1. Gender Perspectives of Time Allocation in China Anne de Bruin, Massey University, New Zealand Na Liu, Xiangtan University, People’s Republic of China IAFFE Conference 12 July - 14 July 2013 Stanford University, Palo Alto, California, USA

2. Women’s Well-being in China: Literature  Post-1978 Reforms and Transition - Widely held up as a macroeconomic success, a development success story  Growing literature on gender-differentiated implications of transition e.g.  Women’s market work, the gender division of domestic labour, household status (McPhail & Dong 2007; Qi & Dong 2013); the gender wage differentials (Chi & Li 2008; Dong & Zhang 2009; Ng 2008: Zhang et al. 2008); gender gap index (World Economic Forum various years); social welfare changes (Zhang & Maclean2012); gender roles (Xu & Yeung 2013)  Time-Use Gender Gap – Valuable insights into the well-being of women (Chang MacPhail & Dong 2011)

3. Our Focus  The overall nature of the time allocation gender gap between men and women in matched husband-wife couple households in China  What is the current gender time-use pattern?  Is gender time-use different in urban and rural regions?  Is gender time-use sensitive to labor income and non-labor income?  Interpretation: Cultural and Family Embeddedness intertwine to differentially affect men’s and women’s time allocation

4. Data  China Family Panel Studies (CFPS) 2010  Full 24 hour time-use details  Rich economic data: across urban and rural regions for each individual surveyed  Sample:  Individuals aged 16-60 years  12066 individuals and 6033 matched (husband-wife) couples  Limitation:  Single year  No fine-grained information on time quality e.g. quality of market work time (Qi and Dong 2013)

5. Gender Time-Use Pattern Table 1 Daily Time-Use across Four Activities hours/day ALL UrbanRural Men （ N=6033 ） Women （ N=6033 ） Mean Difference Men （ N=2896 ） Women （ N=2896 ） Mean Difference Men （ N=3137 ） Women （ N=3137 ） Mean Difference Housework Weekday 1.65 （ 1.86 ） 3.84 （ 2.73 ） 2.19 1.52 (1.77) 3.72 (2.81) 2.20 1.77 (1.94) 3.95 (2.64) 2.18 Weekend 2.04 （ 2.07 ） 4.21 （ 2.72 ） 2.17 1.99 (2.07) 4.23 (2.84) 2.24 2.09 (2.06) 4.20 (2.59) 2.11 Personal Care Weekday 10.14 （ 1.70 ） 10.58 （ 1.80 ） 0.44 9.89 (1.58) 10.30 (1.70) 0.41 10.37 (1.78) 10.82 (1.85) 0.45 Weekend 10.66 （ 1.93 ） 10.94 （ 1.93 ） 0.28 10.49 (1.99) 10.76 (1.96) 0.27 10.82 (1.87) 11.12 (1.89) 0.30 Leisure Weekday 3.48 （ 2.38 ） 3.18 （ 2.29 ） -0.30 4.08 (2.49) 3.72 (2.42) -0.36 2.93 (2.13) 2.68 (2.05) -0.25 Weekend 4.71 （ 3.08 ） 3.88 （ 2.61 ） -0.83 5.56 (3.20) 4.60 (2.73) -0.96 3.92 (2.74) 3.22 (2.31) -0.70 Market Work Weekday 7.08 （ 3.76 ） 4.80 （ 4.12 ） -2.28 6.99 (3.91) 4.60 (4.36) -2.39 7.17 (3.61) 4.97 (3.88) -2.20 Weekend 4.20 （ 4.31 ） 2.91 （ 3.80 ） -1.29 3.59 (4.38) 2.36 (3.81) -1.23 4.77 (4.16) 3.43 (3.72) -1.34 NOTE: Mean Difference=Women’s time minus Men’s time on each activity. In parenthesis : Standard deviation. Significances of t-test are all at t<0.01. The listing of activities is placed according to gender time-use mean difference, which equals to women’s time on a specific activity minus men’s.

6. Gender Time-Use Pattern: Highlight Findings  Generally, women spend more time on housework; men spend more time on market work  Rural women spend more time than urban women on market work and housework at the expense of leisure  Rural men contribute more to housework than urban men in absolute terms  Rural men and women work significantly more than urban residents

7. Fig.1 Gender Time-use: Household Income and Activities (Ten HLI and HNLI Groups; Four Activities) Note: Household Labor Income (HLI) and Household Non-Labor Income (HNLI). We divide the full sample into ten income groups.

8. Findings Highlights (Fig. 1) Housework: Negligible impact when income↑ Market work: ↑ men, ↑ women at weekdays when labor income↑ ↓ men, ↓ women at weekends when labor income↑ ↓ men, ↓ women when non-labor income↑ Leisure: ↑ as household income ↑, corresponding with Personal Care ↓ – Why? Paradoxical result on well-being?

9. Time-Use Gender Gap: Definition  Time-use gender gap (G) in this paper is defined as individual’s time spent on specific activity i minus spouse’s time on i G ij = time ij individual - time ij spouse i= housework /personal care /leisure /market work j=weekday/weekend

10. Model Specification To avoid multi collinearity, household non-labor income (HNLI) is taken into time-use estimated functions.  Equation1: examines the amount of time T ij =α 0 +α 1 log (HNLI k ) +α 2 I+α 3 H+θ+ε ij (1)  Equation2: examines the time-use gender gap G ij =β 0 +β 1 log (HNLI k ) +β 2 I+β 3 H+θ+μ ij (2) T ij Time in minutes spent on a specific activity i per day j G ij Gender time use gap in minutes spent on a specific activity i per day j HNLI k Household Non-Labor Income (HNLI), k= household capital and property income, household transfer payment; with log of HNLI taken in the regressions; I Vector of variables reflecting the characteristics of individuals: gender, age, age square, Hukou, education years, marital status, province dummies; H Vector of variables measuring the characteristics of the household: log of total household income (per year),Number of Family Members (NFM), NFM square, ages of the oldest and youngest family members; θ Regional dummy (urban=1, rural=0); ε Error term.

11. Income Growth and Time Allocation Personal CareLeisure WeekdayWeekendWeekdayWeekend VARIABLES Urban Men Urban Women Rural Men Rural Women Urban Men Urban Women Rural Men Rural Women Urban Men Urban Women Rural Men Rural Women Urban Men Urban Women Rural Men Rural Women Log HNLI -1.649 ** -1.778 ** -0.647-0.630 -1.924 * -2.234 ** -0.0069-0.2780.769-0.690-0.201 -2.552 *** -0.011-1.717-0.780 -3.726 *** (0.795)(0.853)(0.705)(0.743)(0.997)(1.002)(0.756)(0.772)(1.090)(1.116)(0.815)(0.817)(1.383)(1.285)(0.968)(0.925) P 0.0000 N 2,8672,8713,1113,1102,8682,8723,110 2,8692,8733,1113,1102,8692,8733,1113,110 HouseworkMarket Work WeekdayWeekendWeekdayWeekend VARIABLES Urban Men Urban Women Rural Men Rural Women Urban Men Urban Women Rural Men Rural Women Urban Men Urban Women Rural Men Rural Women Urban Men Urban Women Rural Men Rural Women Log HNLI -4.124 *** -0.712 -5.224 *** -1.115 -4.350 *** 0.625 -4.886 *** -0.107 -19.69 *** -37.17 *** -9.138 *** -22.34 *** -43.48 *** -62.14 *** -28.33 *** -36.11 *** (1.109)(1.251)(0.909)(0.949)(1.264)(1.367)(0.984)(0.999)(2.281)(3.387)(1.714)(2.120)(4.196)(5.045)(2.511)(2.530) P 0.0000 N2,8692,8733,1113,1102,8692,8733,1113,1102,8692,8733,1113,1102,8692,8733,1113,110 Table 2 Tobit Estimation: Four Activities, Gender, Regions Notes: Time in regressions is calculated in minutes. Log HNLI stands for Log Household Non-Labor. Other controlled variables: gender, age, age square, Hukou, province dummies, regional dummy, education years, marital status, total household income, household demography, work hours (only in housework, personal care and leisure time-use regressions). *significant at 10%,**significant at 5%,*** significant at 1%.

12. Findings Highlights (Table2 &3)  As HNLI ↑ Housework: ↓ Urban men less than rural men (changing attitudes with engagement in more housework) Market Work: ↓ for all, urban women particularly less than rural women Personal care: ↓urban residents (changing lifestyle?) Leisure: ↓ Only rural women (rural women do more market work and housework)

13. Income Growth and Time Allocation HouseworkPersonal CareLeisureMarket WorkSample VARIABLESWeekdayWeekendWeekdayWeekendWeekdayWeekendWeekdayWeekend Log HCPI-0.685-1.890***-0.0479-0.4421.860***1.721***1.077-5.357*** (0.588)(0.638)(0.429)(0.491)(0.540)(0.658)(1.158)(1.992)Men Log HCPI-0.328-0.8890.807*0.3991.443***1.970***0.681-8.597*** (0.615)(0.653)(0.451)(0.491)(0.541)(0.611)(1.616)(2.235)Women Log HCPI0.123-1.3380.118-0.4590.6580.6651.275-2.633 (0.733)(0.824)(0.517)(0.644)(0.708)(0.893)(1.528)(3.009)Urban Men Log HCPI-0.330-0.9501.052*0.2820.8031.425*-1.736-10.00*** (0.808)(0.875)(0.550)(0.641)(0.719)(0.821)(2.353)(3.765)Urban Women Log HCPI-2.157**-2.770***-0.271-0.5313.545***3.047***-0.430-9.808*** (0.969)(1.023)(0.729)(0.772)(0.842)(0.987)(1.790)(2.755)Rural Men Log HCPI-0.648-1.0100.5190.5562.592***2.995***4.046*-7.092** (0.969)(1.004)(0.758)(0.776)(0.832)(0.928)(2.270)(2.883)Rural Women Log HTP-1.877***-1.214**-0.792**-0.263-0.149-0.549-9.042***-20.03*** (0.536)(0.586)(0.394)(0.453)(0.497)(0.608)(1.051)(1.746)Men Log HTP-0.2880.627-1.060**-0.751*-1.154**-2.276***-17.91***-26.17*** (0.568)(0.605)(0.417)(0.455)(0.502)(0.567)(1.438)(1.915)Women Log HTP-1.381*-0.872-1.132**-0.5900.7960.216-11.02***-22.36*** (0.752)(0.848)(0.533)(0.664)(0.730)(0.920)(1.539)(2.935)Urban Men Log HTP-0.1700.897-1.368**-1.062-0.452-1.425*-17.19***-28.27*** (0.831)(0.900)(0.566)(0.660)(0.740)(0.845)(2.333)(3.633)Urban Women Log HTP-2.492***-1.761**-0.451-0.144-1.111-1.321*-5.502***-15.77*** (0.769)(0.820)(0.587)(0.623)(0.679)(0.798)(1.434)(2.151)Rural Men Log HTP-0.5670.143-0.583-0.317-1.911***-2.996***-16.90***-24.48*** (0.788)(0.821)(0.617)(0.634)(0.678)(0.760)(1.790)(2.197)Rural Women Table 3 Coefficients of Tobit Estimation: HCPI and HTP Note: Household Capital & Property Income (HCPI) and Household Transfer Payments (HTP), *significant at 10%,**significant at 5%,*** significant at 1%.

14. Findings Highlights (Table2 &3)  As HNLI ↑ Housework: ↓ Urban men less than rural men (changing attitudes with urbanization) Market Work: ↓ for all, urban women particularly less than rural women Personal care: ↓urban residents (changing lifestyle?) Leisure: ↓ Only rural women (rural women do more market work and housework)  As HCPI↑ Market Work: ↑rural women in week days (intra- household access to resources and gender power dynamics? feminization of agriculture?)

15. Income Growth and Time-Use Gender Gap Table 4 Tobit Estimation: Four Activities Notes: Log HNLI stands for Log Household Non-Labor. Other controlled variables: gender, age, age square, Hukou, province dummies, regional dummy, education years, marital status, total household income, household demography, work hours (only in housework, personal care and leisure time-use regressions). **significant at 5%,*** significant at 1%. HouseworkPersonal CareLeisureMarket Work VARIABLESWeekdayWeekendWeekdayWeekendWeekdayWeekendWeekdayWeekend Total Sample LogHNLI -3.519***-3.332***-1.467***-1.737***-3.362***-3.977***0.3010.377 (0.664)(0.684)(0.462)(0.497)(0.589)(0.679)(1.063)(0.951) P 0.0000 N 11,963 11,957 11,963 Urban Sample LogHNLI -4.488***-3.695***-1.743**-1.971**-5.451***-5.229***0.3840.699 (1.074)(1.115)(0.746)(0.806)(1.044)(1.188)(1.831)(1.612) P 0.0000 N 5,742 5,7365,7385,742 Rural Sample LogHNLI -2.752***-3.043***-1.229**-1.542**-1.927***-2.951***0.2360.163 (0.853)(0.872)(0.597)(0.637)(0.675)(0.795)(1.281)(1.169) P 0.0000 N 6,221 6,2196,221

16. G Findings Highlights (Table 4, 5 &6)  As HNLI ↑, Activities: G narrows for Housework, Personal Care, Leisure but negligible impact on Market Work Region: G in urban narrows faster than in rural (changing attitudes with urbanization)

17. HouseworkPersonal CareLeisureMarket Work VARIABLESWeekdayWeekendWeekdayWeekendWeekdayWeekendWeekdayWeekend Non-Labor Income Percentile (below 33.3%) Log HNLI -3.587 *** -4.737 *** -1.675 ** -2.372 *** -2.399 *** -4.827 *** 0.0336-0.0261 (1.085)(1.130)(0.764)(0.817)(0.918)(1.084)(1.672)(1.558) P0.0000 N 4,192 4,1904,192 Non-Labor Income Percentile (33.3%- 66.6%) Log HNLI -2.9290.133-1.235-0.0774-2.2400.599-0.0214-0.290 (5.722)(5.829)(4.090)(4.287)(4.988)(5.773)(9.343)(8.805) p0.0000 N 3,755 3,753 3,755 Non-Labor Income Percentile (above66.6%) Log HNLI -6.073-2.615-2.451-1.122 -7.346 * -3.6541.7201.148 (4.409)(4.548)(2.996)(3.297)(4.097)(4.609)(7.319)(6.060) p0.0000 N Income Growth and Time-Use Gender Gap Table 5 Tobit Estimation: Four Activities, Three Income Groups Notes: Log HNLI stands for Log Household Non-Labor. Other controlled variables: gender, age, age square, Hukou, province dummies, regional dummy, education years, marital status, total household income, household demography, work hours (only in housework, personal care and leisure time-use regressions). *significant at 10%,**significant at 5%,*** significant at 1%.

18. G Findings Highlights (Table 4, 5 &6)  As HNLI ↑, Activities: G narrows for Housework, Personal Care, Leisure but negligible impact on Market Work Region: G in urban narrows faster than in rural (changing attitudes with urbanization) Income Groups: – Low HNLI Group: G narrows for Housework, Personal Care, Leisure but insensitive for market work – High HNLI Group: G narrows dramatically for Leisure on weekdays

19. HouseworkPersonal CareLeisureMarket Work VARIABLESWeekdayWeekendWeekdayWeekendWeekdayWeekendWeekdayWeekend Log HCPI0.164-0.5060.0781-0.2220.0530-0.637-0.0637-0.0259 (0.541)(0.552)(0.377)(0.401)(0.480)(0.548)(0.876)(0.784) P 0.0000 N 11963 11957 11963 Log HTP-2.153***-1.725***-0.921***-0.913**-2.039***-2.018***0.2810.304 (0.498)(0.510)(0.347)(0.370)(0.443)(0.506)(0.802)(0.717) P 0.0000 N 11963 11957 11963 Note: Household Capital & Property Income (HCPI) and Household Transfer Payments (HTP), **significant at 5%,*** significant at 1%. Income Growth and Time-Use Gender Gap Table 6 Tobit Estimation: HCPI and HTP (Total Sample)

20. G Findings Highlights (Table 4, 5 &6)  As HNLI ↑, Activities: G narrows for Housework, Personal Care, Leisure but negligible impact on Market Work Region: G in urban narrows faster than in rural (changing attitudes with urbanization) Income Groups: – Low HNLI Group: G narrows for H, Personal C, Leisure but insensitive for market work – High HNLI Group: G narrows dramatically for Leisure on weekdays  As HCPI ↑,G insensitive; As HTP ↑, G narrows significantly G more sensitive to HTP than HCPI

21. Discussions  Traditional social norms of gender work distribution still prevail  Income growth has a significant positive effect on reducing the time-use gender gap in housework, personal care and leisure, and especially for  HTP  Urban regions  Urbanization and economic development lead to change in traditional attitudes to gender roles

22. Policy Implications  To reduce gender time-use inequality  Urbanization measures across regions  Enhance state welfare provision  Improve women’s access to HCPI

23. Concluding Comments  Findings raise more questions than answers and explanations are speculative  More Mixed Method Research – more qualitative empirical research needed to support quantitative findings e.g. MacPhail and Dong 2007