Great (Retirement) Expectations: A Review of Retirement Income Policy and Changes to Expected and Preferred Retirement Age of Australian Workers

BackgroundIn workforce planning for oral and maxillofacial surgeons in the Netherlands, it is important to plan timely, as these dental specialists are required to earn both medical and dental degrees. An important factor to take into account in workforce planning is the outflow of the profession through retirement. In the workforce planning in the Netherlands, it was assumed that retirement plans are a predictor for the actual moment of retirement. The purpose of this study was to investigate this assumption.MethodsA standardised survey to investigate the work activity and retirement plans of oral and maxillofacial surgeons was conducted seven times between 2003 and 2016. With some minor variations, in every edition, all oral and maxillofacial surgeons aged 55 years and older who did not indicate to be retired in an earlier edition were invited to participate. The data of all seven editions was analysed to investigate what factors influence the actual retirement age. For the analyses of the data, ANOVA and linear regression were employed.ResultsThe response rate was at least 80% in all editions. For all editions combined, 185 surgeons were invited one or more times, of whom 170 responded at least once. Between 2003 and 2016, the mean preferred retirement age increased from 63.7 to 66.7. Two thirds of the respondents who participated in more than one edition had revised their preferred retirement age upwards. Regarding the difference between preferred and actual retirement age, 45% of the oral and maxillofacial surgeons retired at a higher age than originally preferred and another 14% was still working at the age the originally preferred to retire. Linear regression shows that preferred retirement age is associated with sex and the number of working hours and that actual retirement age is associated with preferred retirement age, earlier preference to decrease working hours and working in non-academic hospitals.ConclusionAltogether, it seems that in this group the preferred retirement age has some predictive value, but the oral and maxillofacial surgeons tend to retire at a higher age than they originally preferred to.

Structure and Distribution of Household Wealth in Australia: Cohort Differences and Retirement Issues

This paper investigates whether migrant workers are more or less satisfied with their job security than native workers, and whether these differences vary by gender using the 2007 Household, Income and Labour Dynamics in Australia (HILDA) survey. The analysis of migrants’ satisfaction with job security is particularly important in an Australian labour market environment given that it is increasingly dominated by non-permanent jobs and migrant workers. The descriptive statistics indicate a significant difference in satisfaction with job security between migrant and native workers. Linear and ordered probit regressions are invoked to examine whether or not being a migrant has a negative impact on job security satisfaction levels after controlling for key socio-demographic, human capital and labour market characteristics and these regressions are conducted separately for male and female workers. The role of expectations in affecting one’s satisfaction with job security is also explored. The model findings indicate that being a female migrant worker has a significant negative impact of job security satisfaction but the impact is insignificant for males. However, those who have spent the majority of their lifetime in Australia have assimilated more into the Australian labour market and are more comfortable with their job security.

Working hours mismatch, job strain and mental health among mature age workers in Australia

BackgroundThe SF-36 is one of the most widely used self-completion measures of health status. The inclusion of the SF-36 in the first Australian national household panel survey, the Household, Income and Labour Dynamics in Australia (HILDA) Survey, provides an opportunity to investigate health inequalities. In this analysis we establish the psychometric properties and criterion validity of the SF-36 HILDA Survey data and examine scale profiles across a range of measures of socio-economic circumstance.MethodsData from 13,055 respondents who completed the first wave of the HILDA Survey were analysed to determine the psychometric properties of the SF-36 and the relationship of the SF-36 scales to other measures of health, disability, social functioning and demographic characteristics.ResultsResults of principle components analysis were similar to previous Australian and international reports. Survey scales demonstrated convergent and divergent validity, and different markers of social status demonstrated unique patterns of outcomes across the scales.ConclusionResults demonstrated the validity of the SF-36 data collected during the first wave of the HILDA Survey and support its use in research examining health inequalities and population health characteristics in Australia.

Australian Economic ReviewVolume 44, Issue 3 p. 308-320 Policy Forum: Funding of Public and Private Schools in Australia What Determines Private School Choice? A Comparison between the United Kingdom and Australia Lorraine Dearden, Lorraine Dearden Dearden: Institute of Education, University of London and Institute for Fiscal Studies; Ryan: Melbourne Institute of Applied Economic and Social Research, The University of Melbourne; Sibieta: Institute for Fiscal Studies.Search for more papers by this authorChris Ryan, Chris Ryan Dearden: Institute of Education, University of London and Institute for Fiscal Studies; Ryan: Melbourne Institute of Applied Economic and Social Research, The University of Melbourne; Sibieta: Institute for Fiscal Studies.Search for more papers by this authorLuke Sibieta, Luke Sibieta Dearden: Institute of Education, University of London and Institute for Fiscal Studies; Ryan: Melbourne Institute of Applied Economic and Social Research, The University of Melbourne; Sibieta: Institute for Fiscal Studies. The authors would like to thank the Australian Research Council (ARC) and Economic and Social Research Council (ESRC) for funding this research under their ARC–ESRC collaborative bid framework (Ref: ARC – LX0883152; ESRC – RES-000-22-2524). The authors would also like to thank Susan Dynarski and other conference participants who attended the Institute for Fiscal Studies event on ‘Determinants of Private Schooling’ on 17 June 2010 for constructive comments and suggestions. This article uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The HILDA Project was initiated and is funded by the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA) and is managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The findings and views reported in this article, however, are those of the authors and should not be attributed to either FaHCSIA or the Melbourne Institute. This article also uses the British Household Panel Survey (BHPS). Data from the BHPS were supplied by the UK Data Archive. Neither the original collectors of the data nor the archive bear any responsibility for the analysis or interpretations presented here.Search for more papers by this author Lorraine Dearden, Lorraine Dearden Dearden: Institute of Education, University of London and Institute for Fiscal Studies; Ryan: Melbourne Institute of Applied Economic and Social Research, The University of Melbourne; Sibieta: Institute for Fiscal Studies.Search for more papers by this authorChris Ryan, Chris Ryan Dearden: Institute of Education, University of London and Institute for Fiscal Studies; Ryan: Melbourne Institute of Applied Economic and Social Research, The University of Melbourne; Sibieta: Institute for Fiscal Studies.Search for more papers by this authorLuke Sibieta, Luke Sibieta Dearden: Institute of Education, University of London and Institute for Fiscal Studies; Ryan: Melbourne Institute of Applied Economic and Social Research, The University of Melbourne; Sibieta: Institute for Fiscal Studies. The authors would like to thank the Australian Research Council (ARC) and Economic and Social Research Council (ESRC) for funding this research under their ARC–ESRC collaborative bid framework (Ref: ARC – LX0883152; ESRC – RES-000-22-2524). The authors would also like to thank Susan Dynarski and other conference participants who attended the Institute for Fiscal Studies event on ‘Determinants of Private Schooling’ on 17 June 2010 for constructive comments and suggestions. This article uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The HILDA Project was initiated and is funded by the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA) and is managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The findings and views reported in this article, however, are those of the authors and should not be attributed to either FaHCSIA or the Melbourne Institute. This article also uses the British Household Panel Survey (BHPS). Data from the BHPS were supplied by the UK Data Archive. Neither the original collectors of the data nor the archive bear any responsibility for the analysis or interpretations presented here.Search for more papers by this author First published: 01 September 2011 https://doi.org/10.1111/j.1467-8462.2011.00650.xCitations: 10 Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Volume44, Issue3September 2011Pages 308-320 RelatedInformation

ObjectiveThis study examined the association of nuptial/relationship factors, financial difficulties, and socio-demographic factors with the mental health status of Australian adults.DesignCross-sectional quantitative study design.Settings, participants, and interventionsUsing data from the Household, Income and Labour Dynamics in Australia (HILDA) survey wave 19, 6846 adults were included in the analysis. Mental health was measured using the mental component summary (MCS) subscale of the Short-Form Health Survey SF-36. Hierarchical multiple linear regressions were used to examine the predictors of mental health status.ResultsOverall, 7.1% of the participants reported poor mental health status. Individual financial difficulty factors explained 3.2% (p<0.001) of the variance in mental health scores. In addition, financial difficulties were negatively associated with mental health status. Nuptiality and relationship factors accounted for 9.8% (p<0.001) of the variance in mental health status.ConclusionThe study suggests negative marital or relationship perceptions and financial difficulties are significant factors accounting for poor mental health. This finding suggests the need for more policy attention toward the social determinants of poor mental health especially nuptiality or relationship perceptions which have received less policy and research attention in Australia.

In cross-sectional gambling studies, friends, family, and others close to those experiencing gambling problems (concerned significant others ‘CSOs’) tend to report detriments to their quality of life. To date, however, there have been no large, population-based longitudinal studies examining the health and wellbeing of CSOs. We analyse longitudinal data from the Household, Income and Labour Dynamics in Australia (HILDA) survey to examine the 18-year trajectories of general, social, health and financial wellbeing of household CSOs (n = 477) and compare these to those without a gambling problem in the household (n = 13,661). CSOs reported significantly worse long-term wellbeing than non-CSOs in their satisfaction with life, number of life stressors, and social, health and financial wellbeing. However, both social and financial wellbeing showed a temporal effect, declining significantly for CSOs at times closer to the exposure to the gambling problem. This finding suggests a causal link between living in a household with a person with a gambling problem and decreased CSO social and financial wellbeing. Policy responses, such as additional social and financial support, could be considered to assist CSOs impacted by another person’s gambling problem.

This paper provides a brief summary of the Household, Income and Labour Dynamics in Australia (HILDA) Survey, a nationally representative household panel survey. It describes the survey’s key design features, provides an overview of its content, and reports on response rates and sample sizes. It also highlights a few examples of research utilising the data, discusses two challenges currently facing the study, and provides details on how to access the data.

This study examined the association of nuptial/relationship factors, financial difficulties, and socio-demographic factors with the mental health status of Australian adults. Cross-sectional quantitative study design. Using data from the Household, Income and Labour Dynamics in Australia (HILDA) survey wave 19, 6846 adults were included in the analysis. Mental health was measured using the mental component summary (MCS) subscale of the Short-Form Health Survey SF-36. Hierarchical multiple linear regressions were used to examine the predictors of mental health status. Overall, 7.1% of the participants reported poor mental health status. Individual financial difficulty factors explained 3.2% (p<0.001) of the variance in mental health scores. In addition, financial difficulties were negatively associated with mental health status. Nuptiality and relationship factors accounted for 9.8% (p<0.001) of the variance in mental health status. The study suggests negative marital or relationship perceptions and financial difficulties are significant factors accounting for poor mental health. This finding suggests the need for more policy attention toward the social determinants of poor mental health especially nuptiality or relationship perceptions which have received less policy and research attention in Australia.

This study investigates the impact of obesity, long-term health problems and their interaction on three specific aspects of job satisfaction among Australian adult workers. Exploiting longitudinal data from the Household, Income and Labour Dynamics in Australia (HILDA) survey for the years 2006-2017, this study estimates overall job satisfaction, pay satisfaction and job security satisfaction using a common set of explanatory variables. Results from both random effects generalized least squares estimation and random effects ordered probit model confirm that obesity has a significant negative impact on workers' pay and job security satisfaction. The results indicate that overweight workers are dissatisfied about their job security compared to normal weight peers. The study results reveal that long-term health problems significantly reduce all aspects of job satisfaction of the workers. However, the results indicate that the interaction of obesity and long-term health problems positively influences workers' overall job satisfaction. Overall, the study findings are in line with the hypothesis that obese workers with long-term health problems have low expectations about their job.

This study explores whether compensating wage differentials (CWDs) are still found for Australian workers using data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey, and risk data from Safe Work Australia. Our study finds evidence of CWDs for the risk of workplace fatalities that are smaller in magnitude compared to the estimates previously reported in the 1990s for Australia. We find limited evidence of CWDs for the risk of workplace non‐fatal injuries. Using panel data and a risk variable that varies by both the worker’s industry and occupation of employment, we find that Australian workers who face the mean level of fatality risk receive a CWD of between 0.13% and 0.44% for a unit increase in risk, depending on the model specification. These estimates correspond to a value of statistical life of $9.7 million and $34.9 million.

BackgroundExcess weight can increase absenteeism of workers and can have a negative influence on their productivity. Current evidence on this association is mostly based on cross-sectional data and there is little evidence concerning the longitudinal relationship between obesity, and disability with workplace absenteeism. Further, gender differences in this association have often ignored in the existing literature.ObjectivesThis study aims to examine gender differences in the longitudinal association between obesity, and disability with absenteeism in the workplace.MethodsData from thirteen waves (2006 to 2018) of the Household, Income and Labour Dynamics in Australia (HILDA) survey were pooled, resulting in 117,769 observations for 19,851 adult employees. The Zero-Inflated Negative Binomial (ZINB) regression model was deployed to investigate the links between obesity, and disability with workplace absenteeism for the total sample and stratified by gender.ResultsThe findings showed that overweight (Incidence Rate Ratio [IRR]: 1.23, 95% confidence interval [CI]: 1.02–1.47), obesity (IRR: 1.35, 95% CI: 1.12–1.64) and disability (IRR: 2.83, 95% CI: 2.36–3.38) were associated with prolonged workplace absenteeism irrespective of gender. This study found that the multiplicative interaction between weight status and gender is significantly associated with absenteeism. The results reveal that the rate of absenteeism was 2.79 times (IRR: 2.79, 95% CI: 1.96–3.97) and 1.73 times (IRR: 1.73, 95% CI: 1.20–2.48) higher among overweight and obese women than male counterparts, respectively. Moreover, this study found that the weight status of male workers is not associated with absenteeism. However, disability (IRR: 3.14, 95% CI: 2.43–4.05) is positively associated with longer days of absence among male workers. Finally, the study results showed that the rate of absenteeism is 1.82 (IRR: 1.82, 95% CI: 1.36–2.44), 1.61 (IRR: 1.61, 95% CI: 1.21–2.13), and 2.63 (IRR: 2.63, 95% CI: 1.99–3.48) times higher among overweight, obese, and female workers with a disability, respectively, compared with their lower weight counterparts.ConclusionsWorkplace absenteeism is significantly associated with overweight and obesity among Australian workers. An active workplace health promotion program is very important for weight management of overweight and obese workers and thus to reduce workplace absenteeism. For example, employers may provide incentives for maintaining recommended body weights, encourage exercise, and promote healthy diets amongst their workers.

Excess weight can increase absenteeism of workers and can have a negative influence on their productivity. Current evidence on this association is mostly based on cross-sectional data and there is little evidence concerning the longitudinal relationship between obesity, and disability with workplace absenteeism. Further, gender differences in this association have often ignored in the existing literature. This study aims to examine gender differences in the longitudinal association between obesity, and disability with absenteeism in the workplace. Data from thirteen waves (2006 to 2018) of the Household, Income and Labour Dynamics in Australia (HILDA) survey were pooled, resulting in 117,769 observations for 19,851 adult employees. The Zero-Inflated Negative Binomial (ZINB) regression model was deployed to investigate the links between obesity, and disability with workplace absenteeism for the total sample and stratified by gender. The findings showed that overweight (Incidence Rate Ratio [IRR]: 1.23, 95% confidence interval [CI]: 1.02-1.47), obesity (IRR: 1.35, 95% CI: 1.12-1.64) and disability (IRR: 2.83, 95% CI: 2.36-3.38) were associated with prolonged workplace absenteeism irrespective of gender. This study found that the multiplicative interaction between weight status and gender is significantly associated with absenteeism. The results reveal that the rate of absenteeism was 2.79 times (IRR: 2.79, 95% CI: 1.96-3.97) and 1.73 times (IRR: 1.73, 95% CI: 1.20-2.48) higher among overweight and obese women than male counterparts, respectively. Moreover, this study found that the weight status of male workers is not associated with absenteeism. However, disability (IRR: 3.14, 95% CI: 2.43-4.05) is positively associated with longer days of absence among male workers. Finally, the study results showed that the rate of absenteeism is 1.82 (IRR: 1.82, 95% CI: 1.36-2.44), 1.61 (IRR: 1.61, 95% CI: 1.21-2.13), and 2.63 (IRR: 2.63, 95% CI: 1.99-3.48) times higher among overweight, obese, and female workers with a disability, respectively, compared with their lower weight counterparts. Workplace absenteeism is significantly associated with overweight and obesity among Australian workers. An active workplace health promotion program is very important for weight management of overweight and obese workers and thus to reduce workplace absenteeism. For example, employers may provide incentives for maintaining recommended body weights, encourage exercise, and promote healthy diets amongst their workers.

ObjectiveYoung adults with disabilities are less likely to be employed and more likely to have poor mental health than peers without disabilities. Growing evidence shows that social determinants of health...