Modeling rates of inflation in Nigeria: an application of ARMA, ARIMA and GARCH models

Based on time series data on inflation rates in Nigeria from 1960 to 2016, we model and forecast inflation using ARMA, ARIMA and GARCH models. Our diagnostic tests such as the ADF tests indicate that NINF time series data is essentially I (1), although it is generally I (0) at 10% level of significance. Based on the minimum Theil’s U forecast evaluation statistic, the study presents the ARMA (1, 0, 2) model, the ARIMA (1, 1, 1) model and the AR (3) – GARCH (1, 1) model; of which the ARMA (1, 0, 2) model is clearly the best optimal model. Our diagnostic tests also indicate that the presented models are stable and hence reliable. The results of the study reveal that inflation in Nigeria is likely to rise to about 17% per annum by end of 2021 and is likely to exceed that level by 2027. In order to address the problem of inflation in Nigeria, three main policy prescriptions have been suggested and are envisioned to assist policy makers in stabilizing the Nigerian economy

Modeling rates of inflation in Nigeria: an application of ARMA, ARIMA and GARCH models

Based on time series data on inflation rates in Nigeria from 1960 to 2016, we model and forecast inflation using ARMA, ARIMA and GARCH models. Our diagnostic tests such as the ADF tests indicate that NINF time series data is essentially I (1), although it is generally I (0) at 10% level of significance. Based on the minimum Theil’s U forecast evaluation statistic, the study presents the ARMA (1, 0, 2) model, the ARIMA (1, 1, 1) model and the AR (3) – GARCH (1, 1) model; of which the ARMA (1, 0, 2) model is clearly the best optimal model. Our diagnostic tests also indicate that the presented models are stable and hence reliable. The results of the study reveal that inflation in Nigeria is likely to rise to about 17% per annum by end of 2021 and is likely to exceed that level by 2027. In order to address the problem of inflation in Nigeria, three main policy prescriptions have been suggested and are envisioned to assist policy makers in stabilizing the Nigerian economy

Trivariate modelling of the nexus between electricity consumption, urbanization and economic growth in Nigeria : fresh insights from Maki Cointegration and causality tests

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Infrastructure development, human development index, and CO2 emissions in China: A quantile regression approach

This study investigates the relationships between infrastructure development, human development index (HDI), and CO2 emissions in China. Infrastructure has played an essential role in achieving social and economic developmental goals in China, but environmental pollution has significantly increased in the country in the last two decades. Our analysis uses time series data from 1990 to 2021 and quantile regressions, and we find that infrastructure has positive and statistically significant relationships with HDI, CO2 emissions, and GDP in all quantiles. Recent infrastructure upgrades improve living standards and increase HDI but damage the environment, and infrastructure is the main source of CO2 emissions in the country. Therefore, the government should invest in sustainable infrastructure to mitigate CO2 emissions. The government may consider infrastructure options such as low carbon transportation, including railway infrastructure, urban metros, and light rail

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Natural resources, urbanisation, economic growth and the ecological footprint in South Africa: The moderating role of human capital

South Africa is the largest emitter of CO2 and arguably the most developed and urbanised country in Africa. The country currently harbours an ecological deficit territory which could be the outcome of economic expansion, urban explosion, unsustainable resource exploration and a low level of human development. After all, environmental distortions are mainly the outcome of human activities. This study is a maiden attempt to examine the linkage between urbanisation, human capital, natural resources (NR) and the ecological footprint (EF) in South Africa. Unlike previous studies, this study employs positivist and relevant environmental indicators that accommodate built-up land, forest land, carbon footprint, ocean, grazing land and cropland. Findings from the long-run results suggest that urbanisation, economic growth and NR increase the EF, whereas human capital ensures environmental sustainability. The interaction between urbanisation and human capital mitigates environmental degradation by reducing the EF. The canonical cointegrating regression (CCR), dynamic ordinary least squares (DOLS) and the fully modified ordinary least squares (FMOLS) results further confirm the nature of the relationships and linkages existing with respect to NR, urbanisation, economic growth and the EF. A bidirectional causality exists between human capital, economic growth and the EF. Policies related to NR and urban sustainability, the limitations of the study, as well as possible directions for future research are discussed

Revisiting population growth and food production nexus in Nigeria: an ARDL approach to cointegration

Purpose. This study focused on the relationship between the increasing population and level of food growth in Nigeria. Methodology / approach. Agriculture’s contribution to GDP was used to proxy food production alongside population growth rate. The ARDL Model was used to estimate both long and short run population-food growth relations over a 35-year period of 1982–2016. The Augmented Dickey-Fuller, Philip Peron and Kwiatkowski-Philips-Schmidt-Shin stationarity tests were carried out to ensure the stationarity of the variables. Results. The results showed that the variables are integrated of mixed order. The Bounds test established cointegration between population growth and food production in Nigeria which validated the Malthusian theory. However, the estimates revealed that population growth had a positive and significant relationship with food growth in both the long and short run. This implies that increase in population is yet to take a negative effect on availability of food against Malthus postulation. Originality / scientific novelty. This study is the only study on the validation of Malthusian theory of population which employed a rigorous means to establish the order of integration of the variables required for the validation test. It also looked at the place of agriculture in the midst of growing population. Practical value / implications. This outcome is a call to intimate the populace on the dangers of population explosion on one hand and on another hand, the government to ensure provision of adaptable and adoptable technology in the agricultural sector to ensure that food production increases as Nigeria is blessed with the land and weather to make this happen

Environmental Pollution and Energy Research and Development: An Environmental Kuznets Curve Model through Quantile Simulation Approach

Energy research and development (R&amp;D) and environmental sustainability is often referred to as two interrelated trends, especially in the current context of the 4th&nbsp;industrial revolution. As a primary input of energy innovations, R&amp;D in the energy sector constitutes a vital tool in addressing global environmental and energy challenges. In this frame, we observe the effects of disaggregated energy R&amp;D on environmental pollution within the Environmental Kuznets Curve (EKC) framework in thirteen developed countries over the period 2003–2018. By employing the panel quantile regression technique, we find an inverted U-shaped nexus between economic growth and carbon emissions only in higher carbon-emitting countries, thus, confirming the EKC hypothesis. However, the U-shaped nexus is more predominant in lower carbon-emitting countries. As such, we demonstrate that there is not any single dynamic in the relationship between economic growth and pollution as reported in previous studies. Contrary to expectations, we find that energy efficiency research and development is more effective in curbing carbon emissions compared to fossil fuels and renewable energy research and development. The empirical results indicate also that only energy efficiency R&amp;D mitigates significantly the CO2&nbsp;emissions from the 50th&nbsp;quantile up to 90th&nbsp;quantile, although the magnitude of the negative sign is more pronounced (in absolute term) at the highest quantile (90th). In this light, our findings would guide policymakers in the establishment of sustainable energy research and development schemes that will allow the preservation of equilibrium for the environment while also promoting energy innovations.</p

Energy consumption and economic growth linkage: Global evidence from symmetric and asymmetric simulations

The literature reveals that linear models do not accurately represent the asymmetric relationship between economic growth and energy consumption (EC). To fill this gap, we examined the asymmetric relationship between EC and economic growth in a non-linear panel autoregressive distributed lag (ARDL) framework of 85 countries as a whole sample and of Brazil, Russia, India, China, and South Africa (BRICS), the Next Eleven, Big Four in Western Europe, Asia-Pacific region, Group of Seven, South Asian Association for Regional Cooperation (SAARC), Economic Cooperation Organization (ECO) and the Arab League as a sub-sample analysis from 1977 to 2014. A second generational unit root test has been applied to check the problem of cross-sectional dependency. Asymmetric contegration was employed to analyse the co-integration between the variables of interest. Long-run and short-run estimates have been calculated using the non-linear panel ARDL method. Results indicate that positive shocks to energy use tend to have a growth-enhancing effect in ECO and the Next Eleven while in the rest of the regions, the effect is growth con- traction. Moreover, economic recovery from a positive shock to energy use is the case in the Arab League, Asia-Pacific region, Group of Seven and in the whole sample. However, a negative shock to EC is observed in the Group of Seven, Asia Pacific region, Big Four in Western Europe and ECO, and the whole sample worsens the economic contraction. We can deduct from this study’s results that information on the asymmetric relationship between the subject variables is needed to design sound economic policy decisions across different economic regions