Thus, in contrast to adverse shocks and income, adult
human capital factors not only were linked to credit scores and heart age, but also significantly accounted for why credit scores and heart age covary.
This model showed that adjusting for childhood
human capital factors reduced the correlation between credit scores and heart age by 22 % (from r = − 0.247 to r = − 0.192).
Effect of adult
human capital factors on the covariation between credit scores and heart age.
In contrast to the modest changes in correlation between credit scores and heart age evidenced when adjusting for adverse events and income, adjusting for
human capital factors reduced the correlation between credit scores and heart age by 45 % (from r = − 0.247 to r = − 0.136).
Associations between adult
human capital factors, credit scores, and heart age.
All three
human capital factors were also positively associated with income (educational attainment: β = 0.39, P < 0.001; cognitive ability: β = 0.35, P < 0.001; self - control β = 0.38, P < 0.001); however, multivariate regression models revealed that all three
human capital factors were associated with creditworthiness and heart age independent of income (Tables S1 — S4).
This structural equation model illustrates the role of
human capital factors in the correlation between credit scores and heart age.
All three adult
human capital factors — educational attainment, cognitive ability, and self - control — predicted both higher credit scores (Fig. 2A) and younger heart age (Fig. 2B).
Effect of childhood
human capital factors on credit scores, heart age, and their covariation.
Comparison with a model where the covariance between credit scores and heart age is constrained to initial levels showed that
human capital factors accounted for a significant source of the link between credit scores and heart age.
To test whether childhood human capital also accounted for covariation between credit scores and heart age, we replicated our previous SEM model, but substituted adult
human capital factors with their childhood antecedents (Fig. 5).
Under the CRS, candidates will receive up to 600 points for
human capital factors (e.g. age, work experience, education, language ability etc.) and an additional 600 points for having either a Canadian job offer supported by a Labour Market Impact Assessment from Service Canada or a provincial / territorial nomination from a participating province or territory — currently, a certificate of nomination from the Alberta Immigrant Nominee Program can not be used for Express Entry.
Not exact matches
He or she will instead tell you that team and access to
human capital are the most important
factors in a startup's success.
Income, or
human capital, can also be an important
factor when deciding how to build your portfolio.
This renewed interest in Australia (and elsewhere) in upgrading the nation's
human capital reflects a number of
factors, including new growth theory and the demonstration effects already mentioned.
«We've always known that
human capital is important for economic growth and we are also learning that counties that have good amenities and quality of life
factors — mountain views, lakes, shores, and clean environment, for example — are doing quite well, but we haven't looked at having both of these together in a county at the same time and what the policy implications might be,» said Goetz.
According to A * STAR's chair Mr. Philip Yeo, the availability of
human capital is one of the decisive
factors companies consider when moving here.
Third, when examining regional resistance
factors, the results suggest that
human capital is the single most important regional
factor associated with a better resistance to economic shocks.
Migrants possess this breath of life since they are
human beings, and that is why they must not be treated like objects, nor assessed as a production
factor, no matter which one (earth, labor,
capital, technology), because any migrant is superior to any product or static means of production.
It may be considered as a «
factor of production,» paralleling the use by economists of physical
capital, financial
capital, and
human capital (the effectiveness of the individual, defined by education) as
factors in the production of goods.
That measure of
human capital, however, implicitly assumes that each additional year of schooling translates into a comparable increment in the stock of relevant skills, totally ignoring any variations in the quality of the student's home, community, school, teachers, and other
factors.
The states that made the most progress after allowing for other
factors — Maryland, Massachusetts, New Jersey, Kentucky, and Georgia, to name the top five — have taken steps, in various ways, to raise academic standards and back them up with rigorous assessments, implement tough but thoughtful accountability systems, and strengthen
human capital practices to attract, develop, and retain educators who can deliver on high standards.
We use basic multiple linear regression models along with
factors in the US Census data that relate to community social
capital and family
human capital to create predictive algorithms.
This innovative partnership between the district, union, and community is implementing an entirely new teacher effectiveness paradigm that encompasses joint development of differentiated roles for teachers, evaluation that uses data as a significant
factor and is used to make critical
human capital decisions, and implements a compensation structure that rewards effective performance.
Given the fiscal and
human capital expended on teacher attrition, identifying
factors that influence attrition is of the utmost concern, posing a challenge that has drawn the attention of researchers and policy makers alike.
Income, or
human capital, can also be an important
factor when deciding how to build your portfolio.
Your
human capital depends on a combination of
factors that include your age, health, skill set and employment status.
This allows you to
factor your
human capital — your income - earning ability — into your asset allocation.
Among the main
factors that can be influenced by policy decisions, one can list governance,
human and social
capital, technology, and finance.
However it needs an analysis of all of the
factors that can drive long term performance including product innovation, executive compensation, culture,
human capital management, governance, supply chains, selling practices, product life cycles, carbon exposure, resource utilisation, and health and safety.
In employment screening, we address key
human capital risks — those related to the «
human factor» of the organization.
Parental separation may also expose children to loss of social, economic and
human capital.4, 14 Other explanatory
factors may derive from characteristics typical of separating parents such as lower relationship satisfaction and higher conflict levels also before the separation.4 The rising numbers of children with JPC have concerned child clinicians as well as researchers on the subject.20, 21 Child experts have worried about children's potential feelings of alienation from living in two separate worlds, 20 — 22 increased exposure to parental conflict12, 22 and other stressors that JPC may impose on a child.22 Such daily stressors may be long distances to school, friends and leisure activities, lack of stability in parenting and home environment and a need to adjust to the demands of two different family lives.12, 22 The logistics of travelling between their homes and keeping in contact with friends has been stated as a drawback of JPC in interview studies with children.23 — 25 Older adolescents, in particular, indicated that they preferred to be in one place.23