gender econ final

riskiness of work

7.5% of all work related deaths are women. the rest are all men. for men, most dangerous industries are construction, farming, protective services. men are insured against risk in their jobs, women in general are not.

Evidence on discrimination in employment: codes of color, codes of gender -- darity and mason

article looks at discrimination based on race and gender, how employers discriminate in the labor market. when discrimination is increased and reduced/discrimination against black males dropped most sharply b/w 1965 and 75, against women declining more recently (73-94). pre-1964, there was blatant discrimination. after civil whites act, used different methods to discriminate. studies: paired 2 men and 2 women and made them apply for the same job; used resume switching to eliminate the effect of differences in resume. results showed a lot of discrimination against women in restaurants, particularly high priced ones über discrimination -- possible gender discrimination in hiring practices, wages, etc. under investigation Walmart lawsuit: female employee passed over for a promotion multiple times despite having more experience and a higher position. told she was "overqualified" -- over 100 women had similar experiences

statistical discrimination

based on different distributions of labor force attachment for men and women. group differences might arise even without prejudice. this happens when membership in a group conveys information about skills. ex: women's fertility behavior and labor force attachment employer decides to hire a man instead of a woman of equal documented productivity should employers be allowed to use group average and test scores? costly to obtain all the necessary information, max expected value of profit. we already do -- age as indicator of driving ability, gender & driving

Goldin & Katz: career cost of family

career costs of family: penalties to labor supply behavior that's more compatible with having a family, such as job interruptions, shorter hours, part-time work women flock to occupations in which penalties to family have decreased. compensating wage differentials: difference in pay to make up for a disamenity of an occupation. women tend to place higher value on amenities such as flexibility, regular hours, lower stake. as the demand for an amenity increases, its price increases, increasing the gender wage gap. examples: medicine --> more women in ob-gyn, pediatrics, dermatology, etc. rare in cardiology and surgical specialties, bc have higher demands and emergencies. corporate/financial sectors: mba women have lowest LFP rates. gender gap widens over time. for women with kids and high earning husbands, they work less than those with lower earning husbands. if the women don't have kids, they work more if they have higher income husbands. increase in female pharmacists.

occupational segregation -- impact on wages

college major segregation: measuring the impact of segregation on wage gap -- difference between what women would earn if they had men's distribution of college majors, but were still paid the mean wage for women in each major and what women earn on average = wfm - wf. important equation

customer discrimination

customers don't like to be served by a certain group. if served by that group, customers perceive the price as P+d.

what determines wages?

education, tenure, occupation, industry, union membership, experience, hour structure

empirical evidence of women in lower paying jobs

evidence is clear that there is a strong correlation between lower pay and higher percentage women across most occupations. women are more likely to be found on the lower rungs in any occupation (hierarchical segregation) even with higher paying professions, lower pay for women

Goldin U curve

explaining long term trend of women's LFP going in a U shape as economy develops labor demand explanations -- changes from 1890 to 1980: sectoral changes, increase in service, changes in technology, formal education, employer/customer tastes supply: change in preferences -- number of children, cost of producing household goods, income of other members, electricity, running water, fertility control supply elasticities: income and substitution elasticities. estimated wage elasticity is assumed to be the substitution elasticity -- increase in the participation with a rise in wage must signify that entirely new workers have entered. women seen as heterogeneous (could work or not work), income elasticity fixed income response predominantly spousal income.

family policies: Olivetti and petrongolo

family policies such as paternity leave, in-work benefits, childcare benefits. US trails behind other industrial nations. US female employment has fallen since 1990 factors complicating family policies: policy does not occur in a vacuum. must consider other policies, cultural climate, political climate. effects of policy dependent on the wage elasticities of labor supply and demand. theories of statistical discrimination may reinforce the belief that the comparative advantage of women is in the household. family policies most effective in lower income single mother homes.

waldfogel family wage gap

gender gap vs family gap: gender gap is ratio of median wages of full-time women to full-time men. family gap is wage difference between women with and without children. gender gap is narrowing, while family gap is widening. time spent in labor market, occupational changes, increased education, equal pay and policies have led to observed decline in gender gap since 80s and 90s. family gap has widened from 1970s-90s. relationship with increasing income inequality. due to poor maternity leave and childcare options, institutional market features, discrimination, lack of motivation. remedies: paid maternity leave, flexible hours, childcare

general vs specific human capital

general increases productivity in many jobs; specific increases productivity at one firm. who pays for specific human capital? worker, employer avoid adverse selection, implicit contract

anti discrimination legislation

history: pre-1960 there was blatant discrimination. protective labor legislation for women: two views: genuine concern vs restriction on employment in the guise of reform. early legislation: some fair employment laws by state; national fair employment laws set up during WWII by Roosevelt, but dropped after the war (applied to race), Kennedy commission on status of women found blatant employment discrimination, but made no recommendations to address this (why?) civil rights act 1964 even small amount of discrimination can have magnified effects -- motivation, equity, fairness, inefficient allocation of resources

explanations for why female dominated jobs may pay less

hours structure, riskiness, self employment, amenities (pleasantness, location, flexibility) women more likely than men to work part time part time work -- supply side: compensating wage differential. demand side

sexual assault on college campuses

human capital implications? civil vs criminal role of tile 9 -- protecting people from discrimination based on sex in education programs or activities which receive federal financial assistance.

taste-based theories: the discrimination coefficient

if discrimination is taste-based the discriminating unit receives disutility from interacting with a certain group: in this case women. -employers don't like to employ women, employees don't like to work with women, customers dont like to buy from women, etc. this disutility is summarized by the discrimination coefficient (d).

employee discrimination

if employer hires discriminated against employees and keeps existing workforce -- working together, the discriminated against group is less productive. employer options: sex segregate, pay differential, do not hire discriminated against group, if left alone leads to wage gap, diversity training

employer discrimination

if out of two groups A and B, B is discriminated against, the employer acts as if he has to pay d + W to group B. A and B have the same skills and are perfect substitutes in production. if there are relatively many non-discriminating employers and relatively few women seeking employment they may all be absorbed in non-discriminatory jobs in Becker's model: discriminating employers are maximizing utility not profits higher male wages than female. in very competitive industries, you would expect to see less discrimination.

feedback from societal discrimination into occupational choice

if women receive less of a return on a certain type of human capital they will invest less --> wages lower, not only bc of discrimination, but also less investment. similar impact of pre-market discrimination. intermittent labor force participation penalized less with general human capital, shorter/no on the job training, human capital that does not depreciate rapidly (all of these things tend to be associated with a flatter earnings profile) even if women decreased quit rates, increased labor force experience and tenure, and changed occupational/industry composition, up to 20% of the residual is left unexplained.

policy implications

increase amount and alter mix of human capital that women have in order to increase their earnings address discontinuous work histories

bertrand -- risk

individuals less likely to take risks sort into occupations with more stable earnings. Bertrand's experimental findings: women are more risk averse than men. men's willingness to take risk goes down steadily with age. women's rapidly declines during late teens to 30, flattening out and then further declining men display overconfidence more New York times -- are women better decision makers? neuroscientists have uncovered evidence suggesting that when the pressure is on, women bring unique strengths to decision making. when stressed, men have a large increase in cortisol level associated with more risky choices; whereas women have a small increase associated with better decision making performance.

human capital

investment in abilities linked to productive capabilities. a person rents the use of this human capital. types of human capital: education (formal), on the job training, experience, tenure, health care

beauraini and mascletab: effects of affirmative action on hiring decisions and performance

key findings: women rank unfavorably in the absence of a quota. the introduction of a quota significantly reduces gender discrimination. women rank favorably when a quota system is introduced. there is evidence of reverse discrimination in the quota treatments firm performance not affected by introduction of quotas. no evidence of a negative effect of affirmative action on behavior, but improved performance could have resulted from pure learning effect. study doesn't consider whether affirmative action may reduce the incentives for effort in the target group before the hiring stage, as it renders effort less important in determining success.

present value of an income stream

know formula individual chooses to go to college is pv of college > pv of hs. no college if pv college < pv hs. individual's decision depends on wage rate and discount rate (whether they are future or present oriented)

Oaxaca decomposition

know formula -- avg wage for men and women, decomposing into wm and wf and finding wfm, discrimination is wfm-wf. why it might be an underestimation: discriminatory practices lead to real productivity differences. why it might be an overestimation: omitted variable problem (work effort, strength, intensity of work, fields of specialization, quality of education, etc)

goldin's findings

looking at white married women, systematic pattern of change. substitution effects (wage elasticities) have increased then leveled off. income elasticities have decreased. negative income elasticity early in the century stemmed from division of labor within the home -- the higher the husband's income, the more he demanded his wife's household production. these effects strengthened by desire to maintain status (husband whose wife worked was seen less favorably) -- this factor has decreased over time. initial increase in wage effect related to the rise in education among women, bc increased schooling enabled women to enter more pleasant jobs. but effect delayed by the existence of barriers to employment of married women. as women's jobs have become more similar to mens, training and intrinsic value of careers has made substitution effect smaller.

polachek: how the human capital model explains why the gender wage gap narrowed

married women's LFP rose dramatically from 4.6% in 1890-61.4% in 2001; men's LFP has been declining moderately over the same time period. key takeaway: human capital model predicts smaller gender wage gap as male-female work expectations become similar there are costs and benefits to human capital acquisition. the more years one works, the greater their opportunity to reap the benefits of human capital. on average women work less hours than men in their lifetime, so we expect them to purchase less human capital, widening relative wage gap. but if female LFP rises and male LFP falls, women expect to work more hours and thus invest in more human capital and get higher relative wages, narrowing the wage gap.

why women experience less returns to an MBA

may have initially over invested bc they were using the avg man's return to an MBA to make their investment decision the gap could be a glass ceiling (discrimination) and/or choice based representing CWD that reduce women's earnings when they choose positions that better complement balancing market and non-market work.

duncan index of dissimilarity

measuring degree of segregation: percent of men and/or women who would need to change jobs to obtain complete integration. as increase number of occupational categories, the higher the value of the resulting Duncan index. need to standardize for comparisons: controlling for the size of occupations over time. helps to differentiate whether or not change in the index occurs as a result of increased integration as opposed to change in size of the relative occupations.

occupational segregation: US example

median earnings of women and men by type of bachelor degree. age 25-34 bachelors in stem fields -- fraction of wage gap due to differences in the distribution of types of bachelor degrees

decomposition into mix and sex composition

mix effect: assumes that percentage of a major that is female and male remains constant over a particular time interval, but the relative size of majors can change. sex composition effect: assumes the relative size of each major remains the same but the percentage of each major that is male or female can vary.

discrimination and profits

non-discriminating firm hires workers until MRP = wage a firm with d>0 will not make the highest possible profit firms that discriminate could pay less and employ more people -- maximizing utility not profits. discrimination doesn't pay -- discriminatory firms should be competed out of the market. in theory greater competition leads to less of a wage gap.

wage discrimination

one outcome of discrimination. dichotomous variable

human capital theory

one's incentive to invest in training is directly proportional to the time one expects to work over their lifetime. this predicts that as women's relative LFP rises, women's relative human capital investment rises, and thus women's relative earnings rise.

amenities/disamenities

pleasantness of jobs, hour structure, flexibility (working from home), location

trends in job tenure

previous research found a divergence in tenure patterns by gender -- driven by changes specific to married women and mothers. the consistent pattern of declining employer tenure among men and never-married women suggests a broad pattern in the labor market -- countering decline for married women/mothers. increases in tenure among mothers corresponding to periods of rising LFP, more employment continuity

affirmative action

put into place under Johnson to include sex as a protected class. applies to government contractors. an affirmative action program could also be required by a court as a remedy for past discrimination or as a voluntary remedy for past patterns of discrimination. plus: efficiencies (expands pool)/addresses feedback from discrimination to human capital investments cons: tokenism, stigma

rape tax -- post et al

sexual violence has an economic cost. (can be viewed as an economic crime bc of the very costly short and long term financial burdens that sexual violence and rape can cause) tangible costs: medical care, mental health services, loss of economic productivity, criminal prosecutions. intangible costs: psychological pain and suffering, depression, low self-esteem, difficulty concentrating, fear of victimization. consequences of these costs: state and federal governments experience economic burdens. victims pre-market and/or market work activity may be affected. pre-market: no longer invest in one's education. market: taking leave, less productive article's calculation of cost is an underestimate of true total cost. should classify sexual violence as public health issue, have more preventative measures, viewed as economic crime so that survivors can be protected.

differences in optimal levels of schooling: discount rates and specializations

so far we assumed that the individual uses the interest rate as their discount rate, but the individuals discount rate can be higher or lower than the market discount rate. people who discount the future a lot have high discount rates; people who are more patient (less present-oriented) have a low discount rate. differences in discount rates: if A and B are equally able but A has a higher discount rate, A will choose less schooling. schooling levels can also differ bc individuals have different specializations -- higher paying specializations shift the wage-schooling locus upward. if A and B have the same discount rate but A selects a specialization with higher expected returns, A will choose more schooling.

experience earnings profile

steeper for full time, longer hours in full time, receiving formal education or OJT.

age earnings profile

steeper with greater human capital. rate of return on college varies over time -- due to relative demand and supply of two types of workers. males have steeper and higher age-earnings profiles

recruitment in symphony orchestras -- fasang

study focuses on German symphonies' claim that blind auditions ensure gender neutrality. invitation to audition based on written application, audition blind very low proportions of women in orchestras, hasn't grown higher percentage of men in musical organizations growing up will cause more women to quit before college. more women playing woodwind instruments in HS and men playing brass instruments hierarchical segregation in orchestras: men hold more positions in higher tariff classes, more color positions, orchestras are in public sector so less competitive variables: invitation ratio and job ratio conclusions: increased competitive pressure among applicants seem to decelerate trend towards lower gender segregation. women placed at the end of the labor queue. blind audition neutrality almost irrelevant bc of applications. unions might be partly responsible for continuing segregation. would need anonymous applications for blind auditions to work.

persistence of occupational segregation

taste/abilities efficiency comparative advantage, complement market/non-market work market imperfections -- information social welfare part time vs full time/overtime supply vs demand side explanations

human capital vs discrimination theory

these trends cannot be explained by discrimination theory, bc why would employers discriminate more against married women than single women? arguments that corporations refuse to train women are incompatible with economic theory. both employers and employees share training's costs and benefits; proportion of training costs paid by an employer exactly equals the proportion of productivity gains the company keeps.

disparate treatment/impact

treatment: intent to discriminate impact: outcome not necessarily intent cases: decision of Supreme Court that employer needed to show burden of proof in 1971 in 1989 burden of proof placed on employee

union membership

union premium: nonunion workers had median weekly earnings that were 82% of earnings for workers who were union members. in 2018, union membership rate still higher for men than women. the gap between their rates has narrowed considerably since 1983. on average, unionization raises women's wages by 12.9%.

wage gap

wf/wm = wage gap

what is discrimination in the labor market?

when workers who are equally productive on average are treated differently --> wages, hiring, promotion, firing/layoffs