Sagiru Mati

• Doctor of Philosophy
• Academic Staff at Northwest University Kano

This article investigates the performance of three models - Autoregressive Integrated Moving Average (ARIMA), Threshold Autoregressive Moving Average (TARMA) and Evidential Neural Network for Regression (ENNReg) - in forecasting the Brent crude oil price, a crucial economic variable with a significant impact on the global economy. With the increasi...

The exchange of indoor and outdoor air through ventilation systems can affect the heating load (HL). Proper ventilation strategies are essential for maintaining indoor air quality. Therefore, this study utilizes the implementation of feature selection approach and Machine learning (ML) techniques for understanding and simulating the behaviour of HL...

Precise rainfall forecasting is essential for efficient water resource management and disaster preparedness, especially in areas vulnerable to severe weather conditions. This study presents an integrated approach, combining machine learning techniques and statistical models, to predict rainfall patterns in Bangladesh's southwestern and northwestern...

Dynare is a popular software for solving dynamic stochastic general equilibrium (DSGE) and overlapping generations (OLG) models. It is used along with Octave or Matlab. However, writing documents using Dynare outputs can be error-prone and time-consuming, as it requires copying and pasting the outputs into the document. To address this problem and...

Sustainable management of available water resources needs robust and reliable intelligent tools to address emerging water challenges. These days, artificial intelligence (AI) based tools are more efficient and prominent in addressing issues related to water treatment plants. Therefore, in the current study, the extreme learning machine (ELM) was op...

Having accurate and effective wind energy forecasting that can be easily incorporated into smart networks is important. Appropriate planning and energy generation predictions are necessary for these infrastructures. The production of wind energy is linked to instability and unpredictability. Wind energy forecasting has traditionally been performed...

Groundwater salinization is a crucial socio-economic and environmental issue that is significant for a variety of reasons, including water quality and availability, agricultural productivity, health implications, socio-political stability and environmental sustainability. Salinization degrades the quality of water, rendering it unfit for human cons...

Abstract The prediction of CO2 emissions is critical for designing sustainable environmental policies and meeting the Sustainable Development Goals, particularly those related to climate action. Therefore, this paper aims to assess the appropriate predictive model for tracking carbon emissions in four African economies with the highest carbon emis...

The need for qualitative determination of mycotoxins in food samples is of paramount importance in designing procedures for their prevention, as well as understanding their adverse effects on humans and animals. In this article, a machine learning technique, specifically support vector regression (SVR) hyphenated with two metaheuristic algorithms -...

Particulate Matter 2.5 (PM 2.5) is a major air pollutant that can deeply penetrate the respiratory system and enter the bloodstream when inhaled. Therefore, it is significant to monitor and model PM 2.5, which is also considered as a key indicator of overall air quality. The current study employs the use of both Nature inspired Meta-heuristic optim...

In this study, linear and non-linear models are employed to model the Central Bank Rate (CBR), Deposit Interest Rate (DIR), Lending Rate (LER), and Treasury Bill Rate (TBR). The choice of variables is guided by the Fisher Equation (FE). The linear models range from Autoregressive Integrated Moving Average (ARIMA), Simple Linear Regression (SLR), Au...

The knitr package provides an avenue for incorporating programming languages and statistical applications into R Markdown and Quarto document for the sake of reproducibility. However, deep technical knowledge of R programming is required to achieve this task. In addition to this, the existing literature does not provide a guide on how to add econom...

Several governance regulations have been adopted in European countries to promote environmental sustainability, such as environmental taxation and environmental disclosures in financial reports. In this context, this paper examines the linkage between environmental taxation, International Financial Reporting Standards (IFRS), and environmental sust...

Ensembling VECM and ANFIS for Nigeria's interest rate prediction

Four easy steps to add new knit-engine to knitr R package

This article evaluates the asymmetric impact of exchange rate volatility on the exports of nine ECOWAS countries to the Eurozone. By comparing Autoregressive Distributed Lag (ARDL) and Nonlinear ARDL (NARDL) models, the study concludes that the effect of volatility on ECOWAS-Eurozone exports (EEE) is asymmetric. The study also investigates the impa...

Water scarcity is a pressing global challenge, and arid regions like Saudi Arabia face the urgent need for effective water stress management. The current study proposes an innovative method to tackle this issue by utilizing a hybrid time series analysis model, comprising of Autoregressive Integrated Moving Average (ARIMA) and Generalized Least Squa...

EViews is a software designed for conducting econometric data analysis. There exists a one-way communication between EViews and R, as the former can run the code of the latter, but the reverse is not the case. We describe EviewsR, an R package which allows users of R, R Markdown and Quarto to execute EViews code. In essence, EviewsR does not only p...

Conducts and reports EViews unit root tests in a table

Reliable modeling of novel commutative cases of COVID-19 (CCC) is essential for determining hospitalization needs and providing the benchmark for health-related policies. The current study proposes multi-regional modeling of CCC cases for the first scenario using autoregressive integrated moving average (ARIMA) based on automatic routines (AUTOARIM...

This paper employs Autoregressive Integrated Moving Average (ARIMA) modelling and doubling time to assess the effect of lockdown and reopening on the active COVID-19 cases (ACC) based on a sample from 29 February to 3 July 2020. Two models are estimated: one with a sample covering post-lockdown period only and another spanning both post-lockdown an...

Unlike previous studies, the current study uses oil price and inflationary shocks to assess the feasibility of actualizing the ECOWAS Vision 2020, which is aimed at creating a monetary union. With the help of the Blanchard and Quah (BQ) decomposition for a sample from 1975:05 to 2018:08, two sets of models are estimated: models for inflationary sho...

Explain DynareR package

Manual for R package gretlR

Manual for R package EviewsR

EviewsR is an R package that can run EViews program in R. It also adds eviews as a knit engine to knitr package, so that users can embed EViews codes in R Markdown and Quarto document.

p align="center"> ABSTRACT This study operationalizes the Optimum Currency Area (OCA) to investigate the preparedness of Economic Community of West African States (ECOWAS) members to form a Monetary Union (MU). Inflation and output models are estimated, with the sample 1988:01 to 2017:12 for the former and 1967 to 2016 for the latter. Analyses of...

This study examines the degree and extent of exchange rate pass through into domestic consumer price inflation in the Nigerian economy between 1986Q1 and 2013Q1 using structural vector auto regression (SVAR) methodology. The results from impulse response analysis show that the exchange rate pass through to consumer prices is incomplete, higher in t...

The paper examines the impact of both oil and non-oil foreign direct investment (FDI) on economic growth in Nigeria for the period 1980. The paper employed ARDL Approach to Cointegration and conditional EC Model in order to ascertain the long run and short-run relationships between the two categories of FDI (oil and non-oil), investment, export and...

In this study, the impact of exchange rate volatility on Nigerian exports to Eurozone countries is investigated. Monthly export data from January 1999 to December 2016 was used. This study utilizes the bounds test approach to cointegration to analyze how exchange rate volatility exerts influence on Nigeria’s export to the Euro Area. GARCH (1,1) is...