scholarly journals Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence

2021 ◽  
Author(s):  
Andres Algaba ◽  
Samuel Borms ◽  
Kris Boudt ◽  
Brecht Verbeken
Keyword(s):  
Factor Model ◽  
Consumer Confidence ◽  
Dynamic Factor ◽  
Dynamic Factor Model ◽  
Daily News ◽  
Mixed Frequency ◽  
News Sentiment

Dynamic factor model for network traffic state forecast

2018 ◽  
Vol 118 ◽  
pp. 281-317 ◽  
Author(s):  
Tao Ma ◽  
Zhou Zhou ◽  
Constantinos Antoniou
Keyword(s):  
Network Traffic ◽  
Factor Model ◽  
Dynamic Factor ◽  
Dynamic Factor Model ◽  
Traffic State

scholarly journals Dynamic factor model with infinite‐dimensional factor space: Forecasting

2018 ◽  
Vol 33 (5) ◽  
pp. 625-642 ◽  
Author(s):  
Mario Forni ◽  
Alessandro Giovannelli ◽  
Marco Lippi ◽  
Stefano Soccorsi
Keyword(s):  
Factor Model ◽  
Dynamic Factor ◽  
Dynamic Factor Model ◽  
Factor Space ◽  
Infinite Dimensional

Measuring the Output Gap using Large Datasets

2021 ◽  
pp. 1-45
Author(s):  
Matteo Barigozzi ◽  
Matteo Luciani
Keyword(s):  
Factor Model ◽  
Theoretical Models ◽  
Output Growth ◽  
Output Gap ◽  
Dynamic Factor ◽  
Dynamic Factor Model ◽  
Goods And Services ◽  
Long Run ◽  
Slow Drift ◽  
Macroeconomic Indicators

Abstract We propose a new measure of the output gap based on a dynamic factor model that is estimated on a large number of U.S. macroeconomic indicators and which incorporates relevant stylized facts about macroeconomic data (co-movements, non-stationarity, and the slow drift in long-run output growth over time). We find that, (1) from the mid-1990s to 2008, the U.S. economy operated above its potential; and, (2) in 2018:Q4, the labor market was tighter than the market for goods and services. Because it is mainly data-driven, our measure is a natural complementary tool to the theoretical models used at policy institutions.

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