Multivariate decompositions and seasonal gender employment

33 Pages Posted: 12 Aug 2021

See all articles by Jing Tian

Jing Tian

University of Tasmania; Financial Research Network (FIRN)

Jan P. A. M. Jacobs

University of Groningen - Faculty of Economics and Business

Denise R. Osborn

The University of Manchester - School of Social Sciences; University of Tasmania

Date Written: August 11, 2021

Abstract

Multivariate analysis can help to focus on economic phenomena, including trend and cyclical movements. To allow for potential correlation with seasonality, the present paper studies a three component multivariate unobserved component model, focusing on the case of quarterly data and showing that economic restrictions, including common trends and common cycles, can ensure identification. Applied to seasonal aggregate gender employment in Australia, a bivariate male/female model with a common cycle is preferred to both univariate correlated component and bivariate uncorrelated component specifications. This model evidences distinct gender-based seasonal patterns with seasonality declining over time for females and increasing for males.

Keywords: trend-cycle-seasonal decomposition, multivariate unobserved components models, correlated component models, identification, gender employment, Australia

JEL Classification: C22, E24, E32, E37, F01

Suggested Citation

Tian, Jing and Jacobs, Jan P.A.M. and Osborn, Denise R., Multivariate decompositions and seasonal gender employment (August 11, 2021). CAMA Working Paper No. 72/2021, Available at SSRN: https://ssrn.com/abstract=3902903 or http://dx.doi.org/10.2139/ssrn.3902903

Jing Tian (Contact Author)

University of Tasmania ( email )

French Street
Sandy Bay
Tasmania, 7250
Australia

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

Jan P.A.M. Jacobs

University of Groningen - Faculty of Economics and Business ( email )

Postbus 72
9700 AB Groningen
Netherlands

Denise R. Osborn

The University of Manchester - School of Social Sciences ( email )

Oxford Road
Manchester, M13 9PL
United Kingdom

University of Tasmania ( email )

French Street
Sandy Bay
Tasmania, 7250
Australia

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