Monday Osagie Adenomon

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• ND, HND, PGD, B.Sc, M.Sc, PhD, CStat in Statistics FASI FCE FRSS
• Associate Professor ; Chartered Statistician and Consulting Statistician at Nasarawa State University

A talk around scholarships, collaboration and volunteering, grants

Changes in foreign exchange rates and rising costs for products and services are the main causes of fluctuations in economic development. Despite numerous attempts by the government to reduce inflation in Nigeria, prices of goods and services continue to rise. Thus, this study analyzed the exchange rate-inflation relationship in Nigeria using autor...

Article Info Background: With the rapid digital transformation across the African continent, ensuring the protection of personal data through effective regulatory frameworks is crucial.

Quite often, authorities and policies maker are confronted with the challenges to serve society with the little resources at her disposal. More so, the need to distribute the limited resources correctly to the needed persons and location remain nonnegotiable in the present dispensation. Indeed, it became very expedient to sort for means of allocati...

To appropriately serve humanity better, the need to distribute the limited resources correctly to the needed persons and location remain nonnegotiable in our present dispensation. Indeed, it became very expedient to sort for means of allocating these minimum resources to the needy against all odds. The study seeks to identify communities with sever...

The World Health Organization (WHO) conceptualizes mental health as a state of well-being in which individuals realize their own abilities, cope with the normal stresses of life, work productively and fruitfully, and is able to make a contribution to his or her community. With an emphasis on clarifying the patterns, trends, and standardized common...

In this study, the panel autoregressive distributed lag (PARDL) approach was used to investigate the link between the sectoral credit of other depository corporations and economic growth in Nigeria. The sectoral GDP used in the study served as a proxy for the dependent variable measuring economic development, and the sectoral credits made by ODCs t...

This research aimed at creating a machine learning model for predicting birth weight using the maternal risk factors that have been found to be associated with low birth weight. The data covered a period of ten years from 2010 to 2019 was utilized where the variables were extracted from the births recorded file. The study population included mother...

The study investigated the depth of machine learning's capacity to perform prediction tasks. The study used textual data, specifically the daily actions of cryptocurrency (Bitcoin) dealers, which were found in news articles. The data was employed merely because it produced crowd knowledge of trade from News articles that affected the market price t...

This study was carried out on extended least absolute shrinkage with selection operator technique for sparse regression modeling with high dimensional date. The objective of this paper is to advance sparse regression modeling techniques for high-dimensional data through the enhancement of the LASSO algorithm and its application, by developing an ex...

Building the next generation statistician through mentoring

This study analyzes the volatility of Nigerian stock returns from January 2, 2010, to December 31, 2022, using ARMA-EGARCH models with Generalized Error Distribution (GED). Four model specifications are assessed: ARMA-EGARCH (1,1), ARMA-EGARCH (1,2), ARMA-EGARCH (2,1), and ARMA-EGARCH (2,2). The focus is on model selection, parameter estimation, an...

On the dynamics of temperature and rainfall using ARIMA (univariate) model and Vector Autoregressive (bivariate) model. Details are found in the poster

Gross Domestic Product (GDP) is a monetary metric that measures the market value of all final goods and services produced within a country or group of countries over a specific time period. GDP is commonly used by governments to assess a nation’s economic health. This study analyzed the impact of government expenditures (capital and recurrent) and...

The research study was carried out on meta-analysis on the effectiveness of personalized recommendation systems. Inclusion and exclusion criteria was used to extract the dataset through literature search and article selection. The meta-analysis was based on nine studies consisting of a total of 268,132 observations to conduct a meta-analysis of per...

In order to estimate the presence of collinearity, this study used the fixed effect model, pooled effect model, and random effect model in the presence of collinearity regressors. In respond one, data were simulated under several types of collinearity verifiable at varying sample sizes (-0.1,-0.5,-0.9, 0.1, 0.5, and 0.9) in the Monte Carlo simulati...

Replications are important for science, both statistically and otherwise. A plethora of epidemiology studies that have been done shows that there are always variations, errors and inconclusive findings in sickle cell disease. This paper intends to compute the underlying risk factor in sickle cell disease using meta-regression. These efficacy scores...

This study explores the day-to-day activities of cryptocurrency (Bitcoin) traders who might have gotten their crowd knowledge of trade from news articles, thereby shaping the trend of the market prices. The latent Dirichlet allocation (LDA) model and its variant, the supervised latent Dirichlet allocation model (sLDA), were used to analyze 4073 pre...

In a cashless economy, credit or debit cards can be used to complete transactions instead of carrying cash as the main form of paying for goods and services. The government's cashless policy discourages the usage of cash and promotes the development of electronic payment systems with an effort to reduce the amount of actual cash inflow in the econo...

This study explores the modelling performance of EGARCH-X using the skewed student's t, normal, and student's t innovations. The aim of the study was to determine the innovation that best captures the asymmetry and kurtosis exhibited by the returns on financial data. The descriptive statistics revealed that the distributions of returns on the stock...

A crucial component of financial time series is the modeling of volatility and co-volatility. The variances and covariances among financial data are modeled by multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) models. The generalized autoregressive conditional heteroscedasticity (GARCH) model has been used to describe...

The Gross Domestic Product (GDP) of a country is a key indicator of its economic performance and growth. In Africa, understanding the factors that influence GDP is crucial for policymakers to make informed decisions that promote economic development. This study aims to investigate the impact of these selected macroeconomic variables on GDP in Afric...

Meta-analysis is a systematic approach in selecting and integrating multiple finding across studies in order to give chances in control of potential bias. This paper aims to estimate the summary effect on the risk of mortality in sickle cell patient. The effect size index was risk ratio and date was sourced via Pubmed, Science Direct, Web of Scienc...

The economies of Sub-Saharan Africa are experiencing significant growth due to increasing populations, rising incomes, and urbanization. However, these factors also bring challenges to trade stability. This study analyses the impact and causality of agricultural raw materials, information and communications technology, and service exports on econom...

In the existence of outliers, the ongoing impact of biased estimates of ARIMA-GARCH-type model parameters on prediction accuracy was investigated using the daily returns of the share price series of Zenith Bank, one of Nigeria's major banks. The data, consisting of 4398 observations, were collected online from the Nigerian Stock Exchange's daily cl...

The relationship between Energy consumption, Trade openness and Economic growth in Sub-Saharan African Countries remains a critical area of research. Thus, this study aimed at modelling energy consumption, trade openness and economic growth in some selected Sub-Saharan African Countries using Panel Regression and Panel autoregressive distributive l...

The study of statistical distributions has led to the development of numerous extensions of well-known continuous distributions to enhance their flexibility and applicability across various fields. In this paper, we introduce a new three-parameter distribution known as the Odd Exponential-Weibull (OE-W) distribution, which extends the traditional W...

This study aimed at unveiling the connections amidst cryptocurrency activities by users and how traders read these activities online to aid their trading capabilities. Therefore, it examined the daily actions of Bitcoin traders who may have learned about the market from news items. The study employed the latent Dirichlet Allocation (LDA) model and...

In the pursuit to understand the importance of exchange rates to any economy, it becomes very expedient to build reliable models for the prediction of the volatility of exchange rates of home currency vis-à-vis the currencies of the developed nations, especially the nations with whom the home country have bilateral economic relationship; such as th...

Survival data are very common in clinical, chemical, and agronomic assays, among others. However, in practice, experiments are conducted so that all sample units are evaluated at the same time. These data are referred to as grouped survival data, which are a particular case of interval censoring and are characterized by an excessive number of ties....

Energy is necessary for a holistic economic system that includes the production, distribution, and consumption of products and services. This suggests that energy access and consumption are either directly or indirectly related to the growth of the majority of developing and growing economies. As a result, energy is essential to the production of g...

Background: Issue of climate change is a global concern to government, individual and industry. In Africa and in Nigeria specifically, climate change can be seen from increase in temperature and rainfall variability. It can also be reflected in floods, drought, rising sea levels, loss of biodiversity etc.

The accuracy of a predictive model is crucial in various fields, including classification tasks. One commonly used method for classification is logistic regression, which relies on maximum- likelihood estimation. However, there is growing interest in exploring the use of Bayesian logistic regression as an alternative approach. This interest stems f...

This study used a panel ARDL model to analyze the impact of macroeconomic variables on GDP of SSA countries over 33 years (1990 to 2021). It aimed to fit a panel ARDL model for these variables, estimate their long-run impact on GDP, and identify short-run effects. The analysis employed econometric techniques such as panel unit root tests, cointegra...

This study examines the impact of inflation, interest rates, and exchange rates on the Nigerian economy using time series data from the CBN spanning from 1986 to 2022. With two main objectives, it investigates their effects and estimates the short-term impact on GDP. Utilizing methods like Augmented Dickey-Fuller unit root test, Autoregressive Dist...

Population expansion, rising incomes, and increasing urbanization characterize Sub-Saharan Africa's economies, indicating potential market development but also posing trade stability problems. Poor economic performance and dependency on oil exports in the region have necessitated additional research and talks. This study will look into the impact o...

This study investigated the long-run and short-run relationships between solid waste generation in Nigeria and two key climate variables: rainfall and temperature. Employing a Vector Error Correction Model (VECM) analysis on data from 1982 to 2022, then revealed counterintuitive findings. In the long run, lagged rainfall exhibits a negative associa...

In this research, Understanding the assumptions of time series models is crucial. In this study, we aim to analyse and modify Autoregressive models on selected linear and nonlinear time series models to determine their stationarity and non-stationarity at different orders, it would be useful to conduct tests on the null hypothesis of a unit root. T...

This study investigates the long-run and short-run impacts of economic growth on solid waste generation in Nigeria using a Vector Error Correction Model (VECM). Analyzing data from 1982 to 2022, the study reveals cointegration among solid waste, GDP, and real income, indicating a long-run equilibrium relationship. Key findings show that economic gr...

Machine Learning to Finance and economics in Nigeria is becoming popular because of its potential over the classical time series models. High inflation rate is a big economic problem plaguing the economic and standard of living of citizens of developing countries especially Nigeria. This work focused on investigating drivers of inflation rate in Ni...

Meta-analysis is a systematic approach in selecting and integrating multiple finding across studies in order to give chances in control of potential bias. This paper aims to estimate the summary effect on the risk of mortality in sickle cell patient. The effect size index was risk ratio and date was sourced via Pubmed, Science Direct, Web of Scienc...

This study sets out to evaluate and compare the performance of Autoregressive (AR) models against modified versions of several smooth transition autoregressive models models. Specifically, we examine how these models perform across varying sample sizes and different orders. A comprehensive numerical simulation was conducted to assess the relative e...

In time series literature, exogenous variables tend to improve the forecast of the endogenous variables. This paper examined the forecast performance of six (6) versions of Bayesian Vector Autoregressive models with exogenous variables (BVARX) using normal-inverse Wishart Prior when collinearity exist between the exogenous variables for small sampl...

Tuberculosis (TB), remains the leading cause of death among people with HIV and one of the top 10 leading causes of death from a single infection worldwide (WHO, 2020). In 2018, Nigeria was listed as the first in Africa and sixth among the 30 countries of the world with highest burden of TB. Over time study has shown that the emergency and spread o...

The concept of the nonlinear ARDL (NARDL) technique is a model that allows modelling both short run and long run estimates and detecting associated asymmetric effects, and also discovering hidden cointegration. This paper examined the influence of foreign direct investment (FDI) and trade openness on Nigerian GDP using time series data spanning thr...

It is no tittle-tattle that the incidence of the COVID-19 pandemic has impacted the world in many areas. Nigeria got her own share of this virus in February 2020, which led to the closure of schools, worship centres, businesses, and other social arenas by the Federal Government. Based on experience and occurrences, we investigated the economic impa...

Time series data are been generated on the African continent (such as Nigeria etc.) on a daily basis. Such series could be rainfall, temperature, stock prices etc. One of the major purposes of time series and machine learning techniques are for prediction using past behaviours of a time series to predict present and future values of that series. A...

obtained from a secondary source. Most of the models were promising in terms of information criteria and ARCH test after estimation but failed the backtesting analysis. With the backtesting approach, eGARCH (1,1) model with student t distribution emerged as the superior GARCH model among the competing GARCH models for modeling First Bank returns in...

This study compared the extrapolation strengths of two models: Autoregressive Integrated Moving Average (ARIMA) and Autoregressive Integrated Moving Average with an Exogenous Variable (ARIMAX) in the forecast of Nigeria's electricity consumption. Annual data on power generation and consumption from the Central Bank of Nigeria statistical bulletin f...

In this work, panel data that were characterized by features of no first order autocorrelation was modelled using three estimation models: Pool Regression, Fixed Effect, Random Effect models. Panel data like other aspects of econometrics, exploits regression analysis as one of the statistical tools to formulate and illustrate models. The regression...

Improving forecasting of GARCH Models using Backtesting approach

Unit root test is an important means to determine the integration order of a variable which has involved different methods of testing for stationarity. Simulation method is adopted in this study to verify whether unit root, structural breaks and regime shifts exist in the sample considered. For sample sizes of 20 and 50 as small, 100 and 250 as med...

Financial Inclusion involves steps taken by financial institution(s) to make every day financial services available to more of the world’s population at a reasonable cost. This study sets out to investigate the impact of financial Inclusion on economic growth in Nigeria. Annual data covering the period of 2005 to 2020 was sourced from CBN statistic...

In recent times, spatial econometrics application is given reasonable attention as it deals with data of spatial type either in cross-sectional or panel form. This study examined application of Phillips Curve on the Nigerian Economy using 2018 cross-sectional data of consumer price index (CPI) as inflation rate and unemployment rate data sourced fr...

This research work employed Autoregressive distributed lag (ARDL) and Bound Test for co-integration with Vector Error Correction (VEC) Models for estimation of long run and short run effect on Gross Domestic Product (GDP) in Nigeria. In order to achieve this, annual data on GDP, Unemployment, Exchange, and Interest rate from 1980-2017 The Augmented...

This is a mentorship talk to motivate undergraduate students, postgraduate students and early researcher to do rigorous research, publish in high impact journals and build a robust research profile.

This study predict the stock prices of Wheaton Precious metal using machine learning techniques (Linear regression, Support Vector Regression, Random Forest Regression, Decision Tree Regression and Neural Network regression) and Time series method called ARIMAX (Autoregressive Integrated Moving Average with exogenous variable). To achieve this, dai...

This study implemented Panel Vector Autoregression (PVAR) Model to examine short-run dynamic relationships between inflation rate, population and unemployment rate as function of Gross Domestic Product (GDP) for Economic Community of West Africa States (ECOWAS) counties. To achieve this, secondary data was sourced for Population, Inflation rate, Un...

In the bid to produce graduate in statistical sciences that can navigate from theory to practice, better methods of teaching statistics are sought for in developing countries such as Nigeria. BHM (2018) noted that poverty, waning interest from students, inadequate learning aids and incessant strikes as problem hindering Mathematics and Statistics e...

Unit root test is an important means to determine the integration order of a variable which has involved different methods of testing for stationarity. Simulation method is adopted in this study to verify whether unit root and structural breaks exist in the sample considered. For sample sizes of 20 and 50 as small, 100 and 250 as medium, and 2500 a...

This study investigates the impact of the global financial crisis and of the present COVID-19 pandemic on daily and weekly Crude oil futures using four variants of ARMA-GARCH models: ARMA-sGARCH, ARMA-eGARCH, ARMA-TGARCH and ARMA- aPARCH with dummy variables We also investigated the persistence, half-life and backtesting of the models. This study t...

This study provides evidence of the impact of COVID-19 on five (5) Nigerian Stock Exchange (NSE) sectorial stocks (NSE Insurance, NSE Banking, NSE Oil and Gas, NSE Food and Beverages, and NSE Consumer Goods). To achieve the goal of this paper, daily stock prices were obtained from a secondary source ranging from 2 January 2020 to 25 March 2021. Bec...

This book chapter compares the out-of-sample forecast for inflation rates in Nige-ria using ARIMAX and ARIMA models. To achieve this, Annual Data on Exchange Rate, Inflation Rate, Interest Rate and Unemployment Rate from 1981 to 2017 was sourced from Central Bank of Nigeria (CBN). The analysis used data from 1981 to 2010 while 2011 to 2017 was used...

The paper talks about how the activities of IASC African members group and the LISA 2020 network are helping to build new developments in Data Science and Data Science in Africa

The field of Data science and machine learning is young in Nigeria as most universities, colleges and polytechnics do not offer Data science at undergraduate level. This means potentials data scientist comes from statistics, mathematics and computer science fields. One of the major challenges will have seen from experience of teaching machine learn...

Economic theory revealed evidence of interrelationships among inflation, interest and exchange rates. Such theory further states possible effects of money supply and GDP on inflation, interest and exchange rates. This study focuses on the dynamic interrelationships among inflation, interest and exchange rates with the effects of money supply and GD...

Some macroeconomic variables have been studied based on their impacts and contribution to the economic growth especially in Nigeria. The study focuses on the impacts of inflation, import and export on the gross domestic product using Markov switching vector autoregressive(MS-VAR) model which is designed for econometric modeling of univariate and mu...

Bayesian VARs are mostly used in computational analysis of macroeconomic variables of a nation. The natural conjugate prior when combined with the likelihood function gives a posterior distribution that belong to the same distributional family. The study investigates the forecasting of some selected macroeconomic variables with BVAR Model using spe...

Application of Markov-switch models to Nigeria's economy especially the macroeconomic variables in order to determine how it relates to policy making cannot be under-emphasized. This study investigates the relationship between gross domestic products and inflation in Nigeria using a time series data from 1960-2019 with the aid of Markov switching r...

The role of the statistical consultant cannot be overemphasized in evidence-based research and policymaking in the real world. A statistical consultant liaises and collaborates with clients;, delivers statistical analysis and research; and provides statistical training, advice and possible supports to statisticians and non-statisticians. From previ...

This chapter discusses statistical education in Nigeria and proffers better ways to teach statistics in Nigeria through a program of Teaching and Learning Statistics with the Aid of Computing and Survey Datasets from International Organization to help graduate students in statistics relate theoretical statistics learned in the classroom to real-wor...

The recent COVID-19 was first identified in Wuhan, China in December 2019 and now it has caused huge death and spread to almost all over the world. There are news that most of the world economy and financial markets would be affected due to protocols such as lockdown and social distancing. In Nigeria, the first case of COVID-19 was identified on 27...

In this study, Generalized Additive Models for location, scale and shape was deployed to model a typical automobile insurance portfolio. The data set used for this study comprises of seven variables, which are: Kilometres, Zone, Bonus, Make, Insured, Claims and Payments, it was compiled by a Swedish Committee on the Analysis of Risk Premium in Moto...

This study investigates simulation study of the comparison between Error Correction Model (ECM) and Autoregressive Distributed Lag (ARDL) Model on non-normally distributed data. The study utilized both simulated data with 5000 iterations and the real life data of inflation rate and unemployment rate in Nigeria from a period of 1981 to 2016. The Aug...

Bayesian Vector Autoregressive (BVAR) models are mostly used in computational analysis of macroeconomic variables of a nation. Certain issues had led to imprecise estimation by BVAR Model. Recently, it has been discovered that BVAR exhibit some statistical imprecision and inaccuracy in evaluating and forecasting macroeconomic variables. Because of...

This study used QGARCH model to analyze insurance stock in Nigeria. The data used in the study are daily insurance stocks obtained from Nigeria Stock Exchange for a period of 1961-2019. The analysis done in this study were conducted in R-environment using Rugarch package by Ghalanos and E-view. Four competing QGARCH models such as QGARCH (1,1), QGA...

Teaching statistics in North Central Nigeria using TEAM-R Framework. Drawing great lessons from NSUK-LISA stat lab

Modeling road crashes in Nigeria using fractional data and fractional regression models in Nigeria

Unemployment rate in Nigeria is worrisome to both governments and the Populace. This study model and forecast unemployment rate in Nigeria using ARIMA Models. Results show positive growth from 2019 to 2030. To change this narrative, Potentials of Ambitious Africa Nigeria and Ambitious Africa Global can me explore to reduce the menace of unemploymen...

The high unemployment rate among Nigerian graduates is becoming worrisome.

Spatial econometrics should be viewed in a wide sense involving developments of models and statistical tools for the analysis of externalities, spillovers, interactions etc., in various areas including economics, geography and regional science, etc. This study examined application of Okun's law on the Nigerian Economy using 2018 cross-sectional dat...

Economic theory revealed evidence of interrelationships among inflation, interest and exchange rates. Such theory further states possible effects of money supply and GDP on inflation, interest and exchange rates. This study focuses on the dynamic interrelationships among inflation, interest and exchange rates with the effects of money supply and GD...

Time series data often entail counts. Time series count data, which refer to the number of times an item or an event occurs within a fixed period of time, are essential in many fields most of the works on time series count data do not exhaustively consider the effect excess zeros in modeling. This study, therefore, seeks to examine the performance...

In a classical multiple linear regression analysis, multicollinearity and autocorrelation are two main basic assumption violation problems. When multicollinearity exists, biased estimation techniques such as Maximum Likelihood, Restricted Maximum Likelihood and most recent the K-L estimator by Kibria and Lukman [1] are preferable to Ordinary Least...

This paper proposes a new estimator called Two stage K-L estimator by combining these two estimators previously proposed by Prais Winsten (1958) and Kibra with Lukman (2020) for autocorrelation and multicollinearity respectively and to derived the necessary and sufficient condition for its superiority over other competing estimators. Simulation stu...

Application of SARIMA model in modelling and forecasting monthly rainfall in Nigeria was considered in this study. The study utilizes the Nigerian monthly rainfall data between 1980-2015 obtained from World Bank Climate Portal. The Box-Jenkin’s methodology was adopted. SARIMA (2,0,1) (2,1,1) [12] was the best model among others that fit the Nigeria...

There is an acknowledgement that inflation-growth nexus depends on the level of inflation apparently. This is because, at some low levels inflation may be positively correlated with output growth, but at higher levels inflation is likely to be hostile to growth. This occurs at operational level of an economy. The debate on inflation-growth nexus ha...

Spatial econometrics should be viewed in a wide sense involving developments of models and statistical tools for the analysis of externalities, spillovers, interactions etc., in various areas including economics, geography and regional science, etc. This study examined application of Okun’s law on the Nigerian Economy using 2018 cross-sectional dat...

Viral hepatitis infections, Tuberculosis (TB), and Hepatitis, Human Immunodeficiency Virus (HIV), Acquired Immune Deficiency Syndrome (AIDs) are still major causes of illness and death in developing countries like Nigeria. To understand the dynamics of HIV/AIDs, TB and hepatitis in Nigeria, Logarithm Vector Autoregressive (VAR) model was employed i...

In econometrics literature, the Autoregressive Distributed Lag (ARDL) and Fully Modified Ordinary Least Squares (FMOLS) models are often applied in many economic analyses because of their rich methods and robustness when macroeconomic variables are cointegrated. This study applied the ARDL and FMOLS models to examine the long run effects of some ma...

Data ethics can be defined as an aspect of ethics that studies and evaluates moral problems related to data generation, recording and sharing. But authenticity, reliability and genuineness of data collection in survey by some students and so called researchers are become questionable because malpractices in data collection (such as doctored data, c...

In recent times, spatial econometrics application is given reasonable attention as it deals with data of spatial type either in cross-sectional or panel form. This study examined application of Phillip's Curve on the Nigerian Economy using 2018 cross-sectional data of consumer price index (CPI) as inflation rate and unemployment rate data sourced f...

Statistical computing sometimes refers to as computational statistics which is the interface between statistics and computer science. Without doubt the advent of statistical computing had help in teaching and learning statistics in Africa and in Nigeria, although the use of statistical computing in teaching, learning and doing project is still low...

Abstract This study investigates the volatility in daily stock returns for Total Nigeria Plc using nine variants of GARCH models: sGARCH, girGARCH, eGARCH, iGARCH, aGARCH, TGARCH, NGARCH, NAGARCH, and AVGARCH along with value at risk estimation and backtesting. We use daily data for Total Nigeria Plc returns for the period January 2, 2001 to May 8,...

Research background: The relationship between inflation rate, unemployment rate, interest rate and real gross domestic product per capita in Nigeria. However, there seems to be a short-run or long-run relationship among the macroeconomic variables. Purpose: This study investigated the long and short run impacts of the inflation rate, unemployment r...

This book chapter investigated the place of backtesting approach in financial time series analysis in choosing a reliable Generalized Auto-Regressive Conditional Heteroscedastic (GARCH) Model to analyze stock returns in Nigeria. To achieve this, The chapter used a secondary data that was collected from www.cashcraft.com under stock trend and analys...