Data/hora: 11/06/2024 01:05:13

Provedor de dados: 	31	
País: 	United States	
Título: 	“Google it!” Forecasting the US Unemployment Rate with a Google Job Search index	
Autores: 	D’Amuri,   Francesco; Marcucci,   Juri.	
Data: 	2010-04-19	
Ano: 	2010	
Palavras-chave: 	Google Econometrics; Forecast Comparison; Keyword search; US Unemployment; Time Series Models; Labor and Human Capital; C22; C53; E27; E37; J60; J64.	
Resumo: 	We suggest the use of an Internet job-search indicator (the Google Index, GI) as the best leading indicator to predict the US unemployment rate. We perform a deep out-of-sample forecasting comparison analyzing many models that adopt both our preferred leading indicator (GI), the more standard initial claims or combinations of both. We find that models augmented with the GI outperform the traditional ones in predicting the monthly unemployment rate, even in most state-level forecasts and in comparison with the Survey of Professional Forecasters.	
Tipo: 	Working or Discussion Paper	
Idioma: 	Inglês	
Identificador: 	http://purl.umn.edu/60680	
Relação: 	Fondazione Eni Enrico Mattei (FEEM)&gt;Global Challenges Papers

GC

31.2010	
Formato: 	58