Forecasting GDP of Nepal using Autoregressive Integrated Moving Average (ARIMA) Model - Upadhyay, Hari Prasad; Pradhan, Bijay Lal (International Journal of Silkroad Institute of Research and Training, 2023)
Background: Globally many research are working on modeling and forecasting of gross domestic product (GDP). The trend and pattern will help the planner and policy maker to make future monetary policy. The aim of this research is to find the ARIMA model and forecasting. Methods: Box-Jenkins methodology was use for the modeling and forecasting of annual GDP series of Nepal from 1990/91 to 2019/20. Eviews 10 software was use for data analysis. Results: Using the Box-Jenkins methodology this research examine the number of ARIMA family model that describe the annual GDP series and the appropriate model is ARIMA(1,1,1). Conclusions: This research concluded that ARIMA(1,1,1) is the model which capture the GDP series of Nepal for this period.