Examining time use patterns in South Africa, 2000–2010

ABSTRACT

This study comprehensively examines time use patterns in South Africa by Systems of National Accounts (SNA) classification, with the aid of the 2000 and 2010 Time Use Survey (TUS) data. The empirical findings indicated that both mean SNA and non-SNA production time increased at the expense of mean non-productive time, with the former increase being attributed to work in establishments and household maintenance activities, respectively. Mean work in establishments time was particularly higher for middle-aged white male individuals who were highly educated, employed, lived in Western Cape and Gauteng, and resided in small-sized households. On the contrary, mean unpaid work time (especially household maintenance) was higher for unemployed female Africans. Furthermore, individuals in the weighted sample spent over 50% of their time on personal care whereas 20% time was spent on SNA and non-SNA production (paid and unpaid work) altogether. Lastly, all individuals spent non-zero time on personal care activities.

KEYWORDS:

• Time use
• time use survey
• systems of national accounts

JEL CLASSIFICATION:

• J22
• O10

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 For a more detailed explanation it, refer to Vyas & Kumaranayake (2006) and Van der Berg et al. (2003).

2 Whilst it may be possible to adopt this econometric model, we decided not to go for this approach, as a separate study is needed to examine the impact of the use of different functional forms (e.g. log of time spent on each activity) and econometric models on the regression parameters. The choice of a good instrumental variable for Heckman model requires some deep thought and may not even exist. As a result, it is not explored further in this study.

3 The authors re-ran the OLS and Tobit regressions by excluding the labour market status dummy variables, and found that the race and education dummy variables eventually had the correct signs as expected, conforming to the descriptive statistics findings.

4 Table A4 shows the distinction between paid work and unpaid work activities.