Box Jenkins ARMA Model for Forecasting Bangladesh's Remittance Inflow

Sabiha Binta Hasan, Roksana Akhter, Dipti Bhowmik, Shakil Mahmood Shaon and Md. Ariful Islam

International Journal of Social Science Studies, 2024, vol. 12, issue 5, 1-11

Abstract: This study uses Eviews software in order to determine the best Box-Jenkins ARMA model for forecasting the growth rate of remittances in Bangladesh by utilizing time series data from the year 1980 to 2022. In our study, we used the Augmented Dickey-Fuller Test (ADF Test) to check the stationarity of the time series data. This test shows that data is stationary at level 0, i.e., Remittance (0). By performing several selection criteria for the lowest SIGMASQ and the lowest value of AIC and BIC, we obtain ARMA (1, 1), which is the best model for forecasting remittances in Bangladesh. Diagnostic tests additionally demonstrate the stability and acceptability of the parsimonious model that has been given for remittance prediction in Bangladesh. The study's findings reportedly demonstrate that Bangladesh's remittance inflows are declining. The article makes the case that, in order to increase remittance inflows into Bangladesh, the country's emigration policy needs to be strengthened.

Date: 2024
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