The Earnings Function and Human Capital Investment

Transcription

1 The Earnings Function and Human Capital Investment w = α + βs + γx + Other Explanatory Variables Where β is the rate of return on wage from 1 year of schooling, S is schooling in years, and X is experience in years. For simplicity we will assume: Schooling is either High School (HS) or College (C) and other variables are held constant Tuition costs are constant for 4 years Individuals only receive wage benefits from education if they complete all 4 years. Net Present Value Approach Present Discounted Value of Lifetime Earnings P V = n t=18 W t (1 + r) t 18 (1) 1

2 Benefit from Education at time t B t = W C t Present Discounted Value of the Benefit from Education W HS t (2) NP V = n t=18 B t (1 + r) t 18 (3) For the sake of simplification think of tuition as a negative wage for college students for all periods. In that case people will invest in education if Present Discounted Value of the Benefit from Education NP V = 0 (4) Costs of Eduction Direct costs - tuition, textbook and other costs incurred to go to school Indirect/Opportunity costs - forgone earnings by college students that could be earned had they entered the workforce. Internal Rate of Return Use equation (3) and solve for the r such that (3) is equal to zero. Labor Market Discrimination Labor Market Discrimination - Employment, wage and promotion practives that result in workers who are equal with respect to productivity being treated differently because of race, gender, age ethnic group or other characteristics unrelated to job performance. Means of Discrimination Employers prefer to hire a particular group. (Other groups need more qualifications to get hired.) Restrict promotions (Glass ceilings) 2

3 Pay lower wages Consumer discrimination (Buy American) Workers unwilling to work with certain groups. Theories of Labor Market Discrimination (Gary Becker s) Personal Prejudice Theory Certain firms were assumed to have a Taste for discrimination, d. The discriminator acts as if the price of the product or wage of the worker is higher by the proportion d. Discriminators are not profit maximizers and are willing to sacrifice profits for the ability to discriminate. In a perfectly competitive market firms that discriminate will be driven from the marketplace. Discrimination in a Perfectly Competitive Industry Recall, that in a perfectly competitive output market the firm has no control over the price; it must charge the market price. Any firm that choses to discriminate must pay a higher wage to the preferred group. This will result in a higher marginal cost curve, average variable cost curve and average total cost curve for the discriminating firm. Whereas the non-discriminating firm will be able to take advantage of the situation and pay a lower wage to the discriminated group. Likewise, this will result in a lower marginal cost, average variable cost and average total cost for non-discriminating firms. 3

4 The difference in cost curves has significant impacts for each perfectly competitive firm since it must charge the industry price for its product. Given that consumers do not also discriminate against this same group and opt for the product with the lowest price, the discriminating firm will lose money while the non-discriminating firm will make an economic profit. Any entrepreneur considering starting up a firm will see this industry as one in which she may make a profit. This new firm entry will increase the losses of discriminating firms to the point where either their stockholders demand they not discriminate or leave the industry. Eventually, a perfectly competitive output market will be free of discriminating firms. Wage Differentials Caused by Employer Prejudice If the relative wage ratio is equal to 1 then the wages are equal to one another and there is no evidence of discrimination. This is because there are so few of the discriminated group that they are all able to find employment with employers who do not discriminate. It is only when the proportion of discriminated workers to firms who do not discriminate is large enough that we will find evidence of wage or employment discrimination. In this case, discriminated workers are forced to find employment with firms who have a taste for discrimination. These firms will only hire the discriminated group if they are paid a low enough wage to over take the employer s taste for discrimination. 4

5 Statistical Discrimination Result of imperfect information. Employer uses signals (grades, college choice, letters of recommendation, average characteristics of group applicant belongs etc.) to judge prospective employee s level of quality. Differences between groups need not be present for statistical discrimination to exist. It may exist due to differences in reliability of signals between groups. If employer perceptions on differences between groups are correct on average discriminators will not be driven out of market and may even be more profitable. Measuring the Effect of Discrimination on Pay Gaps The Earnings Function Approach w = β 0 + β 1 S + β 2 E + β 3 O + β 4 G (5) where S is years of schooling, E is years of experience, O is a set of dummy variables denoting occupation, G is a dummy variable specifying gender. 5

6 Oaxaca Decomposition Method Assume schooling is the only determinate of wage for both sexes. Male Earnings Function: w m = α m + β m S m (6) Female Earnings Function: w f = α f + β f S f w = w m w f = α m + β m S m α f β f S f (7) where w m is the wage of males, w f is the wage of females, w m is the average wage of males and w f is the average wage of females. The Oaxaca Decomposition separates the average change in wage into the portion that is attributable to labor market discrimination and the part that is caused by differences in skills on average. Add and subtract (β m S f ) to Equation 7 Rearrange terms Factor out like terms w = α m + β m S m (β m S f ) α f + (β m S f ) β f S f (8) = α m α f + β m S f β f S f + β m S m β m S f (9) = α m α f + (β m β f )S }{{ f } + β m(s m S f ) }{{} Due to Discrimination Due to Differences (10) 6

7 Wage Differences for Native American Males The Data Set We use data from the Current Population Survey Annual file, also known as the Merged Outgoing Rotation Groups (MORG) from the Current Population Survey. The same data is used by the U.S. Department of Labor to calculate unemployment rates. Following the procedure used by? we reduce our observations to those individuals between 16 and 65 1 earning a wage rate above $2.80 in 2000 dollars but below the of the top-coded value of 35 th weekly earnings. 1 Each observation is given a new weight; we multiply the CPS earnings weight by the total number of hours worked by the individual in the previous week. Weighting observations this way emphasizes the characteristics of the average hour worked by an individual rather than those of the each individual worker. 2 1 The Personal Consumption Expenditures Price Index is used to convert all wages to real terms. Accessed 2/1/ &FirstYear=2009&LastYear=2010&Freq=Qtr&ViewSeries=Yes 2 The percentage of average characteristics varies greatly between these two weighting techniques. For example, 52% of the hours worked by Native males are worked by those who have never had a college experience. Whereas, 62% of Native men have never had a college experience, respectively when calculated using the earnings weight method. 7

8 The wage for each hourly worker is the log of their real hourly earnings in 2000 dollars. The wage used for non-hourly workers is their reported usual weekly earnings divided by the number of hours they worked in the previous week which is then converted to real terms and logarithms. Education Concentration Figure 1: The percentage of total hours worked by education level for each race White Black Native No Diploma Diploma/GED Some Col/ Assoc Bachelors Grad Deg 8

9 Other Sales/Support Trades/Production Workers Professional Health/Comm Stem Including Social Science Wages, Education and Discrimination - Econ. of NA - RIT - Dr. Jeffrey Burnette Occupation Concentration Figure 2: The percentage of total hours worked within an occupation category for each race. Life, Physical, and Social Services Architecture and Engineering Computer and Mathematical Healthcare Support Healthcare Practitioners and Technical Community and Social Services Education, Training, and Library Legal Business and Financial Operations Management Transportation and Material Moving Production Installation, Repair, and Maintenance Construction and Extraction Building and Grounds Cleaning and Maintenance Office and Administrative Support Sales and Related Personal Care and Service Food Preparation and Serving Related Protective Service Farming, Forestry and Fishing Arts, Design, Entertainment, Sports, and Media Native Black White

10 Education by Occupation Figure 3: The percentage of hours worked for each level of education level by occupation category STEM Health Prof Trade Sales Other 10 0 No Diploma Diploma/GED SomeCol/Assoc Bach Deg Grad Deg Educational attainment is related to the types of occupations people obtain. Those with low levels of education work mostly in Trade where those with high levels work mostly as managers or educators. Average Wages by Category Table 2: Average hourly wage rates are 5 year averages over the period expressed in current dollars. Occupation Category White Native Black Sales/Support $17.20 $13.58 $13.64 STEM (Science, Tech., Engineering Math) $29.77 $26.27 $23.96 Health/Comm Services $24.00 $15.80 $17.40 Professional $29.85 $22.85 $22.06 Trade/Production $17.23 $15.86 $14.16 Other $17.93 $13.11 $

11 Figure 4: The average hourly wage by education level for each race during expressed in current dollars. $40.00 $35.00 $30.00 $25.00 $20.00 $15.00 $10.00 $12.45 $12.10 $10.93 $17.02 $15.12 $13.70 $18.64 $16.53 $15.25 $27.47 $33.93 $24.18 $27.48 $25.98 $21.09 $5.00 $- No Diploma Diploma Some College/Assoc Bach Deg Grad Deg White Native Black Higher education levels result in higher wages on average. The difference in wages between whites and Native Americans becomes larger as educational levels increase. The Regression Equation Ln(Wage) = β 0 + β 1 Age + β 2 Age 2 + β 3 Nat + β 4 Blk + β 5 Ed + β 6 Geo + β 7 Occ + β 8 Marital + Native(β 8 Ed + β 9 Geo + β 10 Occ + β 11 Mar) + Black(β 12 Ed + β 13 Geo + β 14 Occ + β 15 Mar) Table 3: Estimated regression coefficients and standard errors. Coefficients in red are significant at the 1% level. Coefficients in magenta and italic are significant at the 5% level. Coefficients in black are significant at the 10% level. 11

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13 When controlling for all other determinants of hourly wage rate whites and Native Americans receive the same percentage increase in wage from additional levels of education. Native americans earn 14% less than whites in Health occupations and 7% more than whites in Trade. Summary/Conclusions On average Native American males earn less than their white counterparts in all education and occupation categories. The majority of Native American males (52.41%) have have no college experience. Trade/Production occupations account for more hours worked than any other occupational group for all races. This percentage is the largest for Native Americans, 51.69% The proportion of workers employed as Trade or Production is higher for low education levels; this proportion decreases as the amount of education increases. STEM, Professional and Health occupations have the opposite relationship. The average hourly wage rate increases with higher levels of education. Consequently, it is larger in professions attractive to highly educated workers (STEM, Professional and Health) and lower for Trade/Production workers. Differences in educational attainment and the resulting occupational opportunities play the biggest role in explaining hourly wage rate differences between Native Americans and whites. Native Americans are paid lower wages than whites in Health care occupations but experience higher wages than their white counterparts in Trade occupations. This reduces the average wage increase that results from gaining a higher level of education and may contribute to the low education levels of Native Americans. Since, we know that if the benefit from education becomes smaller despite the cost of education remaining the same we would expect a lower rate of college attendance. 13