1. HOME-BASED WORK, GENDER AND TIME USE Jouko NATTI 1, Timo ANTTILA 2, Tomi OINAS 2 & Satu OJALA 1 1 University of Tampere, School of Social Sciences and Humanities, Finland 2 University of Jyväskylä, Department of Social Sciences and Philosophy, Finland Funded by Academy of Finland

2. INTRODUCTION Focus on paid work at home –Increasing phenomenon, indicates changing time-space relations of paid work –Mixed findings in earlier studies Extent –Different estimates (survey / diary data) –Duration: part-time / full-time –Timing: evening, weekend (Breedveld 2003)

3. Predictors Individual (family) factors –Older age (Callister & Dixon) –Family situation (spouse, children) (Golden 2008; Wight & Raley 2009) Home infrastructure –Separate space at home (Tietze & Musson 2002; Kossek et al. 2006) Work characteristics –High socioeconomic status, job autonomy

4. Time use consequences Working time –Longer working hours (Callister & Dixon 2001) –Commuting: no effect / shorter (Michelson & Crouse 2002) Household work: minor effects –Men: less time to childcare (Wight & Raley 2009) Leisure: minor effects –Less social relations (Michelson 2002)

5. AIMS (1) The extent, duration and timing of paid work at home among women and men. (2) The predictors of home-based work. –Individual and family characteristics (age, children, and partner). –Homes infrastructure (internet connection at home, number of rooms at home), and –Work characteristics (socio-economic status, industry, and working time autonomy), (3) The relationship of working at home to time use –Assumptions: HBW is linked to the lengthening of working hours, reduced commuting time. –In addition, home-based work potentially increases time for household work and child care, increases presence at home and time with family and decreases time for social relations.

6. DATA AND METHODS Data –Use of Time -study (2009-2010), collected by Statistics Finland. –Time use diaries (7.480 days) –Focus on15-64 year old employees (n=3.382) Methods –Descriptive: cross tabulation –Multivariate: logistic regression (predictors) and covariate analysis (time use)

7. 1. EXTENT OF HOMEWORKING Interview data –Only few (1% of men and 2% of women) said that they work at home only (full-time) –Working occasionally or partially at home was more common (42% of men and 32% of women). Diary data –Operationalization: combination of main activity (paid work) and location (home) –7 % of men and 6 % of women worked (10+ min.) at home during average diary day Results vary depending on the type of data. –Focus on diary-based working at home.

8. Duration and timing Duration (home-based workers) –Mean 122 min. (men), 139 (women); –Distribution: 3+ hours 21 % (men), 24% women) (Fig.) –Gender differences: longer hours among women Timing –Weekly timing Weekdays 7-9 % (Monday 9-12 %; Friday 4 %) Weekends 6 % (Saturday 3-5 %, Sunday 6-8 %) –Season: Spring 8-9 %; Summer 3-6 % –Type of day: 9-10 % on working days, 5-6 % on holidays, 3-4 % while being sick –Minor gender differences

9. HBW: distribution of duration

10. Prevalence of paid work at home among men and women during the day (%, diary data, employees)

11. 2. PREDICTORS OF HBW Individual-level factors Age was classified into four groups (25-34, 35-44, 45-54, and 55- 64 years old). –Living with a partner or without a partner was indicated by Family status. –Children were classified into two groups: no children at home, or at least one child less than 18 years old at home. Home infrastructure factors (Household interview data) Internet connection (no, yes) Number of rooms at home (1-2, 3-4, 5 or more) Work-related factors –Socio-economic status: manual workers, lower-level non- manuals, upper-level non-manuals –Industry (NACE classification): 8 sectors –Working time autonomy was measured by asking respondents if they can influence the starting and finishing times of their work by at least 30 minutes (no, yes).

13. 3. HBW AND TIME USE In examining overall time use we apply Robinson and Godbeys (1997) classification of the main categories of primary activities. –paid work, –committed time for household maintenance, –personal time devoted for self –free time activities. Covariate analysis: estimated time use by comparison groups –Covariates: day type, background factors (age, partner, children, socioeconomic status)

14. MenWomen Paid work at home NOYESSig.NOYESSig. Contracted time 298345 *** 252285 *** paid work 271319 *** 228273 *** commuting 2726 2412 *** Committed time 159139 208241 household work 4953 96120 Construction, repairs and other 4842 3643 child care 188 * 2540 * shopping and household travel 4336 5138 * Personal time 615610 646608 *** sleep 493496 505491 meals 7772 8166 *** groom 4541 5951 * Education (adult) 413 1824 Free Time 354326 311277 * organizations 57 42 sports and exercise 4028 3633 culture and entertainment 57 64 reading 2736 3740 radio 31 22 television 128113 9395 socializing with family 63 78 socializing with friends 3934 4728 * hobbies 5345 36 other free time 1518 1413 free time travel 3332 2717

15. DISCUSSION The extent of HBW is linked to the type of data –Interview data: 34-43 %, diary data 6-7 % Changes over time: some increase in interview data, no change in diary data (1999 > 2009) –Duration: Still supplementary (average: 2 hours per day) –Daily timing: morning, afternoon, evening (men) –Weekdays: high in Mondays, low in Fridays –Weekend days: high in Sundays, low in Saturdays

16. Predictors of HBW The role of individual and family (spouse, children) characteristics minor Best predictors: –work characteristics: high socioeconomic status (women) and industry (men) –and home infrastructure (space)

17. Time use consequences Working time and commuting: stretching working hours –Longer working hours both among men and women, less commuting time among women Household activities: minor effects –Women: home-based workers spent less time on shopping and more time on child care (men less) Personal time: less time among women –Women: home-based workers spent less time to personal needs, especially to meals. Leisure: minor effects –Women: home-based workers spent less time to socializing with friends,

18. Limitations and strengths Limitations > further studies –Diary data (minutes): Higher limit for HBW hours (now 10 min) –Focus on employees Self-employed workers and freelancers missing –Finnish data > comparative perspective Strengths –Representative data –Combination of interview and diary data

19. Thank you! jouko.natti@uta.fi

20. Table 1. The extent (%) of paid work at home by gender in the interview data (employees only) (in parentheses 1999-2000 figures) MenWomen Paid work at home - Work only at home1 (1)2 (3) - Work sometimes or partly at home42 (35)32 (32) - Does not work at all at home57 (64)66 (65) Total100 N15001882 Motives (only home-based workers) - Overtime46 (42)39 (38) - Agreed (telework)41 (44)45 (41) - Both14 (10)13 (9) - Don't know0 (3)0 (4) Total100 N107121

21. Table 2. The extent (%) of paid work at home by gender in the diary data (employed persons) Proportion of those who have done paid work at home during the diary days (%) MenWomen Weekday 97 - Monday 12 9 - Tuesday 96 - Wednesday 87 - Thursday 87 - Friday 44 Weekend 66 - Saturday 53 - Sunday 68 Season of the year - Winter (December-February) 78 - Spring (March-May) 98 - Summer (June-August) 63 - Autumn (September-November) 77 Type of the day - Workday 109 - Sick 34 - Free day, weekend 11 - Holiday 56 - Other 95

22. Table 3. The duration (minutes) of paid work at home by gender in the diary data MenWomen Duration of paid work at home (minutes) - Those who have worked at home 122140 Distribution of paid work hours at home (%) - 0 9394 - 10-50 min 32 - 1-2 t 32 - 3+ t 12 Only those working at home Distribution of paid work hours at home (%) - 10-50 min 3839 - 1-2 t 4137 - 3+ t 2124