Počet záznamů: 1
Regression Quantiles under Heteroscedasticity and Multicollinearity: Analysis of Travel and Tourism Competitiveness
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SYSNO ASEP 0501434 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Regression Quantiles under Heteroscedasticity and Multicollinearity: Analysis of Travel and Tourism Competitiveness Tvůrce(i) Kalina, Jan (UIVT-O) RID, SAI, ORCID
Vašaničová, P. (SK)
Litavcová, E. (SK)Zdroj.dok. Ekonomický časopis. - : Ekonomický ústav SAV - ISSN 0013-3035
Roč. 67, č. 1 (2019), s. 69-85Poč.str. 17 s. Jazyk dok. eng - angličtina Země vyd. SK - Slovensko Klíč. slova linear regression ; model selection ; robustness ; regression quantiles ; lasso ; tourism Vědní obor RIV BB - Aplikovaná statistika, operační výzkum Obor OECD Statistics and probability Způsob publikování Open access Institucionální podpora UIVT-O - RVO:67985807 UT WOS 000457791100005 EID SCOPUS 85068216962 Anotace In the linear regression, heteroscedasticity and multicollinearity can be characterized as intertwined problems, which often simultaneously appear in econometric models. The aim of this paper is to discuss various approaches to regression modelling for heteroscedastic multi collinear data. A real economic dataset from the World Economic Forum serves as an illustration of various individual methods and the paper provides a practical motivation for quantile regression and particularly for regularized regression quantiles. In the dataset, tourist service infrastructure across 141 countries is modelled as a response of 12 characteristics of the Travel and Tourism Competitiveness Index (TTCI). Regression quantiles and their lasso estimates turn out to be more suitable for the dataset compared to more traditional econometric tools. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2020 Elektronická adresa https://www.sav.sk/journals/uploads/0125113201%2019%20Kalina%20+%20RS.pdf
Počet záznamů: 1