Forecasting Korea’s GDP growth rate based on the dynamic factor model

GDP represents the total market value of goods and services produced by all economic entities, including households, businesses, and governments in a country, during a specific time period.It is a representative economic indicator that helps identify the size of a country's economy and influences government policies, so various studies are being conducted on it.This paper presents a GDP growth rate forecasting model based on a dynamic factor model using key macroeconomic indicators of G20 countries.The extracted factors are combined with various regression analysis methodologies to compare results.Additionally, traditional time series forecasting methods such as the ARIMA model and forecasting using common components are also evaluated.Considering the significant volatility of indicators following the COVID-19 pandemic, the forecast period is divided into pre-COVID and post-COVID periods.The findings reveal that the dynamic factor model, incorporating ridge regression and lasso regression, demonstrates the best performance both before and after COVID.