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Nominal and Real Union Wage Differentials and the Effects of Industry and SMSA Density:1973-83Author(s): Barry T. Hirsch and John L. NeufeldReviewed work(s):Source: The Journal of Human Resources, Vol. 22, No. 1 (Winter, 1987), pp. 138-148Published by: University of Wisconsin PressStable URL: http://www.jstor.org/stable/145872 .Accessed: 19/04/2012 18:30

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Nominal and Real Union Wage Differentials and the Effects of Industry and SMSA Density: 1973-83

I. Introduction

Estimation of union-nonunion relative wage differentials has for some time received considerable attention from labor economists. Lewis (1986) has recently surveyed about 200 empirical studies providing empiri- cal analysis of data through 1979. In this paper, we provide estimates of nominal and real union-nonunion wage differentials for the period 1973-83, based on separate samples of male production workers in manufacturing, production workers in nonmanufacturing, and nonproduction workers economy wide.

The purpose of this study is threefold. First, systematic comparison of nominal versus real wage differentials allows us to evaluate Lewis's conclu- sion, based on a limited number of studies, that there is no significant difference between these measures. Second, we are able to provide esti- mates of the union-nonunion differential over an eleven year period, includ- ing several sample years since Lewis ended his survey. Finally, we provide estimates of the effects of both industry and SMSA density on the union differential and the wages of union and nonunion workers.

II. Estimation and Data

In order to obtain estimates of the union-nonunion wage differential, micro log wage functions are specified for union and nonunion workers. Letting i index individual workers, k a worker's 3-digit industry, m a worker's SMSA, and superscripts u and n union and nonunion status, respectively, the following equations are estimated by OLS:

(1) ln(w)' = Ox" + SEIP"X + UPik + 8UPim + e'

(2) ln(w)i = an + SX? + ^"P + 8p + e

where w is the wage, X is a vector of earnings-related individual characteris-

The authors acknowledge the helpful comments of two anonymous referees. [Submitted August 1985; accepted July 1986] THE JOURNAL OF HUMAN RESOURCES ? XXII * 1

Communications 139

tics, P is union density, and e" and en are error terms assumed to be uncorrelated with zero means and constant variances.'

The logarithmic union-nonunion wage differential (or wage gap), d, is calculated by:

(3) d = (ou -

") + ( - n)+ (U - yn)Pk + (u -

)Pm.

where the means of X, Pk, and Pm are all-worker means (hence, d is a weighted average of log differentials calculated using union and nonunion means). The percentage differential, D, is most easily approximated by:

(4) D = [exp(d) - 1]100.

More precise estimation methods are provided in Kennedy (1981) and Giles (1982). Below, all results are presented as log differentials.

The primary data used in this study come from the May 1973-81 and 1983 Current Population Survey (CPS) tapes. All employed nonfarm nonschool males between the ages of 18 and 64 residing in 29 of the largest 30 SMSAs are included.2 Union density, defined here as the percentage of eligible workers who are union members, is available for three-digit Census indus- tries and SMSAs in Kokkelenberg and Sockell (1985).3 In order to obtain real wage estimates, nominal wages (usual weekly earnings divided by usual hours worked per week) are deflated by BLS intermediate budget figures once provided annually for large SMSAs (Census Bureau).4 The vector X includes years of schooling, experience (age - schooling - 5), experience

1. As is well known, OLS is not without problems. Receiving the most attention in the literature has been the potential bias resulting because of the simultaneous determination of union status and wages and, relatedly, selectivity bias resulting from unobserved differences between union and nonunion workers with identical measured characteristics. Lewis (1986) provides an analysis of methods intended to address these problems (e.g., inclusion of a

selectivity variable in the wage equations and the use of fixed-effects models with panel data). Because alternative methods also introduce potentially serious problems, OLS is used here. This helps avoid entangling the effects of cost-of-living or union density adjustments with those from use of alternative estimation procedures. 2. There was no public use 1982 survey. Sample sizes are reduced after 1978 because all rotations were not asked their usual weekly earnings. CPS coding of the SMSAs is based on 1970 Census population counts. Miami is excluded due to insufficient cost-of-living data. 3. Kokkelenberg and Sockell (1985) provide union data based on the 1973-81 May CPS (the CPS union question did change during this period; see Footnote 6). Density data for SMSAs are

provided yearly while for industries, data are presented as three-year moving averages. Hence our 1973 and 1974 regressions include industry density for 1973-75, regressions for 1980 on include the 1979-81 industry density measures, and the 1983 regressions include the 1981 SMSA density measure. Measurement error associated with this imperfect matching is prob- ably minor given the year-to-year stability in relative interindustry and interarea unionization. 4. Such figures are no longer provided by BLS. Our 1983 budget figures were generated by inflating prior year budget figures by SMSA-specific consumer price indices (U.S. Bureau of the

Census).

140 The Journal of Human Resources

squared, and dummies for race, marital status, veteran status, region, 1-digit occupation, and 1-digit industry (in the nonmanufacturing samples).

III. Nominal versus Real Wage Differentials by Year

As noted by Lewis (1986, 105), the use of nominal rather than real wage rates might lead to an upward bias in wage gap estimates since union workers are more likely to reside in higher cost-of-living areas. Based on unpublished results extracted from four studies, however, Lewis tenta- tively concludes that adjustments for cost of living have little effect on wage differential estimates. We first examine the potential for bias in union wage differential estimates by comparing differences between nominal and real wage rates for union and nonunion workers over the 1973-83 period. As hypothesized by Lewis, we find a potential for bias. Adjusting for cost-of- living differences reduces union wages by an average 1.15 percent relative to nonunion wages.

Table 1 presents estimates of union-nonunion log wage differentials by year for the three subsamples of male workers. As found in previous studies, the union wage effect for production workers is smaller in manufacturing than in nonmanufacturing, while estimated union wage effects for nonpro- duction workers are close to zero (see Antos 1983).

The average (unweighted) difference between the nominal and real dif- ferential over the 1973-83 period, d(nom) - d(real), is presented in the next to last row of Table 1. Among production workers in manufacturing (the most frequently studied group in the empirical literature), nominal and real differentials are virtually identical, the average difference being less than a tenth of a percent. However, among production workers outside of manufacturing, estimates of nominal differentials are about 1 percentage point higher than estimates of real differentials. While a 1 percentage point bias is not trivial, it is less than the bias attributed to the exclusion of fringe benefits (Freeman 1981), work conditions (Duncan and Stafford 1980), union dues (Raisian 1983), selectivity, and other factors (for a survey, see Lewis 1986). Among nonproduction workers, no evidence is found of a union-nonunion wage differential; hence, values of d(nom) - d(real) for this group have less meaning. The bottom line of Table 1 presents d(nom) - d(real) calculated from regressions excluding the regional variables, which to some extent proxy cost-of-living differences. Even with the exclusion of these control variables, differences between nominal and real union wage gaps are small on average (complete results are available on request).

On the basis of the results presented in Table 1, it appears fair to conclude that no significant portion of the union-nonunion differential constitutes a

Communications 141

compensating differential for higher living costs. It likewise follows that no significant bias has been introduced in previous studies by ignoring cost-of- living differences. For most research efforts in this area, the benefits from considering cost-of-living differences are likely to be less than the costs of limiting one's sample to large SMSAs (plus the costs from introducing additional measurement error associated with the cost-of-living indices).5 Indeed, it should be noted that union wage gaps estimated for workers in SMSAs are lower than corresponding economy-wide wage gaps (Lewis 1986, 134-36).

Our results also provide evidence on changes over time in the union- nonunion wage differential, using a common methodology, specification, and data source.6 The far right columns of Table 1 report the full-sample weighted averages of the nominal and real differentials. Similar to results reported by Lewis (1986, 179, 186), we find relatively stable wage effects from 1973 through 1975. However, we find a more marked upward shift than reported in Lewis for the 1976-78 period. As in the three studies cited by Lewis, we find a sharp drop in the 1979 estimated gap. Our post-1979 results show considerable year-to-year variability, with somewhat higher produc- tion-worker gap estimates for 1980 and 1983 than in 1979 and 1981. It appears fair to conclude that the upward trend occurring in the union differential in the late seventies may have been less marked than that estimated by some (e.g., Johnson 1984, Linneman and Wachter 1986), and it was not maintained in the early eighties.

IV. Union Density and the Wages of Union and Nonunion Workers

Lewis (1986) has argued forcefully that much of the empirical literature measuring union relative wage effects entangles to some degree the effects of individual union status and of union density. In order to separate these effects, variables measuring union density in workers' three- digit industry group and SMSA are included in Equations (1) and (2). Because inclusion of density variables in wage equations has only recently

5. We have no reason to believe that these results, based on large SMSAs, cannot be general- ized. 6. The union variable does change in definition over the period. The 1973-75 surveys asked, "Does ... belong to a labor union?" The 1976-78 surveys added to the end, ". . . or employee association." The 1979-81 surveys added, ". .. or employee association similar to a union." The 1983 survey asked, "Is . . . covered by a union or employee association contract?" These changes in definition qualify any inferences we make regarding intertemporal changes in the union wage gap.

-?

0

CD

0

;D

~q

0

V3

0

0 d

(ys

Table 1 Nominal and Real Union-Nonunion Log Wage Differentials: 1973-83

All Workers Production Workers Nonproduction (Weighted

Workers Average) Manufacturing Nonmanufacturing

Year nominal real nominal real nominal real nominal real

0.0775 0.0770 [1107; 663]

0.0978 0.0970 [1055; 625]

0.0746 0.0784 [992; 638]

0.1038 0.1026 [870; 626]

0.1220 0.1229 [956; 660]

0.1881 [1336;

0.2350 [1214;

0.1993 [1177;

0.2419 [1128;

0.2950 [1257;

0.1819 1391]

0.2262 1228]

0.1917 1325]

0.2333 1267]

0.2826 1451]

-0.0192 -0.0258 [618; 2876]

-0.0337 -0.0427 [599; 2797]

0.0060 -0.0045 [599; 2994]

0.0003 -0.0062 [573; 2774]

0.0064 -0.0001 [662; 2806]

1973

1974

1975

1976

1977

0.0730

0.0830

0.0831

0.1016

0.1307

0.0678

0.0759

0.0765

0.0955

0.1237

1978

1979

1980

1981

1983

1973-83a d(nom) - d(real) 1973-83b

d(nom) - d(real)

0.1330 0.1339 [819; 557]

0.0835 0.0837 [540; 358]

0.1037 0.0999 [250; 220]

0.0549 0.0590 [236; 233]

0.1133 0.1152 [281; 243] - 0.0005

0.0005

0.2697 0.2577 [1137; 1333]

0.1907 0.1835 [677; 787]

0.2237 0.2142 [371; 485]

0.1457 0.1304 [325; 483]

0.2045 0.1946 [300; 381]

0.0097

0.0074

0.0008 -0.0003 [581; 2771]

-0.0515 -0.0574 [408; 1654]

-0.0238 -0.0315 [206; 961]

0.0097 0.0001 [192; 949]

-0.0225 -0.0240 [342; 11471

0.0065

0.0106

Note: Sample sizes for union and nonunion workers, respectively, are in brackets. a. Unweighted average for 1973-83, calculated from values in the table. b. Unweighted average for 1973-83, calculated from differentials estimated with regressions excluding regional dummy variables.

0

0 rd'

0

cn

-4-1 wf

0.1183

0.0561

0.0852

0.0639

0.0613

0.1139

0.0510

0.0776

0.0551

0.0583

o

r- 0

0

PO

7d cD Table 2 o

Industry and SMSA Union Density Coefficients from Union and Nonunion Real Wage Equations: 1973-1983 : n y>

Equation- Un- Density weighted Variable 1973 1974 1975 1976 1977 1978 1979 1980 1981 1983 Average

Production workers: manufacturing Union- Pk(IND) 0.2657 0.1117 0.2032 0.2419 0.3204 0.3908 0.2500 0.3966 0.2511 0.1663 0.2598

(4.78) (1.69) (3.78) (4.42) (5.88) (5.92) (3.31) (3.45) (1.94) (1.46) Union- Pm(SMSA) 0.1662 0.3183 0.0579 0.4578 0.5785 0.2240 0.2957 0.1098 0.9852 0.2833 0.3477

(0.94) (1.32) (0.32) (2.49) (3.46) (1.10) (1.33) (0.32) (2.71) (0.89) Nonunion - Pk(IND) 0.1677 0.3112 0.3574 0.2569 0.1870 0.2519 0.4056 0.0817 0.3090 0.2114 0.2540

(1.56) (2.96) (3.23) (2.35) (2.12) (2.57) (3.20) (0.49) (2.04) (1.26) Nonunion - Pm(SMSA) -0.3133 -0.0603 -0.0997 0.1989 0.3681 0.0310 0.0580 -0.3739 0.4714 -0.0896 0.0191

(-1.04) (-0.19) (-0.35) (0.65) (1.55) (0.10) (0.17) (-0.79) (1.05) (-0.20) Production workers: nonmanufacturing

Union- Pk(IND) 0.4338 0.3587 0.3523 0.4482 0.3863 0.4732 0.3292 0.3249 0.4469 0.5250 0.4079 (8.44) (6.35) (7.15) (7.69) (7.35) (8.34) (4.18) (3.72) (3.76) (4.97)

Union - Pm(SMSA) 0.0813 0.1435 -0.3503 -0.1115 -0.2130 -0.1911 0.1450 0.2550 0.0211 -0.0458 -0.0266 (0.46) (0.68) (-2.04) (-0.53) (-1.27) (-0.99) (0.53) (0.80) (0.06) (-0.13)

Nonunion- Pk(IND) 0.7152 0.6651 0.5924 0.5668 0.5845 0.6192 0.5366 0.4234 0.6535 0.4038 0.5761 (7.24) (7.63) (7.14) (6.44) (7.10) (7.49) (4.50) (3.57) (4.86) (2.74)

Nonunion - Po(SMSA) -0.5160 -0.0205 -0.1323 0.4298 0.0559 -0.2334 -0.0680 -0.0737 -0.2245 0.0001 -0.0783 (-2.31) (-0.09) (-0.64) (2.03) (0.31) (-1.05) (-0.23) (-0.23) (-0.72) (0.00)

Nonproduction workers Union - Pk(IND) 0.0873 0.1270 0.1876 0.2259 0.2089 0.0954 0.2304 0.0011 0.0703 0.1526 0.1387

(1.22) (1.48) (2.17) (2.35) (2.50) (1.21) (2.38) (0.01) (0.34) (1.31) Union - Po (SMSA) -0.2493 0.0196 -0.0787 0.0142 0.1470 -0.3340 -0.6410 0.0283 -0.2266 0.0214 -0.1296

(-0.97) (0.06) (-0.26) (0.04) (0.54) (-1.18) (-1.86) (0.05) (-0.35) (0.07) Nonunion - Pk(IND) 0.3907 0.3104 0.3466 0.3256 0.2383 0.3126 0.1812 0.3287 0.2312 0.3120 0.2977

(7.72) (6.36) (6.84) (6.27) (5.01) (6.28) (2.90) (4.24) (2.83) (3.82) Nonunion - Po(SMSA) 0.0895 0.1793 0.1532 0.3419 0.2701 0.1221 0.1029 -0.3458 -0.1864 -0.3395 0.0387

(0.55) (1.09) (0.94) (2.10) (1.86) (0.74) (0.50) (-1.33) (-0.82) (-1.53)

Note: t-statistics in parentheses.

0 C)

0

PO cn

r Ct2

...

146 The Journal of Human Resources

become widespread, a brief discussion of results seems warranted (we are unaware of other studies including both industry and SMSA density). Table 2 presents the coefficients y and 6 on the density variables Pk and P, respectively, from the union and nonunion wage equations.

Industry union density, Pk, is found to positively and significantly affect both union and nonunion wages (for comparison with other studies, see Freeman and Medoff 1981, Antos 1983, Moore, Newman, and Cunningham 1985, and the survey by Lewis 1986). The positive effect of increased density on union wages is typically interpreted as resulting from a decreased labor demand elasticity. The positive effect of density on nonunion wages is thought to result primarily from a dominant threat effect in which nonunion employers must increase wages as industry density increases in order to remain nonunion. Or alternatively, nonunion firms can pay higher wages and be at less of a competitive disadvantage the greater is industry-wide coverage (see Freeman and Medoff 1981 and Moore, Newman, and Cun- ningham 1985 for related discussions).

In contrast to industry density, labor market (SMSA) union density has little clear-cut impact on union or nonunion wages (see Holzer 1982 for more detailed evidence on SMSA density). The greater significance of Pk than Pm on union wages is consistent with the argument that industry coverage, but not labor market coverage, impacts on the elasticity of labor demand. The minor net impact of Pm on nonunion wages suggests that threat effects from SMSA density, to the extent they exist, are offset by spillover (or surplus labor) effects that place downward pressure on nonun- ion wages. While labor spillover effects are likely to be captured by mea- sures of SMSA density (assuming imperfect interarea mobility), they seem less likely to be associated with industry density.

Comparison of the density coefficients from the union and nonunion equations in Table 2 also permit inferences as to their effect on the size of the wage differential. The finding that yu > yn implies the union wage gap increases with industry density, while 6u > an implies the gap increases with SMSA density. Surprisingly we do not find the wage gap increasing with industry density, as theory and limited past evidence would predict (Free- man and Medoff 1981). However, we are reluctant to draw strong inferences based on the relative magnitudes of the density coefficients, since it seems likely they are proxying for other omitted variables (Lewis 1986, 153).7 Coefficient estimates on SMSA density do suggest, however, that labor market density has no significant impact on the magnitude of the union wage gap.

7. Indeed, Moore, Newman, and Cunningham (1985) find that the nonunion industry density coefficient is sharply reduced for a sample of manufacturing workers when a firm size variable is included.

Communications 147

V. Summary

This paper has provided a detailed analysis of nominal and real union-nonunion relative wage effects during the 1973-83 period. For all years, differences between the nominal and real union wage effects are small. No difference is found for production workers in manufacturing, while approximately a one percentage point difference is found for produc- tion workers outside of manufacturing. Based on these results, it is con- cluded that for most research endeavors in this area, the costs of considering cost-of-living differences (e.g., restricting the sample) outweigh the ben- efits.

Evidence has also been provided on the union wage gap over the 1973-83 period and the effects of both industry and SMSA density on union and nonunion wages. Union-nonunion wage differentials appear to have wid- ened during the 1976-78 period, but returned to earlier levels after 1978. Industry density was found to increase significantly both union and nonun- ion wages, whereas labor market density appears to have little significant impact on union or nonunion wages.

Barry T. Hirsch University of North Carolina at Greensboro

John L. Neufeld University of North Carolina at Greensboro

References

Antos, Joseph R. 1983. "Union Effects on White-Collar Compensation." Industrial and Labor Relations Review 36:461-79.

Duncan, Greg J., and Frank P. Stafford. 1980. "Do Union Members Receive Compensating Wage Differentials?" American Economic Review 70:355-71.

Freeman, Richard B. 1981. "The Effect of Unionism on Fringe Benefits." Industrial and Labor Relations Review 34:489-509.

Freeman, Richard B., and James L. Medoff. 1981. "The Impact of the Percent Organized on Union and Nonunion Wages." Review of Economics and Statistics 62:561-72.

- . 1984. What Do Unions Do? New York: Basic Books, 1984. Giles, David E. A. 1982. "The Interpretation of Dummy Variables in

Semilogarithmic Equations: Unbiased Estimation." Economics Letters 10:77-79.

Holzer, Harry J. 1982. "Unions and the Labor Market Status of White and Minority Youth." Industrial and Labor Relations Review 35:392-405.

Johnson, George E. 1984. "Changes over Time in the Union-Nonunion Wage Differential in the United States." In The Economics of Trade Unions: New Directions, ed. Jean-Jacques Rosa. Boston: Kluwer-Nijhoff.

148 The Journal of Human Resources

Kennedy, Peter E. 1981. "Estimation with Correctly Interpreted Dummy Variables in Semilogarithmic Equations." American Economic Review 71:801.

Kokkelenberg, Edward C., and Donna Sockell. 1985. "Newer Estimates of Unionism in the United States: 1973-1981." Industrial and Labor Relations Review 38:497-543.

Lewis, H. Gregg. 1986. Union Relative Wage Effects: A Survey. Chicago: University of Chicago Press.

Linneman, Peter, and Michael L. Wachter. 1986. "Rising Union Premiums and the Declining Boundaries Among Noncompeting Groups." American Economic Review Papers and Proceedings 76:103-08.

Moore, William J., Robert J. Newman, and James Cunningham. 1985. "The Effect of the Extent of Unionism on Union and Nonunion Wages." Journal of Labor Research 6:21-44.

Raisian, John. 1983. "Union Dues and Wage Premiums." Journal of Labor Research 4:1-18.

U.S. Bureau of the Census. Various years. Statistical Abstract of the United States. Washington: GPO.

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