Logo
Munich Personal RePEc Archive

Estimation of the Unemployment Rate in Moldova: A Comparison of ARIMA and Machine Learning Models Including COVID-19 Pandemic Periods

Vîntu, Denis (2025): Estimation of the Unemployment Rate in Moldova: A Comparison of ARIMA and Machine Learning Models Including COVID-19 Pandemic Periods.

[thumbnail of MPRA_paper_125941.pdf] PDF
MPRA_paper_125941.pdf

Download (60kB)

Abstract

This study investigates the estimation of the unemployment rate in the Republic of Moldova, focusing on the impact of the COVID-19 pandemic. Two forecasting approaches are compared: the traditional ARIMA model and several machine learning models. The performance of these models is evaluated based on prediction accuracy metrics over pre-pandemic and pandemic periods. Results indicate that while ARIMA captures general trends effectively, machine learning models can better adapt to sudden shocks, such as those induced by the pandemic.

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.