Distributional counterfactual analysis with (common) deterministic trend units

Detalhes bibliográficos
Autor(a) principal: Masini, Ricardo Pereira
Data de Publicação: 2018
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
Texto Completo: https://hdl.handle.net/10438/27665
Resumo: The goal of this paper is to extend the counterfactual methodologies in particular Carvalho et al. (2016), by considering the estimation of quantile counterfactuals in the presence of trend units. We derive an asymptotically normal test statistics for the quantile intervention effect and for the distribution effect as a whole. As a by-product, we show the consistency of the quantile regression under heterogeneity and temporal dependence. More importantly, the consistency is obtained without relying on common assumptions of compactness and uniform convergence of the objective function. In fact due to the deterministic trend the objective function fails to be stochastically equicontinuos, which provided that the parameter space is totally bounded, is necessary for uniform convergence. Our procedure is illustrated in a detailed simulation experiment as well as in an empirical application in Corporate Finance.
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spelling Masini, Ricardo PereiraDemais unidades::RPCAFGV2019-07-03T14:58:06Z2019-07-03T14:58:06Z2018-01https://hdl.handle.net/10438/27665The goal of this paper is to extend the counterfactual methodologies in particular Carvalho et al. (2016), by considering the estimation of quantile counterfactuals in the presence of trend units. We derive an asymptotically normal test statistics for the quantile intervention effect and for the distribution effect as a whole. As a by-product, we show the consistency of the quantile regression under heterogeneity and temporal dependence. More importantly, the consistency is obtained without relying on common assumptions of compactness and uniform convergence of the objective function. In fact due to the deterministic trend the objective function fails to be stochastically equicontinuos, which provided that the parameter space is totally bounded, is necessary for uniform convergence. Our procedure is illustrated in a detailed simulation experiment as well as in an empirical application in Corporate Finance.engCounterfactual analysisQuantile panel dataQuantile counterfactualArCoEconomiaSociedades comerciais - FinançasAnálise de regressãoDistributional counterfactual analysis with (common) deterministic trend unitsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVRede de Pesquisa e Conhecimento AplicadoORIGINAL147_2018_Distributional Counterfactual Analysis_RICARDO MASINI.PDF147_2018_Distributional Counterfactual Analysis_RICARDO MASINI.PDFapplication/pdf461722https://repositorio.fgv.br/bitstreams/0b474ba7-7f23-4d85-bedb-010fd6d28f55/download49e48f19416369b71222666b8b11e494MD51TEXT147_2018_Distributional Counterfactual Analysis_RICARDO MASINI.PDF.txt147_2018_Distributional Counterfactual 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dc.title.eng.fl_str_mv Distributional counterfactual analysis with (common) deterministic trend units
title Distributional counterfactual analysis with (common) deterministic trend units
spellingShingle Distributional counterfactual analysis with (common) deterministic trend units
Masini, Ricardo Pereira
Counterfactual analysis
Quantile panel data
Quantile counterfactual
ArCo
Economia
Sociedades comerciais - Finanças
Análise de regressão
title_short Distributional counterfactual analysis with (common) deterministic trend units
title_full Distributional counterfactual analysis with (common) deterministic trend units
title_fullStr Distributional counterfactual analysis with (common) deterministic trend units
title_full_unstemmed Distributional counterfactual analysis with (common) deterministic trend units
title_sort Distributional counterfactual analysis with (common) deterministic trend units
author Masini, Ricardo Pereira
author_facet Masini, Ricardo Pereira
author_role author
dc.contributor.unidadefgv.por.fl_str_mv Demais unidades::RPCA
dc.contributor.affiliation.none.fl_str_mv FGV
dc.contributor.author.fl_str_mv Masini, Ricardo Pereira
dc.subject.eng.fl_str_mv Counterfactual analysis
Quantile panel data
Quantile counterfactual
ArCo
topic Counterfactual analysis
Quantile panel data
Quantile counterfactual
ArCo
Economia
Sociedades comerciais - Finanças
Análise de regressão
dc.subject.area.por.fl_str_mv Economia
dc.subject.bibliodata.por.fl_str_mv Sociedades comerciais - Finanças
Análise de regressão
description The goal of this paper is to extend the counterfactual methodologies in particular Carvalho et al. (2016), by considering the estimation of quantile counterfactuals in the presence of trend units. We derive an asymptotically normal test statistics for the quantile intervention effect and for the distribution effect as a whole. As a by-product, we show the consistency of the quantile regression under heterogeneity and temporal dependence. More importantly, the consistency is obtained without relying on common assumptions of compactness and uniform convergence of the objective function. In fact due to the deterministic trend the objective function fails to be stochastically equicontinuos, which provided that the parameter space is totally bounded, is necessary for uniform convergence. Our procedure is illustrated in a detailed simulation experiment as well as in an empirical application in Corporate Finance.
publishDate 2018
dc.date.issued.fl_str_mv 2018-01
dc.date.accessioned.fl_str_mv 2019-07-03T14:58:06Z
dc.date.available.fl_str_mv 2019-07-03T14:58:06Z
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