Suchergebnisse

Using a rich micro dataset drawn from administrative archives, we explore whether Social Security Wealth (SSW) is an important factor affecting the decision to become selfemployed. We focus on the two main categories of self-employed professions covered by the Italian public pension system: craftsmen and shopkeepers. We use the large exogenous variation in individual expected SSW that occurred as a result of the policy reform process undertaken in Italy during the 1990s to identify the effect of this variable and we study how the probability of being self-employed or employed depends, amongst other things, on the difference in the expected SSW that accrues under the two alternative employment scenarios. Our key finding is that a higher difference in expected SSW from self-employment compared with employment has a positive effect on the probability of being self-employed and on the probability of switching to self-employment, whereas it has a negative effect on the probability of switching from self-employment to employment.

"The long-term increase in longevity, coupled with the progressive compression of morbidity experienced in Europe in the last decades, improved the well-being of many older individuals. However, a failure to adjust the retirement age has exposed poor households to financial distress (Angelini et al. 2009). Staying longer in the labour force may be a solution to preserve an adequate level of resources and limit the risk of economic deprivation, it is also an effective mean to maintain social ties and foster an active life. However, working longer requires investment in human capital over the life cycle (Mahyew & Rjkers 2004), as acquired skills become obsolete as time goes by. The rapid technological progress prevailing in many sectors makes training the older workforce the only effective policy to prevent skills obsolescence (Bishop 1997, Belloni & Villosio 2014).; The aim of this chapter is to investigate whether participation in training helps keeping older workers (aged 50 - 65) in employment. In particular, we use Wave 4 and Wave 5 of SHARE to test the effect of training participation in 2010 (Wave 4) on changes in labour market status between 2010 and 2012 (Wave 5), controlling for a rich set of observable individual characteristics. Information on self-reported current economic status allows us to distinguish between six labour force states: employed or self-employed, unemployed, permanently sick or disabled, retired, homemaker and 'other'. To measure training participation we exploit a question in Wave 4 (part of the module 'Activities') which asks respondents whether they attended any educational or training course in the last twelve months.; The main result of this chapter is that individuals who took part in training activities in the year prior to the 2010 (2009 for Estonia) interview are significantly less likely to leave the labour market. Training older workers may therefore prevent them from being exposed to the risk of poverty and social exclusion. This chapter is organised as follows: the next section reports the descriptive evidence regarding labour market status in the last two waves of SHARE and participation in training activities. The following section presents the results of a multivariate analysis, which aims at capturing the effect of training on the probability of exiting the labour market. The last section concludes the chapter, providing some policy implications of our analysis." (Author's abstract, IAB-Doku).

"The long-term increase in longevity, coupled with the progressive compression of morbidity experienced in Europe in the last decades, improved the well-being of many older individuals. However, a failure to adjust the retirement age has exposed poor households to financial distress (Angelini et al. 2009). Staying longer in the labour force may be a solution to preserve an adequate level of resources and limit the risk of economic deprivation, it is also an effective mean to maintain social ties and foster an active life. However, working longer requires investment in human capital over the life cycle (Mahyew & Rjkers 2004), as acquired skills become obsolete as time goes by. The rapid technological progress prevailing in many sectors makes training the older workforce the only effective policy to prevent skills obsolescence (Bishop 1997, Belloni & Villosio 2014).; The aim of this chapter is to investigate whether participation in training helps keeping older workers (aged 50 - 65) in employment. In particular, we use Wave 4 and Wave 5 of SHARE to test the effect of training participation in 2010 (Wave 4) on changes in labour market status between 2010 and 2012 (Wave 5), controlling for a rich set of observable individual characteristics. Information on self-reported current economic status allows us to distinguish between six labour force states: employed or self-employed, unemployed, permanently sick or disabled, retired, homemaker and 'other'. To measure training participation we exploit a question in Wave 4 (part of the module 'Activities') which asks respondents whether they attended any educational or training course in the last twelve months.; The main result of this chapter is that individuals who took part in training activities in the year prior to the 2010 (2009 for Estonia) interview are significantly less likely to leave the labour market. Training older workers may therefore prevent them from being exposed to the risk of poverty and social exclusion. This chapter is organised as follows: the next section reports the descriptive evidence regarding labour market status in the last two waves of SHARE and participation in training activities. The following section presents the results of a multivariate analysis, which aims at capturing the effect of training on the probability of exiting the labour market. The last section concludes the chapter, providing some policy implications of our analysis." (Author's abstract, IAB-Doku) ((en))

This article studies coding errors in occupational data, as the quality of this data is important but often neglected. In particular, we recoded open-ended questions on occupation for last and current job in the Dutch sample of the "Survey of Health, Ageing and Retirement in Europe" (SHARE) using a high-quality software program for ex-post coding (CASCOT software). Taking CASCOT coding as our benchmark, our results suggest that the incidence of coding errors in SHARE is high, even when the comparison is made at the level of one-digit occupational codes (28% for last job and 30% for current job). This finding highlights the complexity of occupational coding and suggests that processing errors due to miscoding should be taken into account when undertaking statistical analyses or writing econometric models. Our analysis suggests strategies to alleviate such coding errors, and we propose a set of equations that can predict error. These equations may complement coding software and improve the quality of occupational coding. ; This article studies coding errors in occupational data, as the quality of this data is important but often neglected. In particular, we recoded open-ended questions on occupation for last and current job in the Dutch sample of the "Survey of Health, Ageing and Retirement in Europe" (SHARE) using a high-quality software program for ex-post coding (CASCOT software). Taking CASCOT coding as our benchmark, our results suggest that the incidence of coding errors in SHARE is high, even when the comparison is made at the level of one-digit occupational codes (28% for last job and 30% for current job). This finding highlights the complexity of occupational coding and suggests that processing errors due to miscoding should be taken into account when undertaking statistical analyses or writing econometric models. Our analysis suggests strategies to alleviate such coding errors, and we propose a set of equations that can predict error. These equations may complement coding software and improve the quality of occupational coding.

► Working conditions are significantly related to health outcomes among older workers in Europe ► General health is correlated with the following work domains: physical environment, work intensity and skills and discretion ► Low job security and uncertain career prospects are associated with mental and behavioural disorders ► An increase in the legal retirement age can have adverse effects on workers' health and should be accompanied by policies aimed to benefit the most vulnerable workers and jobs