1 THE MOST EGALITARIAN OF ALL PROFESSIONS PHARMACY AND THE EVOLUTION OF A FAMILY- FRIENDLY OCCUPATION
2 WHY ARE THESE PEOPLE SMILING?
3 The Most Egalitarian of All Professions: Pharmacy and the Evolution of a Family-Friendly Occupation Penalty to workplace flexibility and its impact on the gender gap Compensating differentials model Mid-Western Pharmacy Research Consortium surveys for 2000, 2004, 2009, termed the Pharmacist Workforce Surveys Pharmacy is the most egalitarian of all professions High and increasing earnings relative to other professions High earnings for women relative to men 8 th highest paid occupation for men and 3 rd highest for women out of 460 Census occupations in 2010 $119K Median Annualized Earnings for Pharmacists in 2013 in OES
4 Relative Earnings (Median, FT-FY) of Pharmacists, 1970 to 2010: Females 1,6 1,4 Pharm/Physician Pharm/Lawyer Pharm/Vet 1,2 1,0 0,8 0,6 0,4 0,2 0, Notes: Restricted to 25 to 64 years full-time (35+ hours/week), full-year (40+ weeks/ year) workers.
5 Relative Earnings (Median, FT-FY) of Pharmacists, 1970 to 2010: Males 1,4 1,2 Pharm/Physician Pharm/Lawyer Pharm/Vet 1,0 0,8 0,6 0,4 0,2 0, Notes: Restricted to 25 to 64 years full-time (35+ hours/week), full-year (40+ weeks/ year) workers.
6 U.S. Census 1970 to 2000 and ACS, : Median Earnings Ratios (F/M) for Full time, Year round Workers 1,0 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0, ,0 Dentists Lawyers Optometrists Pharmacists Physicians Veterinarians
7 Gender Annual Earnings Gaps for Selected Occupations ACS, Full Time, Full Year Workers, Years Old F/M Median Earnings F/M Mean Earnings Median Female % in Male Dist SD Log Earnings for Males Pharmacists Dentists Lawyers Optometrists Physicians Veterinarians Pharmacists have smallest gender earnings gap since (1) women are higher in the male earnings distribution; and (2) male earnings are more compressed than in other occupations
8 Full time, Full year with Time and Education Controls, ACS 0,05 Atmosph & Space Scnts Ln (Male Wage and Business Income) 0,00 11,0 11,1 11,2 11,3 11,4 11,5 11,6 11,7 11,8 11,9 12,0 12,1 0,05 Chem Engineers Engineering Mngrs Coefficient on Female Occupation 0,10 0,15 0,20 0,25 0,30 0,35 Chiros Airplane Pilots Optometrists Veterinarians Pharmacists Petrol & Mining Engs Economists Personal Fin Advisers Actuaries Lawyers & Judges CEOs Dentists Physicians & Surgeons 0,40 0,45 Financial Specialists Podiatrists health business tech science other Controls and sample: age as a quartic, race, ln(hours), ln(weeks), education, ACS years; none with < 25 individuals either male or female; 35+ hours, 40 + weeks; 25 to 64 year olds.
9 The Most Egalitarian of All Professions: Pharmacy and the Evolution of a Family-Friendly Occupation Penalty to workplace flexibility and its impact on the gender gap Compensating differentials model Mid-Western Pharmacy Research Consortium surveys for 2000, 2004, 2009, termed the Pharmacist Workforce Surveys Pharmacy is the most egalitarian of all professions High and increasing earnings relative to other professions High earnings for women relative to men Low variance in earnings Fairly linear earnings with respect to hours (contrast with lawyers & MBAs) Women with children take off little time; high part-time; low hours; similar in demographic characteristics to male pharmacists
10 Compensating Differentials Model of Gender Gaps Demand by workers: D 0 = amenity 1 = disamenity C = consumption U(C, D), such that U(C 0, 0) = U(C*, 1) and C* > C 0. Z = (C* C 0 ) Z ~ G(Z), workers are heterogeneous with regard to tastes for the amenity (disamenity) ΔW = W(D = 1) W(D = 0) Supply by firms: B = costs to firm of amenity (benefit from disamenity) B ~ F(B): firms are heterogeneous with regard to the costs of providing the amenity (the benefits to having the disamenity)
11 Assume ΔW* is the compensating differential. If Z < ΔW*, take job with disamenity. If Z > ΔW* do not, because compensation is too low. G(Z) U(C, D), such that U(C 0, 0) = U(C*, 1); C* > C 0 Z = (C* C 0 ); Z~G(Z) ΔW = W(D = 1) W(D = 0) D = 0 ΔW* Schematic Representation of the Market for an Occupational Amenity (D= 0) Part A: Amenity demand by workers ΔW
12 Assume ΔW* is the compensating differential. If B < ΔW*, get rid of disamenity b/c cost is less than compensation. If B > ΔW* pay compensatory amount b/c cost is too great. D = 0 F(B) ΔW* Schematic Representation of the Market for an Occupational Amenity (D= 0) Part B: Amenity supply by firms ΔW
13 G M (Z) G F (Z) (D M = 0)+ (D F = 0) ΔW** Schematic Representation of the Market for an Occupational Amenity (D= 0) Part C: Amenity demand by two types of workers ΔW
14 Wage/time B = 0 A = 0 Job flexibility Job inflexibility
15 ΔW Supply 0 ΔW* Demand 0 Amenity Schematic Representation of the Market for an Occupational Amenity Equilibrium in the Market for the Amenity ΔW = wage difference between earnings without and with the amenity
16 ΔW Supply 0 Increase in preferences for the amenity ΔW* Demand 0 Demand 1 Amenity Schematic Representation of the Market for an Occupational Amenity Equilibrium in the Market for the Amenity ΔW = wage difference between earnings without and with the amenity
17 Compensating Differentials Model of Gender Gaps: Implications Demand for amenity. An increase of those who value the amenity (e.g., women) will: Increase ΔW* and therefore likely to widen the gender gap Increase the fraction of the workforce with the amenity Decrease the fraction of men with the amenity
18 ΔW Increase in productive benefits from the amenity or decrease in costs of getting rid of disamenity Supply 0 Supply 1 ΔW* Demand 0 Demand 1 Amenity Schematic Representation of the Market for an Occupational Amenity Equilibrium in the Market for the Amenity ΔW = wage difference between earnings without and with the amenity
19 Compensating Differentials Model of Gender Gaps: Implications Supply of amenity. A change in production technology that decreases the cost of producing the amenity will: Decrease ΔW* and therefore likely to reduce the gender gap Increase the fraction of the total workforce with the amenity Increase the fraction of men with the amenity
20 Motivation from National Trends: Rising female share of college attendees and graduates; Age at first marriage increased for college graduates; Deferred births; rising share of college women having births in their thirties; Increased share of women in various professions (e.g., M.D., J.D., M.B.A., Ph.D., Pharmacist, Veterinarians); Implications for career and family tradeoffs, particularly among the educational elite; Popular press speculation about opting out and the squandering of elite college education and professional degrees by women.
21 College Graduate Share at Age 30 by Sex, U.S. Born College Graduate Share Year of Birth Male Female
22 0,6 0,5 Fraction Female among Professional School Graduates Med Law Dental MBA 0,4 0,3 0,2 0,1 0, Year of Professional School Graduation
23 0,8 Fraction Female among Professional School Graduates 0,7 0,6 0,5 Optometrist Chiropractor Veterinarian Pharmacist 0,4 Pharmacy 0,3 0,2 0,1 0, Year of Professional School Graduation
24 Major Changes in U.S. Pharmacy Sector since 1970 Pharmaceutical industry: greater standardization in drugs being directly produced by pharmaceutical companies rather than being compounded in pharmacies and hospitals IT changes: Extensive use of computer systems that track clients across pharmacies, insurance companies, and physicians mean that any licensed pharmacist can know a client s needs as well as any other Both changes make pharmacists better substitutes for each other Increase in economies of scale in pharmacy sector from integration of pharmacies with general retailers and grocery stores (e.g., Walmart) Leads to increase in share of pharmacists who are employees and managers in chain retailers and in hospitals Reduces market share of independent pharmacies and share self-employed Rapid growth in demand for pharmaceuticals with aging population, medical advances, and Medicare Part D
25 Changes in Pharmacist Work Force Pharmacist Training: Four to Six Years of College Training in pharmacy (currently 5-year B.S. degree know as PharmD) plus practical experience and state license to practice pharmacy in U.S. Pharmacy has become a female-friendly occupation Female share of pharmacy graduates up from 14% in 1960s to 65% in 2010 Female share of active pharmacists up from 8% in 1960 to 55% in 2010 Large decline in share working in independent pharmacies from 78% in 1957 to 14% in 2009 Large decline in self-employment share from 40% in 1966 to 4% in 2010 Percent working part-time up from 9% in 1970 to 19% in 2010 from rising female share Share of female pharmacists working part-time declined from 36% in 1970 to 27% in 2010
26 Fraction Female among All Pharmacists and Pharmacy Graduates 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0, Fraction Female All Pharmacists Fraction Female Graduates
27 Fraction Female by Age of Pharmacist PWS 2000, 2004, ,9 0,8 0,7 Fraction female 3 year centered moving average 0,6 0,5 0,4 0,3 0,2 0,
28 Fraction of Pharmacists Working in Independent Practice, by Sex: 1957 to ,8 0,7 0,6 0,5 0,4 0,3 0,2 0, Fraction Ind Male Ind. Female Ind.
29 Pharmacists: Fraction Female, Gender Pay Gap, Fraction Working in Independent Practice, 1965 to ,7 0,6 Working for independent pharmacy Female/Male Median Annual Earnings w f /w m 0,95 0,9 0,5 0,85 0,4 Fraction female 0,8 0,3 0,75 0,2 0,7 0,1 0,65 0 0,
30 Pharmacy Setting Type and Position: 2000s Setting, Position Males Females Setting type Independent Chain, Mail order, etc Hospital Other Position Employee Manager Owner Source: Pharmacist Workforce Surveys (PWS).
31 Demographics of Active Pharmacists: 2000s Males Females Demographics (for year olds) Ever-married Number of children a Number of children conditional on having one a No children a No children, years a Source: Pharmacist Workforce Surveys (PWS).
32 46 Weekly Hours by Age and Gender, Pharmacists 2000, 2004, Male Female Source: Pharmacist Workforce Surveys (PWS).
33 Fraction Part Time, Pharmacists 2000, 2004, ,45 0,40 0,35 0,30 0,25 0,20 0,15 0,10 0,05 0, Male Part-time Female Part-time Source: Pharmacist Workforce Surveys (PWS).
34 Gender Earnings Gap for Active Pharmacists 27 log point raw gender earnings gap in PWS in 2000s Reduced to 7.6 log points with controls for hours/weeks and 4.7 log points in hourly wage and 4 log points with controls Earnings essentially linear in hours for pharmacists (some measurement error downward bias in hours/weeks) Shorter work week of female pharmacists is largest single component of annual gender earnings gap Females work 6.6 fewer hours per weeks than males (36.6 vs. 34.2) account for a 20 log point earnings gap Gender differences in hours worked only for those with children (3 log point raw gap for those w/o children vs. 33 log points with children) Women more likely to be employees than managers or owners accounting for a few points in gap Little impact of labor market experience on pharmacist earnings Smaller part-time work penalty in pharmacy than other occupations for college graduates in 2000s not different in 1980
35 Ln (Annual Total Earnings), Pharmacists 2000, 2004, 2009 Currently Active Pharmacists Variable (1) Annual (2) Annual (3) Hourly (4) Annual (5) Annual Female Children Female children Ln (hours) Ln (weeks) Owner Manager Year dummies Yes Yes Yes Yes Yes Age in quadratic, Race Yes Yes Yes Yes Yes Education Yes Yes Yes Yes Yes Sector Yes Yes Yes Yes Yes Number of observations 3,508 3,508 3,508 2,610 2,610 R S.e.e Source: Pharmacist Workforce Surveys (PWS).
37 Hourly Wage Penalty for Part-time Work by Pharmacists (col. 1) and All College Graduates (cols. 2, 3) PWS CPS, College Graduates (1) (2) (3) Female (dummy) ( ) (0.0249) ( ) Part-time (dummy) ( ) ( ) ( ) Pharmacist (dummy) (0.0177) Pharmacist female (0.0429) (0.0226) Pharmacist part-time (0.0334) (0.0304) Occupation dummies no yes R Total observations 1, , ,845 Pharmacist observations 1,640 1,891 1,891 Sources: Pharmacist Workforce Surveys (PWS), 2000 and 2004; CPS-MORG, 2005 to 2011.
38 Pharmacists vs. MBAs and Lawyers: Linear vs. Nonlinear Occupations Pharmacy is a classic linear occupation Earnings fairly linear with respect to hours worked Women with children earn less than males since work fewer hours and many part-time but a negligible part-time penalty Business (MBA) and Law (JD) remain classic nonlinear occupations U. Chicago MBAs little gender gap 1 year out rises to 60 log points at 15 years out children, time out, lower hours MBAs: Large nonlinear costs to time out and lower hours U. Michigan Lawyers large growth in gender earnings gap in first 15 years out also substantially associated with children Nonlinear rise in earnings with hours worked also seen in hourly fees
39 Annual (Log) Earnings Gender Gap for University of Chicago MBAs by Years since MBA 0,1 Gender Gap in (Log) Annual Earnings 0 0,1 0,2 0,3 0,4 0,5 Years since MBA No controls 2. Pre MBA charac. 3. MBA performance 0,6 Controls and sample: University of Chicago MBAs 1990 to 2006, all regressions include cohort year dummies. See Bertrand, Goldin and Katz (2010).
40 Annual (Log) Earnings Gender Gap for University of Chicago MBAs by Years since MBA 0,1 Gender Gap in (Log) Annual Earnings 0 0,1 0,2 0,3 0,4 0,5 Years since MBA No controls 2. Pre MBA charac. 3. MBA performance 4. Labor market exp. 5. Weekly hours 6. Reason for choosing job 7. Job setting charac. 0,6 Controls and sample: University of Chicago MBAs 1990 to 2006, all regressions include cohort year dummies. See Bertrand, Goldin and Katz (2010).
41 Hours and Earnings of Law Occupations 15 Years after the JD Annual Earnings 1000 (2007$) Annual Earnings Fraction female With children Hourly Fee (2007$) Average weekly hours UM Law School Alumni Survey Research Dataset for individuals graduating from 1982 to 1991 who returned both the five year and 15 year surveys. Data given here are for those working > 9 hours/week at year 15. Source: Goldin (2014 AER)
42 Hours and Earnings of Law Occupations 15 Years after the JD Hourly Fee Annual Earnings (2007$) Annual Earnings Hourly Fee (2007$) Average weekly hours UM Law School Alumni Survey Research Dataset for individuals graduating from 1982 to 1991 who returned both the five year and 15 year surveys. Data given here are for those working > 9 hours/week at year 15. Source: Goldin (2014 AER)
43 Goldin (2014 AER) Framework 1. Why non-linearity? Need for employees to be around, facetime, contact with others, decision making frequency, interpersonal relations, costly hand off of clients, interdependent teams (e.g., law, finance). 2. Why linearity? Better substitutes, independent teams, role of scale, use of information systems to hand off clients (e.g., pharmacists, physicians, veterinarians, discount stockbrokers). 3. The more non-linear: Lower earnings of women with kids and fewer will have family and career. 4. The more linear: Higher relative earnings of women and more will remain in the labor force and have family and career.
44 Summary: Lessons from Pharmacists Much of the gender gap is due to career penalties from family-related lower hours and time off. Relative earnings for women in various professions have increased and part is due to a reduction in the penalties. Career cost of family is low in some professions, such as pharmacy, and the gender gap is also low. Penalties in pharmacy have decreased because of changes in the organization of the industry that reduced costs to firms. Does not appear driven by licensing requirements or regulations in pharmacy vs. other licensed occupations (law, medicine, veterinarians, ) But other professions have changed little and have had the greatest exit of women. Pharmacy is the most egalitarian of all professions.
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