Department of Employment and Workplace Relations

Men's limited movement into female occupations has been identified as a key barrier to future declines in occupational sex segregation and achieving greater gender equality. So why are men so reticent to enter jobs normatively regarded as female? Drawing from qualitative interviews with multiple stakeholders in four female‐dominated occupations in Australia, this article documents the processes that influence men's employment in gender‐atypical jobs. Gender essentialism is central to many processes that generate and/or stall changes in men's representation in female‐dominated occupations. While gender essentialism's role in producing and reproducing occupation sex segregation is well known, its role in reducing occupational sex segregation is a critical process which has previously received limited attention. The article details gender essentialism's integrative function.

Using firm‐level data, we analyse the patterns, innovation characteristics and determinants of turnover high‐growth firms (HGFs) in Australia. We find most HGFs do not stay in the high‐growth phase for long, and following the Global Financial Crisis the proportion of HGFs has declined. For HGFs, the results suggest that innovation in goods and services has a much greater impact on turnover growth than for the average firm. For all firms, innovations in goods and services and marketing, and business focus on innovation contribute to turnover growth. Finally, HGFs generate greater returns on investment in research and development than slower growing firms.

Abstract Determinants of the decision to stay at school or to enter the youth labour market are analysed. It is shown that the commonly used participation rates for both youth labour market and secondary school analysis are flawed. Consequently secondary school retention rates are estimated as aggregate measures of that first decision. Australian data for 1968 to 1983 are utilized. A wide variety of factors appear to affect retention rates including inter-state institutional differences, youth unemployment rates, demographic cohort structures, credentialism at grade 10 and the availability of apprenticeships, but wages only to a much lesser degree. Nevertheless, strong unexplained time trends appear, as do very strong differences between males and females and different years of age. Major implications of the complex relationships found are that simple marginal changes in policy variables, such as scholarship levels, are unlikely to be effective.

Abstract Detailed labour market and economic data are often released infrequently and with considerable time lags between collection and release, making it difficult for policy‐makers to accurately assess current conditions. Nowcasting is an emerging technique in the field of economics that seeks to address this gap by ‘predicting the present’. While nowcasting has primarily been used to derive timely estimates of economy‐wide indicators such as GDP and unemployment, this article extends this literature to show how big data and machine‐learning techniques can be utilised to produce nowcasting estimates at detailed disaggregated levels. A range of traditional and real‐time data sources were used to produce, for the first time, a useful and timely indicator—or nowcast—of employment by region and occupation. The resulting Nowcast of Employment by Region and Occupation (NERO) will complement existing sources of labour market information and improve Australia's capacity to understand labour market trends in a more timely and detailed manner.

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