Multiple Regression Model for Predicting GDP Using Macroeconomic Variables (Part 1)

Abstract

This research explores how one may predict the Gross Domestic Product (GDP) of a country using a technique known as multiple linear regression (MLR). Specifically, we explore whether other macroeconomic variables such as population, interest rates, unemployment rates, amongst others, can be used to predict the GDP of a country. We also examine the impact of new variables on the model base model fit using p-values and variance inflation factor (VIF) as a performance metric. The MLR model appears to be a suitable model for determining a linear relationship between dependent and independent features.

Keywords: GDP, Regression, Multicollinearity, P-Value

JEL Classification: C30, C52, C53,C82