia Ph.D.

Department of Economics, Ajayi Crowther University, Oyo, Nigeria.

DOI: https://dx.doi.org/10.47772/IJRISS.2025.90400091

Received: 15 March 2025; Accepted: 19 March 2025; Published: 30 April 2025

ABSTRACT

Economic policy uncertainty posed a significant challenge to economic stability by discouraging investment, weakening market confidence, and slowing growth. This study examined the impact of economic policy uncertainty on Nigeria’s economic growth from April 2016 to June 2023 using the Nonlinear Autoregressive Distributed Lag (NARDL) model and the Nishiyama Granger causality test. The findings revealed that the negative effects of economic policy uncertainty on growth were stronger and statistically significant compared to its positive effects. In the long run, trade openness and labor force expansion contributed positively to economic growth, while inflation had a harmful impact. These results highlighted the need for policymakers to implement transparent and stable economic policies to reduce uncertainty and encourage investment. Structural reforms were necessary to strengthen macroeconomic stability, improve institutional frameworks, and ensure regulatory consistency. Additionally, policies that promoted trade openness helped drive economic expansion, while labor market reforms enhanced productivity. Effective inflation control through sound fiscal and monetary policies was also crucial for maintaining sustainable economic growth in Nigeria.

Keywords: Economic Policy Uncertainty, Economic Growth, Nonlinear ARDL, Trade Openness, Inflation

JEL Classification Codes: C22, E32, O40

INTRODUCTION

One of the major issues facing the world today is the pursuit of sustained economic growth, a goal that has become increasingly central in global development agendas (Islam, 2025; Meka & Venkateswarlu, 2024). With the introduction of the Sustainable Development Goals (SDGs), countries worldwide have intensified their efforts to achieve robust economic growth as a means to alleviate poverty, reduce inequality, and promote overall development (Khan et al, 2024). Over the years, various nations have implemented diverse strategies and policies aimed at fostering economic growth. Nigeria, as one of the largest economies in Africa, has similarly embarked on multiple policy initiatives to stimulate economic development. However, despite these efforts, Nigeria’s economic progress has been hampered by frequent policy changes and inconsistencies, often resulting from shifts in government. These abrupt changes contribute to what is termed economic policy uncertainty, which refers to the unpredictability surrounding government policies that affect economic decisions and outcomes (Adeosun et al, 2023).

Economic policy uncertainty (EPU) is characterized by a lack of clarity regarding fiscal, monetary, and regulatory policies, which can lead to increased risks for investors, businesses, and consumers. In Nigeria, this uncertainty is worsened by frequent political transitions, inconsistent policy implementation, and sudden regulatory shifts. These factors create an unstable environment where businesses and investors are unsure of future economic conditions, leading to reduced investments, slowed economic activities, and hindered growth. EPU can influence key economic variables such as inflation, interest rates, and exchange rates, thereby affecting overall economic stability. The unpredictable nature of economic policies in Nigeria has made it challenging to achieve consistent economic growth, despite the country’s rich natural resources and potential (Aluko et al, 2024; Banjo et al, 2024; Redmond & Nasir, 2020).

Over the years, several policies have been introduced in Nigeria to promote economic growth and reduce policy uncertainty. These included the Structural Adjustment Program (SAP) of the 1980s, the National Economic Empowerment and Development Strategy (NEEDS) in the early 2000s, and more recent initiatives like the Economic Recovery and Growth Plan (ERGP) launched in 2017. These policies aimed to diversify the economy, reduce dependency on oil revenues, and promote sustainable development. However, despite these initiatives, Nigeria’s economic growth has struggled to maintain a positive trend. The frequent changes in leadership and shifts in policy directions have contributed to persistent economic policy uncertainty, undermining the effectiveness of these growth strategies (Ndu-Anunobi et al, 2024).

Various studies have examined the relationship between economic policy uncertainty and economic growth, yielding mixed and inconclusive results. For instance, studies by Adedoyin et al (2021); Gomado, (2025); Istiak and Serletis (2018), opined that high levels of economic policy uncertainty negatively affect economic growth by reducing investment and slowing down economic activities. Conversely, other research, such as by Aye and Kotur, (2022) and Ogbuabor, et al (2021) argued that certain policy changes, even when perceived as uncertain, can stimulate economic growth by introducing necessary reforms and encouraging innovation. These conflicting findings stress the need for further investigation into the specific context of Nigeria, where the relationship between policy uncertainty and economic growth remains inadequately explored. This study, therefore, seeks to determine whether the positive effects of economic policy changes outweigh the negative impacts, making it imperative to examine the asymmetric impact of economic policy uncertainty on Nigeria’s economic growth.

The objective of this paper, therefore, is to determine the asymmetric effects of economic policy uncertainty on economic growth in Nigeria.  To achieve this objective, monthly data from April 2016 to June 2023 were used to investigate the effects of economic policy uncertainty on economic growth in Nigeria. The choice of this period is primarily due to the availability of data on EPU for the period. In addition, the period under review was characterized by at five major events that may have heightened the level of economic uncertainty. These events include the 2016 economic recession, 2019 general elections, COVID-19 pandemic, 2020 economic recession, and the 2023 general elections.

Apart from the introduction, the rest of the paper is structured to provide a comprehensive review of the relevant literature, and highlight key theories and previous empirical findings. A section presents the materials and methods used in the study, detailing the data sources and analytical techniques employed. The final sections discussed the results of the analysis and offers conclusions and policy recommendations based on the study’s outcomes.

LITERATURE REVIEW

Conceptual Review

Economic Policy Uncertainty (EPU) refers to the unpredictability surrounding government actions related to fiscal, monetary, and regulatory policies, which can significantly influence business decisions, investment, and overall economic performance (Al‐Thaqeb et al, 2022). Uncertainty can stem from political instability, shifting regulatory frameworks, or ambiguous government policies. According to Baker, Bloom, and Davis (2016), EPU is measured using indicators such as the frequency of newspaper coverage on policy-related uncertainty, the number of tax code provisions set to expire, and the level of disagreement among economic forecasters. High levels of EPU can lead to delayed investment, reduced consumer spending, and slower economic growth, as businesses and individuals become more cautious in the face of uncertain policy environments (Pastor & Veronesi, 2012).

Economic Growth refers to the sustained increase in a country’s output of goods and services over time, typically measured by the rise in Gross Domestic Product (GDP) or GDP per capita (Dragoi, 2020). Economic growth is driven by factors such as capital accumulation, technological innovation, labor force expansion, and improvements in productivity. According to Solow (1956), technological progress plays a crucial role in long-term economic growth, while endogenous growth theorists like Romer (1986) emphasize the importance of knowledge, innovation, and human capital investment. Economic growth is essential for improving living standards, reducing poverty, and generating resources for public services, but it can also pose challenges related to environmental sustainability and income inequality. Accordingly, the GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for the depreciation of fabricated assets or for the depletion and degradation of natural resources.

Stylized Facts

Figure 1 shows the trend of Economic Policy Uncertainty (EPU) in Nigeria between April 2016 and June 2023, and highlights periods of significant fluctuations driven by various political and global economic events.

Figure 1: Trend of Economic Policy Uncertainty in Nigeria

In Figure 1, high levels of uncertainty were observed in 2016, coinciding with Nigeria’s economic recession triggered by the global oil price crash, foreign exchange restrictions, and inflationary pressures, with further spikes due to the government’s fiscal and monetary policy responses. A period of relative stability was observed from 2018 to early 2019, reflecting gradual economic recovery, although slight increases in EPU during 2019 may be linked to uncertainties surrounding the general elections. A sharp spike occurred in early 2020, marking the peak for the country, corresponding to the COVID-19 pandemic, which caused economic disruptions, oil price volatility, and policy shifts. Post-pandemic, from 2021 to 2023, the EPU showed intermittent fluctuations, influenced by foreign exchange instability, inflation, petrol subsidy removal, and the global impact of the Russia-Ukraine war on Nigeria’s economy. By mid-2023, the trend stabilized at moderate levels, possibly reflecting clearer government policies and post-election reforms aimed at economic stabilization.

Figure 2 illustrates the trend of economic growth in Nigeria between April 2016 and June 2023, and highlights significant fluctuations shaped by various economic shocks and recovery phases.

Figure 2: Trend of Economic Growth in Nigeria.

The graph shows a negative growth rate in 2016, reflecting the recession triggered by the global oil price crash, foreign exchange restrictions, and high inflation. By late 2016 and into 2017, the growth rate began to recover, turning positive as oil prices stabilized and government reforms supported economic stabilization. Between 2018 and 2019, growth maintained a moderate pace, hovering around 2%, indicative of a gradual but steady recovery. However, in 2020, the economy experienced a sharp decline back into negative growth, coinciding with the global economic fallout from the COVID-19 pandemic, which led to lockdowns, decreased oil demand, and significant fiscal strain. By late 2020 into 2021, the graph shows a strong rebound with growth reaching nearly 4%, driven by the easing of pandemic restrictions, increased oil production, and recovery in global demand. From 2021 to 2023, growth remained positive but slightly declined, reflecting persistent structural challenges such as inflation, foreign exchange volatility, and the economic impact of global geopolitical tensions like the Russia-Ukraine conflict. By mid-2023, the growth rate stabilized around 2.9%, signaling cautious optimism amidst ongoing economic reforms and recovery efforts.

Theoretical Framework

The theoretical framework guiding this study is the Endogenous Growth Theory propounded by Romer (1986) and Lucas (1988). The theory posits that economic growth is primarily driven by factors internal to the economy, such as human capital accumulation, innovation, knowledge spillovers, and investments in Research and Development (R&D). These factors lead to increasing returns to scale, thereby promoting sustained economic growth.

Unlike the neoclassical models that assume diminishing returns to capital, endogenous growth models highlight the role of policy interventions, technological innovations, and institutional quality in influencing growth trajectories. This theory suggests that well-designed economic policies can foster innovation, enhance productivity, and support continuous growth. Conversely, uncertainty in economic policies can disrupt investment decisions, reduce innovation incentives, and hinder both physical and human capital accumulation, which are essential components for sustained growth.

The endogenous growth model is given as:

\( Y_t = A_t K_t^{\alpha} H_t^{\beta} \)      (1)

Where:

• \( Y_t \): Output (GDP) at time \( t \)
• \( A_t \): Level of technology at time \( t \)
• \( K_t \): Physical capital stock at time \( t \)
• \( H_t \): Human capital stock at time \( t \)
• \( \alpha, \beta \): Elasticities of output with respect to physical and human capital

Since Economic Policy Uncertainty (EPU) influences both capital accumulation and productivity, \( A_t \) is modeled as:

\( A_t = A_0 e^{-\theta \, \text{EPU}_t} \)      (2)

Where:

• \( A_0 \): Initial level of technology
• \( \text{EPU}_t \): Economic Policy Uncertainty at time \( t \)
• \( \theta \): Sensitivity of technological progress to EPU

Substituting equation (2) into equation (1):

\( Y_t = A_0 e^{-\theta \, \text{EPU}_t} K_t^{\alpha} H_t^{\beta} \)      (3)

Taking the natural logarithm of both sides:

\( \ln Y_t = \ln A_0 – \theta \, \text{EPU}_t + \alpha \ln K_t + \beta \ln H_t \)      (4)

Empirical Review

Gomado (2025) investigated the mediating role of pro-market institutional quality in the relationship between economic performance and uncertainty, focusing on whether institutional reforms during periods of uncertainty could mitigate negative economic impacts. The study analyzed data from sixty-one developing countries between 1990 and 2014, considering various global and domestic shocks, such as the Gulf War, the US recession, the 9/11 attacks, financial crises, and political upheavals. The findings revealed that higher-quality pro-market institutions significantly reduced the adverse effects of uncertainty on economic performance, with the decline in GDP growth due to uncertainty decreasing by 93 percentage points in countries with stronger institutional frameworks. Additionally, the results indicated that pro-market institutional reforms implemented during uncertain periods not only mitigated negative impacts but also supported medium-term economic growth, with variations depending on the specific nature of the reforms.

Kotur et al. (2024) investigated the asymmetric effect of economic policy uncertainty on food security in Nigeria using data from 1970 to 2021. The analysis was conducted using the nonlinear autoregressive distributed lag (NARDL) model. Their findings showed that, in the short run, both positive and negative effects of economic policy uncertainty had a positive and significant relationship with food security in Nigeria. However, in the long run, the negative impact of economic policy uncertainty outweighed its positive effect on food security.

Ekeocha et al. (2023) investigated the effects of economic policy uncertainty (EPU) on economic activities in Africa, as well as the unexplored moderating role of governance institutions and potential regional differences in responses to EPU across the continent. Using system GMM and quantile regression techniques on panel data from 47 African countries spanning 2010 to 2019, the study found that global EPU, along with uncertainties originating from China, the United States of America (USA), and Canada, significantly influenced economic performance in Africa. In contrast, domestic EPU and uncertainties from Europe, the United Kingdom (UK), Japan, and Russia had negligible effects, indicating the resilience of African economies to these sources of uncertainty. Furthermore, governance institutions in Africa were found to have no significant moderating effect on the relationship between uncertainty and economic performance. The study also revealed regional variations, with Central, North, and Southern Africa displaying greater resilience to global EPU and uncertainties compared to East and West Africa.

Ashiru and Oladele (2023) investigated the impact of economic policy uncertainty on inflation in Nigeria, a developing economy facing distinct economic challenges. Utilizing the Autoregressive Distributed Lag (ARDL) Bounds Testing Approach, the study employed the newly developed Economic Policy Uncertainty (EPU) index for Nigeria, covering the period from January 2010 to November 2022. The findings revealed that economic policy uncertainty exerts a positive and significant influence on inflation in both the short and long run.

Aye and Kontur (2022) investigated the long- and short-run effects of economic policy uncertainty on agricultural growth in Nigeria, using annual data obtained from secondary sources. The analysis was conducted using the autoregressive distributed lag (ARDL) model along with the bounds testing approach to assess long-run relationships. The study found that monetary policy uncertainty (MPU) exhibited the highest volatility (2.522), followed by the consumer price index (CPI) at 1.968, while fiscal policy uncertainty (FPU) showed the lowest volatility (0.179). The bounds test results confirmed the existence of a long-run relationship between economic policy uncertainty and agricultural growth. In the long run, the impact of economic policy uncertainty on agricultural growth was negative, with coefficients of -0.004 for MPU, -0.218 for FPU, and -0.507 for trade policy uncertainty (TPU). Similarly, in the short run, all economic policy uncertainty variables negatively and significantly affected agricultural growth and welfare, both in their current values and lagged terms.

Adedoyin et al. (2021) investigated the long-run relationship between energy consumption, tourist arrivals, economic policy uncertainty, and ecological footprint in the top ten international tourism-earning countries from 1995 to 2015. Utilizing fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and Dumitrescu and Hurlin causality tests, the study explored how these factors contribute to environmental degradation. The empirical findings revealed that economic policy uncertainty, alongside tourism and energy consumption, significantly drives environmental degradation. However, it was noted that the impact of energy consumption on the ecological footprint is moderated by economic policy uncertainty, with a 1% increase in uncertainty reducing environmental damage by 0.71%.

Istiak and Serletis (2018) examined the impact of economic policy uncertainty on real income activity in G7 countries using monthly data from January 1985 to March 2015. The analysis employed the dynamic autoregressive distributed lag (ARDL) model alongside impulse response functions. Their findings indicated that the real output of G7 countries responded differently in both direction and magnitude to positive and negative shocks, with country-specific variations. They concluded that economic policy uncertainty was countercyclical, with real output responding negatively to negative shocks, while the response to positive shocks was more severe.

METHODOLOGY

Model

The nonlinear ARDL model by Pesaran et al. (2001) extends the linear ARDL by incorporating an error correction model that captures both positive and negative changes. This study applies the model to analyze the asymmetric impact of economic policy uncertainty on economic growth, considering both short-run and long-run effects. The model is as follows:

\( \text{ECG}_t = \beta_0 + \beta_1 \, \text{EPU}_t + \beta_2 x_t + \varepsilon_t \)      (5)

Here, ECG denotes economic growth, EPU stands for economic policy uncertainty, and \( x_t \) represents the vector of control variables incorporated in the study, which include inflation (INF), labor force (LF), and trade openness (TOP). \( \beta_0 \), stands for the constant while, \( \beta_k \)(k=1,2) represents the coefficients of the independent variables and \( \varepsilon_t \) represents the error term.

Estimation Techniques

Many existing studies on economic policy uncertainty have predominantly utilized conventional linear models; however, research suggests that economic variables often exhibit nonlinear behavior (Gamal et al, 2025; Lee et al, 2022). This poses a major challenge in the empirical literature, as relying on linear models in the presence of nonlinearities can lead to inconsistent and unreliable estimates. Moreover, nonlinear dynamics make it difficult for policymakers to accurately assess the varying impacts both positive and negative of economic policy uncertainty. To address these limitations, this study adopts the nonlinear autoregressive distributed lag (NARDL) model to examine the relationship between economic policy uncertainty and economic growth in Nigeria. This approach effectively captures potential nonlinearities that may arise due to factors such as policy shifts, technological advancements, regulatory changes, and structural transformations. Furthermore, it facilitates a comprehensive analysis of both the short-run and long-run asymmetric effects, allowing for a better understanding of how positive and negative changes in economic policy uncertainty influence economic growth in Nigeria.

To assess the asymmetric impact of economic policy uncertainty on Nigeria’s economic growth within a nonlinear framework, the economic policy uncertainty variable was separated into distinct series—positive and negative based on a zero threshold.:

\( \text{EPU}_t = \text{EPU}_0 + \text{EPU}_t^+ + \text{EPU}_t^- \tag{6} \)

Where EPU₀ stands for the initial value of economic policy uncertainty. EPU_t⁺ is the partial sum process of positive changes in economic policy uncertainty and EPU_t^– represents the partial sum process of negative changes in economic policy uncertainty. Therefore, the asymmetric long-run regression equation is stated as follows:

\( \text{ECG}_t = \alpha_1^+ \text{EPU}_t^+ + \alpha_1^- \text{EPU}_t^- + \alpha_2 x_t + \varepsilon_t \tag{7} \)

From equation 7, ‘+’ and ‘-’ superscripts means positive and negative changes while  and  means the associated long run parameters.

The NARDL model, expressed in its error correction form, is specified as follows:

\[
\Delta \text{ECG}_t = \rho_0 + \rho_1 \text{ECG}_{t-1} + \beta_1^+ \text{EPU}_{t-1}^+ + \beta_1^- \text{EPU}_{t-1}^- + \beta_2 x_{t-1}
+ \sum_{i=1}^{p} \gamma_i \Delta \text{ECG}_{t-i}
+ \sum_{i=0}^{q} \Pi_i^+ \Delta \text{EPU}_{t-i}^+
+ \sum_{i=0}^{r} \Pi_i^- \Delta \text{EPU}_{t-i}^-
+ \sum_{i=0}^{s} \theta_i \Delta x_{t-i}
+ \varepsilon_t
\tag{8}
\]

Where \( \rho_0 \) represents the intercept, and \( \rho_1 \) is the coefficient of the error correction term.
\( \Pi_j^+ \) and \( \Pi_j^- \) capture the adjustments in both the short-run and long-run responses to changes
in economic policy uncertainty. The long-run elasticities are given by:

\( -\beta_1^+ / \rho_1 \) and \( \alpha_1^- = -\beta_1^- / \rho_1 \).

The OLS is employed to estimate Equation (5), while the Wald test was used to determine the short-run symmetry as well as the long-run symmetry. Asymmetric cointegration between the variables is assessed using the bounds testing approach, applying the non-standard Fpass and tBDM tests developed by Pesaran et al. (2001) and Shin et al. (2014), which evaluate the null hypothesis of no cointegration

\( \rho_1 = \beta_1^+ = \beta_1^- = \beta_2 = 0 \)

against the alternative of long-run cointegration:

\( \rho_1 \neq \beta_1^+ \neq \beta_1^- \neq \beta_2 \neq 0 \)

Data

The study was conducted in Nigeria, covering the period from April 2016 to June 2023. The data used included Economic Policy Uncertainty (EPU), GDP growth (annual %), inflation (annual %), labor force participation rate, total (% of total population ages 15-64) (modeled ILO estimate), and trade openness. The EPU data were sourced from the Economic Policy Uncertainty Index developed and compiled by Tumala et al. (2023), while all other variables were obtained from the World Bank World Development Indicators.

RESULTS

Table 1 shows the descriptive statistics of the variables used for the study.

Source: Computed by Author (2025)

The mean value of ECG is 1.415%, indicating that Nigeria experienced modest economic growth over the period studied. The standard deviation of 1.971 suggests significant fluctuations in growth, reflecting the country’s vulnerability to economic shocks such as oil price volatility and political instability. The minimum growth rate of -1.794% points to recessionary periods, possibly linked to global economic downturns or domestic crises, while the maximum of 3.647% signifies periods of robust recovery, driven by favorable economic policies and external conditions.

The mean economic policy uncertainty (EPU) stands at 100. However, the standard deviation of 27.813 indicates high variability in policy uncertainty, suggesting frequent shifts in the economic, political, and global landscape. The minimum EPU value of 57.395 represents periods of relative policy stability, fostering investor confidence and economic activity. Conversely, the maximum value of 200.180 reflects periods of extreme uncertainty, possibly driven by political transitions, inconsistent regulations, and external shocks, which have dampened investor sentiments and slowed economic growth.

Labor force participation (LF) shows a high mean of 82.144%, indicating strong engagement in the workforce throughout the period. The standard deviation is remarkably low at 0.358, suggesting that the participation rate remained relatively stable with minimal fluctuations. The minimum and maximum values, 81.915% and 83.415% respectively, further confirm this stability. Such consistency could be attributed to demographic factors, structural employment trends, and steady labor market conditions that were less sensitive to short-term economic shocks compared to other variables.

Trade openness (TOP) has a mean of 37.302%, reflecting moderate integration of Nigeria’s economy into global markets. The standard deviation of 9.953 indicates considerable fluctuations in trade activities over the period, influenced by factors such as changes in trade policies, global commodity prices, and currency dynamics. The minimum value of 20.723% suggests periods of reduced international trade, potentially due to economic sanctions or protectionist measures, while the maximum value of 54.131% points to periods of heightened trade activity, likely driven by oil export booms or trade liberalization policies.

Inflation (INF) averaged 15.606%, highlighting persistent inflationary pressures in Nigeria’s economy. The standard deviation of 3.538 indicates moderate variability, suggesting that while inflation fluctuated, it remained within a predictable range. The minimum inflation rate was 11.396% which reflects rare periods of relative price stability, possibly due to effective monetary policies and favorable economic conditions. In contrast, the maximum inflation rate was 24.660% which is high and driven by factors such as currency devaluation, supply chain disruptions, and fiscal mismanagement, which have adversely affected purchasing power and overall economic stability.

Unit Root Test Results

To examine the stationarity of the variables used in the study, the Phillips-Perron (PP) and Augmented Dickey-Fuller (ADF) unit root tests were conducted. These tests determine whether a time series variable is non-stationary, which is essential for selecting the appropriate econometric model. The results, presented in Table 2, indicated that economic policy uncertainty (EPU) was stationary at levels, meaning it does not require differencing to achieve stationarity (I(0)). In contrast, economic growth (ECG), labor force participation (LF), trade openness (TOP), and inflation (INF) became stationary only after their first differencing, indicating they are integrated of order one (I(1)).

Source: Computed by Author (2025)

Note: *** denotes significance at 5%

Unit Root Test with Structural Break

Conducting a unit root test with structural breaks is essential because traditional unit root tests, such as the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests, may provide misleading results if there are significant structural changes in the data. Structural breaks, often caused by economic crises, policy shifts, or external shocks, can influence the stationarity of a time series. The results in Table 3 indicate that economic policy uncertainty (EPU) and labor force (LF) are stationary at levels, as their test statistics (-5.540 and -6.552, respectively) are significant at the 5% level. This suggests that these variables do not require differencing for stationarity. However, economic growth (ECG), trade openness (TOP), and inflation (INF) are non-stationary at level but become stationary after first differencing, as evidenced by their highly significant test statistics at first difference (-12.942, -11.359, and -10.632, respectively). These findings confirm the presence of structural breaks in the dataset and highlight the need for appropriate econometric techniques to account for such breaks when modeling relationships among these variables.

Source: Computed by Author (2025)

Test for Nonlinearity

The BDS (Brock-Dechert-Scheinkman) nonlinearity test is essential in this study to determine whether the variables exhibit nonlinear dynamics, which is crucial for accurately modeling the asymmetric effect of economic policy uncertainty on economic growth in Nigeria. Traditional linear models assume a uniform relationship between variables, but if nonlinearity is present, these models may produce misleading results. Table 4 presents the BDS test statistics across different embedding dimensions (m=2 to m=6), with all variables (ECG, EPU, LF, TOP, and INF) showing significant test statistics at the 5% level. This strong statistical significance confirms the presence of nonlinearity in the data, justifying the need for employing the nonlinear autoregressive distributed lag (NARDL) model.

Source: Computed by Author (2025)

Note: *** denote significance at 5%.

Long Run Asymmetry Results

Table 5 presented the results of the long-run and short-run asymmetry tests, which were essential for determining whether economic policy uncertainty had differential effects on economic growth in Nigeria over time. The Wald test for long-run asymmetry (WLR) produced an F-statistic of 4.896 with , indicating statistical significance at the 5% level. This confirmed the existence of an asymmetric relationship in the long run, meaning that positive and negative changes in economic policy uncertainty had differing impacts on economic growth. In contrast, the Wald test for short-run asymmetry (WSR) resulted in an F-statistic of 1.984 with , which was not statistically significant. This suggested that in the short run, the effects of economic policy uncertainty on economic growth were symmetric, implying that both positive and negative shocks influenced growth similarly.

Note: LR = Long run, SR= Short run, *** denote significance at 5%

Bound Test

Table 6 presents the results of the Bound Test for Cointegration, which was conducted to assess the existence of a long-run relationship between economic policy uncertainty and economic growth in Nigeria. The test compared the computed F-statistics with the critical values at significance levels of 1%, 5%, and 10%. The F-statistics from Pesaran, et al (2001) (FPSS = 5.78***) and Banerjee, et al (1998) (FBDM = 5.66***) exceeded the upper bound critical values at all significance levels. Since the test statistics were greater than the upper bound (I(1)), the null hypothesis of no cointegration was rejected. This confirmed the presence of a long-run equilibrium relationship, suggesting that economic policy uncertainty and economic growth in Nigeria were cointegrated and moved together over time, despite short-term fluctuations.

Note: *** denote significance at 5%

Short-Run and Long-Run ResultsTable 7 presents the short-run and long-run asymmetric effects of economic policy uncertainty (EPU) on economic growth (ECG) alongside selected control variables. In the short run, a 1% increase in EPU reduces economic growth by 0.030%, while a 1% decrease in EPU raises economic growth by 0.042%, indicating that the negative impact of economic policy uncertainty outweighs its positive effect. However, both effects are statistically insignificant, suggesting that short-term fluctuations in EPU do not have a significant immediate influence on economic growth. In the long run, a 1% increase in EPU leads to a 0.329% rise in economic growth, while a 1% decrease in EPU results in a 0.456% decline in economic growth, demonstrating that the negative effect of declining EPU outweighs the positive effect of increasing EPU over time. This suggests that while uncertainty may sometimes stimulate economic adjustments, reducing economic policy uncertainty is critical for sustaining long-term growth. The result confirms the findings by Das et al (2024) and Lensink et al (1999).

In the short run, the labor force has a significant negative impact on economic growth. Specifically, a 1% increase in labor force reduces economic growth by 11.02% but was not significant. This implies that fluctuations in labor force participation adversely affect economic growth, possibly due to structural unemployment, underemployment, or inefficiencies in the labor market. However, in the long run, labor force participation becomes insignificant, indicating that, over time, changes in the labor market may not necessarily drive economic growth. Specifically, a 1% increase in labor force participation increases economic growth by 21.68% with . The result supported the findings by Apinran et al (2022) and Emeka (2024).

The short-run results indicate that trade openness has a positive and significant effect on economic growth. As reported a single percent increase in trade openness increases economic growth by 0.529% with  This suggests that increasing trade activities and integration into the global market contribute to short-term economic expansion. However, in the long run, the coefficient of trade openness though positively related to economic growth was statistically insignificant, implying that, over time, trade liberalization alone may not guarantee sustained economic growth unless complemented by other structural policies such as improving trade infrastructure, reducing trade barriers, and enhancing production capacity. Specifically, a percentage increase in trade openness in the long-run increases economic growth by 1.350%. The findings supported the outcome reported by Seti et al (2025).

Inflation from the result shows a negative and insignificant effect on economic growth in the short run, with a percentage point increase in inflation reducing economic growth by 0.074% in the short run, meaning that temporary fluctuations in inflation do not immediately affect economic growth. However, in the long run, inflation has a negative and significant effect on economic growth with a one percentage point increase reducing economic growth by 0.802%, indicating that persistent inflationary pressures harm economic growth by reducing purchasing power, increasing production costs, and creating macroeconomic instability.

The error correction term (-0.092) with  confirms the existence of a long-run equilibrium relationship between economic policy uncertainty and economic growth. However, the negative coefficient value indicates a slow speed of adjustment, meaning that deviations from the long-run equilibrium take time to correct. This suggests that while economic policy uncertainty has a lasting impact on growth, the effects of policy interventions are not immediate and require time to fully materialize.

Note: ** denotes significant at 5%.

As a final step, the Nishiyama et al. (2011) causality test was conducted, with the results presented in Table 8. The findings provided evidence of a one-way nonlinear causality from economic policy uncertainty to economic growth in the first moment (mean), indicating that economic policy uncertainty significantly influenced economic growth in Nigeria. Additionally, a bidirectional causal relationship was observed in the second moment (variance), suggesting that fluctuations in both variables influenced each other over time. This implies that economic policy uncertainty serves as a key predictor of economic growth in Nigeria, while economic growth also contributes to variations in policy uncertainty.

Note: *** denotes significance at 5%

CONCLUSION AND RECOMMENDATIONS

The study examined the asymmetric effect of economic policy uncertainty on economic growth in Nigeria from April 2016 to June 2023 and concluded that while both positive and negative changes in economic policy uncertainty influenced growth, the negative effects outweighed the positive, indicating that periods of uncertainty and instability hindered economic performance more than stable policies promoted it. Additionally, the findings showed that labor force expansion and trade openness contributed positively to economic growth, whereas inflation had a detrimental effect on the Nigerian economy. The existence of a long-run equilibrium relationship suggested that economic policy uncertainty had a lasting impact on growth, though the speed of adjustment was slow. Moreover, the short-run effects were statistically insignificant, reinforcing the notion that economic policy uncertainty primarily influenced growth in the long run.

A key policy implication of these findings was that reducing policy uncertainty could enhance investor confidence and economic stability, ultimately fostering sustainable growth. To mitigate the adverse effects, policymakers needed to implement transparent and consistent policies to improve economic predictability. Furthermore, promoting trade openness, strengthening labor force participation, and ensuring price stability were essential strategies for minimizing the negative impact of inflation and enhancing overall economic resilience.

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