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Robust Estimators

Robust estimators control the impact of outliers, limiting their influence on the results. One robust estimator is the quantile regression, which allows to compute the regression modelnot only at the center but also at different points of the distribution.

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Publications - Robust tests for unit root and changes in persistence, International Journal of Computational Economics and Econometrics, 2014. Furno, M.
- Quantile regression and structural change in the Italian wage equation (2013) Economic Modelling, 30 (1), pp. 420-434. Q2
- Returns to education and gender gap, International Review of Applied Economics (2014)
- Furno, M. Tests for structural break in quantile regressions (2012) AStA Advances in Statistical Analysis, 96 (4), pp. 493-515. Q2
- Furno, M. Goodness of fit and misspecification in quantile regressions (2011) Journal of Educational and Behavioral Statistics, 36 (1), pp. 105-131.  Q1
- Furno, M. A robust test of specification based on order statistics (2010) Computational Statistics, 25 (4), pp. 707-723. Q3
- Furno, M. Quantile regression analysis of the Italian school system (2010) Statistical Modelling, 10 (3), pp. 333-351. Q3
- Quantile Regression: Theory and Applications, (con C. Davino e D. Vistocco), chpt. 3 p. 63-92, and chpt. 5 p. 127-156, vol. 1, Wiley, London, 2014.
- Qu test for structural breaks in quantile regressions, (con D. Vistocco), International Journal of Statistics and Probability, vol. 2, n. 4, pg 42-55, 2013.
Permanent staff Marilena Furno, Ordinario di Statistica, S01
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