Narrow search
Showing 1 - 10 of 418
Cover Image
Efficient estimation of an additive quantile regression
Cheng, Yebin; Gooijer, Jan G. de; Zerom Godefay, Dawit - 2009
In this paper two kernel-based nonparametric estimators are proposed for estimating the components of an additive quantile regression model. The first estimator is a computationally convenient approach which can be viewed as a viable alternative to the method of De Gooijer and Zerom (2003). By...
Persistent link: https://www.econbiz.de/10011379443
Cover Image
Intercept estimation in nonlinear selection models
Arulampalam, Wiji; Corradi, Valentina; Gutknecht, Daniel - 2021
We propose various semiparametric estimators for nonlinear selection models, where slope and intercept can be separately identifed. When the selection equation satisfies a monotonic index restriction, we suggest a local polynomial estimator, using only observations for which the marginal...
Persistent link: https://www.econbiz.de/10012518068
Cover Image
Structural vector autoregressions with smooth transition in variances : the interaction between US monetary policy and the stock market
Lütkepohl, Helmut; NetŠunajev, Aleksei - 2014
In structural vector autoregressive analysis identifying the shocks of interest via heteroskedasticity has become a … standard tool. Unfortunately, the approaches currently used for modelling heteroskedasticity all have drawbacks. For instance … used conventional identification schemes in this context are rejected by the data if heteroskedasticity is allowed for …
Persistent link: https://www.econbiz.de/10010361372
Cover Image
Structural vector autoregressions : checking identifying long-run restrictions via heteroskedasticity
Lütkepohl, Helmut; Velinov, Anton - 2014
mechanism and multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models. Using changes in volatility …
Persistent link: https://www.econbiz.de/10010233639
Cover Image
Structural vector autoregressions checking identifying long-run restrictions via heteroskedasticity
Lütkepohl, Helmut; Velinov, Anton - 2014
mechanism and multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models. Using changes in volatility …
Persistent link: https://www.econbiz.de/10010233991
Cover Image
Structural vector autoregressions with smooth transition in variances : the interaction between US monetary policy and the stock market
Lütkepohl, Helmut; Netšunajev, Aleksei - 2014
In structural vector autoregressive analysis identifying the shocks of interest via heteroskedasticity has become a … standard tool. Unfortunately, the approaches currently used for modelling heteroskedasticity all have drawbacks. For instance … used conventional identification schemes in this context are rejected by the data if heteroskedasticity is allowed for …
Persistent link: https://www.econbiz.de/10010364697
Cover Image
Fixed effects and random effects estimation of higher-order spatial autoregressive models with spatial autoregressive and heteroskedastic disturbances
Badinger, Harald; Egger, Peter - 2014
panel data models with spatial autoregressive disturbances and heteroskedasticity of unknown form in the idiosyncratic error … heteroskedasticity of unknown form in the idiosyncratic error component. Finally, we derive a robust Hausman-test of the spatial random …
Persistent link: https://www.econbiz.de/10010367382
Cover Image
Structural vector autoregressions : checking identifying long-run restrictions via heteroskedasticity
Lütkepohl, Helmut; Velinov, Anton - 2014
mechanism and multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models. Using changes in volatility …
Persistent link: https://www.econbiz.de/10010249640
Cover Image
Misspecified heteroskedasticity in the panel probit model : a small sample comparison of GMM and SML estimators
Inkmann, Joachim - 1999
. The GMM estimators outperform SML in the presence of misspecification in terms of multiplicative heteroskedasticity. This … holds in particular for the three-stage GMM estimator. Allowing for heteroskedasticity over time increases the robustness … with respect to misspecification in terms of ultiplicative heteroskedasticity. An application to the product innovation …
Persistent link: https://www.econbiz.de/10011545114
Cover Image
Treatment effects with many covariates and heteroskedasticity
Cattaneo, Matias D.; Jansson, Michael; Newey, Whitney K. - 2015
covariates and heteroskedasticity. Our results are obtained using high-dimensional approximations, where the number of covariates … are allowed to grow as fast as the sample size. We find that all of the usual versions of Eicker-White heteroskedasticity … heteroskedasticity consistent standard error formula that is fully automatic and robust to both (conditional) heteroskedasticity of …
Persistent link: https://www.econbiz.de/10011295589