Wage Inequality and Varieties of Capitalism
Published online by Cambridge University Press: 13 June 2011
This article draws on a new data set that enables the authors to compare the distribution of income from employment across OECD countries. Specifically, the article conducts a pooled cross-sectional time-series analysis of the determinants of wage inequality in sixteen countries from 1973 to 1995. The analysis shows that varieties of capitalism matter. The authors find that the qualities that distinguish social market economies from liberal market economies shape the way political and institutional variables influence wage inequality. Of particular interest to political scientists is the finding that the wage-distributive effects of government partisanship are contingent on institutional context. Union density emerges in the analysis as the single most important factor influencing wage inequality in both institutional contexts.
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- Copyright © Trustees of Princeton University 2000
1 Cf. Wallerstein, Michael, “Wage-Setting Institutions and Pay Inequality in Advanced Industrial Societies,” AmericanJournal of Political Science 43 (July 1999Google Scholar).
2 Katzenstein, Peter, Small States in World Markets (Ithaca, N.Y.:Cornell University Press, 1985Google Scholar); Hall, Peter, Governing the Economy (New York:Oxford University Press, 1986Google Scholar); Esping-Ander-sen, Gosta, The Three Worlds of Welfare Capitalism (Princeton:Princeton University Press, 1990Google Scholar); Sos-kice, David, “Wage Determination,” OxfordReview ofEconomic Policy 6 (Winter 1990Google Scholar); and idem, “Divergent Production Regimes,” in Kitschelt, Herbert et al., eds., Continuity and Change in Contemporary Capitalism (New York:Cambridge University Press, 1999CrossRefGoogle Scholar).
3 In seeking to incorporate institutional insights into regression analysis, we follow the lead of Western, Bruce, Between Class and Market (Princeton:Princeton University Press, 1997Google Scholar); Garrett, Geoffrey, Partisan Politics in the Global Economy (New York:Cambridge University Press, 1998CrossRefGoogle Scholar); and Iversen, Torben, Contested Economic Institutions (New York:Cambridge University Press, 1999Google Scholar). However, none of these works explicitly tests the idea that causal dynamics vary by political economy type. Previous work in this particular vein includes O'Connel, Philip, “National Variations in the Fortunes of Labor,” in Janoski, Thomas and Hicks, Alexander, eds., The Comparative Political Economy of the Welfare State (New York:Cambridge University Press, 1994Google Scholar); and Swank, Duane, “Political Institutions and Welfare State Restructuring,” in Pierson, Paul, ed., The New Politics ofthe Welfare State (New York:Oxford University Press, 2000Google Scholar).
4 Cf. Wallerstein (fn. 1), 649; OECD, , Income Distribution in OECD Countries: Evidencefromthe Luxembourg Income Study (OECD, 1995Google Scholar); and Gottschalk, Peter and Smeeding, Timothy, “Cross-National Comparisons of Earnings and Income Inequality,” Journal of Economic Literature 35 (June 1997Google Scholar). For further specifications of the wage data used here, see OECD, , “Earnings Inequality, Low-Paid Employment and Earnings Mobility,” Employment Outlook (July 1996CrossRefGoogle Scholar).
5 The high level of wage inequality in Austria is partly attributable to the fact that the underlying wage data include part-time employees, but other data sources also indicate that the Austrian distribution of wages is quite inegalitarian by continental European standards. See Rowthorn, Bob, “Corpo-ratism and Labour Market Performance,” in Pekkarinen, Jukka, Pohjola, Matti, and Rowthorn, Bob, eds., Social Corporatism (Oxford:Clarendon Press, 1992Google Scholar); and Pontusson, Jonas, “Wage Distribution and Labor Market Institutions,” in Iversen, Torben, Pontusson, Jonas, and Soskice, David, eds., Unions, Employers and Central Banks (New York:Cambridge University Press, 2000Google Scholar). The use of country dummies and the small number of Austrian observations (7) renders our analysis essentially unaffected by the exceptional nature of the Austrian wage data.
6 The trend for wage inequality becomes more impressive ifwe look at the wage distribution among men and women separately. See OECD (fn. 4,1996); and Pontusson, Jonas, Rueda, David, and Way, Christopher, “The Role of Political-Institutional Variables in the Making of Gendered Patterns of Wage Inequality” (Working paper, Institute for European Studies, Cornell University, 1999Google Scholar). In most countries increases of within-gender inequality have been offset by continued compression of between-gender wage differentials.
7 Topel, Robert, “Wage Inequality and Regional Labor Market Performance in the United States,” in Tachibanaki, Toshiaki, ed., Labour Market and Economic Performance (New York:St. Martin's 1994Google Scholar); and Svensson, Lars, Closing the Gender Gap (Lund:Ekonomisk-Historiska Foreningen, 1995Google Scholar)
8 Wood, Adrian, North-South Trade, Employment and Inequality (Oxford:Clarendon Press, 1994Google Scholar).
9 Gottschalk and Smeeding (fn. 4); Rowthorn (fn. 5); Blau, Francine and Kahn, Lawrence, “International Difference in Male Wage Inequality,” Journal ofPolitical Economy 104 (August 1996CrossRefGoogle Scholar); and various contributions to Freeman, Richard and Katz, Lawrence, eds., Differences and Changes m Wage Structures (Chicago:University of Chicago Press, 1995CrossRefGoogle Scholar).
11 Freeman, Richard, “Unionism and the Dispersion of Wages,” Industrial and Labor Relations Review 34 (October 1980CrossRefGoogle Scholar); idem, “Union Wage Practices and Wage Dispersion within Establishments,” Industrial and Labor Relations Review 36 (October 1982Google Scholar); cf. also Blau and Kahn (fn. 9).
12 Cf. Freeman (fn. 11,1980).
13 The Eurobarometer of June—July 1994 yields the following figures for average union density by income quartile in the EU member states: lowest quartile, 37.5 percent; second-to-lowest quartile, 37.8 percent; second-to-highest quartile, 34.2 percent; and highest quartile, 23.7 percent. For all countries but Canada the union-density data used in our regressions refer to net rather than gross union density (“employed union members as a percentage of the employed labor force” rather than “union members as a percentage of the total labor force”).
14 Wallerstein (fn. 1); Iversen (fn. 3), 2-5; Rowthom (fn. 5); Blau and Kahn (fn. 9); and OECD, , “Economic Performance and the Structure of Collective Bargaining,” Employment Outlook (July 1997Google Scholar).
15 Wallerstein (fn. 1), 674.
17 For a detailed specification, see Iversen (fn. 3), 83–86.
18 To capture the inertia associated with institutional change, these yearlyfigureswere lagged so that the value for a given year used in our regressions is the average for that year and the previous four years. It should also be noted that we have extrapolated centralization values for the last two years of our time series.
19 Kahn, Lawrence, “Wage Inequality, Collective Bargaining and Relative Employment 1985–94” (Working paper, Institute for Labor Market Policies, Cornell University, 1999Google Scholar).
21 Focusing on wage restraint rather than wage distribution, Geoffrey Garrett and Christopher Way present similar arguments about the distinctive dynamics of public sector bargaining; see Garrett and Way, “Public Sector Unions, Corporatism and Wage Determination,” in Iversen, Pontusson, and Sos-kice (fn. 5).
22 Drawing on microdata for the early 1990s from the Luxembourg Income Survey, Gornick and Jacobs report very sizable public sector wage premiums for men and women alike in Belgium, Canada, Germany, the Netherlands, the U.K., and the U.S., but not in Sweden. See Gornick, Janet and Jacobs, Jerry, Gender, the Welfare State and Public Employment, Luxembourg Income Study Working Paper no. 168 (1997Google Scholar).
23 Cf, e.g., Garrett (fn. 3).
25 Katzenstein (fn. 2); and idem, Policy and Politics in West Germany (Philadelphia:Temple Univer sity Press, 1987Google Scholar).
26 E.g., Soskice (fn. 2, 1990 and 1999).
27 Esping-Andersen (fn. 2).
28 Collective bargaining coverage rates exceed union density either because governments decide to extend negotiated agreements to firms or sectors that were not party to the agreements (the French case) or because employers are better organized than unions and collective agreements encompass all employees of the firms that are party to the agreement (the German case).
29 The coverage rates estimated by the OECD do not necessarily pertain to wage agreements. A government decision to extend a collective agreement on summer holidays could account for France's exceptionally high coverage rate.
30 Hall, Peter, “Organized Market Economies and Unemployment in Europe” (Manuscript, Center for European Studies, Harvard University, 1998Google Scholar).
31 As we explain in the conclusion, the question of how to code Japan and Switzerland turns out to be of no consequence for our main findings.
32 Beck, Nathaniel and Katz, Jonathan, “Nuisance vs. Substance,” in Freeman, John, ed., Political Analysis (Ann Arbor:University of Michigan Press, 1996Google Scholar), 6:1. The results of Breusch-Godfrey tests indicate that there is no significant autocorrelation in our regressions. In tests with a variety of lags, we could not reject the null hypothesis (nonexistence of autocorrelation) at a level even close to the 90 percent traditional significance threshold. See Greene, William, Econometric Analysis (Englewood Cliffs, N.J.:Prentice Hall, 1997), 595Google Scholar.
33 Cf. Box, George and Jenkins, Gwilyn, Time Series Analysis (Oakland, Calif.:Holden-Day, 1976Google Scholar), chap. 1.
34 See Hsiao, Cheng, Analysis ofPanel Data (New York:Cambridge University Press, 1986Google Scholar).
35 For the regressions reported in Tables 2 and 3 the results of F-tests show that the country dummies are significant at better than the 99 percent level.
37 See Anderson, T. W. and Hsiao, Cheng, “Estimation of Dynamic Models with Error Components,” Journal oftheAmerican StatisticalAssociation 76 (September 1981Google Scholar); and idem, “Formulation Estimation of Dynamic Models Using Panel Data,” Journal of'Econometrics 18 (January 1982Google Scholar). This similar to the method suggested by Hibbs and employed by Alvarez, Garrett, and Lange. See Hibbs, Douglas, “Problems of Statistical Estimation and Causal Inference in Dynamic Time Series Models,” in Costner, Herbert, ed., Sociological Methodology 1973/1974 (San Francisco:Jossey-Bass, 1974Google Scholar); and Alvarez, Michael, Garrett, Geoffrey, and Lange, Peter, “Government Partisanship, Labor Organization and Macroeconomic Performance,” American Political Science Review 85 (June 1991CrossRefGoogle Scholar).
38 In both the linear and the interaction models, the instruments we use turn out to be excellent predictors of the lagged dependent variable. The R2 obtained in the first-stage IV regressions was higher than .95.
39 Nathaniel Beck and Jonathan Katz propose a method for deriving consistent standard error estimates in the presence of panel-heteroscedastic errors that has been widely adopted by students of comparative political economy, e.g., Garrett (fn. 3); and Iversen (fn. 3); see Beck, and Katz, , “What to Do (and Not to Do) with Time-Series Cross-Section Data,” American Political Science Review 89 (Sep tember 1995CrossRefGoogle Scholar). When we ran our regressions with the Beck-Katz procedure (estimating panel-corrected standard errors without instrumental variables), we obtained results that were essentially the same as those reported below (available upon request). None of our substantive findings are affected by the choice of one or the other of these setups.
40 In terms of overall numbers, the interpolations make up for the loss of observations entailed by the use of a lagged dependent variable. More importantly, interpolation enables us to include Norway in our analysis.
41 Wallerstein (fn. 1), 650.
42 Our analysis is based on a much larger number of observations and covers a longer time period than Wallerstein's. Different measures of bargaining centralization constitute another potential source of divergent results.
43 In Figures 1 and 2 Austria has an even more dispersed wage distribution than Germany, but the fact that the Austrian wage data include part-time employees makes the Sweden-Germany comparison more appropriate.
44 Wood (fn. 8). The more fine-grained analysis by Vincent Mahler, David Jesuit, and Douglas Roscoe also fails to establish any clear and consistent pattern of association between wage inequality and various dimensions of “globalization.” See Mahler, , Jesuit, , and Roscoe, , “Exploring the Impact of Trade and Investment on Income Inequality,” Comparative Political Studies 32 (May 1999CrossRefGoogle Scholar).
46 Among the statistically significant variables, the single largest coefficient change we obtained was for government employment in LMEs: this coefficient fell from .104 to .086 when we recoded Japan and Switzerland. For the mixed cases, the coding change produced statistically significant coefficients for wage bargaining centralization (negative, as in SMEs), government employment (negative, as in SMEs) and government partisanship (positive, as in LMEs). Results available from the authors upon request.
47 Peter Swenson, Labor Markets and Welfare States (forthcoming)
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