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    2008年--外文翻译--带薪年假和工作时长(节选)

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    2008年--外文翻译--带薪年假和工作时长(节选)

    1、2100 单词, 1.1 万英文字符, 2860 汉字 出处: Published version: Mark Wooden and Diana Warren, Paid Annual Leave and Working Hours: Evidence from the HILDA Survey, Journal of Industrial Relations 50(4), September 2008, pp. 664-670. http:/dx.doi.org/10.1177/0022185608094118 Paid Annual Leave and Working Hours: Evi

    2、dence from the HILDA Survey Mark Wooden and Diana Warren University of Melbourne, Australia M Wooden, D Warren Abstract Using data from wave 5 of the Household, Income and Labour Dynamics in Australia (HILDA) Survey, this study examines: (i) the extent to which Australian employees use their annual

    3、leave entitlements; and (ii) the association between annual leave taking and weekly hours of work. After restricting attention to employees likely to have entitlement to at least four weeks of paid annual leave, it is found that the mean number of days of leave taken per year is around 16 and that t

    4、he majority of employees (63%) take less than 20. The incidence of annual leave taking is found to vary positively with the number of usual weekly hours of work, but the size of this effect is small and weak. Keywords: Annual leave; Australia; HILDA Survey; Working hours Introduction A focal point i

    5、n the recent debate about work-life balance has been the long hours many Australians work. Most of this debate has focused on the number of hours worked in a usual week, and only occasionally (e.g., Dennis, 2004) is any recognition given to the possibility that increases in the length of the working

    6、 year arising from not fully utilising annual leave entitlements might also be important. This paper reports on the extent of usage of paid annual leave in Australia using new data collected in wave 5 of the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The paper also examines the extent to which annual leave use is correlated with usual weekly working hours. A priori the direction of association between these two variables is difficult to predict. Regularly


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