Forecasting with Unobserved Heterogeneity
AbstractForecasting based on random intercepts models requires imputation of the individual permanent effects to the simulated individuals. When these individuals enter the simulation with a history of past outcomes this involves sampling from conditional distributions, which might be unfeasible. I present a method for drawing individual permanent effects from a conditional distribution which only requires to invert the corresponding estimated unconditional distribution. While the algorithms currently available in the literature require polynomial time, the proposed method only requires matching two ranks and works therefore in N lnN time.
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Bibliographic InfoPaper provided by LABORatorio R. Revelli, Centre for Employment Studies in its series LABORatorio R. Revelli Working Papers Series with number 123.
Date of creation: 2012
Date of revision:
forecasting; microsimulation; random intercept models; unobserved heterogeneity;
Find related papers by JEL classification:
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-10-13 (All new papers)
- NEP-CMP-2012-10-13 (Computational Economics)
- NEP-ECM-2012-10-13 (Econometrics)
- NEP-FOR-2012-10-13 (Forecasting)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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UNU-MERIT Working Paper Series
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Carlo Alberto Notebooks
267, Collegio Carlo Alberto.
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- Ambra Poggi & Matteo G. Richiardi, 2012. "Imputing Individual Effects in Dynamic Microsimulation Models.An application of the Rank Method," LABORatorio R. Revelli Working Papers Series 124, LABORatorio R. Revelli, Centre for Employment Studies.
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