Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Gender inequalities in unpaid work are a serious concern in the present era. Unpaid work is often seen as women's responsibility. The purpose of the study is to analyse the nature and magnitude of women's unpaid work in Maradu Municipality based on their employment status. The convenience sampling technique is used to recruit sample units. The study also examines the comparative differences in the amount of leisure that employed and unemployed women enjoy. The study's findings imply that there is no significant difference in the average time allocated to household work by employed and unemployed women. This means that employment status does not significantly affect the magnitude of women's unpaid care work. Employed women, on average, allocate 1.24 hours a day for leisure, whereas unemployed women, on average, spend 2.14 hours for leisure. The results of a Mann-Whitney U test suggest that there is a statistically significant difference in the average time allocated to leisure of employed and unemployed women. While employment status is found to affect women's time allocation to leisure significantly, it does not influence household work.
Keywords:
Unpaid Care Work, Employment, Leisure, Household work
Cite Article:
"An Economic Analysis of the Time Allocation by Employed and Unemployed Women.", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 2, page no.a208-a212, February-2026, Available :http://www.ijrti.org/papers/IJRTI2602023.pdf
Downloads:
000170
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator