Chapter 7 Women at Work Outline of Chapter: 1) Review employment trends and discuss various reasons for observed trends. 2) Economics of employment behavior. Key terms: –Employment –Unemployment –Labor force participation rate (LFPR) –Measured with CPS.

Review LFP Trends Table 7.1: –LFPR by sex and race (U.S. in year 2002). –Shows breakdown for entire population, then prime-aged workers (to exclude students and retirees). –By race/ethnicity. Figure 7.1: –LFPR over time for men and women. –Note  for men and  for women – Men Women –1950: 86% 34% –2001: 74% 60%

Further Details Concerning Female LFP Figure 7.2: –Female LFP by marital status over time. Married Single % 44% % 68% Other persisting differences: –Ex., married women more likely to work part-time than single women. Figure 7.3: Female LFP in 2002 for ages 25+, by education (relates to increasing potential market wage). Table 7.2: Female LFP over time for selected countries. –Usefulness of int’l comparisons.

Women’s Work Over the Lifecycle Supplemental Figure 3.7: –Age-participation profiles for years 1940, 1960, and –Each separate year’s profile: a snapshot of data, so not following the same person over time. –To note: change in LFP at peak- childbearing years. Lifecycle patterns by birth cohorts: (whites only). –Research by Claudia Goldin. –Plots same birth cohort over a lifetime Birth cohort: individuals born in same decade but not same people –Helps to explain relatively low wages for older working women (limited experience).

Notes From Goldin’s Research on Lifecycle Employment Patterns Table 7.3: Compiled data from U.S. decennial censuses to construct 6 birth cohorts –Follow a single cohort across each row. Youngest age range: –Huge difference by marital status; –Implies nearly all women drop out of LF upon marriage; –Difference slowly falls as move to more recent cohorts (comparing 1 st 2 columns) First cohort: –See birth years: –Very low LFP all periods, even when children probably grown up.

More Using Goldin’s Birth Cohorts To notice: –1) 2 nd cohort: noticeable  LFP after age 45; still only about 1/5 working. –2) 3 rd cohort: 1 st time get big  LFP starting age 35 (17% to 25%). –3) 3 rd and 4 th cohort: noticeable  LFP starting age 25. –4) 5 th cohort: More young working, interpreted as less LF withdrawal at marriage, more at pregnancy. Little change between first two periods due to baby boom. Big  LFP at each age range. Now over half of older women work. –5) 6 th cohort: now LFP for married young is 75% of LFP for single young.

Major Trends for Shown Cohorts Major trends: –Early on, LF withdrawal at marriage; near-permanent end to paid work. –Later, some LF withdrawal delayed till pregnancy; still most never work again. –At end: LF withdrawal at pregnancy but more return as kids age. –Relate back to Supplemental Figure 3.7.

Implications for Wage Comparisons Important implication for comparing wages across sex: –Consider which cohorts included in wage averages. If have individuals from earlier cohorts, they are likely to have little work experience throughout their lifetimes so will have lower wages. Implies that some of wage gap will go away once the earlier cohorts age their way out of the data, leaving more and more female workers with full (or nearly full) lifetime work histories.

Historical Experience of College Women Research by Goldin: –Family and work experiences of college-educated throughout 1 st half of 20 th century. For that 1 st birth cohort: –For both men and women, college rare around year 1900 –For women: very rare to combine work and family. –1/3 of women who went to college never married. –Nearly half never had kids (including ¼ who did marry). –Occupations: 60% school teachers.

More on College and Work Trends As move forward by cohort: college-educated women more and more likely to marry and have kids. From then to now: –First choice was work or family. –Then choice was work and family. –Now with so many more college- educated women, choice is career then family. Claudia Goldin: –Chaired economics professor at Harvard; –1972 PhD from Univ. of Chicago. –Never had children.

Economic Model of Paid Hours/Employment Original model: –Modeled choice between paid work and leisure. Model set up: –Fixed total number of hours that individual chooses to divide between work and leisure (L + M = T). –Factors that affect decision include own preferences for work vs leisure, market wage, and nonlabor income. –Model assumes individual will maximize utility subject to budget constraints (limits on time, money to spend, etc.). –Individual has no influence on market wage (W same for each hour worked).

More on Economic Model of Work Marginal decision-making: –Actually two margins: Hours of work; Employment. Hours choice easier to understand: –Question: Should I  work hours by 1 (and therefore  leisure by 1)? –Answer: I will  work by 1 hour as long as the market values my time more than I do. –Relate to employment choice:  work hours implies  probability of being employed. Market time valuation: wage Leisure time valuation: How I am willing to trade off work/leisure.

More on Original Model of Work Both time valuations measured on the margin: for extra hour. Marginal value of time in mkt: MVT M = MU M = change in utility from  paid work by one hour. MU M =  U/  M Or: MU M = [  U/  C *  C/  M] So: MU M = MU C * w/P If  M then  MU C so  MU M Diminishing marginal utility.

More on Economic Model Marginal Value of Leisure Time: MVT L = MU L = change in utility from  leisure by one hour. As L  then MU L . Diminishing marginal utility. Formal Rule: –Keep  work by one hour as long as MVT M  MVT L. Utility maximizaton : –I.e., best choice about work/leisure. –MVT M = MVT L for last work hour added.

What is Effect of  in Nonlabor Income? To start: –Assume Mark has maximized utility subject to his budget constraint so that he is working for pay 40 hours per week with wage = $10/hour. Now there is an  nonlabor Y: –Law of Demand: any  Y   demand for all normal goods including leisure   paid work hours. –Hours of work margin:  pd hrs. –Employment margin:  probability of working for pay (because it means a higher market wage is required to induce Mark to work for pay). –Effect is opposite if nonlabor Y falls.

What is Effect of  Wage? To start: (same as before) –Assume Mark has maximized utility subject to his budget constraint so that he is working for pay 40 hours per week with wage = $10/hour.  wage to $15/hr (an  MVT M ): –Substitution effect:  w is an  opportunity cost of leisure, so  demand for leisure and  paid work hours. –Income effect:  w is like  real purchasing power (  Y ), so causes  demand for all normal goods including leisure, which means work hours fall. –Key: net effect is uncertain. Cannot know in advance if  wage will cause work hours to go up or down.

Effect of  Wage on Employment For women: –Dominant substitution effect, at least at lower wages. –Macunovich: suggests that perhaps income effect has become more dominant in recent years. Employment Margin: 1) If only working few hours per week: –  wage could cause person to leave labor force. 2) If start out of LF and then wage increases: –Causes only substitution effect so will increase probability of working for pay.

Modify Original Model Problem with the model: only allows for two uses of time: paid work or leisure. In reality, 3 choices: paid work, home (unpaid) work, leisure. –Now: M + L + H = T. Influx of women into labor market led to expansion of model. So now each of the three choices has its own marginal valuation:

Three Activities Review leisure and mkt time: MVT M = MU C * wage. MVT L = MU L Third Use of Time: Home Prod. MVT H = MU H: MU H = MU G * MP H.  H   MP H so MU H . [known as diminishing marginal productivity]  G   MU G and so  MU H.

Best Choice When Have 3 Uses for Time Marginal decision-making: Choose M*, L*, and H* such that: Always equate utility on the margin: increase time in an activity until marginal value of time equal for all 3 activities. Remember: must always satisfy the time constraint: M* + L* + H* = 24.

More on Expanded Work Theory Whenever  work by 1 hour: –Same as  (L + H ). –Individual is  leisure by 1 hour or  unpaid home work time by one hour. –To restate: when  M:  L so  MU L ;  H so  MU H.  M   MU M (due to  M   C   MU C ) –Comparative Statics: 1) Effect of  wage. 2) Effect of  nonlabor income. 3) Effect of kids. 3) Effect of  in household production.

Explaining  LFP Using Comparative Statics 1. Effect of  husband’s earned income: –Like any  nonlabor income: Demand theory: will  D for all normal goods including leisure   paid work and  home production. –Will  MVT M since will  MU C (as purchase more from husband’s increased income). Relate to real world: –Explains race differences in LFP. –Does not explain  female LFP since husband’s Y has been  until very recently. Contradicts notion that married women “pushed” into LF from low husband’s Y.

Continue with Comparative Statics 2. Effect of  female wages: –Rising wages  opportunity costs of leisure and home production so will  both and  LFP. (pure substitution effect) –Remember: MVT M = MU C * wage. So  wages is an  MVT M. Relate to historical trends: –Wages  throughout 1900s but mostly from after WWII till early 1970s.

Continue with Comparative Statics 3. Children and LFP: –Presence of children (young kids in particular) will increase value of time in home production for all hours (  MVT H ) so will reduce paid work and leisure. –Relate to history: fewer kids so lower MVT H. 4.  Home Productivity (  MP H ): –Impact is unclear—complicated. –Relate to history: much  so probably contributed to  LFP.

Evidence from Costa (2000) Summarized evidence about importance of married women’s wages on their LFP. Divides 20 th century into 3 periods: 1) 1900 – 1930: little influence of own wages; primary influence was husband’s income. 2) Mid-century: big influence of own wages. 3) End of century: less influence of own wage or husbands’ income as LFP became norm.

Exercise For Country X: –Population = 100,000; –Employed = 60,000; –Unemployed = 3,000; –Not in LF = 37,000. Answer these questions: –1) Calculate size of LF; LFPR, and unemployment rate. –2) Give examples of not in LF. –3. Give reasons woman might switch from not in LF to LF. –4) If go into recession, what expect will happen to: A. # employed and # unemployed. B. # not in LF.