Using Google Trends Data to forecast homicide mortality: the case of Mexico

 

Đã lưu trong:
Chi tiết về thư mục
Nhiều tác giả: Vazquez, Eduardo, Silva, Eliud
Định dạng: artículo original
Trạng thái:Versión publicada
Ngày xuất bản:2025
Miêu tả:Introduction: In Mexico a major public safety concern is how to predict and reduce homicides to implement effective mitigation policies. Methodology: This study aims to compare traditional forecasting models —ARIMA and Vector Autoregressive (VAR)—with and without Google Trends data, the research explores ways to enhance prediction accuracy. Using homicide records from the National Institute of Statistics and Geography (INEGI, for its Spanish acronym) and Google Trends data from 2006–2020, the study highlights the integration of real-time online data to complement official statistics. Results: Considering a forecast horizon of 15 months up to March 2020, results show that VAR models with Google Trends provide the best performance for both female and male homicides. Conclusions: The findings underscore the potential of integrating digital data sources into traditional models to provide more accurate and timely tools for public safety planning and intervention.
Quốc gia:Portal de Revistas UCR
Tổ chức giáo dục:Universidad de Costa Rica
Repositorio:Portal de Revistas UCR
Ngôn ngữ:Inglés
OAI Identifier:oai:portal.revistas.ucr.ac.cr:article/2568
Truy cập trực tuyến:https://revistas.ucr.ac.cr/index.php/rpsm/article/view/2568
Từ khóa:Homicides
forecasting
Google Trends
VAR model
Homicidios
pronóstico
modelo VAR