Specialized Human Capital, Unemployment Risk, and the Value Premium

Summary

In this article, the authors want to see whether specialized human capital’s negative shocks are listed under the cross-section of stock returns. These shocks are calculated by studying the employment growth of that industry where the human capital is. In the industries in which there is a contract in employment, the risk for value factor is higher than in the industries where employment grows. Results show that the companies where employment growth is higher have lower expected returns than companies where growth rate is lower. The premium for the big, small, and micro stocks is extensive for employment growth. CAPM cannot explain the premium, but the value minus growth risk factor is inversely related to portfolio payoff.

For a household, earning and living human capital is important. But as the human capital is only specialized in one field or industry most of the time, it is risky for the household to invest in the same industry they are working in as that industry could be a dying one because of technological advancements, for example, a journalist is specialized in a particular industry, i.e., media industry which is becoming obsolete with the social media advances. The portfolio of their investments should be diversified rather than just buying stock in that dying industry. The investors in industries where employment is contracting are in a risky place to face value risk factors compared to those who have investments in industries where employment is expanding. Where employment is contracting, the employees should avoid buying the stocks and evade the value investment strategy, and they should buy the stocks in the industries where employment is expanding.

The authors have proposed a specific measure, using employment growth, to check shocks at the industry level for specialized human capital. Employment will contract if the industry is becoming obsolete. With the contraction in employment, specialized human capital will be at risk. If you have skills for more than one industry, you will face only a loss of income but can work in another company or industry. Industry-specific human capital will not be facing any risk. Employment growth is used to measure shocks for human capital instead of using wage growth because when an industry faces distress, the decrease in the income of the workers can be measured by wages, but for those who are unemployed, we can not measure their reduction in income through wage growth.

The data was collected from the U.S. stock market databases. Data for employment is collected from the U.S. BLS and QCEW to measure the salaries and wages of employed workers. Employees working for a specific industry that specializes in human capital must avoid investing in stock in that particular industry. The regression model has been used for data analysis in this article, and the cross-sectional predictive regression model is also applied to measure the relationship between expected returns and employment growth. Cross-sectional predictive regressions show unfavorable results for the firms that have a strong impact on small stocks. A large pool of small stocks will be obtained due to the dominating effect of micro and small stocks due to massive market capitalization. Therefore, it is essential to build an impact on various groups of market capitalization using a pervasive predictive variable. In this study, predictive regressions were applied separately to determine the impact of the predictive variable on different market groups. As a whole, it has been inferred that for all size groups, the predictive power is pervasive for industry employment growth. There is a negative link between expected returns and employment growth of a firm, as observed through cross-sectional predictive regressions. Interestingly, if the returns are calculated by CAPM, assets with higher returns will be linked to higher industry employment growth. Market beta is low for the industries that have low employment growth. Market beta is high for the industries with high employment growth, and statistically, the value is greater than 1.

In this article, the results show a strong and consistent link between specialized human capital and value premium. Workers do not like to invest in stocks whose payoff is associated with a decreased shock in their industry-specific human capital. Employment growth has been taken in order to measure the shocks for specialized human capital. I observe that industries that possess employment contraction have considerable exposure to value premiums compared to industries that have employment contractions. In this study, hedging portfolios, as well as cross-sectional predictive regressions, have been used. Expected returns are higher for industries where employment growth is low than for firms that possess higher employment growth. Among many forms of market capitalization, the return premium of the firm is pervasive and corresponds to industry-specific human capital.

This research can be used by investment managers as it allows them to understand that they need to invest in a portfolio of different industries as the risk in investing in one industry where the employment is contracting is higher as compared to the industries where employment is expanding because the risk is low in those industries. They should invest in industries where the employment growth is low as the expected return in such industries is higher, and they should avoid investing in industries where employment growth is higher. Investors may find from the study that workers feel reluctant to value investment strategy as with technological advancement, and there will be obsolete jobs and industry-specified skills, which will cause a negative shock to industry-specific human capital. The workers affected by these negative shocks avoid investing in shares of these companies. Investment managers can also avoid such negative shocks by investing in a portfolio of different industries.

References

Jank, S. (2014). Specialized human capital, unemployment risk, and the value premium.