A Forecasting Model for the Number of Establishments Registered with the Social Security Fund

Abstract

The objective of this study is to construct an appropriate forecasting model for the number of establishments registered with the social security fund. We used four statistical methods: the Box-Jenkins method, Holt's exponential smoothing method, Brown’s exponential smoothing method, and the damped trend exponential smoothing method to construct the models. We used monthly data from the Social Security Office website from January 2012 to September 2022 (129 months) to analyze. The forecasting model’s accuracy was checked using the mean absolute percentage error (MAPE) and root mean square error (RMSE). The study found that the forecasting model from Brown's exponential smoothing method was the most accurate, with MAPE = 0.6639 and RMSE = 3,720. The forecasting model was

 where m = 1 represented January 2022.