Factor models in large cross sections of time series
Abstract
This Paper reviews recent econometric work on factor models in large cross-sections of time series. In this literature, traditional factor analysis is adapted to develop parsimonious estimation methods for high dimension time series models. The review covers problems of consistency and rates â as the dimension of the cross-section and the time dimension become large â identification and forecasting. We also review empirical applications on measuring and interpreting business cycles.(This abstract was borrowed from another version of this item.)
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Bibliographic Info
Paper provided by ULB -- Universite Libre de Bruxelles in its series ULB Institutional Repository with number 2013/10179.Length:
Date of creation: 2003
Date of revision:
Handle: RePEc:ulb:ulbeco:2013/10179
Note: Conference paper presented at: World congress of the econometric society(8)
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Keywords:Other versions of this item:
- Reichlin, Lucrezia, 2002. "Factor Models in Large Cross-Sections of Time Series," CEPR Discussion Papers 3285, C.E.P.R. Discussion Papers.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Bork, Lasse, 2009.
"Estimating US Monetary Policy Shocks Using a Factor-Augmented Vector Autoregression: An EM Algorithm Approach,"
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