Forecasting Cost-Push Inflation with LASSO over Ridge Regression

Sree Nair, N. Deepa

2023

Abstract

This study undertook an experimental analysis to forecast Cost-push Inflation using the Novel LASSO regression algorithm, contrasting it with the Ridge algorithm. Moreover, future Consumer Price Index (CPI) values were determined. To achieve maximum accuracy in predicting Cost-Push Inflation, the performance of the Novel LASSO algorithm (N=21) was evaluated against the Support vector regression algorithm (N=21). Sample sizes were determined utilising G-power, considering a pretest power of 0.80 and an alpha of 0.05. Notably, the mean accuracy value for the Novel LASSO algorithm stood at 81.95%, surpassing the Support vector regression algorithm’s 75.57%. Statistical analysis highlighted a significant difference between the two methods (p=0.001, p<0.05), emphasising the superior accuracy of the Novel LASSO approach.

Paper Citation

in Harvard Style

Nair S. and Deepa N. (2023). Forecasting Cost-Push Inflation with LASSO over Ridge Regression. In Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT; ISBN 978-989-758-661-3, SciTePress, pages 64-70. DOI: 10.5220/0012559200003739

in Bibtex Style

@conference{ai4iot23,
author={Sree Nair and N. Deepa},
title={Forecasting Cost-Push Inflation with LASSO over Ridge Regression},
booktitle={Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT},
year={2023},
pages={64-70},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012559200003739},
isbn={978-989-758-661-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT
TI - Forecasting Cost-Push Inflation with LASSO over Ridge Regression
SN - 978-989-758-661-3
AU - Nair S.
AU - Deepa N.
PY - 2023
SP - 64
EP - 70
DO - 10.5220/0012559200003739
PB - SciTePress