National Unemployment Rate Forecast with Google Trends
Year: 2025
Type: article
Abstract: The significant economic recession and ongoing COVID-19 pandemic are impacting various sectors. The decrease in employment, one of the main consequences of this economic stagnation, is felt intensely in Türkiye. The concern that today's unemployment problem will be experienced more intensely in the future brings to the fore studies on unemployment forecasting. To date, unemployment forecasting studies have received extensive coverage in the literature. This study aims to make more successful forecasts of unemployment data by using Google Trends (GT), which is frequently used in different fields today. Four GT-based variables were incorporated into traditional forecasting methods, including ARIMA, ARIMAX, and VAR models. The VAR GT3 model, which integrates GT data with annual inflation, provided the best forecasting performance among all tested models. The findings indicate that models incorporating GT data derived from various keywords yield more successful results than traditional models.
Authors: Savaş Gayaker, Hasan Türe
Institution: Ankara Hacı Bayram Veli University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4408966648