Dynamic factor models with jagged edge panel data: Taking on board the dynamics of the idiosyncratic components
AbstractThe estimation of dynamic factor models for large cross-sections poses a challenge in a real time environment. As macroeconomic data become available with different delays, unbalanced panel data sets with missing values at the end of the sample period (the so-called "jagged edge") have to be handled when estimating the factor model. In this paper, we propose an EM algorithm which copes with such data sets, accounts for autoregressive common factors and allows for serial correlation in the idiosyncratic components. Based on Monte Carlo simulations, we find that taking on board the dynamics of the idiosyncratic components improves significantly the accuracy of the estimation of both the missing values and the common factors at the end of the sample period.
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Bibliographic InfoPaper provided by Banco de Portugal, Economics and Research Department in its series Working Papers with number w200913.
Date of creation: 2009
Date of revision:
Other versions of this item:
- Maximiano Pinheiro & António Rua & Francisco Dias, 2013. "Dynamic Factor Models with Jagged Edge Panel Data: Taking on Board the Dynamics of the Idiosyncratic Components," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(1), pages 80-102, 02.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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