[HTML][HTML] On bootstrap inference for quantile regression panel data: A Monte Carlo study
AF Galvao, G Montes-Rojas - Econometrics, 2015 - mdpi.com
This paper evaluates bootstrap inference methods for quantile regression panel data
models. We propose to construct confidence intervals for the parameters of interest using …
models. We propose to construct confidence intervals for the parameters of interest using …
On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study
A Galvao, G Montes-Rojas - Econometrics, 2015 - econpapers.repec.org
This paper evaluates bootstrap inference methods for quantile regression panel data
models. We propose to construct confidence intervals for the parameters of interest using …
models. We propose to construct confidence intervals for the parameters of interest using …
[PDF][PDF] On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study
AF Galvao, G Montes-Rojas - researchgate.net
This paper evaluates bootstrap inference methods for quantile regression panel data
models. We propose to construct confidence intervals for the parameters of interest using …
models. We propose to construct confidence intervals for the parameters of interest using …
On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study
AF Galvao, G Montes-Rojas - Econometrics, 2015 - search.proquest.com
This paper evaluates bootstrap inference methods for quantile regression panel data
models. We propose to construct confidence intervals for the parameters of interest using …
models. We propose to construct confidence intervals for the parameters of interest using …
[PDF][PDF] On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study
AF Galvao, G Montes-Rojas - pdfs.semanticscholar.org
This paper evaluates bootstrap inference methods for quantile regression panel data
models. We propose to construct confidence intervals for the parameters of interest using …
models. We propose to construct confidence intervals for the parameters of interest using …
On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study
A Galvao, GV Montes Rojas - 2015 - ri.conicet.gov.ar
This paper evaluates bootstrap inference methods for quantile regression panel data
models. We propose to construct confidence intervals for the parameters of interest using …
models. We propose to construct confidence intervals for the parameters of interest using …
On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study
AF Galvao, G Montes-Rojas - Econometrics, 2015 - ideas.repec.org
This paper evaluates bootstrap inference methods for quantile regression panel data
models. We propose to construct confidence intervals for the parameters of interest using …
models. We propose to construct confidence intervals for the parameters of interest using …
[PDF][PDF] On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study
AF Galvao, G Montes-Rojas - Citeseer
This paper evaluates bootstrap inference methods for quantile regression panel data
models. We propose to construct confidence intervals for the parameters of interest using …
models. We propose to construct confidence intervals for the parameters of interest using …
On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study
A Galvao, GV Montes Rojas - 2015 - notablesdelaciencia.conicet.gov.ar
This paper evaluates bootstrap inference methods for quantile regression panel data
models. We propose to construct confidence intervals for the parameters of interest using …
models. We propose to construct confidence intervals for the parameters of interest using …
On bootstrap inference for quantile regression panel data: A Monte Carlo study
AF Galvão Júnior, G Montes-Rojas - Econometrics, 2015 - econstor.eu
This paper evaluates bootstrap inference methods for quantile regression panel data
models. We propose to construct confidence intervals for the parameters of interest using …
models. We propose to construct confidence intervals for the parameters of interest using …