Publications

Abstract This study provides a life-course analysis of the relationship between self-employment, health, and health care use among individuals aged 50 and older in Europe. Using data from the Survey of Health, Ageing, and Retirement in Europe (SHARE), we apply first-difference and dynamic panel data models that go beyond standard approaches in mitigating endogeneity concerns. Our findings show that the self-employed enjoy better health at younger ages, consistent with a selection effect. In addition, they experience a steeper decline in physical health over time. We also document two distinct phases of health care use: during working life, the self-employed are more likely to be hospitalised, suggesting delayed care until acute needs arise; after retirement, the number of medical visits increases, consistent with a lower opportunity cost of care.
Keywords Self-employment, SHARE, Health care use, Health
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Abstract Background: Breast cancer and its treatment may contribute to an increased risk of unemployment, influenced by both disease-related factors and socioeconomic determinant. Few longitudinal studies have examined employment outcomes among women diagnosed with cancer. This retrospective study investigated long-term employment among breast cancer survivors (BCS) and assessed disease specific and socioeconomic factors associated with employment. Design and methods: Registry-based data included working age BCS in Norway 2004–2008 alive at 6 years follow-up ( N = 3560). The employment status on each BCS was compared to two matched non-cancer controls ( N = 7081) by means of logistic regression analyses with marginal effects. Separate analyses by employment status at the time of diagnosis were conducted. Results: Among BCS employed at diagnosis, 73.7%, 71.5% and 71.8% of BCS were in employment at 1, 2 and 6 years after diagnosis, respectively. BCS employed at diagnosis had significantly lower probability of being employed at all follow-up time points, compared to controls. BCS outside employment at the time of diagnosis experienced lower probability of employment compared to controls. BCS with secondary or higher education had higher probability of employment compared to BCS with basic education, and BCS living in families with children were more likely to enter employment during follow-up compared to BCS without children. Conclusions: BCS employed at diagnosis had a subsequent risk of unemployment, and BCS not employed at diagnosis had lower probability of entering employment. Additional risk factors are high age, low education, and being single without children. Significance for public health: The risk of unemployment after a breast cancer diagnosis was increased. Job loss is costly economically and socially, both for individuals and for society. Early focus on employment particularly among employees with low education and with little family support may alleviate this problem.
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Abstract Drift and volatility are two mainsprings of asset price dynamics. While volatilities have been studied extensively in the literature, drifts are commonly believed to be impossible to estimate and largely ignored in the literature. This paper shows how to detect drift using realized autocovariance implemented on high-frequency data. We use a theoretical treatment in which the classical model for the efficient price, an Itō semimartingale possibly contaminated by microstructure noise, is enriched with drift and volatility explosions. Our theory advocates a novel decomposition for realized variance into a drift and a volatility component, which leads to significant improvements in volatility forecasting.
Keywords Volatility Forecasting, Serial Covariance, High-frequency Data, Drift
Publication HAL Google Scholar