Chapter 13: [ 10 Questions on Exam] Human Capital and the Distribution of Income

 

This is a short chapter and it was going to be used to tie together some of the substantive issues in the rest of the course. Now it will have to be cut short and focus on the parts that are easier to learn (but nonetheless important).

 

Ø      Know the definitions and relevance/uses of the key terms

Ø      Pay particular attention to the Lorenz Curve and the Gini Coefficients

 

Human Capital is defined as the stock of accumulated capacity and expertise that contribute to the productive potential of the individual human. Potentially/hopefully it also contributes to the earnings of that individual.

 

Human capital can be accumulated through the formal process of education (schooling), can be acquired through training on the job (apprenticeship), or can be acquired through work experience. 

 

Section 13.2 “Productivity Differences and Education” explores the impact of an educational premium (wage differential) based on productivity differences attributed to education.  Figure 13.2 simply shows the fact that (on average) lifetime earnings are consistently higher for more education workers than they are for less educated workers.

(Of course here are outliers, neither Bill Gates (Microsoft) nor Steve Jobs (Apple) has a university degree.

 

The education premium operates in two ways. It gets a job seeker through the first level of an employer’s hiring filter – that being to only consider educational graduates. The second is to equip the worker with augmented skills to perform well in the workplace.

“Getting through the door” is such a challenge that it supports a market in phoney degrees. Here is a Toronto Star link to a former York/Atkinson/Human Resource Management student who has been making his living producing phoney degrees.

 

 Phoney Degree Scam: http://www.thestar.com/news/gta/article/549772

 

One challenge to formal education is the fact that students are credit-constrained. This means that individual students will under-demand formal education, and that society will under-supply formally educated workers. The reasons for this are several: (a) human capital, unlike physical capital, cannot be bought and sold (no slavery); (b) the production performance –and factor income- are uncertain compared to buying a machine that can do so many activities per time period (metal lathe, computer, etc) and (c) one cannot borrow in private markets against one’s future earnings.

 

This is why there are government backed student loan programs. The backing insures that lenders face less risk. The shortcoming is that student loans with fixed principle and set payback schedules can be both a deterrent and a burden to students. Wealthy students don’t need loans and poor students can be deterred by the risks associated with the burden of repayment. Some countries tie loan repayment to income and earnings so that a financially successful student pays all back quickly, and a financially unsuccessful student pays back less or little at all. Schemes linked to earnings also facilitate job mobility since debt ridden workers don’t have to remain in a job just because of the burden of student loan repayments. For reasons unclear to your Professor, Canadian student organizations tend to oppose income-related payback schemes.

 

Section 13.3: On the Job Training

 

On the job training clearly increases the human capital of the worker. The book differentiates between human capital represented by firm-specific skills and human capital represented by general skills. We have a problem here similar to the market failure for education in general. If a firm invests in skills training, what is the risk that the worker – and those skills – will walk away to a job elsewhere (or with a competitor)?  The more mobile the skills are the less willing the firm is to invest in them, and the more firm-specific the skills are the less willing the individual is to bear part of the cost.  This is why, for example, health professionals are willing to work for lower wages as they first practice their skills as apprentice professionals.

 

Section 13.4: Education as employee signalling (and the challenge of employer screening). Short section….read this again  ( - :

 

 Phoney Degree Scam: http://www.thestar.com/news/gta/article/549772

 

Section 13.5: Measuring Educational Benefits and Educational Quality

 

The section refers to research that suggests that education augments productivity, and income, more than just being smart, and that advanced degrees (graduate education) on average augments income even more. Note: this is a complicated area since there are different advanced degree fields and the average MA English poet does less well than the average MBA, which explains why there is less demand for phoney degrees in English than in business, at the BA or graduate levels.

 

Section 13.6: Discrimination

 

By discrimination here we mean negative discrimination against job seekers based on their gender, ethnicity, age, or some other factor that has little to do with ability and productivity.

 

Discrimination is still present in varying degrees (depending on the market and the attributes of the job seeker) and is unfortunate for two reasons. First, if offends our sense that all humans are essentially created equal (but may differ in inborn abilities and acquired human capital). Discrimination on non-human capital grounds is unjust. In addition, keeping qualified workers out of jobs through discrimination denies the larger society the fruits of their skills and abilities. How many poor rural peasants, or urban shanty town dwellers would have made major contributions to society had they been educated and allowed to pursue a productive career?

Table 13.1 Average Score on Science Test for Grade 8 Students. (skip)

 

The twin issues of what do these tests measure, and what does testing do to the curriculum (too test-centric – teaching to the test) are important but not dealt with in this truncated course. The book’s suggestion that we simply have to wait longer to see the effects of high science test scores on Canadian productivity is too simple an explanation of lagging Canadian productivity. 

 

Application Box 13.3: Canada’s Human Capital and the “Brain Drain” (skip)

 

This is an important topic but there is not time to do it justice under the compressed time we will have when the course resumes. There are both human capital and ethical questions with regard to the international migration of human capital (Should Canada suck nurses out of developing countries because it refuses to train enough to supply its own needs?)

 

Section 13.7: The Income Distribution (Know this section, I will surely test you on it!)

 

Understand:

Ø      Income distribution by quintiles

Ø      The Lorenz Curve

Ø      The Gini Coefficient (comes from Lorenz Curve)

o       You will not be expected to calculate it, just understand it and know what the numbers mean, in terms of relative magnitude (e.g. what does a Gini Coefficient of .34 mean relative to .43?).

 

This material in income distributions will be the last material I cover for the course. I will go a bit beyond what is in the book. What is happening to income and wealth distributions is important for what is going on in the world today.