The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Yan Sun - One of the best experts on this subject based on the ideXlab platform.
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magical transition intergenerational educational and Occupational Mobility in rural china 1988 2002
Research Papers in Economics, 2015Co-Authors: Shahe M Emran, Yan SunAbstract:This paper presents evidence on intergenerational educational and Occupational Mobility in rural China over a period of 14 years (1988–2002). To understand whether the estimated inter-generational persistence can be driven solely by unobserved heterogeneity, biprobit sensitivity analysis and heteroskedasticity-based identification are implemented. The empirical results show that there have been dramatic improvements in Occupational Mobility from agriculture to nonfarm occupations; a farmer’s children are not any more likely to become farmers in 2002, although there was significant persistence in occupation choices in 1988. In contrast, the intergenerational Mobility in educational attainment has remained largely unchanged for daughters, and it has deteriorated significantly for sons. There is strong evidence of a causal effect of parental education on a son’s schooling in 2002. The paper provides some possible explanations for the dramatic divergence between Occupational and educational Mobility in rural China from 1988 to 2002.
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magical transition intergenerational educational and Occupational Mobility in rural china 1988 2002
Social Science Research Network, 2011Co-Authors: Shahe M Emran, Yan SunAbstract:This paper presents evidence on intergenerational educational and Occupational Mobility in Rural China over a period of 14 years (1988-2002). To understand whether the estimated intergenerational persistence can be driven solely by unobserved heterogeneity, we implement biprobit sensitivity analysis (Altonji et al. (2005)) and heteroskedasticity based identification of Klein and Vella (2009). The empirical results show that there have been dramatic improvements in Occupational Mobility from agriculture to non-farm occupations; a farmer’s children are not any more likely to become farmers in 2002, even though there was significant persistence in occupation choices in 1988. In contrast, the intergenerational Mobility in educational attainment has remained largely unchanged for daughters, and it has deteriorated significantly for sons. There is strong evidence of a causal effect of parental education on a son’s schooling in 2002. We provide some possible explanations for the dramatic divergence between Occupational and educational Mobility in rural China from 1988 to 2002.
Maarten Van Ham - One of the best experts on this subject based on the ideXlab platform.
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Occupational Mobility and living in deprived neighbourhoods housing tenure differences in neighbourhood effects
Social Science Research Network, 2013Co-Authors: Maarten Van Ham, David ManleyAbstract:The literature on neighbourhood effects suggests that the lack of social Mobility of some groups has a spatial dimension. It is thought that those living in the most deprived neighbourhoods are the least likely to achieve upward Mobility because of a range of negative neighbourhood effects. Most studies investigating such effects only identify correlations between individual outcomes and their residential environment and do not take into account that selection into neighbourhoods is a non-random mechanism. This paper investigates Occupational Mobility between 1991 and 2001 for those who were employed in Scotland in 1991 by using unique longitudinal data from Scottish Longitudinal Study (SLS). We add to the existing literature by investigating neighbourhood effects on Occupational Mobility separately for social renters, private renters and home owners.We find that 'neighbourhood effects' are strongest for home owners, which is an unexpected finding. We argue that the correlation between characteristics of the residential environment and Occupational Mobility can be explained by selection effects: homeowners with the least resources, who are least likely to experience upward Mobility, are also most likely to sort into the most deprived neighbourhoods. Social housing tenants experience less selective sorting across neighbourhoods as other than market forces are responsible for the neighbourhood sorting mechanism.
Shahe M Emran - One of the best experts on this subject based on the ideXlab platform.
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magical transition intergenerational educational and Occupational Mobility in rural china 1988 2002
Research Papers in Economics, 2015Co-Authors: Shahe M Emran, Yan SunAbstract:This paper presents evidence on intergenerational educational and Occupational Mobility in rural China over a period of 14 years (1988–2002). To understand whether the estimated inter-generational persistence can be driven solely by unobserved heterogeneity, biprobit sensitivity analysis and heteroskedasticity-based identification are implemented. The empirical results show that there have been dramatic improvements in Occupational Mobility from agriculture to nonfarm occupations; a farmer’s children are not any more likely to become farmers in 2002, although there was significant persistence in occupation choices in 1988. In contrast, the intergenerational Mobility in educational attainment has remained largely unchanged for daughters, and it has deteriorated significantly for sons. There is strong evidence of a causal effect of parental education on a son’s schooling in 2002. The paper provides some possible explanations for the dramatic divergence between Occupational and educational Mobility in rural China from 1988 to 2002.
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magical transition intergenerational educational and Occupational Mobility in rural china 1988 2002
Social Science Research Network, 2011Co-Authors: Shahe M Emran, Yan SunAbstract:This paper presents evidence on intergenerational educational and Occupational Mobility in Rural China over a period of 14 years (1988-2002). To understand whether the estimated intergenerational persistence can be driven solely by unobserved heterogeneity, we implement biprobit sensitivity analysis (Altonji et al. (2005)) and heteroskedasticity based identification of Klein and Vella (2009). The empirical results show that there have been dramatic improvements in Occupational Mobility from agriculture to non-farm occupations; a farmer’s children are not any more likely to become farmers in 2002, even though there was significant persistence in occupation choices in 1988. In contrast, the intergenerational Mobility in educational attainment has remained largely unchanged for daughters, and it has deteriorated significantly for sons. There is strong evidence of a causal effect of parental education on a son’s schooling in 2002. We provide some possible explanations for the dramatic divergence between Occupational and educational Mobility in rural China from 1988 to 2002.
Doyne J Farmer - One of the best experts on this subject based on the ideXlab platform.
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Occupational Mobility and automation a data driven network model
Journal of the Royal Society Interface, 2021Co-Authors: Maria R Del Riochanona, Penny Mealy, Mariano Beguerissediaz, Francois Lafond, Doyne J FarmerAbstract:The potential impact of automation on the labour market is a topic that has generated significant interest and concern amongst scholars, policymakers and the broader public. A number of studies have estimated occupation-specific risk profiles by examining how suitable associated skills and tasks are for automation. However, little work has sought to take a more holistic view on the process of labour reallocation and how employment prospects are impacted as displaced workers transition into new jobs. In this article, we develop a data-driven model to analyse how workers move through an empirically derived Occupational Mobility network in response to automation scenarios. At a macro level, our model reproduces the Beveridge curve, a key stylized fact in the labour market. At a micro level, our model provides occupation-specific estimates of changes in short and long-term unemployment corresponding to specific automation shocks. We find that the network structure plays an important role in determining unemployment levels, with occupations in particular areas of the network having few job transition opportunities. In an automation scenario where low wage occupations are more likely to be automated than high wage occupations, the network effects are also more likely to increase the long-term unemployment of low-wage occupations.
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automation and Occupational Mobility a data driven network model
arXiv: General Economics, 2019Co-Authors: Maria R Del Riochanona, Penny Mealy, Francois Lafond, Mariano Beguerissed Iaz, Doyne J FarmerAbstract:The potential impact of automation on the labor market is a topic that has generated significant interest and concern amongst scholars, policymakers, and the broader public. A number of studies have estimated occupation-specific risk profiles by examining the automatability of associated skills and tasks. However, relatively little work has sought to take a more holistic view on the process of labor reallocation and how employment prospects are impacted as displaced workers transition into new jobs. In this paper, we develop a new data-driven model to analyze how workers move through an empirically derived Occupational Mobility network in response to automation scenarios which increase labor demand for some occupations and decrease it for others. At the macro level, our model reproduces a key stylized fact in the labor market known as the Beveridge curve and provides new insights for explaining the curve's counter-clockwise cyclicality. At the micro level, our model provides occupation-specific estimates of changes in short and long-term unemployment corresponding to a given automation shock. We find that the network structure plays an important role in determining unemployment levels, with occupations in particular areas of the network having very few job transition opportunities. Such insights could be fruitfully applied to help design more efficient and effective policies aimed at helping workers adapt to the changing nature of the labor market.
David Manley - One of the best experts on this subject based on the ideXlab platform.
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Occupational Mobility and Living in Deprived Neighbourhoods: Housing Tenure Differences in ‘Neighbourhood Effects’
Applied Spatial Analysis and Policy, 2015Co-Authors: Maarten Ham, David ManleyAbstract:The literature on neighbourhood effects suggests that the lack of social Mobility of some groups has a spatial dimension. It is thought that those living in the most deprived neighbourhoods are the least likely to achieve upward Mobility because of a range of negative neighbourhood effects. Most studies investigating such effects only identify correlations between individual outcomes and their residential environment and do not take into account that selection into neighbourhoods is a non-random mechanism. This paper investigates Occupational Mobility between 1991 and 2001 for those who were employed in Scotland in 1991 by using unique longitudinal data from Scottish Longitudinal Study (SLS). We add to the existing literature by investigating neighbourhood effects on Occupational Mobility separately for social renters, private renters and home owners. We find that ‘neighbourhood effects’ are strongest for home owners, which is an unexpected finding. We argue that the correlation between characteristics of the residential environment and Occupational Mobility can at least partially be explained by selection effects: homeowners with the least resources, who are least likely to experience upward Mobility, are also most likely to sort into the most deprived neighbourhoods. Social housing tenants experience less selective sorting across neighbourhoods as other than market forces are responsible for the neighbourhood sorting mechanism.
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Occupational Mobility and living in deprived neighbourhoods housing tenure differences in neighbourhood effects
Social Science Research Network, 2013Co-Authors: Maarten Van Ham, David ManleyAbstract:The literature on neighbourhood effects suggests that the lack of social Mobility of some groups has a spatial dimension. It is thought that those living in the most deprived neighbourhoods are the least likely to achieve upward Mobility because of a range of negative neighbourhood effects. Most studies investigating such effects only identify correlations between individual outcomes and their residential environment and do not take into account that selection into neighbourhoods is a non-random mechanism. This paper investigates Occupational Mobility between 1991 and 2001 for those who were employed in Scotland in 1991 by using unique longitudinal data from Scottish Longitudinal Study (SLS). We add to the existing literature by investigating neighbourhood effects on Occupational Mobility separately for social renters, private renters and home owners.We find that 'neighbourhood effects' are strongest for home owners, which is an unexpected finding. We argue that the correlation between characteristics of the residential environment and Occupational Mobility can be explained by selection effects: homeowners with the least resources, who are least likely to experience upward Mobility, are also most likely to sort into the most deprived neighbourhoods. Social housing tenants experience less selective sorting across neighbourhoods as other than market forces are responsible for the neighbourhood sorting mechanism.
