Applying multiple regression to distinguish the nature and
intensity of labor market, population and household effects on
GPG across world economies

D 2023

Applying multiple regression to distinguish the nature and intensity of labor market, population and household effects on GPG across world economies

JAŠOVÁ, Emilie

Basic information

Original name

Applying multiple regression to distinguish the nature and intensity of labor market, population and household effects on GPG across world economies

Name in Czech

Použití vícenásobné regrese k rozlišení povahy a intenzity vlivu trhu práce, populace a domácností na GPG napříč světovými ekonomikami

Authors

JAŠOVÁ, Emilie

Edition

Brno, 2nd Proceedings of the Open Scientific Conference, 2023, p. 20-35, 16 pp. 2023

Publisher

European Research Center

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

50200 5.2 Economics and Business

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

Odkaz na fulltext sborníku

Organization unit

University of Finance and Administration

ISBN

978-80-907553-2-1

ISSN

DOI

http://dx.doi.org/10.52950/3OSC.Istanbul.2023.5.006

Keywords (in Czech)

mzdové rozdíly mezi muži a ženami, minimální mzda, index nákladů práce podle NACE, neaktivní obyvatel, NEET, NAIRU

Keywords in English

the pay gap between men and women, minimum wage, labour cost index by NACE, inactive population, NEET, NAIRU

Abstract

ORIG CZ

V originále

The aim of the article is to verify and expand knowledge about the existence and nature of the influence of the labor market, the population and the family on the differences in the remuneration of women and men. For age across world economies, negative values outweighed positive values for the NAIRU of women (40 to 44 years) with upper secondary and post-secondary non-tertiary education. For the ownership of economic activity, positive values prevailed over negative ones for the NAIRU indicator of women (30 to 34 years old) with upper secondary and post-secondary non-tertiary education. For the type of employment agreements, the average positive values outweighed the negative ones for the indicator tax rate for people with low income. Our econometric analysis also found a statistically insignificant effect that foreign and domestic research does not mention.

In Czech

Cílem článku je ověřit a rozšířit poznatky o existenci a povaze vlivu trhu práce, populace a rodiny na rozdíly v odměňování žen a mužů. Pokud jde o věk ve světových ekonomikách, záporné hodnoty převažovaly nad kladnými hodnotami pro NAIRU žen (40 až 44 let) s vyšším sekundárním a postsekundárním neterciárním vzděláním. U vlastnictví ekonomické činnosti převažovaly kladné hodnoty nad zápornými u ukazatele NAIRU žen (30 až 34 let) s vyšším středním a postsekundárním neterciárním vzděláním. U typu dohod o pracovní činnosti převažovaly průměrné kladné hodnoty nad zápornými u ukazatele sazba daně u osob s nízkými příjmy. Naše ekonometrická analýza také zjistila statisticky nevýznamný vliv, který zahraniční ani domácí výzkumy nezmiňují.

Citovat

JAŠOVÁ, Emilie. Applying multiple regression to distinguish the nature and intensity of labor market, population and household effects on GPG across world economies. Online. In Jiří Rotschedl. 2nd Proceedings of the Open Scientific Conference, 2023. Brno: European Research Center, 2023, p. 20-35. ISBN 978-80-907553-2-1. Available from: https://dx.doi.org/10.52950/3OSC.Istanbul.2023.5.006.

@inproceedings{10928,
   author = {Jašová, Emilie},
   address = {Brno},
   booktitle = {2nd Proceedings of the Open Scientific Conference, 2023},
   doi = {http://dx.doi.org/10.52950/3OSC.Istanbul.2023.5.006},
   editor = {Jiří Rotschedl},
   keywords = {the pay gap between men and women, minimum wage, labour cost index by NACE, inactive population, NEET, NAIRU},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Brno},
   isbn = {978-80-907553-2-1},
   pages = {20-35},
   publisher = {European Research Center},
   title = {Applying multiple regression to distinguish the nature and intensity of labor market, population and household effects on GPG across world economies},
   url = {https://conference.eurrec.org/proceedings/open-scientific-conference-istanbul-2023},
   year = {2023}
}

TY  - JOUR
ID  - 10928
AU  - Jašová, Emilie
PY  - 2023
TI  - Applying multiple regression to distinguish the nature and intensity of labor market, population and household effects on GPG across world economies
PB  - European Research Center
CY  - Brno
SN  - 9788090755321
KW  - the pay gap between men and women, minimum wage, labour cost index by NACE, inactive population, NEET, NAIRU
UR  - https://conference.eurrec.org/proceedings/open-scientific-conference-istanbul-2023
N2  - The aim of the article is to verify and expand knowledge about the existence and nature of the influence of the labor market, the population and the family on the differences in the remuneration of women and men. For age across world economies, negative values outweighed positive values for the NAIRU of women (40 to 44 years) with upper secondary and post-secondary non-tertiary education. For the ownership of economic activity, positive values prevailed over negative ones for the NAIRU indicator of women (30 to 34 years old) with upper secondary and post-secondary non-tertiary education. For the type of employment agreements, the average positive values outweighed the negative ones for the indicator tax rate for people with low income. Our econometric analysis also found a statistically insignificant effect that foreign and domestic research does not mention.
ER  -

JAŠOVÁ, Emilie. Applying multiple regression to distinguish the nature and intensity of labor market, population and household effects on GPG across world economies. Online. In Jiří Rotschedl. \textit{2nd Proceedings of the Open Scientific Conference, 2023}. Brno: European Research Center, 2023, p.~20-35. ISBN~978-80-907553-2-1. Available from: https://dx.doi.org/10.52950/3OSC.Istanbul.2023.5.006.

Detailed Information on Publication Record