Class-Biased Institutional Change and Rising Wage Inequality Kim A. Weeden David B. Grusky RC28, Brno, 2007

Fig. 1: Rising wage inequality, Men Women Variance ln(wages)

Standard explanation of take-off  Skill-biased technological change (SBTC)  Rising demand and increased productivity  Market assumption  Reaction to problems with SBTC account  Sniping is norm  Beyond sniping: Supplement SBTC account with complementary umbrella narrative that has reach of SBTC  Standing on the shoulders of giants: Parkin, Sørensen, DiPrete, Western, Morris, Picketty, and many more

Rent-based approach  Starting point: Extra-market institutions of rent extraction  Rents  Wages in excess of counterfactual wage under perfect market competition  Demand for labor cannot be met because of barriers to entry  Examples  Union wage premium  Minimum wage  Wage premium to occupational closure  Rent matters

Laws of motion of rent  Conventional view (e.g., Sørensen)  Rent destruction is global, inevitable  More inequality, but “structureless”  Class-biased institutional change (CBIC)  Rent destruction at bottom of class structure  Unions  Minimum wage  Rent creation at top of class structure  Successful occupational closure projects  Market expansion more likely for nonmanual workers  Asymmetry of rent creation and destruction is powerful force for inequality-generation  Why the asymmetry? Rent at top is better cloaked with efficiency story (as it’s only partly a “story”)

Rent creation  Diffusion of occupational “closure”  Licenses: Mandated by state  10% (1970s) to 20% (2004) of labor force: More licensed workers than union workers  MN data: 47 closed occupations in 1968, approx. 160 in 2004  Certifications: Voluntary credentials offered by associations also increasing (see Procertis)  Increasing use of educational credentials (e.g., MBA)  Expanding markets for services of closed occupations

CBIC account: Fractal change  Sectoral shift  Manual occupations (decline of unions, minimum wage)  Nonmanual occupations (specialized or abstract knowledge, market expansion)  Class shifts  Nonmanual sector winners: Managers (credentialing), sales (licensure and certification), professions (market expansion)  Manual sector losers (all classes but service)  Occupation shifts: “Matthew effect” in which occupations at top can more readily effect closure

Data  May/ORG CPS,  Wage and salary workers  Unedited earnings  Topcode imputation  Weighted by hours usually worked  1.8 million men, 1.6 million women  Approx. 500 occupations (indigenous SOC)  10 classes: Featherman-Hauser scheme ( prof., mgr., sales, clerical, craft, service, operative, labor, farm, farm labor)  2 sectors (nonmanual, manual)

Analytic approach  First cut: Are structural inequalities growing (i.e., four-way decomposition of variance in (log) wages)  BS: Between sector (manual vs. nonmanual)  BC: Between big class  BO: Between occupation  WO: Within occupation  Second cut: Are patterns of change consistent with CBIC account?  Is manual-nonmanual divide growing?  Are big classes winning and losing as predicted?  Is between-occupation inequality growing as predicted? Structural inequality

Fig. 2: Decomposition of men’s total wage inequality Total WO BS BO Variance ln(wages) Struct. BC

Table 1: Estimated change in components of men’s wage inequality Component % of total increase % share in 1973 % share in 2005 Structural Between- sector Between- class Between- occupation

Fig. 3: Decomposition of women’s wage inequality Total WO BC BO Variance ln(wages) E Struct BS

Table 2: Estimated change in components of women’s (total) wage inequality Component % of total increase % share in 1973 % share in 2005 Structural Between- sector Between- class Between- occupation

Conservative test  Structural component is partly generated by education and experience differences  Example: When JD instituted as requirement for becoming a lawyer, two interpretations of resulting restriction on labor supply obtain  SBTC: New educational requirement reflects new skill requirements  CBIC: New educational requirement is imposed without precipitating changes in skill  Lower-bound estimate: How large are structural effects if education and experience are given over wholly to STBC?  Residual wage inequality (i.e., standard Mincerian wage regression)  Education (5 categories)  Potential experience quartic  Full interactions between education and experience

Table 3: Structural share of residual wage inequality Component MenWomen % share in 1973 % share in 2005 % share in 1973 % share in 2005 Structural Between- sector Between- class Between- occupation

Fig. 4: Nonmanual sector: Men’s residual wages Mgr. Prof. Clerical NOTE: Trends are smoothed with 3-year moving average, and are net of occupational composition Smoothed Coefficient Sales

Mgr. Prof. Clerical NOTE: Trends are smoothed with 3-year moving average, and are net of occupational composition Smoothed Coefficient Sales Fig. 5: Nonmanual sector: Women’s residual wages

Craft Labor Service NOTE: Trends are smoothed with 3-year moving average, and are net of occupational composition Smoothed Coefficient Oper. Fig. 6: Manual sector: Men’s residual wages

Craft Labor Service NOTE: Trends are smoothed with 3-year moving average, and are net of occupational composition Smoothed Coefficient Oper. Fig. 4: Manual sector: Women’s residual wages

Summary of class-specific trends  Nonmanual sector  Managers and professionals pulling away (esp. after 1982)  Sales: Curvilinear trend explicable in rent terms  Clerical workers: Wage declines  Manual sector  Craft, operative, and labor wages declined (except that craft wages for women increased in 1970s)  Service class wages increased

Conclusions  CBIC account has potential (albeit evidence is just as indirect as that on behalf of SBTC)  Implications for future of inequality  Decline in inequality is not intrinsic effect of industrialization (e.g., Kuznets Curve) but historically contingent process  Rent-creation at top has more staying power  Culture: Cloaked with efficiency story  Power: Backed by powerful actors  A long run-up is plausible