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Wives' earnings and the level and distribution of married couples' earnings in developed countries
WIVES‘ EARNINGS AND THE LEVEL AND DISTRIBUTION OF MARRIED COUPLES EARNINGS IN DEVELOPED COUNTRIES Maria Cancian Institute of Public Aflairs and School of Social Work University of Wisconsin Robert F. Schoeni RAND Corporation
This study examines the contribution of wives’ earnings to the distribution of married couples’ earnings in 10 developed countries. There is substantial variation among countries in wives’ labor force participation, the relative earnings of husbands and wives, the distribution of earnings, and the correlation of spouses’ earnings. Even though these countries differ on these dimensions, wives’ earnings mitigate inequality in the earnings of married couples. For the countries we are able to analyze over time, the labor force participation of wives married to high earning husbands increased more than the labor force participation of wives married to middle-earning men. Despite this trend, the mitigating effect of wives’ earnings actually increased slightly in all countries examined. Moreover, all other things equal, the correlation of spouses’ earnings would have to experience an unprecedented increase in order for wives’ earnings to become disequalizing.
1.
INTRODUCTION
In the United States during the 198Os, married women’s labor force participation continued its upward trend. Partly as a consequence, wives’ earnings have been the most important source of growth in household income among married couples, Direct all correspondence to: Maria Can&an, institute of Public Affairs and School of Social Work, 1225 Observatory Drive, University of Wisconsin, Madison, Wisconsin 53706
Journal of Income Distribution, 8(l), 45-61
Copyright 0 1998 JAI Press Ltd. All rights of reproduction in any form reserved.
ISSN: 09266437
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accounting for about half of the increase during the 1980s (Cancian, Danziger, & Gottschalk, 1993a). During the same time, the gap in income between rich and poor families widened (Danziger & Gottschalk, 1993). Several recent studies have analyzed the role that the trend in women’s labor force involvement has had in determining the level and change in the gap between rich and poor (Burtless, 1996; Juhn & Murphy, 1996; Karoly & Burtless, 1995; Cancian, Danziger, & Gottschalk 1993b; Ryscavage, 1992). Many of these studies are consistent with earlier research which found wives’ earnings to be equalizing (see Tress, 1987 for a review). However, the disproportionate increase in the labor force participation and earnings of women with high earning husbands has caused concern about the potential for wives’ earnings to increase inequality. The objective of this paper is to analyze the impact of wives’ labor force participation and wives’ earnings on the level and distribution of household earnings in other developed countries during the 1980s. Using the Luxembourg Income Study (LIS), we are able to make comparisons across 10 countries, and, for four countries, at different times within the 1980s. We find that wives in the countries analyzed in this study work at very different rates, from a low of 45% in Switzerland in 1982 to a high of 92% in Sweden in 1987. The contribution that wives make to total family earnings varies greatly, from 13% to 35%. The correlation in spouses’ earnings and the relative dispersion of husbands’ and wives’ earnings are also quite different across the countries analyzed. Even so, we find that in all countries, wives’ earnings mitigate inequality in total family earnings among married couple families in that the distribution of earnings is more equal than it would be in the absence of wives’ earnings.’ The reduction, utilizing the squared coefficient of variation as our measure of inequality, ranges from 11% in Israel to 33% in Sweden in 1987. As stated, these results derive from an accounting exercise which compares the distribution of earnings with and without wives’ earnings. We do not model the impact of wives’ earnings on husbands’ labor supply, an analysis which is beyond the scope of this paper. There are a number of other studies which analyze crosscountry difference in men’s and women’s labor supply and earnings (see for example: Gomick, Meyers, & Ross, 1996a and 1996b; Blackbum & Bloom, 1994; Forster, 1994; Knudsen & Peters, 1994; Phipps, 1993: Saunders, O’Connor, & Smeeding, 1994). We begin by discussing the measure of inequality that is utilized and the data that are examined. Next, we document the similarities and differences in wives’ and husbands’ labor force participation and earnings across 10 developed countries and, when the data permit, across time within countries. The role of wives’ earnings in determining the level and distribution of household earnings in each of the 10 countries is then analyzed. The final section summarizes the findings.
47
Inequality in Developed Countries
2.
MEASURE OF INEQUALITY AND THE DATA 2.1. Measure of Inequality
We use the squared coefficient of variation, i.e., the ratio of the variance to the squared mean, as our measure of inequality.2 Consider the squared coefficient of variation of total family earnings (y) when there are only two components of income: earnings of the husband (h) and earnings of the wife (w):
where /li is the mean of earnings source i, phw is the correlation between husbands’ and wives’ earnings, and CV; is the squared coefficient of variation of earnings source i. We are interested in the than e in in%quality Then wives’ earnings are gz included as a source of income, i.e. (CV, - CVh ) / CVh . The key components of this change are the share of total earnings attributable to wives’ earnings relative to husbands’, the correlation of spouses’ earnings, and the dispersion of wives’ and husbands’ earnings. Furthermore, as is evident from (l), the greater the correlation in spouses’ earnings the greater the inequality in total household earnings regardless of all other parameters. These components are analyzed empirically for each country.3
Table 1 Source of Each Data Set Country, Year Australia 1981/82 Australia 1985186 Canada 1987 France 1979 France 1984 West Germany 1984 Israel 1979 Norway 1979 Sweden 1981 Sweden 1987 Switzerland 1982 United Kingdom 1979 United States 1979 United States 1986 Note:
Original Data Set
Size*
Income and Housing Survey Income and Housing Survey Survey of Consumer Finances Survey of Indiv Income Tax Returns Income Survey of Taxes German Panel Survey Family Expenditures Survey Norwegian Tax Files Swedish Income Distribution Survey Swedish Income Distribution Survey Income and Wealth Survey Family Expenditure Survey March Current Population Survey March Current Population Survey
15,985 7,560 10,999 11,044 12,693 5,174 2,271 10,414 9,625 9,421 7,036 6,777 15,225 11,614
‘(Data set size refers to the unweighted LIS sample size.
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2.2. Data
We examine microdata from 10 countries: Australia, Canada, France, West Germany, Israel, Norway, Sweden, Switzerland, United Kingdom, and the United States. Data from two periods are analyzed for Australia, France, Sweden, and the United States. Table 1 lists the original data source for each country and year. Access to the data was obtained through the Luxembourg Income Study (LB). The survey instrument, sampling frame, and variable definitions differed among countries. However, one advantage of the LIS data is that, whenever possible, they have utilized common definitions of income sources (see Coder, Rainwater, & Smeeding, 1988 for a detailed discussion of the LIS project and data sources).4 Annual wage and salary income (gross of taxes) is the earnings variable analyzed for each country. This variable is available for the head and spouse of each household.5 Reports of earnings are top-coded in the U.S. data. In 1986, 1.4% of our sample of husbands and wives had earnings of at least $100,000, which was the top-code in that year. For 1979,2.6% had earnings at or above the top-code of $50,000. To examine the sensitivity of our findings to top-coding, we replicated our results for the U.S. trimming the top-five percent of earners and found that the qualitative results were unchanged when the sample was trimmed. (See the table note in Table 3 for specific estimates). The analyses are restricted to married couples in which the husband is 25 to 55 years of age in order to minimize the potential confounding effects of retirement and school attendance. LIS’s (family) sample weights are used for all analyses. Table 2 Share of Wives Who Are Working by Husbands’ Earnings Quintile for Each Country Share of Wives Working by Husbands’ Earnings Quintile Country, Year Australia 1981-82 Australia 1985-86 Canada 1987 France 1979 France 1984 West Germany 1984 Israel 1979 Norway 1979 Sweden 1981 Sweden 1987 Switzerland 1982 United Kingdom 1979 United States 1979 United States 1986 Note:
Husband
Wife
1st*
2nd
3rd
4th
5th
74.8 80.6 87.5 83.5 83.7 84.7 78.0 89.7 91.3 93.3 99.0 87.6 88.5 86.2
48.4 57.5 71.2 46.7 54.9 49.0 46.0 70.9 85.8 91.7 44.6 59.8 61.5 68.7
30.3 36.5 66.2 24.4 32.5 49.0 31.7 53.4 73.3 82.4 44.6 51.2 55.2 63.2
53.3 61.7 75.2 50.5 58.2 51.6 40.3 74.7 84.8 93.1 56.9 65.6 68.0 73.6
57.4 63.6 71.6 58.8 61.2 55.8 50.9 76.7 90.1 93.4 47.5 65.4 67.0 73.1
54.9 63.4 74.2 55.6 67.7 47.2 48.9 78.4 92.0 94.5 47.1 62.5 63.2 71.9
52.5 62.2 68.9 44.2 54.7 41.2 59.1 71.2 88.9 95.0 32.6 54.7 53.8 61.7
*lst is the lowest quintile.
Inequality in Developed Countries
3.
49
RELATIONSHIP BETWEEN WIVES’ AND HUSBANDS’ EARNINGS
The share of husbands who are working ranges from 75% to 93%, except in Switzerland where 99% of the husbands have positive earnings (Table 2). The employment rate among husbands declined between 1979 and 1986 in the US., a result which is consistent with a more general decline in men’s labor force attachment (Bound & Waidmann, 1992). In contrast, the share of husbands working was constant or rose slightly during the early 1980s in Australia, France, and Sweden. There is much greater variance across countries in the share of wives working. In the early 1980s just 45% of the wives in Switzerland worked while 86% of
201 111
i 2nd
3rd
uh
Nmvw, S-UK loo. 90.
Figure 2. Relationship Between Share of Wives Working and Husbands’ Earnings Quintile
5th
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Swedish wives did so. If we look at the eight countries for which we have data between 1979 and 1982, four (Australia, France, Israel, and Switzerland) had work-rates in the mid- to upper-forties, two (the U.K. and the U.S.) had work-rates close to sixty percent, while Norway and Sweden had higher shares working, 71 and 86%, respectively. Furthermore, we find a pattern of increasing attachment to the labor force for married women in all those countries for which we have two observations. In Australia, France, Sweden, and the U.S., the share of married women working increased by at least one percentage point per year over the period analyzed. As discussed in Section II, the association between husbands’ and wives’ labor market outcomes is important in understanding the effects of wives’ earnings on the inequality of total family earnings. The more highly (positively) correlated spouses’ earnings, the greater the inequality, ceteris paribus. In addition, because many wives do not work, the relationship between the share of wives working and husbands’ earnings has an important impact on the correlation of earnings. The share of wives who work increases with husbands’ earnings, but not over the entire range of husbands’ earnings; in most cases, the relationship is negative for those couples in which the husband is in the higher earnings quintiles. In most all countries, the share working is lowest for those wives whose husbands are the highest and lowest earners (Figure 1). For example, in the U.S. in 1986, of those Alrrmlia
1981-1985
3rd
2nd Swdcn
Fnncs 1979-1984
4th
5eb
1st
1981-1987
U&d
35
35
30
30
20 25 i
20 25 i
Figure 2.
3rd
2nd
Stata
4th
5th
1979-1986
Percent Change Over Time in the Share of Wives Working by Husbands’ Earnings Quintile
Country-Year
Sample
Australia-1981/82 AII couples Working wives Working husbands Both working Australia-1985/86 All couples Working wives Working husbands Both working Canada-1987 AU couples Working wives Working husbands Both working France-1979 AII couples Working wives Working husbands Both working France-1984 AII couples Working wives Working husbands Both working 75 84 100 100 81 88 100 100 87 89 100 100 84 93 100 100 84 92 100 100
57 100 63 100 71 100 73 100 47 100 52 100 55 100 60 100
Husbands
48 100 55 100
Wives
28.2 40.3 26.5 38.3
23.5 38.7 22.1 36.8
28.2 35.6 26.0 33.1
26.1 36.2 23.8 33.4
23.2 35.8 20.5 32.2
(%)
Wives’ Share of Income
0.160 0.255 0.087 0.288
0.107 0.230 0.036 0.283
1.514 0.389 1.295 0.379
2.105 0.451 1.750 0.431
1.204 0.570 1.160 0.573
1.618 0.505 1.392 0.496
0.113 0.056 0.013 0.039 0.092 0.149 0.082 0.183
2.064 0.484 1.701 0.473
Wives
0.144 0.081 0.029 0.085
Phw
0.795 0.502 0.503 0.377
0.912 0.454 0.597 0.352
0.551 0.484 0.357 0.327
0.589 0.368 0.280 0.198
0.576 0.381 0.178 0.162
Husband
CV2
0.601 0.296 0.390 0.251
0.703 0.287 0.460 0.251
0.410 0.309 0.294 0.244
0.474 0.227 0.245 0.149
0.507 0.235 0.189 0.134
Total
Table 3 of Husbands’ and Wives’ Earnings for Each Country
Percent Working
Level and Distribution
(continued)
-24.4 -40.9 -22.5 -33.6
-22.9 -36.7 -22.9 -28.9
-25.5 -36.2 -17.5 -25.3
-19.5 -38.2 -12.6 -25.0
-12.0 -38.3 6.2 -17.4
(%I
Change Due to Wives
Country-Year Sample
Germany-1984 AI1 couples Working wives Working husbands Both working Israel-1979 Ail couples Working wives Working husbands Both working Norway-1979 All couples Working wives Working husbands Both working Sweden-1981 AU couples Working wives Working husbands Both working Sweden-1987 AU couples Working wives Working husbands Both working 0.447 0.314 0.421 0.309
0.227 0.204 0.205 0.209
35.1 36.7 34.0 35.6
93 95 100 100
92 100 93 100
0.400 0.355 0.306 0.284
0.377 0.319 0.257 0.232
0.590 0.365 0.548 0.360
0.186 0.148 0.151 0.154
33.0 35.6 31.6 34.2
91 93 100 100
86 100 88 100
0.451 0.295 0.302 0.210
1.213 0.569 1.099 0.551
0.140 0.153 0.060 0.112
25.0 31.2 24.2 30.2
90 93 100 100
71 100 74 100
0.420 0.372 0.203 0.182
Husband
0.671 0.498 0.304 0.271
0.203 0.179 0.189 0.243
21.0 33.5 18.4 30.0
78 85 100 100
46 100 50 100
1.956 0.447 1.908 0.447
Wives
cv2
2.160 0.453 1.920 0.461
-0.052 -0.008 -0.068 0.061
Phw
21.4 36.8 18.7 33.0
(%)
85 86 100 100
Husbands
49 100 50 100
Wives
Wives’ Share of Income
0.267 0.216 0.215 0.185
0.272 0.202 0.199 0.000
0.368 0.222 0.250 0.169
0.595 0.309 0.311 0.210
0.334 0.208 0.188 0.138
Total
Table 3 of Husbands’ and Wives’ Earnings for Each Country
Percent Working
Level and Distribution
-33.2 -39.1 -29.8 -34.8
-27.8 -36.8 -22.3 0.0
-18.3 -24.8 -17.0 -19.7
-11.3 -38.0 2.3 -22.4
-20.6 -44.2 -7.5 -24.1
Change Due to Wives (%)
hWs:
20.3 29.8 18.3 27.9
88 90 100 100 89 91 100 100 86 88 100 100
60 loo 59 100 61 100 63 100 69 100 70 100
26.7 35.4 24.4 32.6
20.9 30.5 19.5 28.7
12.5 25.6 12.3 25.2
99 99 100 100
45 100 44 100
0.077 0.175 0.064 0.209
0.028 0.095 -0.016 0.106
0.053 0.086 0.003 0.086
-0.100 -0.091 -0.094 -0.079
1.431 0.669 1.389 0.678
1.635 0.619 1.529 0.602
1.572 0.538 1.560 0.522
2.629 0.619 2.647 0.621
0.642 0.570 0.416 0.385
0.443 0.375 0.278 0.254
0.390 0.330 0.216 0.203
0.413 0.269 0.398 0.252
0.476 0.371 0.338 0.294
0.357 0.258 0.235 0.196
0.326 0.226 0.197 0.157
0.334 0.175 0.326 0.169
-25.9 -34.9 -18.6 -23.7
-19.6 -31.2 -15.5 -23.0
-16.4 -31.6 -8.9 -22.4
-19.0 -34.8 -18.2 -33.0
For the U.S. in each year, we re-estimated each model trimming the top five percent of earners. Reading across the row for ‘Ml Couples,” the estimates become 62,88,21.9,0.057,1.561,0.387,0.326, and -15.8 for 1979 and 69,86,27.5,0.004,1.354, 0.556,0.418, and -25.1 for 1986.
Switzerland-1982 All couples Working wives Working husbands Both working UK-1979 All couples Working wives Working husbands Both working us-1979 All couples Working wives Working husbands Both working US-1986 AU couples Working wives Working husbands Both working
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wives whose husbands’ earnings ranked in the lowest quintile, 63% worked. Similarly, for those with the highest earning husbands, 62% had positive earnings, At the same time, the share of wives working among wives whose husbands ranked in the middle three quintiles is 10 points higher. The tendency for U.S. women with high earning husbands to work less has been cited as an explanation for the low correlation of spouses’ earnings, which in turn contributes to the equalizing impact of wives’ earnings. This may reflect an income effect on wives’ labor-leisure decision, with greater family income, derived primarily from a high-earning husband, purchasing greater leisure for the wife. Similar to the experience of couples in the U.S. and the U.K., most countries exhibit some version of an inverted-U relationship between wives’ participation and husbands’ earnings, although the strength of the relationship varies. Some have argued that this relationship may disappear over time as women married to higher earning men enter the labor force (Ryscavage, 1992). The evidence from the U.S. is consistent with this claim. While an inverted-U relationship continues to exist in 1986, the strength of the relationship diminished somewhat between 1979 and 1986, which is consistent with Can&n et al. (1993a). There is also some evidence that the relationship weakened in Australia, France, and Sweden. This pattern is more clearly shown in Figure 2 where we display the percent change over time in wives’ labor force participation by husbands’ earnings quintile in these four countries. We find that the smallest percentage increase in labor force participation of wives occurred for those women married to men who were in the middle of the earnings distribution. Among women married to the highest earning men in the U.S., the share working rose by 15% between 1979 and 1986. During the same period, the share working among women married to the middle-earning men increased by nine percent, resulting in a difference in growth rates of six points. Similar results are found for Sweden, France, and Australia, where the differences in growth rates of the share working among wives married to high earning versus middle earning men are 3, 19, and 8 points, respectively. All other things equal, the increasing labor force participation of wives of high earners will reduce the equalizing impact of wives’ earnings. On the other hand, wives of the lowest earning men also increased their participation quickly relative to wives of middleearning men. The trend towards greater participation of wives of men at the bottom of the earnings distribution will increase the equalizing impact of wives’ earnings. The correlation in husbands’ and wives’ earnings is positive but small in all countries except Switzerland and Germany, where it is -.lOO and -.052, respectively (Table 3). In France, Sweden, and the United States the correlation increased in the early to mid-1980s. In the U.S., the increase was from .03 in 1979 to .08 in 1986. In France, the correlation was . 11 in 1979 and .16 in 1984, and during the first five years of the 1980s in Sweden, the correlation increased from .19 to .23. In contrast, the correlation of spouses earnings fell from .14 to . 11 in Australia. Our interest is in the distribution of earnings among all married couples. However, considerin-g the correlation of earnings among only those married couples in
hequality in Developed Countries
55
which the wife works may illuminate the patterns behind the correlation observed for all couples. Previous analyses have suggested that the low correlation of spouses’ earnings in the U.S. is the result of labor force participation patterns (Lehrer & Nerlove, 1984). Thus, in Table 3 we report the correlation of spouses’ earnings among couples with a working wifea In the U.S., restricting the sample in this way increases the correlation coefficient to .175 in 1986. For most countries, the correlation of spouses’ earnings is greater among couples in which the wife works. However, in Australia, Israel, and Sweden, the correlation of spouses’ earnings actually falls when we restrict the sample to these couples. In each of these three countries, wives’ labor force participation rates are low for women married to men in the lowest earnings quintile, but otherwise relatively invariant with respect to husbands’ earnings. Thus the correlation falls due to the exclusion of non-working women married to non-working or low earning men.7
4.
RELATIVE MAGNITUDE AND VARIABILITY OF WIVES AND HUSBANDS’ EARNINGS
In addition to their correlation, the relative size and dispersion of spouses’ earnings are also influential in determining the effects of wives’ earnings on the inequality of total earnings. Table 3 reports wives’ share of total household earnings and the CV2 of husbands’ earnings, wives’ earnings, and total earnings. We see that for all married couples, wives’ earnings generally account for 20 to 30% of total earnings. The exceptions are Switzerland, where only 13% of total earnings are attributable to wives’ earnings, and Sweden, where they account for 33 to 35%. Focusing on those countries for which we have data over time, we see that wives’ earnings grew more rapidly than husbands’ in every country. Thus, wives’ earnings accounted for 32% of earnings growth in Australia, 34% in France, 37% in the U.S., and 38% in Sweden.* Wives’ earnings have become an increasingly important source of income. Restricting to the sample of married couples with working wives, the typical contribution of wives’ earnings is between 30 and 40% of total earnings. The exception is Switzerland, where even among couples with working wives, only 26% of family earnings is attributable to wives’ earnings. If we look only at countries for which we have data over time, we see that growth in wives’ earnings accounted for 37 to 44% of the growth in family earnings among couples with working wives. For every country and each time period, when we consider all couples, wives’ earnings are more widely dispersed than husbands’ earnings as measured by the CV’. In fact, the CV2 of wives’ earnings is generally 2 to 4 times greater than the CV2 of husbands’ earnings. In Sweden, where the labor force participation rate of married women is exceptionally high, the CV2 for husbands and for wives are not
Country-Year/ Sample Australia-1981 All couples Working wives Working husbands Both working Australia-1985 All couples Working wives Working husbands Both working Canada-1987 All couples Working wives Working husbands Both working France-1979 All couples Working wives Working husbands Both working 5.61 5.88 4.07 3.35 4.92 4.37 11.78 2.98
0.417 0.763 0.170 0.395 0.519 0.876 0.335 0.614 0.526 1.005 0.424 0.845
0.113 0.056 0.013 0.039 0.092 0.149 0.082 0.183 0.107 0.230 0.036 0.283
3.71 13.56 12.67 10.12
2.24 10.13 -1.17 3.76
0.322 0.819 -0.033 0.318
0.144 0.081 0.029 0.085
-
Phw
Phw
Simulated/ Actual
Simulated
Actual
Country-Year/ Sample Norway-1979 AU couples Working wives Working husbands Both working Sweden-1981 All couples Working wives Working husbands Both working Sweden-1987 All couples Working wives Working husbands Both working Switzerland-1982 All couples Working wives Working husbands Both working -0.100 -0.091 -0.094 -0.079
0.227 0.204 0.205 0.209
0.186 0.148 0.151 0.154
0.140 0.153 0.060 0.112
0.245 0.512 0.235 0.480
0.915 1.099 0.771 0.936
0.688 0.898 0.505 0.000
0.438 0.568 0.303 0.401
Phw
Phw
-
Simulated
Actual
Table 4 Simulated Correlation Coefficients: Correlation of Spouses’ Earnings Such that Wives’ Earnings Have No Impact on the Income Distribution
-2.44 -5.63 -2.51 -6.12
4.04 5.38 3.77 4.49
3.71 6.06 3.33 0.00
3.13 3.72 5.06 3.58
Simulated/ Actual
-4.50 -106.08 -0.17 6.66 1.94 5.99 0.84 2.68
0.596 1.221 0.447 0.995 0.232 0.859 0.012 0.409 0.393 1.071 0.159 0.651
-0.052 -0.008 -0.068 0.061 0.203 0.179 0.189 0.243
AII couples
Working wives Working husbands Both working
Working wives Working husbands Both working Israel-1979
AII couples
Working wives Working husbands Both working Germany-1984
0.255 0.087 0.288
3.73 4.78 5.16 3.46
AII couples
0.160
France-1984 UK-1979 AII couples Working wives Working husbands Both working us-1979 AI1 couples Working wives Working husbands Both working US-1986 AII couples Working wives Working husbands Both working 0.077 0.175 0.064 0.209
0.028 0.095 -0.016 0.106
0.053 0.086 0.003 0.086
0.519 0.879 0.341 0.615
0.336 0.666 0.194 0.470
0.306 0.679 0.113 0.433
6.72 5.03 5.32 2.94
12.16 7.04 -11.81 4.44
5.78 7.85 36.60 5.02
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much different, with husbands at .397 and wives at .440 in 1987. In contrast, in Switzerland, where wives’ participation ‘rate is exceptionally low, the CV2 of wives’ earnings is more than six times that of husbands.’ This suggests that much of the difference in the distributions between men and women is derived from the people not working. If we restrict the sample to couples with working wives (Table 3), the CV2 of wives’ earnings falls by over one-half in every country except Sweden. Nevertheless, the CV2 of wives’ earnings remains higher than that of husbands’ except in Sweden in 1987 and in France. This may reflect greater dispersion in hours rather than wages. If we consider only those couples in which both spouses work, the CV2 of wives’ earnings is higher in all cases (Table 3). The CV2 of wives’ earnings has fallen over time in all those countries for which we have data over time. At least in Australia and the U.S., this trend appears to be related to a decline in the number of women with no earnings. In both countries the CV2 of earnings has actually risen for those wives who work. Inequality in husbands’ earnings has increased in the early to mid- 1980s in Australia, Sweden, and the U.S., which is consistent with Gottschalk and Joyce’s (1992) findings for all men, regardless of marital status.
5.
EFFECT OF WIVES’ EARNINGS ON INEQUALITY
Although wives’ earnings are more widely dispersed than husbands,’ their impact on the distribution of total earnings among married couples also depends on the correlation and relative magnitudes of spouses’ earnings. As discussed in Sections 3 and 4, the correlation of spouses’ earnings is relatively low, and wives’ earnings typically account for 20 to 30% of total earnings. Having examined each of these factors individually, we now turn to the total effect of wives’ earnings on inequality. The last column of Table 3 reports the percent chpge in2the CV: when wives’ earnings is included as a source of income, i.e. (CV, - CV, ) / CV, . For all couples, in every country and every time period, the effect of wives’ earnings is to reduce inequality. Wives’ earnings reduce the CV2 of total earnings by 18 to 26% in most cases. Sweden is an exception; wives’ earnings has a larger impact (28% in 1981 and 33% in 1987). Wives have a more modest equalizing impact in Australia in 1981 (12%), in Israel (1 l%), and in the U.K. (16%). The reduction in inequality is even greater among those couples with working wives, where the CV’ generally falls by 30 to 40% when wives’ earnings are included. Recall that we found that the correlation in spouses’ earnings increased over time in each of the four countries (Australia, France, Sweden, and the U.S.) analyzed (Table 3). Even so, the effect of wives’ earnings continues to have a mitigating effect on the distribution of family earnings, and the mitigating effect has actually become greater over time.
59
inequality in Developed Countries
To further examine the potential importance of the correlation in spouses’ earnings, we calculate the correlation in spouses’ earnings that would have to exist, given all other parameters, in order for the distribution of family earnings to remain unchanged when wives’ earnings are added. The results are given in Table 4. The correlation would have to be substantially higher in order for wives’ earnings not to mitigate inequality in family earnings as measured here. For the U.S. in 1986, the correlation would have to be 52, which is 6.7 times the actual value of .08. Moreover, the actual increase in the correlation for the U.S. was only .06 (from .02 to .08) between 1979 and 1986, suggesting that an unprecedented change in behavior would have to occur in order to drive the correlation to .52. For the remaining countries, the correlation would have to increase by at least two fold and typically by three or four times. These results suggest that increases in the correlation of spouses’ earnings of the magnitude experienced in the early to mid-1980s are most likely not going to reverse the mitigating effect that wives’ earnings has had on family income inequality.
6.
SUMMARY
OF FINDINGS
The wives in the countries analyzed in this study participate in the labor force at very different rates, from a low of 45% in Switzerland in 1982 to a high of 92% in Sweden in 1987. The contribution that wives make to total family earnings also varies substantially among countries, as does the correlation in spouses’ earnings. Even though these countries differ on these dimensions, in all countries wives’ earnings mitigate inequality in total family income. This can be traced, in part, to the tendency for women married to high earning men to work less. For the countries we are able to analyze over time, the labor force participation of the wives married to high earning husbands increased more than the labor force participation for wives married to middle-earning men. If this trend continues, the correlation in spouses’ earnings can be expected to increase, which, by itself, would cause wives’ earnings to be less equalizing. During the early to mid-1980s, however, the effect of an increasing correlation in spouses’ earnings did not dominate. In fact, the mitigating effect of wives’ earnings actually increased slightly in the U.S., Australia, France, and Sweden. Moreover, the correlation of spouses’ earnings would have to experience an unprecedented increase in order for wives’ earnings to become disequalizing. In particular, if all other parameters remained the same, the correlation of spouses’ earnings would have to double, and in many cases increase more than five fold, before wives’ earnings would cease to be equalizing. ACKNOWLEDGMENTS: We thank Sheldon Danziger and Lynn Karoly for helpful comments and discussions and the Sloan Foundation for dissertation fellowship support of Cancian’s work in this area.
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NOTES 1. This counterfactual may be the most commonly used approach to assessing the impact of wives’ earnings on the distribution of income However, it is but one of the many counterfactuals that can be used. See Cancian and Reed (Forthcoming) for a discussion of alternative counterfactuals and their potential importance. 2. Previous studies of the impact of wives’ earnings in the US. show relatively consistent results with a variety of summary measures of income distribution. For example, see Ryscavage ( 1992). 3. One limitation of this method is that it assumes that income from other sources does not respond to changes in the income source under investigation, in this case, that husbands’ earnings are not responsive to changes in wives’ labor force participation or earnings. 4. Note that the LIS drew a sample of observations from data sets for some countries This is why, for example, there are only 11,6 14 cases for the 1986 March CPS. 5. Because consistent measures of hours of market work are not available across countries, we do not analyze the intensity of labor market attachment We also limit our analyses to income from husbands’ and wives’ earnings due to incompatibility of the measures of other income sources across countries and years. Evidence from the U.S. suggests that the impact of wives’ earnings on the inequality of total family income is not sensitive to inclusion of other income sources (Cancian et. al, 1993a). 6. To completely adjust for the impact of participation we would need to consider hours worked and wages; however, consistent data are not available for the LIS data. In addition, selection issues preclude us from generalizing from the sample of couples with working wives to all couples. Nevertheless, the data suggest the extent to which ahw and CV2 reflect labor force participation as opposed to wage patterns. 7. In these countries, about one fourth of zero-earning women are married to zero-earning men. Thus, by excluding zero-earning women we exclude a substantial proportion of couples with perfectly correlated (0,O) earnings. A table comparable to Table 3, but for a sample restricted to couples with working husbands, is available from the authors. In almost all cases, the correlation of spouses’ earnings falls when we exclude zero-earning husbands, as reported in Table 3. 8. We measure the contribution of wives earnings to total earnings growth as the ratio of the change in wives’ earnings to the change in the total of wives’ and husbands’ earnings.
REFERENCES Burtless, G. 1996. “Trends in the Level and Distribution of U.S. Living Standards, 1973-1993,” Paper presented at the 1996 Allied Social Science Associations meetings, January. San Francisco, California. Blackbum, M.L., and Bloom, D.E. 1994. “Changes in the Structure of Family Income Inequality in the U.S. and Other Industrialized Nations During the 1980s.” Luxembourg Income Study Working Paper, #118, Maxwell School of Citizenship and Public Affairs, Syracuse University, Syracuse, New York. Bound, J. and Waidmann, T. 1992. “Disability Transfers, Self-Reported Health, and the Labor Market Attachment of Older Men: Evidence from the Historical Record,” Quarterly Journal of Economics, 107(4): 1393-1419. Cancian, M., Danziger, S., and Gottschalk, P. 1993a. “The Impact of Working Wives on the Level and Distribution of Family Income.” In S. Danziger and P. Gottschalk (Eds.), Uneven Tides: Increasing Inequality in America. New York: Russell Sage Foundation.
Inequality in Developed Countries Can&n,
61
M., Danziger, S., and Gottschalk, P. 1993b. “The Changing Contributions of Men and Women to the Level and Distribution of Family Income 1968-1988.” In E. Wolff (Ed.), Poverty and Prosperity at the Close of the Twentieth Century. New York: MacMillan. Can&n, M., and Reed, D. 1998. “Assessing the Effects of Wives’ Earnings on Family Income Inequality,” Review of Economics and Statistics, 80(l). Coder, J., Rainwater, L., and Smeeding, T. 1988 . “LIS Information Guide,” Luxembourg Income Study Working Paper, #7, Maxwell School of Citizenship and Public Affairs, Syracuse University, Syracuse, New York. Danziger. S. and Gottschalk, P. (Eds.) 1993 . Uneven Tides: Increasing InequaliQ in America. New York: Russell Sage Foundation. Forster, M. 1994. “Family Poverty and the Labor Market,” Luxembourg Income Study Working Paper, #114, Maxwell School of Citizenship and Public Affairs, Syracuse University, Syracuse, New York. Gornick, J., Meyers, M., and Ross, K. 1996. “Supporting the Employment of Mothers: Policy Variation Across Fourteen Welfare States,” Luxembourg Income Study Working Paper, #139, Maxwell School of Citizenship and Public Affairs, Syracuse University, Syracuse, New York. Gomick, J., Meyers, M., and Ross, K. 1996. “Public Policies and the Employment of Mothers: A Cross-National Study,” Luxembourg Income Study Working Paper, #140, Maxwell School of Citizenship and Public Affairs, Syracuse University, Syracuse, New York. Gottschalk, P. and Joyce, M. 1992. “Is Earnings Inequality Also Rising in Other Industrialized Countries?’ Mimeo, Boston College, Department of Economics. Juhn, C. and Murphy, K.M. 1996. “Wage Inequality and Family Labor Supply,” National Bureau of Economics Research Working Paper, #5459, Cambridge, MA. Karoly, L. and Burtless, G. 1995. “Demographic Change, Rising Earnings Inequality, and the Distribution of Personal Well-Being, 1959-1985,” Demography, 32(3): 379406. Knudsen, C. and Peters, H.E. 1994. “An International Comparison of Married Woman’s Labor Supply,” Luxembourg Income Study Working Paper, #106, Maxwell School of Citizenship and Public Affairs, Syracuse University, Syracuse, New York. Lehrer, E. and Nerlove, M. 1984. “A Lifecycle Analysis of Family Income Distribution,” Economic Inquiry, 22: 360-374. Phipps, S.A. 1993. “Determinants of Women’s Labour-Force Participation: An Econometric Analysis for Five Countries,” Luxembourg Income Study Working Paper, #99, Maxwell School of Citizenship and Public Affairs, Syracuse University, Syracuse, New York. Ryscavage, P. 1992 . “Working Wives and Growing Income Inequality,” Paper presented at the Western Economic Association, July. Saunders, P., O’Connor, I., and Smeeding, T. 1994. “The Distribution of Welfare: Inequality, Eamings Capacity, and Household Production in a Comparative Perspective,” Luxembourg Income Study Working Paper, #122, Maxwell School of Citizenship and Public Affairs, Syracuse University, Syracuse, New York. Treas. J. 1987. “The Effect of Women’s Labor Force Participation on the Income Distribution in the United States,” Annual Review of Sociology, 13: 259-288.
This study examines the contribution of wives’ earnings to the distribution of married couples’ earnings in 10 developed countries. There is substantial variation among countries in wives’ labor force participation, the relative earnings of husbands and wives, the distribution of earnings, and the correlation of spouses’ earnings. Even though these countries differ on these dimensions, wives’ earnings mitigate inequality in the earnings of married couples. For the countries we are able to analyze over time, the labor force participation of wives married to high earning husbands increased more than the labor force participation of wives married to middle-earning men. Despite this trend, the mitigating effect of wives’ earnings actually increased slightly in all countries examined. Moreover, all other things equal, the correlation of spouses’ earnings would have to experience an unprecedented increase in order for wives’ earnings to become disequalizing.
1.
INTRODUCTION
In the United States during the 198Os, married women’s labor force participation continued its upward trend. Partly as a consequence, wives’ earnings have been the most important source of growth in household income among married couples, Direct all correspondence to: Maria Can&an, institute of Public Affairs and School of Social Work, 1225 Observatory Drive, University of Wisconsin, Madison, Wisconsin 53706
Journal of Income Distribution, 8(l), 45-61
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ISSN: 09266437
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accounting for about half of the increase during the 1980s (Cancian, Danziger, & Gottschalk, 1993a). During the same time, the gap in income between rich and poor families widened (Danziger & Gottschalk, 1993). Several recent studies have analyzed the role that the trend in women’s labor force involvement has had in determining the level and change in the gap between rich and poor (Burtless, 1996; Juhn & Murphy, 1996; Karoly & Burtless, 1995; Cancian, Danziger, & Gottschalk 1993b; Ryscavage, 1992). Many of these studies are consistent with earlier research which found wives’ earnings to be equalizing (see Tress, 1987 for a review). However, the disproportionate increase in the labor force participation and earnings of women with high earning husbands has caused concern about the potential for wives’ earnings to increase inequality. The objective of this paper is to analyze the impact of wives’ labor force participation and wives’ earnings on the level and distribution of household earnings in other developed countries during the 1980s. Using the Luxembourg Income Study (LIS), we are able to make comparisons across 10 countries, and, for four countries, at different times within the 1980s. We find that wives in the countries analyzed in this study work at very different rates, from a low of 45% in Switzerland in 1982 to a high of 92% in Sweden in 1987. The contribution that wives make to total family earnings varies greatly, from 13% to 35%. The correlation in spouses’ earnings and the relative dispersion of husbands’ and wives’ earnings are also quite different across the countries analyzed. Even so, we find that in all countries, wives’ earnings mitigate inequality in total family earnings among married couple families in that the distribution of earnings is more equal than it would be in the absence of wives’ earnings.’ The reduction, utilizing the squared coefficient of variation as our measure of inequality, ranges from 11% in Israel to 33% in Sweden in 1987. As stated, these results derive from an accounting exercise which compares the distribution of earnings with and without wives’ earnings. We do not model the impact of wives’ earnings on husbands’ labor supply, an analysis which is beyond the scope of this paper. There are a number of other studies which analyze crosscountry difference in men’s and women’s labor supply and earnings (see for example: Gomick, Meyers, & Ross, 1996a and 1996b; Blackbum & Bloom, 1994; Forster, 1994; Knudsen & Peters, 1994; Phipps, 1993: Saunders, O’Connor, & Smeeding, 1994). We begin by discussing the measure of inequality that is utilized and the data that are examined. Next, we document the similarities and differences in wives’ and husbands’ labor force participation and earnings across 10 developed countries and, when the data permit, across time within countries. The role of wives’ earnings in determining the level and distribution of household earnings in each of the 10 countries is then analyzed. The final section summarizes the findings.
47
Inequality in Developed Countries
2.
MEASURE OF INEQUALITY AND THE DATA 2.1. Measure of Inequality
We use the squared coefficient of variation, i.e., the ratio of the variance to the squared mean, as our measure of inequality.2 Consider the squared coefficient of variation of total family earnings (y) when there are only two components of income: earnings of the husband (h) and earnings of the wife (w):
where /li is the mean of earnings source i, phw is the correlation between husbands’ and wives’ earnings, and CV; is the squared coefficient of variation of earnings source i. We are interested in the than e in in%quality Then wives’ earnings are gz included as a source of income, i.e. (CV, - CVh ) / CVh . The key components of this change are the share of total earnings attributable to wives’ earnings relative to husbands’, the correlation of spouses’ earnings, and the dispersion of wives’ and husbands’ earnings. Furthermore, as is evident from (l), the greater the correlation in spouses’ earnings the greater the inequality in total household earnings regardless of all other parameters. These components are analyzed empirically for each country.3
Table 1 Source of Each Data Set Country, Year Australia 1981/82 Australia 1985186 Canada 1987 France 1979 France 1984 West Germany 1984 Israel 1979 Norway 1979 Sweden 1981 Sweden 1987 Switzerland 1982 United Kingdom 1979 United States 1979 United States 1986 Note:
Original Data Set
Size*
Income and Housing Survey Income and Housing Survey Survey of Consumer Finances Survey of Indiv Income Tax Returns Income Survey of Taxes German Panel Survey Family Expenditures Survey Norwegian Tax Files Swedish Income Distribution Survey Swedish Income Distribution Survey Income and Wealth Survey Family Expenditure Survey March Current Population Survey March Current Population Survey
15,985 7,560 10,999 11,044 12,693 5,174 2,271 10,414 9,625 9,421 7,036 6,777 15,225 11,614
‘(Data set size refers to the unweighted LIS sample size.
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2.2. Data
We examine microdata from 10 countries: Australia, Canada, France, West Germany, Israel, Norway, Sweden, Switzerland, United Kingdom, and the United States. Data from two periods are analyzed for Australia, France, Sweden, and the United States. Table 1 lists the original data source for each country and year. Access to the data was obtained through the Luxembourg Income Study (LB). The survey instrument, sampling frame, and variable definitions differed among countries. However, one advantage of the LIS data is that, whenever possible, they have utilized common definitions of income sources (see Coder, Rainwater, & Smeeding, 1988 for a detailed discussion of the LIS project and data sources).4 Annual wage and salary income (gross of taxes) is the earnings variable analyzed for each country. This variable is available for the head and spouse of each household.5 Reports of earnings are top-coded in the U.S. data. In 1986, 1.4% of our sample of husbands and wives had earnings of at least $100,000, which was the top-code in that year. For 1979,2.6% had earnings at or above the top-code of $50,000. To examine the sensitivity of our findings to top-coding, we replicated our results for the U.S. trimming the top-five percent of earners and found that the qualitative results were unchanged when the sample was trimmed. (See the table note in Table 3 for specific estimates). The analyses are restricted to married couples in which the husband is 25 to 55 years of age in order to minimize the potential confounding effects of retirement and school attendance. LIS’s (family) sample weights are used for all analyses. Table 2 Share of Wives Who Are Working by Husbands’ Earnings Quintile for Each Country Share of Wives Working by Husbands’ Earnings Quintile Country, Year Australia 1981-82 Australia 1985-86 Canada 1987 France 1979 France 1984 West Germany 1984 Israel 1979 Norway 1979 Sweden 1981 Sweden 1987 Switzerland 1982 United Kingdom 1979 United States 1979 United States 1986 Note:
Husband
Wife
1st*
2nd
3rd
4th
5th
74.8 80.6 87.5 83.5 83.7 84.7 78.0 89.7 91.3 93.3 99.0 87.6 88.5 86.2
48.4 57.5 71.2 46.7 54.9 49.0 46.0 70.9 85.8 91.7 44.6 59.8 61.5 68.7
30.3 36.5 66.2 24.4 32.5 49.0 31.7 53.4 73.3 82.4 44.6 51.2 55.2 63.2
53.3 61.7 75.2 50.5 58.2 51.6 40.3 74.7 84.8 93.1 56.9 65.6 68.0 73.6
57.4 63.6 71.6 58.8 61.2 55.8 50.9 76.7 90.1 93.4 47.5 65.4 67.0 73.1
54.9 63.4 74.2 55.6 67.7 47.2 48.9 78.4 92.0 94.5 47.1 62.5 63.2 71.9
52.5 62.2 68.9 44.2 54.7 41.2 59.1 71.2 88.9 95.0 32.6 54.7 53.8 61.7
*lst is the lowest quintile.
Inequality in Developed Countries
3.
49
RELATIONSHIP BETWEEN WIVES’ AND HUSBANDS’ EARNINGS
The share of husbands who are working ranges from 75% to 93%, except in Switzerland where 99% of the husbands have positive earnings (Table 2). The employment rate among husbands declined between 1979 and 1986 in the US., a result which is consistent with a more general decline in men’s labor force attachment (Bound & Waidmann, 1992). In contrast, the share of husbands working was constant or rose slightly during the early 1980s in Australia, France, and Sweden. There is much greater variance across countries in the share of wives working. In the early 1980s just 45% of the wives in Switzerland worked while 86% of
201 111
i 2nd
3rd
uh
Nmvw, S-UK loo. 90.
Figure 2. Relationship Between Share of Wives Working and Husbands’ Earnings Quintile
5th
50
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Swedish wives did so. If we look at the eight countries for which we have data between 1979 and 1982, four (Australia, France, Israel, and Switzerland) had work-rates in the mid- to upper-forties, two (the U.K. and the U.S.) had work-rates close to sixty percent, while Norway and Sweden had higher shares working, 71 and 86%, respectively. Furthermore, we find a pattern of increasing attachment to the labor force for married women in all those countries for which we have two observations. In Australia, France, Sweden, and the U.S., the share of married women working increased by at least one percentage point per year over the period analyzed. As discussed in Section II, the association between husbands’ and wives’ labor market outcomes is important in understanding the effects of wives’ earnings on the inequality of total family earnings. The more highly (positively) correlated spouses’ earnings, the greater the inequality, ceteris paribus. In addition, because many wives do not work, the relationship between the share of wives working and husbands’ earnings has an important impact on the correlation of earnings. The share of wives who work increases with husbands’ earnings, but not over the entire range of husbands’ earnings; in most cases, the relationship is negative for those couples in which the husband is in the higher earnings quintiles. In most all countries, the share working is lowest for those wives whose husbands are the highest and lowest earners (Figure 1). For example, in the U.S. in 1986, of those Alrrmlia
1981-1985
3rd
2nd Swdcn
Fnncs 1979-1984
4th
5eb
1st
1981-1987
U&d
35
35
30
30
20 25 i
20 25 i
Figure 2.
3rd
2nd
Stata
4th
5th
1979-1986
Percent Change Over Time in the Share of Wives Working by Husbands’ Earnings Quintile
Country-Year
Sample
Australia-1981/82 AII couples Working wives Working husbands Both working Australia-1985/86 All couples Working wives Working husbands Both working Canada-1987 AU couples Working wives Working husbands Both working France-1979 AII couples Working wives Working husbands Both working France-1984 AII couples Working wives Working husbands Both working 75 84 100 100 81 88 100 100 87 89 100 100 84 93 100 100 84 92 100 100
57 100 63 100 71 100 73 100 47 100 52 100 55 100 60 100
Husbands
48 100 55 100
Wives
28.2 40.3 26.5 38.3
23.5 38.7 22.1 36.8
28.2 35.6 26.0 33.1
26.1 36.2 23.8 33.4
23.2 35.8 20.5 32.2
(%)
Wives’ Share of Income
0.160 0.255 0.087 0.288
0.107 0.230 0.036 0.283
1.514 0.389 1.295 0.379
2.105 0.451 1.750 0.431
1.204 0.570 1.160 0.573
1.618 0.505 1.392 0.496
0.113 0.056 0.013 0.039 0.092 0.149 0.082 0.183
2.064 0.484 1.701 0.473
Wives
0.144 0.081 0.029 0.085
Phw
0.795 0.502 0.503 0.377
0.912 0.454 0.597 0.352
0.551 0.484 0.357 0.327
0.589 0.368 0.280 0.198
0.576 0.381 0.178 0.162
Husband
CV2
0.601 0.296 0.390 0.251
0.703 0.287 0.460 0.251
0.410 0.309 0.294 0.244
0.474 0.227 0.245 0.149
0.507 0.235 0.189 0.134
Total
Table 3 of Husbands’ and Wives’ Earnings for Each Country
Percent Working
Level and Distribution
(continued)
-24.4 -40.9 -22.5 -33.6
-22.9 -36.7 -22.9 -28.9
-25.5 -36.2 -17.5 -25.3
-19.5 -38.2 -12.6 -25.0
-12.0 -38.3 6.2 -17.4
(%I
Change Due to Wives
Country-Year Sample
Germany-1984 AI1 couples Working wives Working husbands Both working Israel-1979 Ail couples Working wives Working husbands Both working Norway-1979 All couples Working wives Working husbands Both working Sweden-1981 AU couples Working wives Working husbands Both working Sweden-1987 AU couples Working wives Working husbands Both working 0.447 0.314 0.421 0.309
0.227 0.204 0.205 0.209
35.1 36.7 34.0 35.6
93 95 100 100
92 100 93 100
0.400 0.355 0.306 0.284
0.377 0.319 0.257 0.232
0.590 0.365 0.548 0.360
0.186 0.148 0.151 0.154
33.0 35.6 31.6 34.2
91 93 100 100
86 100 88 100
0.451 0.295 0.302 0.210
1.213 0.569 1.099 0.551
0.140 0.153 0.060 0.112
25.0 31.2 24.2 30.2
90 93 100 100
71 100 74 100
0.420 0.372 0.203 0.182
Husband
0.671 0.498 0.304 0.271
0.203 0.179 0.189 0.243
21.0 33.5 18.4 30.0
78 85 100 100
46 100 50 100
1.956 0.447 1.908 0.447
Wives
cv2
2.160 0.453 1.920 0.461
-0.052 -0.008 -0.068 0.061
Phw
21.4 36.8 18.7 33.0
(%)
85 86 100 100
Husbands
49 100 50 100
Wives
Wives’ Share of Income
0.267 0.216 0.215 0.185
0.272 0.202 0.199 0.000
0.368 0.222 0.250 0.169
0.595 0.309 0.311 0.210
0.334 0.208 0.188 0.138
Total
Table 3 of Husbands’ and Wives’ Earnings for Each Country
Percent Working
Level and Distribution
-33.2 -39.1 -29.8 -34.8
-27.8 -36.8 -22.3 0.0
-18.3 -24.8 -17.0 -19.7
-11.3 -38.0 2.3 -22.4
-20.6 -44.2 -7.5 -24.1
Change Due to Wives (%)
hWs:
20.3 29.8 18.3 27.9
88 90 100 100 89 91 100 100 86 88 100 100
60 loo 59 100 61 100 63 100 69 100 70 100
26.7 35.4 24.4 32.6
20.9 30.5 19.5 28.7
12.5 25.6 12.3 25.2
99 99 100 100
45 100 44 100
0.077 0.175 0.064 0.209
0.028 0.095 -0.016 0.106
0.053 0.086 0.003 0.086
-0.100 -0.091 -0.094 -0.079
1.431 0.669 1.389 0.678
1.635 0.619 1.529 0.602
1.572 0.538 1.560 0.522
2.629 0.619 2.647 0.621
0.642 0.570 0.416 0.385
0.443 0.375 0.278 0.254
0.390 0.330 0.216 0.203
0.413 0.269 0.398 0.252
0.476 0.371 0.338 0.294
0.357 0.258 0.235 0.196
0.326 0.226 0.197 0.157
0.334 0.175 0.326 0.169
-25.9 -34.9 -18.6 -23.7
-19.6 -31.2 -15.5 -23.0
-16.4 -31.6 -8.9 -22.4
-19.0 -34.8 -18.2 -33.0
For the U.S. in each year, we re-estimated each model trimming the top five percent of earners. Reading across the row for ‘Ml Couples,” the estimates become 62,88,21.9,0.057,1.561,0.387,0.326, and -15.8 for 1979 and 69,86,27.5,0.004,1.354, 0.556,0.418, and -25.1 for 1986.
Switzerland-1982 All couples Working wives Working husbands Both working UK-1979 All couples Working wives Working husbands Both working us-1979 All couples Working wives Working husbands Both working US-1986 AU couples Working wives Working husbands Both working
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wives whose husbands’ earnings ranked in the lowest quintile, 63% worked. Similarly, for those with the highest earning husbands, 62% had positive earnings, At the same time, the share of wives working among wives whose husbands ranked in the middle three quintiles is 10 points higher. The tendency for U.S. women with high earning husbands to work less has been cited as an explanation for the low correlation of spouses’ earnings, which in turn contributes to the equalizing impact of wives’ earnings. This may reflect an income effect on wives’ labor-leisure decision, with greater family income, derived primarily from a high-earning husband, purchasing greater leisure for the wife. Similar to the experience of couples in the U.S. and the U.K., most countries exhibit some version of an inverted-U relationship between wives’ participation and husbands’ earnings, although the strength of the relationship varies. Some have argued that this relationship may disappear over time as women married to higher earning men enter the labor force (Ryscavage, 1992). The evidence from the U.S. is consistent with this claim. While an inverted-U relationship continues to exist in 1986, the strength of the relationship diminished somewhat between 1979 and 1986, which is consistent with Can&n et al. (1993a). There is also some evidence that the relationship weakened in Australia, France, and Sweden. This pattern is more clearly shown in Figure 2 where we display the percent change over time in wives’ labor force participation by husbands’ earnings quintile in these four countries. We find that the smallest percentage increase in labor force participation of wives occurred for those women married to men who were in the middle of the earnings distribution. Among women married to the highest earning men in the U.S., the share working rose by 15% between 1979 and 1986. During the same period, the share working among women married to the middle-earning men increased by nine percent, resulting in a difference in growth rates of six points. Similar results are found for Sweden, France, and Australia, where the differences in growth rates of the share working among wives married to high earning versus middle earning men are 3, 19, and 8 points, respectively. All other things equal, the increasing labor force participation of wives of high earners will reduce the equalizing impact of wives’ earnings. On the other hand, wives of the lowest earning men also increased their participation quickly relative to wives of middleearning men. The trend towards greater participation of wives of men at the bottom of the earnings distribution will increase the equalizing impact of wives’ earnings. The correlation in husbands’ and wives’ earnings is positive but small in all countries except Switzerland and Germany, where it is -.lOO and -.052, respectively (Table 3). In France, Sweden, and the United States the correlation increased in the early to mid-1980s. In the U.S., the increase was from .03 in 1979 to .08 in 1986. In France, the correlation was . 11 in 1979 and .16 in 1984, and during the first five years of the 1980s in Sweden, the correlation increased from .19 to .23. In contrast, the correlation of spouses earnings fell from .14 to . 11 in Australia. Our interest is in the distribution of earnings among all married couples. However, considerin-g the correlation of earnings among only those married couples in
hequality in Developed Countries
55
which the wife works may illuminate the patterns behind the correlation observed for all couples. Previous analyses have suggested that the low correlation of spouses’ earnings in the U.S. is the result of labor force participation patterns (Lehrer & Nerlove, 1984). Thus, in Table 3 we report the correlation of spouses’ earnings among couples with a working wifea In the U.S., restricting the sample in this way increases the correlation coefficient to .175 in 1986. For most countries, the correlation of spouses’ earnings is greater among couples in which the wife works. However, in Australia, Israel, and Sweden, the correlation of spouses’ earnings actually falls when we restrict the sample to these couples. In each of these three countries, wives’ labor force participation rates are low for women married to men in the lowest earnings quintile, but otherwise relatively invariant with respect to husbands’ earnings. Thus the correlation falls due to the exclusion of non-working women married to non-working or low earning men.7
4.
RELATIVE MAGNITUDE AND VARIABILITY OF WIVES AND HUSBANDS’ EARNINGS
In addition to their correlation, the relative size and dispersion of spouses’ earnings are also influential in determining the effects of wives’ earnings on the inequality of total earnings. Table 3 reports wives’ share of total household earnings and the CV2 of husbands’ earnings, wives’ earnings, and total earnings. We see that for all married couples, wives’ earnings generally account for 20 to 30% of total earnings. The exceptions are Switzerland, where only 13% of total earnings are attributable to wives’ earnings, and Sweden, where they account for 33 to 35%. Focusing on those countries for which we have data over time, we see that wives’ earnings grew more rapidly than husbands’ in every country. Thus, wives’ earnings accounted for 32% of earnings growth in Australia, 34% in France, 37% in the U.S., and 38% in Sweden.* Wives’ earnings have become an increasingly important source of income. Restricting to the sample of married couples with working wives, the typical contribution of wives’ earnings is between 30 and 40% of total earnings. The exception is Switzerland, where even among couples with working wives, only 26% of family earnings is attributable to wives’ earnings. If we look only at countries for which we have data over time, we see that growth in wives’ earnings accounted for 37 to 44% of the growth in family earnings among couples with working wives. For every country and each time period, when we consider all couples, wives’ earnings are more widely dispersed than husbands’ earnings as measured by the CV’. In fact, the CV2 of wives’ earnings is generally 2 to 4 times greater than the CV2 of husbands’ earnings. In Sweden, where the labor force participation rate of married women is exceptionally high, the CV2 for husbands and for wives are not
Country-Year/ Sample Australia-1981 All couples Working wives Working husbands Both working Australia-1985 All couples Working wives Working husbands Both working Canada-1987 All couples Working wives Working husbands Both working France-1979 All couples Working wives Working husbands Both working 5.61 5.88 4.07 3.35 4.92 4.37 11.78 2.98
0.417 0.763 0.170 0.395 0.519 0.876 0.335 0.614 0.526 1.005 0.424 0.845
0.113 0.056 0.013 0.039 0.092 0.149 0.082 0.183 0.107 0.230 0.036 0.283
3.71 13.56 12.67 10.12
2.24 10.13 -1.17 3.76
0.322 0.819 -0.033 0.318
0.144 0.081 0.029 0.085
-
Phw
Phw
Simulated/ Actual
Simulated
Actual
Country-Year/ Sample Norway-1979 AU couples Working wives Working husbands Both working Sweden-1981 All couples Working wives Working husbands Both working Sweden-1987 All couples Working wives Working husbands Both working Switzerland-1982 All couples Working wives Working husbands Both working -0.100 -0.091 -0.094 -0.079
0.227 0.204 0.205 0.209
0.186 0.148 0.151 0.154
0.140 0.153 0.060 0.112
0.245 0.512 0.235 0.480
0.915 1.099 0.771 0.936
0.688 0.898 0.505 0.000
0.438 0.568 0.303 0.401
Phw
Phw
-
Simulated
Actual
Table 4 Simulated Correlation Coefficients: Correlation of Spouses’ Earnings Such that Wives’ Earnings Have No Impact on the Income Distribution
-2.44 -5.63 -2.51 -6.12
4.04 5.38 3.77 4.49
3.71 6.06 3.33 0.00
3.13 3.72 5.06 3.58
Simulated/ Actual
-4.50 -106.08 -0.17 6.66 1.94 5.99 0.84 2.68
0.596 1.221 0.447 0.995 0.232 0.859 0.012 0.409 0.393 1.071 0.159 0.651
-0.052 -0.008 -0.068 0.061 0.203 0.179 0.189 0.243
AII couples
Working wives Working husbands Both working
Working wives Working husbands Both working Israel-1979
AII couples
Working wives Working husbands Both working Germany-1984
0.255 0.087 0.288
3.73 4.78 5.16 3.46
AII couples
0.160
France-1984 UK-1979 AII couples Working wives Working husbands Both working us-1979 AI1 couples Working wives Working husbands Both working US-1986 AII couples Working wives Working husbands Both working 0.077 0.175 0.064 0.209
0.028 0.095 -0.016 0.106
0.053 0.086 0.003 0.086
0.519 0.879 0.341 0.615
0.336 0.666 0.194 0.470
0.306 0.679 0.113 0.433
6.72 5.03 5.32 2.94
12.16 7.04 -11.81 4.44
5.78 7.85 36.60 5.02
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58
much different, with husbands at .397 and wives at .440 in 1987. In contrast, in Switzerland, where wives’ participation ‘rate is exceptionally low, the CV2 of wives’ earnings is more than six times that of husbands.’ This suggests that much of the difference in the distributions between men and women is derived from the people not working. If we restrict the sample to couples with working wives (Table 3), the CV2 of wives’ earnings falls by over one-half in every country except Sweden. Nevertheless, the CV2 of wives’ earnings remains higher than that of husbands’ except in Sweden in 1987 and in France. This may reflect greater dispersion in hours rather than wages. If we consider only those couples in which both spouses work, the CV2 of wives’ earnings is higher in all cases (Table 3). The CV2 of wives’ earnings has fallen over time in all those countries for which we have data over time. At least in Australia and the U.S., this trend appears to be related to a decline in the number of women with no earnings. In both countries the CV2 of earnings has actually risen for those wives who work. Inequality in husbands’ earnings has increased in the early to mid- 1980s in Australia, Sweden, and the U.S., which is consistent with Gottschalk and Joyce’s (1992) findings for all men, regardless of marital status.
5.
EFFECT OF WIVES’ EARNINGS ON INEQUALITY
Although wives’ earnings are more widely dispersed than husbands,’ their impact on the distribution of total earnings among married couples also depends on the correlation and relative magnitudes of spouses’ earnings. As discussed in Sections 3 and 4, the correlation of spouses’ earnings is relatively low, and wives’ earnings typically account for 20 to 30% of total earnings. Having examined each of these factors individually, we now turn to the total effect of wives’ earnings on inequality. The last column of Table 3 reports the percent chpge in2the CV: when wives’ earnings is included as a source of income, i.e. (CV, - CV, ) / CV, . For all couples, in every country and every time period, the effect of wives’ earnings is to reduce inequality. Wives’ earnings reduce the CV2 of total earnings by 18 to 26% in most cases. Sweden is an exception; wives’ earnings has a larger impact (28% in 1981 and 33% in 1987). Wives have a more modest equalizing impact in Australia in 1981 (12%), in Israel (1 l%), and in the U.K. (16%). The reduction in inequality is even greater among those couples with working wives, where the CV’ generally falls by 30 to 40% when wives’ earnings are included. Recall that we found that the correlation in spouses’ earnings increased over time in each of the four countries (Australia, France, Sweden, and the U.S.) analyzed (Table 3). Even so, the effect of wives’ earnings continues to have a mitigating effect on the distribution of family earnings, and the mitigating effect has actually become greater over time.
59
inequality in Developed Countries
To further examine the potential importance of the correlation in spouses’ earnings, we calculate the correlation in spouses’ earnings that would have to exist, given all other parameters, in order for the distribution of family earnings to remain unchanged when wives’ earnings are added. The results are given in Table 4. The correlation would have to be substantially higher in order for wives’ earnings not to mitigate inequality in family earnings as measured here. For the U.S. in 1986, the correlation would have to be 52, which is 6.7 times the actual value of .08. Moreover, the actual increase in the correlation for the U.S. was only .06 (from .02 to .08) between 1979 and 1986, suggesting that an unprecedented change in behavior would have to occur in order to drive the correlation to .52. For the remaining countries, the correlation would have to increase by at least two fold and typically by three or four times. These results suggest that increases in the correlation of spouses’ earnings of the magnitude experienced in the early to mid-1980s are most likely not going to reverse the mitigating effect that wives’ earnings has had on family income inequality.
6.
SUMMARY
OF FINDINGS
The wives in the countries analyzed in this study participate in the labor force at very different rates, from a low of 45% in Switzerland in 1982 to a high of 92% in Sweden in 1987. The contribution that wives make to total family earnings also varies substantially among countries, as does the correlation in spouses’ earnings. Even though these countries differ on these dimensions, in all countries wives’ earnings mitigate inequality in total family income. This can be traced, in part, to the tendency for women married to high earning men to work less. For the countries we are able to analyze over time, the labor force participation of the wives married to high earning husbands increased more than the labor force participation for wives married to middle-earning men. If this trend continues, the correlation in spouses’ earnings can be expected to increase, which, by itself, would cause wives’ earnings to be less equalizing. During the early to mid-1980s, however, the effect of an increasing correlation in spouses’ earnings did not dominate. In fact, the mitigating effect of wives’ earnings actually increased slightly in the U.S., Australia, France, and Sweden. Moreover, the correlation of spouses’ earnings would have to experience an unprecedented increase in order for wives’ earnings to become disequalizing. In particular, if all other parameters remained the same, the correlation of spouses’ earnings would have to double, and in many cases increase more than five fold, before wives’ earnings would cease to be equalizing. ACKNOWLEDGMENTS: We thank Sheldon Danziger and Lynn Karoly for helpful comments and discussions and the Sloan Foundation for dissertation fellowship support of Cancian’s work in this area.
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Vol. 8 No. 1 (1998)
NOTES 1. This counterfactual may be the most commonly used approach to assessing the impact of wives’ earnings on the distribution of income However, it is but one of the many counterfactuals that can be used. See Cancian and Reed (Forthcoming) for a discussion of alternative counterfactuals and their potential importance. 2. Previous studies of the impact of wives’ earnings in the US. show relatively consistent results with a variety of summary measures of income distribution. For example, see Ryscavage ( 1992). 3. One limitation of this method is that it assumes that income from other sources does not respond to changes in the income source under investigation, in this case, that husbands’ earnings are not responsive to changes in wives’ labor force participation or earnings. 4. Note that the LIS drew a sample of observations from data sets for some countries This is why, for example, there are only 11,6 14 cases for the 1986 March CPS. 5. Because consistent measures of hours of market work are not available across countries, we do not analyze the intensity of labor market attachment We also limit our analyses to income from husbands’ and wives’ earnings due to incompatibility of the measures of other income sources across countries and years. Evidence from the U.S. suggests that the impact of wives’ earnings on the inequality of total family income is not sensitive to inclusion of other income sources (Cancian et. al, 1993a). 6. To completely adjust for the impact of participation we would need to consider hours worked and wages; however, consistent data are not available for the LIS data. In addition, selection issues preclude us from generalizing from the sample of couples with working wives to all couples. Nevertheless, the data suggest the extent to which ahw and CV2 reflect labor force participation as opposed to wage patterns. 7. In these countries, about one fourth of zero-earning women are married to zero-earning men. Thus, by excluding zero-earning women we exclude a substantial proportion of couples with perfectly correlated (0,O) earnings. A table comparable to Table 3, but for a sample restricted to couples with working husbands, is available from the authors. In almost all cases, the correlation of spouses’ earnings falls when we exclude zero-earning husbands, as reported in Table 3. 8. We measure the contribution of wives earnings to total earnings growth as the ratio of the change in wives’ earnings to the change in the total of wives’ and husbands’ earnings.
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