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Nowcasting inflation expectations using twitter

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Název:	Nowcasting inflation expectations using twitter
Autoři:	Gorham, Nicholas
Přispěvatelé:	Han, Qiwei
Rok vydání:	1486
Sbírka:	Repositório da Universidade Nova de Lisboa (UNL)
Témata:	Nowcasting, Twitter, Inflation expectations, Dynamic topic modelling, CEMS MIM, Domínio/Área Científica::Ciências Sociais::Economia e Gestão
Popis:	This study explores the potential of Twitter to forecast inflation expectations through various machine learning models. Twitter-based measures of inflation were shown to be correlated with survey-based inflation expectations. No single regression model was consistently superior, although PCA-Ridge appears to be appropriate. The study also unveiled potential issues with data cleaning, model overfitting, and limitations in available data. These findings advance the understanding of economic forecasting using unconventional data sources, opening pathways for future research.
Druh dokumentu:	master thesis
Jazyk:	English
Relation:	UID/ECO/00124/2013; http://hdl.handle.net/10362/173357; 203366670
Dostupnost:	http://hdl.handle.net/10362/173357
Rights:	embargoedAccess
Přístupové číslo:	edsbas.1512FE71
Databáze:	BASE

Popis
Abstrakt:	This study explores the potential of Twitter to forecast inflation expectations through various machine learning models. Twitter-based measures of inflation were shown to be correlated with survey-based inflation expectations. No single regression model was consistently superior, although PCA-Ridge appears to be appropriate. The study also unveiled potential issues with data cleaning, model overfitting, and limitations in available data. These findings advance the understanding of economic forecasting using unconventional data sources, opening pathways for future research.