TITLE:
A Multiple Linear Regression Model for Inflation Rate in the UK
AUTHORS:
Shihan Miah, Daniel Ata-Baah
KEYWORDS:
Inflation, Simple Linear Regression, Multiple Linear Regression, Statistical Significance, Variance Inflation Factor
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.15 No.9,
September
24,
2025
ABSTRACT: In this study, the key factors influencing the yearly inflation rate in the United Kingdom (UK) have been investigated using data spanning from 1974 to 2023. A range of economic factors, including interest rates (IR), unemployment rates (UR), exchange rates (EXR), gross domestic product (GDP), consumer price index (CPI), retail price index (RPI), value-added taxes (VAT), producer price index (PPI), and GDP growth (GDPG) has been chosen as predictor variables to analyze the model under consideration. Using these factors, a multiple linear regression without interaction and another model with interaction have been constructed and investigated using least squares methods to estimate the coefficients and identify the most significant determinants of inflation. The interaction model yields better performance, with a high coefficient of determination (
R
2
=0.979
), indicating that the most impactful variables are interactions between the Producer Price Index (PPI) and GDP, the Retail Price Index (RPI) and GDP, the RPI and inflation rate (IR), the PPI and IR, as well as GDP itself. These outcomes offer valuable insights into the complex dynamics driving the inflation rate in the UK.