Economic Growth Analysis and Forecasting towards unemployment rate using Arima Model
Keywords:Economy, GDP, Forecasting, ARIMA model, Box and Jenkins
Gross Domestic Product (GDP) are used to assess the healthiness status of the economy and determine the economic performance of the country. If GDP growth of a country decreases continuously then the country will be facing recession. In this paper, the GDP growth of Malaysia is observed and forecasted using the ARIMA model for the next 5 years using IBM SPSS. The relationship between economic growth and unemployment rate are also determined. The results showed that past economic downtown was mainly about the unfortunate economics or financial policies such as Asian financial crisis, US economic downturn and in 2020 it was disrupted by the existence of a new species of virus that causes a pandemic of Covid-19. Then, it also showed that from the year 2023 to 2026 Malaysia GDP growth will be decreasing and the relationship between economic growth and unemployment rate follows Okun’s law. Therefore, the Malaysian government should take effective measures to overcome this situation. This research can be proceeded by forecasting the GDP growth of Malaysia using different models such as the Artificial Neural Network (ANN) model and comparing the results with ARIMA model.