Forecasting the Population of Türkiye Using Grey Models

Year 2024, , 227 - 248, 31.12.2024

Muhammet Mesut Ertilav , Muhammet Burak Kılıç

https://doi.org/10.17093/alphanumeric.1507101

Abstract

Population forecasting plays a significant role in determining demography, economics, and agriculture policies for developing countries. In this study, we employ the five different grey prediction models to estimate the population of Türkiye until 2050 using the 2007 to 2022 address-based data. These models are given as the grey standard (GM (1,1)), grey time-varying dynamic (GM (1,1) t), grey Gompertz (GGM), grey Verhulst (GVM), and grey exponential (EXGM (1,1). The comparison of grey models is evaluated by mean absolute percentage error (MAPE), regression coefficient (R2), variance ratio (C), and probability of error (P). The GGM and GM (1,1) t are identified as the most suitable models for predicting the period 2007-2022. For the future population forecasts from 2023 to 2050, the five models are compared with the projection values of the Turkish Statistical Institute published in 2018. The GGM is determined to be the most compatible based on the MAPE value of 0.68116 and the C value of 0.05218, and the Grey Verhulst model is provided the most compatible R2 value of 0.99818. According to the GGM, the population of Türkiye is projected to reach 105,948,975 by 2050, 106,877,632 based on the GM (1,1) t, and 102,591,471 based on the GVM.

Keywords

Population Forecasting, Grey System, Grey Prediction, GM (1,1), Time Series

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