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Class-Biased Institutional Change and Rising Wage Inequality Kim A. Weeden David B. Grusky RC28, Brno, 2007
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Fig. 1: Rising wage inequality, 1973-2005 Men Women Variance ln(wages)
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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
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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
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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”)
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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
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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
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Data May/ORG CPS, 1973-2005 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)
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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
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Fig. 2: Decomposition of men’s total wage inequality Total WO BS BO Variance ln(wages) Struct. BC
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Table 1: Estimated change in components of men’s wage inequality Component % of total increase % share in 1973 % share in 2005 Structural66.330.943.5 Between- sector 38.75.817.5 Between- class 6.311.59.7 Between- occupation 21.313.616.4
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Fig. 3: Decomposition of women’s wage inequality Total WO BC BO Variance ln(wages) E Struct BS
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Table 2: Estimated change in components of women’s (total) wage inequality Component % of total increase % share in 1973 % share in 2005 Structural55.237.745.9 Between- sector 18.712.715.5 Between- class 13.013.213.1 Between- occupation 23.611.817.3
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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
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Table 3: Structural share of residual wage inequality Component MenWomen % share in 1973 % share in 2005 % share in 1973 % share in 2005 Structural22.925.027.428.9 Between- sector 0.23.05.6 Between- class 9.56.48.411.3 Between- occupation 13.315.613.418.0
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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
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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
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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
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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
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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
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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
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