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All Journal ESTIMASI: Journal of Statistics and Its Application
Taiwo, Abass Ishola
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Mathematics

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Modeling the Effects of Climate Change and Socio-Ecomonic Variables on Agricultural Production Taiwo, Abass Ishola; Ayo, Femi Emmanual; Ogundele, Lukman Adebayo
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 1, Januari, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i1.26843

Abstract

Climate change has serious effects on human life and existence in various forms. This study used Principal Component Analysis (PCA) and Mutiple Regression model (MRM) to determine the effects of meteorological factors and socio-economic factors on agricultural production. PCA showed 95.6% aggregated variation within the variables and the correlation matrix of the principal components was used to reduce the variables to six. MRM was employed for determining linear association within agricultural productions and the reduced factors showed that climate change and socio-economic factors influenced Nigerian agriculture production. The model obtained was validated with respect to coefficient of determination, adjusted coefficient of determination and Durbin Watson statistics values. Overall, this study indicated that climate change and socio-economic factors influenced the level of agriculture productions in Nigeria.
Nigerian Population Growth Modelling and Forecasting using Univariate Time series model Taiwo, Abass Ishola; Titilola, A A; Olatayo, Timothy Olabisi; Lasisi, Taiwo Abideen
ESTIMASI: Journal of Statistics and Its Application Vol. 6, No. 1, Januari, 2025 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v6i1.34349

Abstract

The Nigerian population is growing rapidly, and this poses significant challenge to human existence. To have an insight, Autoregressive Integrated Moving Average (ARIMA) model was used to model and predict population growth. The results showed a yearly population mean of 99,611,692 with a standard deviation of 53,188,740. After estimation, the ARIMA(3,2,1) model was chosen for having lowest Akaike and Schwarz information criterion with the adequacy of the model attained using the Ljung-Box Statistic Autocorrelation and partial autocorrelation functions of the residuals. Coefficient and adjusted coefficient of determinations showed the model has a strong predictive accuracy, with the forecast indicating a continuous population growth increase of over 5 million annually. Conclusively, Nigerian government must plan how to curtail this explosive growth expected at over 418 million by 2050.
Co-Authors Ayo, Femi Emmanual Lasisi, Taiwo Abideen Ogundele, Lukman Adebayo Olatayo, Timothy Olabisi Titilola, A A