Determinants of Gender Inequality in the Paid-Unpaid Labor Balance: A Tree-Based Analysis of Employed Iranian Time-Use Data

مقالات آماده انتشار

نوع مقاله : مقاله پژوهشی

نویسندگان

1 Associate Professor of Biostatistics, Department of Statistical Methods and Demographic Modelling, National Institute for Population Research, Tehran, Iran

2 Associate Professor of Applied Statistics, Department of Statistical Methods and Demographic Modelling, National Institute for Population Research, Tehran, Iran

چکیده

Background and Aim: Gender inequalities in the Paid-Unpaid Labor Balance (P-ULB) within the family sphere can lead to delayed marriage, decreased fertility rates, and a diminished quality of marital satisfaction. The main objective of this study is to examine the distribution of this balance among employed men and women in Iranian households and to identify the key socio-demographic determinants influencing it.
 
Data and Method: The P-ULB indicator is operationalized as the ratio of daily time allocated to paid versus unpaid labor. The Classification and Regression Tree (CART) machine learning algorithm was employed to model the P-ULB indicator into categorical outcomes (paid-dominant vs. unpaid-dominant). The CART model was applied to a sample of 9,296 employed individuals, comprising 7,962 men (85.6%) and 1,334 women (14.4%), extracted from the Iranian Time-Use Survey (2019–2020). Covariates included age group, children's age status, marital status, day type, socio-economic status, and internet use.
 
Findings: The results indicate that employed women shoulder a disproportionate burden of unpaid labor (50.4% falling into the unpaid-dominant category), whereas employed men dedicate the vast majority of their time to paid labor (93.8% paid-dominant). With a tree classification accuracy of 74%, all analyzed covariates exerted a significant influence on the CART model for women, with the exception of internet usage with tree accuracy of 74%.
 
Conclusion: Gender gaps in time allocation for childcare and are deeply embedded in long-standing socio-cultural norms that dictate traditional female roles within the home and family. Mitigating these imbalances and advancing gender equity in Iran requires a synchronized approach involving macro-level policy interventions and progressive cultural shifts.
 
Key Message: The discrepancy between the ideal and the empirical reality of gender inequality among employed Iranian men and women remains substantial. To foster an environment conducive to higher fertility intentions, structural changes are imperative, specifically increasing husbands' participation in unpaid domestic labor alongside expanding opportunities for women in formal paid employment.

کلیدواژه‌ها

عنوان مقاله [English]

Determinants of Gender Inequality in the Paid-Unpaid Labor Balance: A Tree-Based Analysis of Employed Iranian Time-Use Data

نویسندگان [English]

  • Mahsa Saadati 1
  • Arezoo Bagheri 2
1 Associate Professor of Biostatistics, Department of Statistical Methods and Demographic Modelling, National Institute for Population Research, Tehran, Iran
2 Associate Professor of Applied Statistics, Department of Statistical Methods and Demographic Modelling, National Institute for Population Research, Tehran, Iran
چکیده [English]

Background and Aim: Gender inequalities in the Paid-Unpaid Labor Balance (P-ULB) within the family sphere can lead to delayed marriage, decreased fertility rates, and a diminished quality of marital satisfaction. The main objective of this study is to examine the distribution of this balance among employed men and women in Iranian households and to identify the key socio-demographic determinants influencing it.
 
Data and Method: The P-ULB indicator is operationalized as the ratio of daily time allocated to paid versus unpaid labor. The Classification and Regression Tree (CART) machine learning algorithm was employed to model the P-ULB indicator into categorical outcomes (paid-dominant vs. unpaid-dominant). The CART model was applied to a sample of 9,296 employed individuals, comprising 7,962 men (85.6%) and 1,334 women (14.4%), extracted from the Iranian Time-Use Survey (2019–2020). Covariates included age group, children's age status, marital status, day type, socio-economic status, and internet use.
 
Findings: The results indicate that employed women shoulder a disproportionate burden of unpaid labor (50.4% falling into the unpaid-dominant category), whereas employed men dedicate the vast majority of their time to paid labor (93.8% paid-dominant). With a tree classification accuracy of 74%, all analyzed covariates exerted a significant influence on the CART model for women, with the exception of internet usage with tree accuracy of 74%.
 
Conclusion: Gender gaps in time allocation for childcare and are deeply embedded in long-standing socio-cultural norms that dictate traditional female roles within the home and family. Mitigating these imbalances and advancing gender equity in Iran requires a synchronized approach involving macro-level policy interventions and progressive cultural shifts.
 
Key Message: The discrepancy between the ideal and the empirical reality of gender inequality among employed Iranian men and women remains substantial. To foster an environment conducive to higher fertility intentions, structural changes are imperative, specifically increasing husbands' participation in unpaid domestic labor alongside expanding opportunities for women in formal paid employment.

کلیدواژه‌ها [English]

  • Unpaid Labor
  • Paid-Unpaid Labor Balance (P-ULB)
  • Classification and Regression Trees (CART)
  • Gender Inequality
  • Women

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