Publications

This study employs the recently proposed bootstrap autoregressive distributed lag (ARDL) model, augmented with a Fourier function, and the dynamic ARDL simulation procedures, to examine whether the oil price economic growth relationship depends on the level of corruption in an oil-dependent economy. Using Nigerian quarterly data from the 1996Q1–2021Q4 period, the results of the bounds-testing provide evidence of cointegration between the variables. In addition, the results indicate that oil price and corruption are growth-enhancing, but the effect of oil price on growth is contingent on the level of corruption. Moreover, evidence suggests that the marginal effect of oil price on economic growth varies with the level of corruption: the lower the level of corruption, the higher the growth-enhancing effect of oil price on economic growth, and vice versa. The dynamic ARDL simulation plots demonstrate a significant increase (decrease) in predicted growth in the short term due to a counterfactual rise in the price of oil (corruption), which gradually deflates (increases) after the shock in the long term. Therefore, policies geared toward diversifying the economy away from oil, reducing corruption in the oil and gas industry and the security sector, improving agricultural output, and reducing the unemployment rate are recommended to enhance growth.

Utilizing a nonlinear autoregressive distributed lag (NARDL) model, this study aims to find out if the shadow economy's (SE) effect on Malaysia's economic growth is not linear from 1970 to 2022. This model uniquely identifies potential nonlinearities or asymmetries in the relationship between SE and growth. The results of the bounds tests show that there is a strong long-term link between economic growth and both good and bad changes in the SE, as well as variables like inflation, urban population growth in cities, financial development, and economic uncertainty. Furthermore, the results indicate that the SE’s influence on growth is nonlinear, both in the short and long term. In particular, both growing and shrinking the SE have positive effects on growth, but growing the SE has a bigger long-term effect than shrinking it. Conversely, in the short term, reductions in the SE’s size have a greater impact. Additionally, inflation, urban population growth, financial development, and economic uncertainties emerge as key determinants of growth across both time horizons. These findings suggest the need for policies that reduce the size of the shadow economy and encourage the shift from informal to formal economic activities to foster sustained economic growth.

The study assesses external debt’s impact on MINT countries’ (Mexico, Indonesia, Nigeria, and Turkiye) manufacturing sector’s performance during the 1980–2021 period, using dynamic heterogeneous panel methods (i.e. dynamic fixed effects, mean group, and pooled mean group estimators). The findings portray the presence of long-term relation between external debt and manufacturing performance (alongside external debt service, inflation rate, population size, exchange rate, FDI, and agricultural output) based on the Kao’s residual cointegration test. The empirical outcomes portray a dampening impact of external debt on manufacturing sector’s performance during the short and long term. Moreover, external debt servicing, FDI, population size, and inflation rate promote the sector’s performance, but exchange rate (depreciation) hurts manufacturing performance. Furthermore, the Dumitrescu-Hurlin heterogeneous panel causality test portrays a one-way causality from external debt servicing (and exchange rate) to manufacturing sector’s performance and a two-way causality between manufacturing sector and population (and FDI and agricultural output). Thus, policies aimed at lowering external debt, lessening exchange rate variability and inflation rate, and boosting inward FDI are recommended to promote the sector’s performance.

This study examines whether the effect of oil prices on economic growth is influenced by the level of corruption. I focus on 30 oil-rich economies and employ dynamic heterogeneous panel estimation techniques to address the issue of cross-sectional dependence. Evidence from the study reveals that the impact of oil prices on growth varies with corruption levels. Specifically, the marginal effect of oil prices on growth is positive at low levels of corruption but hampers immediate and long-term growth at high levels of corruption. Essentially, the results indicate that a simultaneous increase in oil prices and corruption impairs growth, whereas increase in oil prices coupled with a reduction in corruption benefits the economy more. Using a disaggregated sample of countries based on their corruption levels, the results suggest that the adverse effect of simultaneous increases in oil prices and corruption is more pronounced in oil-rich countries with higher levels of corruption compared to those with lower levels. The study implies that the level of corruption is a crucial factor in how changes in oil prices impact long-term growth in oil-rich economies. Therefore, for sustainable long-term economic growth, an increase in oil prices must be accompanied by a significant reduction in corruption.

Over the past three decades, Nigeria has experienced unstable domestic investment and direct foreign investment inflows, and the country continues to face rising corruption and related problems. An ARDL technique has been adopted to explore long-term FDI impact on domestic investment including evaluating if FDI-domestic investment nexus is dependent on corruption level in Nigeria over this period. The bounds test result shows an evidence of a long-term relation amongst FDI, domestic investment and corruption (including GDP per capita, lending rate, exchange rate and oil price). We find that increasing inward FDI reduces (crowds-out) domestic investment and greater corruption control (lowering corruption level) leads to higher domestic investment in Nigeria over the long-term. Also, the influence of FDI on domestic investment depends on (or varies with) corruption level. FDI crowds-in domestic investment at greater corruption control than at lesser corruption control in the long-term. Other significant long-term influencers of domestic investment are exchange rate and oil price. Given these outcomes, we offer some recommendations to boost domestic investment in Nigeria.

This study examines the asymmetric effect of the shadow economy on environmental pollution in Egypt during the 1970 and 2022 period. Using the bootstrap nonlinear autoregressive distributed lag (NARDL) bounds-testing approach, the study presents evidence of nonlinear cointegrating relationship between environmental degradation (carbon emission) and shadow economic activities (alongside globalisation, urbanisation, GDP per capita, and industrial growth). In addition, the results demonstrate that the impact of the shadow economy (SE) on environmental pollution (ENV) is nonlinear, with the positive shock in shadow economy promoting environmental degradation and negative shocks promoting environmental quality, both in the short- and long-run. However, the study discovered that the magnitude of the impact of the SE on ENV is larger in the short-run. This is further validated by the dynamic ARDL simulation technique which demonstrates that the immediate effect of the SE on ENV is large. Additionally, the results suggest that income growth, urbanisation, and industrial growth are important drivers of environmental pollution. Therefore, the study recommends the adoption, and most importantly, implementation, of policies and strategies geared towards reducing the shadow economy, and consequently environmental pollution.

Purpose: Despite the huge financial resources associated with oil, Nigeria has consistently recorded poor growth performance. Therefore, this study aims to examine how corruption and oil rent influence Nigeria’s economic performance during the 1996–2021 period.
Design/methodology/approach: Various estimation techniques were used. These include the bootstrap autoregressive distributed lag (ARDL) bounds-testing, dynamic ordinary least squares (DOLS), the fully modified OLS (FMOLS) and the canonical cointegration regression (CCR) estimators and the Toda–Yamamoto causality.
Findings: The bounds testing results provide evidence of a cointegrating relationship between the variables. In addition, the results of the ARDL, DOLS, CCR and FMOLS estimators demonstrate that oil rent and corruption have a significant positive impact on growth. Further, the results indicate that human capital and financial development enhance economic growth, whereas domestic investment and unemployment rates slow down long-term growth. Additionally, the causality test results illustrate the presence of a one-way causality from oil rent to economic growth and a bi-directional causal relationship between corruption and economic growth.
Originality/value: Existing studies focused on the effects of either oil rent or corruption on growth in Nigeria. Little attention has been paid to the exploration of how the rent from oil and the pervasiveness of corruption contribute to the performance of the Nigerian economy. Based on the outcome of this study, strategies and policies geared towards reducing oil dependence and the pervasiveness of corruption, enhancing human capital and financial development and reducing unemployment are recommended.

We employ dynamic heterogeneous panel estimation techniques which include Dynamic Fixed Effects (DFE), Mean Group (MG), and Pooled Mean Group (PMG) estimators to explore the underground economy (UE) and financial inclusion (FI) relation for ten West African nations during the 2004-2021 period. Applying Pedroni cointegration test, the results present evidence of a long-term relation between UE and FI (alongside corruption, inflation rate, money supply, agricultural output, and trade). The results of panel estimation portray a long-term significant positive influence of FI on UE, but a short-term significant negative relation between FI and UE. In addition, corruption, money supply, and international trade have a long-term significant negative influence on UE, while inflation supports long-term expansion of UE. Also, a short-term significant negative relation exists between inflation (and trade) and UE, while a short-term significant positive relation is found between money supply and UE. The results of Dumitrescu-Hurlin causality test signal a one-way causality from FI to UE. Therefore, policies geared towards enhancing FI, reducing corruption and money supply, and improving international trade are recommended to reduce UE.

Purpose: Despite the vulnerability of rapidly developing and emerging market economies, researchers have paid less attention to the determination of the size of money laundering (ML) in these economies, including the United Arab Emirates (the UAE). Therefore, this paper aims to estimate the magnitude of ML in the UAE between 1975 and 2020 based on the currency demand approach (CDA).
Design/methodology/approach: The study uses the Gregory–Hansen cointegration technique alongside the autoregressive distributed lag bounds testing procedure to estimate the CDA model.
Findings: The results illustrate that an amount equivalent to about 19.034% of the GDP is laundered in the UAE between 1975 and 2020, on average, with the value lying between 15.129% and 23.121%. In addition, the results demonstrate the importance of the real estate market, gold trade, remittance channels and the size of the underground economy in facilitating the laundering of illicit funds in the country.
Originality/value: To the best of the authors’ knowledge, the study is a pioneering attempt at estimating the amount of illicit funds laundered in the UAE. Besides, the adoption of a novel, yet robust, approach based on the modification of the CDA technique also sets the study apart as it ensures a correct, clear, unambiguous and indisputable estimate of the magnitude of ML is obtained. In addition, it is expected that the outcome of the study will expand the frontiers of knowledge among policymakers and relevant agencies and ensure the adoption of the most efficient and effective measures to curb the ML menace in the country.

This study employs the logistic regression method to examine the effect of financial inclusion on the level of poverty in Niger State of Nigeria based on cross-sectional data randomly collected from 624 respondents across 224 towns and villages in 12 local government areas (LGAs) of the state. The estimation results illustrate that financial inclusion (proxied by bank account ownership, including access to bank, credit, and mobile phone) is significantly and negatively related to the level of poverty. This empirical outcome is further validated by the results of the Probit regression technique which show a significant negative relationship between financial inclusion and poverty in the state. Based on these empirical findings, the study recommends policies which include broadening bank coverage, softening credit requirements, and enhancement of people’s access to mobile phone and internet services in rural areas of Niger state.