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on Econometrics |
By: | Jesús Fernández-Villaverde; Juan F. Rubio-Ramirez; Thomas J. Sargent |
Date: | 2005–04–05 |
URL: | http://d.repec.org/n?u=RePEc:cla:levrem:172782000000000096&r=ecm |
By: | Cizek,Pavel; Haerdle,Wolfgang (Tilburg University, Center for Economic Research) |
Abstract: | Most dimension reduction methods based on nonparametric smoothing are highly sensitive to outliers and to data coming from heavy-tailed distributions. We show that the recently proposed methods by Xia et al. (2002) can be made robust in such a way that preserves all advantages of the original approach. Their extension based on the local one-step M-estimators is sufficiently robust to outliers and data from heavy tailed distributions, it is relatively easy to implement, and surprisingly, it performs as well as the original methods when applied to normally distributed data. |
JEL: | C14 C20 |
Date: | 2005 |
URL: | http://d.repec.org/n?u=RePEc:dgr:kubcen:200531&r=ecm |
By: | Audrey Laporte; Frank Windmeijer |
Abstract: | We show that two commonly employed estimation procedures to deal with correlated unobserved heterogeneity in panel data models, within-groups and first-differenced OLS, can lead to very different estimates of treatment effects when these are not constant over time and treatment is a state that only changes occasionally. It is therefore important to allow for flexible time varying treatment effects when estimating panel data models with binary indicator variables as is illustrated by an example of the effects of marital status on mental wellbeing. |
Keywords: | panel data, treatment effects. |
JEL: | C23 C51 |
Date: | 2005–03–11 |
URL: | http://d.repec.org/n?u=RePEc:tor:tecipa:laporte-04-01&r=ecm |