Wednesday, April 22, 2009

Discrimination and the economics of life

Here are five examples that illustrate the importance of initial conditions, family and societal environment, and contextual factors in influencing outcomes in unexpected manners.

1. Edgar Johns of JobApp Network, a firm that helps other companies hire, has done an interesting study of over 25,000 applicants to restaurant and retail job positions. Of those job seekers applying by phone, more than 40% were minorities. When it came to applying over the web, the share of minorities fell to less than 20%. His conclusion: as firms move more and more toward taking only online applications, there could be an adverse impact on minority applicants.

He writes, "Employers who offer only a web-based employment application process limit their applicant pool and may also adversely impact their efforts to promote diversity. In the worst case, it may unwittingly contribute to discrimination in hiring. Fortunately, low-cost and highly effective automated hiring solutions incorporating both the phone and the web enable employers to avoid these pitfalls without investing in hiring kiosks or devices."

(HT: Freakonomics)

2. Sendhil Mullainathan and Marianne Bertrand, found that applicants named Lakisha or Jamal were less likely to be considered for jobs, even when they had qualifications on paper that were similar to those of applicants named Emily or Greg. They conducted an experiment using fictitous resumes on job placement ads in Boston and Chicago, with each resume assigned either a very African American sounding name or a very White sounding name so as to manipulate race perceptions. They found that white names received 50% more callbacks for interviews. Further, it was also found that race affects the benefits of a better resume, with a higher quality resume eliciting a 30% more callbacks for white names, against a much smaller increase for African-American names. Applicants living in better neighborhoods receive more callbacks but, interestingly, this effect does not differ by race.

They found that the amount of discrimination is uniform across occupations and industries, with even the federal contractors and employers who list Equal Opportunity Employer' in their ad discriminating as much as other employers. All these conclusively point to the salience of racial discrimination in the hiring decisions of employers in the labour markets. More evidence of such labour market discrimination is available in the NBER working papers here.

3. Alan Krueger surveys the emerging literature on intergenerational transmission of economic status and writes that it is becomingly increasingly apparent the "secret to success is to have a successful parent". Bhashkar Mazumder and David I. Levine studied the correlation in earnings, family income and wages between brothers from 1970s to 1990s and conclude that family and community influences shared by siblings have become increasingly important in determining economic outcomes.

Research by Mark Huggett, Gustavo Ventura and Amir Yaron finds that from the age of 20, differences in initial conditions account for more of the variation in lifetime utility and in lifetime wealth than do differences in shocks received over the lifetime. Among initial conditions, variation in initial human capital is relatively more important than variation in learning ability for determining how an agent fares in life.

4. Anne Case, Angela Fertig, and Christina Paxson compare data from a birth cohort that has been followed from birth into middle age, and find that "controlling for parental income, education and social class, children who experience poor health have significantly lower educational attainment, poorer health, and lower social status as adults". They find that childhood health and circumstance appear to operate both through their impact on initial adult health and economic status, and through a continuing direct effect of prenatal and childhood health in middle age.

Cohort members born into poorer families experienced poorer childhood health, lower investments in human capital and poorer health in early adulthood, all of which are associated with lower earnings in middle age — the years in which they themselves become parents.

5. Resul Cesur and Inas Rashad find that children with a high birthweight (over 4.5kg) (like children with low birth weight too) score worse on maths and reading tests age six than those with average birthweight, a result which holds even controlling for family income among other things. This assumes significance in the light of recent findings that cognitive skills even at a young age are correlated with an ability to do well at school and thus with earnings in later life.

Update 1 (15/4/2011)

Daniel Hamermesh and Jason Abrevaya writes,

We measure the impact of individuals’ looks on their life satisfaction or happiness using various sets of data from the US, Canada, the U.K., and Germany. The results show that:
1. Personal beauty raises happiness.
2. The majority of this positive effect comes about because personal beauty improves economic outcomes – incomes, marriage prospects, and others – that increase happiness. Thus much of the positive effect of beauty on happiness is indirect – through its effects on aspects of economic life that increase happiness.
3. The total effects of beauty on happiness are about the same for men and women. But the direct effect is larger among women – beauty affects their happiness independent of its impact on their incomes, marriage prospects, and other outcomes.
Because the beauty measures are collected in a variety of ways, and because happiness is also measured in various ways, we can be quite confident in the general validity of the conclusions.
Update 2 (28/3/2012)

A working paper by researchers examining evidence of discrimination based on physical appearance in donations made through Kiva has more evidence of such discrimination. They write,

We find that donors appear to discriminate in favor of more attractive, lighter-skinned, and less obese borrowers, even as donors appear to systematically favor regions of the world where lighter skin is less prevalent. These effects are statistically and quantitatively significant and robust across a variety of specifications. Discrimination on the basis of physical attraction and skin color appears to be heightened for female borrowers, while obesity matters more for male borrowers.

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