Summary
ONS currently measure Human Capital Stocks (HCS) using a well-established method that cumulates the expected value of discounted future earnings for individuals in the working age population. Human capital is defined as the stock of skills, knowledge and experience of an individual or population, which can productively be applied in the economy and is widely referred to as one of the main drivers of economic growth. This project makes an important contribution to improving this measure by incorporating health status into the HCS model and developing a skills classification measure that can be used instead of qualifications. The research also considers the impact of internal and international migration on regional HCS and assesses the extent to which these affect regional growth and standards of living.
Overview
This project makes several contributions to improving the measurement of HCS in the UK. We review existing measures and suggest a number of extensions and alternatives.
Recent research on HCS combined data from the Understanding Society survey and the Labour Force Survey to model the impact of health on retirement decisions and wages. We carry out research to understand how health status impacts on participation in the workforce, including on unemployment, hours worked and inactivity other than retirement. Using a full accounting framework, we develop historical and current estimates of how a person being in poor rather than good health impacts on HCS.
The UK has well-documented regional disparities in economic growth. Variation in the level of skills and qualifications of each region is one contributing factor. If more productive individuals congregate in specific local areas, generally cities, this generates a regional brain drain which has a negative impact on growth in affected regions. We aim to assess the extent to which regional HCS can explain the disparity in regional economic growth and analyse the extent to which domestic and international migration attenuates or exacerbates this effect.
Finally, we develop a classification of occupation-based skillsets. Current estimates divide workers by qualification level, but this does not always provide an accurate reflection of skills. Building on other ESCoE research we use online data sources to improve understanding of the skill sets associated with particular occupations.
