THE MOST EGALITARIAN OF ALL PROFESSIONS PHARMACY AND THE EVOLUTION OF A FAMILY- FRIENDLY OCCUPATION
WHY ARE THESE PEOPLE SMILING?
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
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 0,0 1970 1980 1990 2000 2007 2010 Notes: Restricted to 25 to 64 years full-time (35+ hours/week), full-year (40+ weeks/ year) workers.
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 0,0 1970 1980 1990 2000 2007 2010 Notes: Restricted to 25 to 64 years full-time (35+ hours/week), full-year (40+ weeks/ year) workers.
U.S. Census 1970 to 2000 and ACS, 2006 2008: 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 0,1 1970 2007 1980 2000 0,0 Dentists Lawyers Optometrists Pharmacists Physicians Veterinarians 1970 1980 1990 2000 2007
Gender Annual Earnings Gaps for Selected Occupations 2009 10 ACS, Full Time, Full Year Workers, 25 64 Years Old F/M Median Earnings F/M Mean Earnings Median Female % in Male Dist SD Log Earnings for Males Pharmacists.922.849 38.2.458 Dentists.688.732 32.0.691 Lawyers.792.706 34.9.740 Optometrists.850.760 35.5.617 Physicians.590.673 30.5.799 Veterinarians.785.712 32.3.635 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
Full time, Full year with Time and Education Controls, 2009 2011 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.
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
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)
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
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
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
Wage/time B = 0 A = 0 Job flexibility Job inflexibility
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
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
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
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
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
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.
College Graduate Share at Age 30 by Sex, U.S. Born College Graduate Share 0.05.1.15.2.25.3.35.4 1875 1890 1905 1920 1935 1950 1965 1980 Year of Birth Male Female
0,6 0,5 Fraction Female among Professional School Graduates Med Law Dental MBA 0,4 0,3 0,2 0,1 0,0 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Year of Professional School Graduation
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 0,0 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Year of Professional School Graduation
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
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
Fraction Female among All Pharmacists and Pharmacy Graduates 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0,1 0 1950 1960 1970 1980 1990 2000 2010 Fraction Female All Pharmacists Fraction Female Graduates
Fraction Female by Age of Pharmacist PWS 2000, 2004, 2009 0,9 0,8 0,7 Fraction female 3 year centered moving average 0,6 0,5 0,4 0,3 0,2 0,1 0 25 30 35 40 45 50 55 60 65
Fraction of Pharmacists Working in Independent Practice, by Sex: 1957 to 2009 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0,1 0 1950 1960 1970 1980 1990 2000 2010 Fraction Ind Male Ind. Female Ind.
Pharmacists: Fraction Female, Gender Pay Gap, Fraction Working in Independent Practice, 1965 to 2010 0,7 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 0,6 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
Pharmacy Setting Type and Position: 2000s Setting, Position Males Females Setting type Independent 0.190 0.112 Chain, Mail order, etc. 0.437 0.412 Hospital 0.242 0.313 Other 0.131 0.162 Position Employee 0.543 0.738 Manager 0.337 0.235 Owner 0.120 0.027 Source: Pharmacist Workforce Surveys (PWS).
Demographics of Active Pharmacists: 2000s Males Females Demographics (for 25-44 year olds) Ever-married 0.813 0.825 Number of children a 1.343 1.213 Number of children 2.02 1.99 conditional on having one a No children a 0.333 0.392 No children, 40-44 years a 0.180 0.210 Source: Pharmacist Workforce Surveys (PWS).
46 Weekly Hours by Age and Gender, Pharmacists 2000, 2004, 2009 44 42 40 38 36 34 32 30 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 Male Female Source: Pharmacist Workforce Surveys (PWS).
Fraction Part Time, Pharmacists 2000, 2004, 2009 0,45 0,40 0,35 0,30 0,25 0,20 0,15 0,10 0,05 0,00 25-29 30-34 35-39 40-44 45-49 50-54 55-59 Male Part-time Female Part-time Source: Pharmacist Workforce Surveys (PWS).
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
Ln (Annual Total Earnings), Pharmacists 2000, 2004, 2009 Currently Active Pharmacists Variable (1) Annual (2) Annual (3) Hourly (4) Annual (5) Annual Female -0.235-0.0737-0.0402-0.0337-0.0100 Children 0.0360 0.0538 Female children -0.302-0.0843 Ln (hours) 0.823 0.867 Ln (weeks) 0.902 0.914 Owner 0.468 0.121 0.0527 0.462 0.0962 Manager 0.242 0.067 0.0326 0.251 0.0648 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 2 0.231 0.728 0.273 0.220 0.765 S.e.e. 0.439 0.261 0.268 0.452 0.249 Source: Pharmacist Workforce Surveys (PWS).
Hourly Earnings, Pharmacists 2000, 2004, 2009 70 65 60 Hourly Earnings, Current $ 55 50 45 40 35 30 25 30 35 40 45 50 55 60 65 Age Males 2000 Fems 2000 Males 2004 Fems 2004 Males 2009 Fems 2009
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) -0.0247-0.185-0.131 (0.00768) (0.0249) (0.00195) Part-time (dummy) -0.00416-0.249-0.135 (0.00863) (0.00313) (0.00298) Pharmacist (dummy) 0.262 (0.0177) Pharmacist female 0.0854 0.0465 (0.0429) (0.0226) Pharmacist part-time 0.195 0.0684 (0.0334) (0.0304) Occupation dummies no yes R 2 0.568 0.143 0.294 Total observations 1,640 329,845 329,845 Pharmacist observations 1,640 1,891 1,891 Sources: Pharmacist Workforce Surveys (PWS), 2000 and 2004; CPS-MORG, 2005 to 2011.
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
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 0 2 4 6 8 10 12 14 1. 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).
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 0 2 4 6 8 10 12 14 1. 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).
Hours and Earnings of Law Occupations 15 Years after the JD 400 400 350 350 Annual Earnings 1000 (2007$) 300 250 200 150 100 50 Annual Earnings Fraction female 0.830 0.353 0.229 0.185 With children 0.852 0.798 0.617 0.536 300 250 200 150 100 50 Hourly Fee (2007$) 0 0 20 25 30 35 40 45 50 55 60 65 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)
Hours and Earnings of Law Occupations 15 Years after the JD 400 000 400 350 000 Hourly Fee 350 300 000 300 Annual Earnings (2007$) 250 000 200 000 150 000 100 000 Annual Earnings 250 200 150 100 Hourly Fee (2007$) 50 000 50 0 0 20 25 30 35 40 45 50 55 60 65 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)
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.
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.
Pharmacist Earnings by Synthetic Cohorts and Sex: 2000, 2004, 2009 120 000 Males 120 000 Females 110 000 110 000 Cohort 1 Cohort 2 Cohort 3 Cohort 4 100 000 100 000 90 000 90 000 80 000 80 000 70 000 Cohort 1 Cohort 2 Cohort 3 Cohort 4 70 000 60 000 25 30 35 40 45 50 55 60 000 25 30 35 40 45 50 55