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EnglishThe availability of reliable estimates of income distribution parameters at a sub-national level is essential for the study of regional disparities. For European Union, countries the estimation of income parameters can be obtained from the European Community Household Panel, that provides reliable estimates for large areas within countries. The aim of this work is to find a suitable small area estimator of the average income at a smaller geographical scale, based on data from this survey. Since it is a panel survey, we suggest some different specifications of unit level Linear Mixed Models leading to small area estimators that borrow strength across both areas and times. In the Small Area Estimation context, full time series and “time series and cross-sectional” aggregate models have been applied in the literature, while small area unit level models for panel data have not been studied extensively. We compare the estimators performance by a Monte Carlo simulation study. Results show a significant gain in efficiency of estimators connected to models that take into account units autocorrelation.
| Titolo: | Small Area Estimation of Average Household Income Based on Panel Data | |
| Autore/i: | E. Fabrizi; FERRANTE, MARIA; PACEI, SILVIA | |
| Autore/i Unibo: | ||
| Anno: | 2004 | |
| Titolo del libro: | 2004 Proceedings of the American Statistical Association, Statistical Computing Section | |
| Pagina iniziale: | 3464 | |
| Pagina finale: | 3470 | |
| Abstract: | The availability of reliable estimates of income distribution parameters at a sub-national level is essential for the study of regional disparities. For European Union, countries the estimation of income parameters can be obtained from the European Community Household Panel, that provides reliable estimates for large areas within countries. The aim of this work is to find a suitable small area estimator of the average income at a smaller geographical scale, based on data from this survey. Since it is a panel survey, we suggest some different specifications of unit level Linear Mixed Models leading to small area estimators that borrow strength across both areas and times. In the Small Area Estimation context, full time series and “time series and cross-sectional” aggregate models have been applied in the literature, while small area unit level models for panel data have not been studied extensively. We compare the estimators performance by a Monte Carlo simulation study. Results show a significant gain in efficiency of estimators connected to models that take into account units autocorrelation. | |
| Data prodotto definitivo in UGOV: | 13-ott-2005 | |
| Appare nelle tipologie: | 4.01 Contributo in Atti di convegno |
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