PUBLISHED PAPERS #06.02
| Makrufa Hajirahimova, Aybeniz Aliyeva. ARIMA Model for Birth Rate Forecasting in Azerbaijan |
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| Abstract. The purpose of this study is to evaluate Autoregressive Integrated Moving Average (ARIMA) model ability to forecast the births rate in Azerbaijan. In the analysis, the Box-Jenkins methodology was followed when building the suggested model. Yearly data from 1990 to 2023 was collected from the website of the Statistics Committee of the Republic of Azerbaijan. Python programming languages and its Scikit Learn library were used for the analysis of the data. Besides, Akaike’s information criterion (AIC) and Bayesian Information Criteria (BIC) are used to select the best ARIMA model, compared to another estimated models. The prediction results of the models are evaluated using the mean absolute percentage error (MAPE) and the root mean square error (RMSE) . Comparing the predicted data from the ARIMA models shows that the correct selection of model parameters, it possible to fairly accurately predict the births rates. Obtained predictions reflect the dynamic of the births, and can be useful for the demographers and government officials. |
| Keywords: time series forecasting, Birth Rate, Box-Jenkins method, ARIMA model, MAPE, RMSE |
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| DOI: https://doi.org/10.30546/MaCoSEP2025.1116 |