Robust penalized quantile regression estimation for panel data

By Carlos Lamarche. 2010

387 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/14f2e4c306da91815c3e8e4ec19dd6c6fd87b103

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Citations in the corpus

Panel data quantile regression with grouped fixed effects (2018, background): “004) takes the xed eect approach and introduces individual latent eects as location shifts. These individual eects are regularized through an ‘ 1 penalty which shrinks them towards a common value. Lamarche (2010) proposes an optimal way to choose the corresponding penalty parameter in order to optim”
VAR for VaR: Measuring Tail Dependence Using Multivariate Regression Quantiles (2015, background): “…to a vector autoregressive (VAR) structure: 1 = 0 1 + 11 1 1 + 12 2 1 2 = 0 2 + 21 1 1 + 22 2 1 1Some relevant and important papers are Koenker and Xiao (2004, 2006), Xiao (2009) in the time-series domain and Abrevaya and Dahl (2008), Lamarche (2010), Galvao (2011) in the panel data setting.”
The effects of FDI, economic growth and energy consumption on carbon emissions in ASEAN-5: Evidence from panel quantile regression (2016, background): “Some works, such as those by Koenker (2004), Lamarche (2010), Galvao (2011) and Canay (2011), are focused on the econometric theory of applying quantile regressions to panel data.”
IV Quantile Regression for Group-Level Treatments, with an Application to the Distributional Effects of Trade (2016, background): “Including many variables in a standard quantile regression can drastically increase the computational time (see Koenker (2004), Lamarche (2010), Galvao and Wang (2013), and Galvao (2011) for further discussion) and, in our experience, can often lead standard optimization packages to fail to…”
Democracy, Financial Openness, and Global Carbon Dioxide Emissions: Heterogeneity Across Existing Emission Levels (2015, methodology): “…the advantages of quantile regression model with panel data, there has been little but growing work have focused on the econometric theory of applying quantile regression to panel data contexts, such as Koenker (2004), Lamarche (2010), Galvao and Montes-Rojas (2010), Galvao (2011) and Canay (2011).”
Asymptotics for panel quantile regression models with individual effects (2012, methodology): “Lamarche (2010) studied Koenker’s (2004) penalization method and discussed an optimal choice of the tuning parameter.”
Econometric modelling of the regional knowledge production function in Europe (2015, background): “Very recently, Harding and Lamarche (2014) proposed a linear quantile regression estimator for a panel data model with interactive effects (factor model) potentially correlated with covariates (see also Koenker, 2004 and Lamarche, 2010 for quantile regression models with individual fixed effects).”
Estimation of Censored Quantile Regression for Panel Data With Fixed Effects (2013, background): “2, the performance of the fixed effects estimator improves by selecting λ to minimize RMSE [Lamarche (2010)].”