Female Employment, Earnings Inequality and Household Well-being: The case of urban Turkey

5. Women’s Employment and Household Welfare
In our data set, women who are gainfully employed make up 7.9% of adult household members between the ages of 15 to 64. Including the unpaid female workers among the employed increases this proportion to 8.6%. Women’s earnings, on the other hand, constitute 12.2% of total earnings of working age adults (simply referred to as household earnings) and 6.7% of household income, the latter of which includes non-wage income as well as labor market earnings. Despite the gender earnings gap illustrated earlier, women contribute disproportionately more to household earnings. In households where there is at least one gainfully employed woman, women’s contribution increases further to 54.1% and 35.3%, respectively. The drastic increase in these figures indicates that women’s gainful employment carries a heavy weight in households where they are found. We suspect the true contribution of women to be even higher than what is estimated here due to the presence of unpaid female family workers. Even when we solely concentrate on gainfully employed women, their true contribution is dwarfed by the fact that the proceeds of unpaid workers appear implicitly within the personal earnings reported by the male household head. So, although the work of unpaid family workers is not remunerated explicitly, they are included within total household earnings. Assigning such women wages based on what they would have earned had they chosen wage employment by taking into account the sector they are in, increases women’s total contribution to 12.6% of household earnings and 7% of household income.⁸
As discussed earlier, women’s earnings differ by employment status. On average, employers and wage earners receive higher earnings compared to the self-employed and causal workers. To see whether women’s contribution to total household earnings follows a similar order - which is not necessarily the case if the household is made up of a mix group of low and high wage earners - , we compute separate shares for the five categories of working women. If there are more than one working women within the same household, each belonging to a different employment category, we ignore the income generated by women belonging to other categories but the category we are presently interested in. This is indeed a simplistic approach, but nevertheless provides a clue regarding the relative contribution of different categories of women to household income.⁹ Proceeding with this methodology, we find that in households where there is at least one female regular wage earner, women’s average contribution to household earnings is 50.5%. The corresponding figures for casual workers, employers, the self-employed and unpaid family workers are 36.7%, 53.7%, 33% and 22.6%, respectively (see Table 7).
--- Insert Table 7 about here. ---
These figures reveal that the two highest earning groups of women also make the largest contribution (around 50%) to the total earnings of the household which is indicative of a good match between working women and the other earners in the household. Considering that the households of female regular wage earners and that of employers are mostly nuclear, these finding is suggestive of assortative mating; i.e. that higher earning women are matched with higher earning men.¹⁰ In the case of casual wage earners and the self-employed women, we observe lower income shares that are in similar magnitudes. These findings, in turn, possibly indicate that the match between male and female earners in such households is not as close as what we observe among regular wage earners and employers. Unpaid family workers are estimated to contribute the least, which might be due to a number of reasons, one being that we are underestimating their earnings and therefore, their contribution to household earnings. The other explanation is that they are poorly matched with the rest of the earners in the household. When women’s earnings are compared to total household income similar results follow.

--- Insert Table 8 about here. ---

It might also be interesting to look at the relative contribution of women to household budget at different points in the income distribution. Such an exercise will provide further clues regarding the heterogeneity of households in terms of the earnings potential of their members, which of course has implications for income distribution. When households are ranked according to total household income and divided into five equal groups, we observe a rather large gap in the proportion of employed women between the top and the bottom quintiles. While, in the bottom quintile, only 11.8% of women are employed, the corresponding figure for households in the top quintile is 28.7%. As shown in Table 8, the proportion of employed women between the top and the bottom quintiles does not increase linearly. In the second quintile, this proportion drops a little to 10.7%, picking up in the third quintile where it is estimated at 11.9%. From the third to the fourth quintile the proportion of employed women registers an only 2.8 percentage points increase, while the increase between the fourth and the top quintile is on the order of 14 percentage points. The ranking of the households are naturally affected by the earnings of their female labor market participants. When the earnings of female workers are deducted from household income and households are re-ordered, we see a big drop in the proportion of employed women in the top quintile and a sharp increase in the bottom quintile (see Table 8). In other quintiles, the changes are not as dramatic. These observations are consistent with the diversity observed among working women. As discussed earlier positive sorting means that there are highly educated, high earning women in the labor market. However, at the opposite end, there are poorly educated women with low earnings. Nevertheless, we have shown that even the low earning women contribute significantly to household earnings with the result that deducting their earnings from household income possibly results in a drop in their household’s position in income distribution.
Table 9 allows us to observe the change in households’ position in income distribution as a result of the change in the definition of household income to include and exclude female earnings. We find that roughly 14 percent of the households in the bottom quintile move up, in many cases to the 2^nd quintile with the inclusion of female earnings. Note that the off-diagonal observations indicate the cases where the households switch from one quintile to another after the inclusion of female earnings in household income such that the entries below the main diagonal are upward moves. At the other end of the distribution, 15 percent of the households in the top quintile move down to the 4^th quintile after the inclusion of female earnings. Overall, almost a quarter of the households move up or down the distribution so as to switch to a different quintile as a result of the redefinition of household income.
--- Insert Table 9 about here. ---
When the contribution of women to total earnings of the household is examined by quintile, different patterns emerge depending on the measure of income used to rank households. When total household income is used in placing the household in income distribution, with the exception of the lowest income group, we see that the contribution increases with income quintiles. This is consistent with the rising share of employed women among working age adults with quintiles. At the top quintile, women’s contribution to total household earnings amount to 20%. When judged against their employment share this is a significant contribution. In fact, in all income quintiles, women are found to contribute disproportionately more to household earnings. When women’s earnings are deducted from household income and households are re-ranked, the biggest monetary contribution is observed among women in the bottom quintile at 20.6%. Hence, it seems that women’s earnings do play a role in changing the position of households in income distribution. The question that comes to mind at this point is whether these earnings lead to an increase or decrease in household income inequality.
6. Contribution of Women’s Earnings to Inequality
There is an extensive literature on the contribution of various sources of income to inequality. The majority of these studies analyze two broad earnings categories i.e. labor market earnings and non-labor income and conclude that the latter is less equally distributed (see for instance Fields, 1979; Reed and Cancian, 2001, for Turkey see; Silber and Özmucur, 2000; TÜSİAD, 2000). Following this line of tradition, we also employ these two broad categorizations but focus our attention particularly on earnings by dividing it into those contributed by male and female household members. Our aim here is two-fold; first, to determine whether female earnings are ‘equalizing’ or not and secondly, to quantify the relative contribution of female earnings to overall inequality. Earlier in of the paper, we showed that working women are more diverse than men on the basis of various indicators but most notably labor market earnings. Whether or not this diversity will impact the income distribution negatively is an empirical question and depends on the distribution of these women across households. To the extent that women belonging in low and middle income families become economically active to maintain a certain standard of living, female earnings could reduce inequality. Conversely, the positive assortative mating of more educated, thus better paid, couples could imply that the contribution of female earnings to household income inequality is positive. In the Turkish case, there is evidence of assortative mating. Furthermore, we noted that although working women are positively sorted into the labor market, in the sense that it is the more educated women who enter the labor market on average, nevertheless, in comparison to men, a larger proportion of working women have very low education levels. We conjecture that such women, despite their low earnings potential, enter to uplift household income.
The empirical work produces mixed results and, therefore, does not help identify which of the conjectures suggested above are correct. The “before-and-after” computations where the potential labor supply adjustment of other household members is ignored reveal that the inclusion of female earnings to the rest of the sources of household income leaves the distribution unchanged or at most, leads to a small increase in inequality (see Table 10). Interestingly, the inclusion of female earnings to household income in the top and bottom quintiles, leads to a small decline in inequality. In the other income quintiles, the inequality measures do not register a change. To make sense of these results, we can view the overall inequality as the sum of intra and inter-group inequalities. It seems that the inclusion of female earnings works to reduce the former in the top and bottom quintiles, but increases the across the group inequality, producing the result that the overall inequality remains roughly the same. In view of the greater diversity among working women across the income groups, this result is not surprising.
--- Insert Table 10 about here. ---
When the alternative decomposition technique (Shorrock’s formulation) is used, women’s earnings are found to contribute disproportionately more to income inequality. In this exercise, we distinguish between the earnings of (i) working age males and (ii) females, (iii) earnings contributed by other members (under age or over-age individuals), and (iv) non-labor income. Using simple sample averages, while the share of female earnings is 9.2%¹¹ of total income, the proportionate contribution is disproportionately large at 13.7% (See Table 11). In comparison to the income shares, relatively higher proportionate contributions of female earnings are observed in second, third and fourth quintiles. Per unit contribution is especially large in the fourth quintile where female earnings make up 7.3% of household income but contribute to inequality by 16.5%. In parallel with the findings of the ‘before-and-after’ analysis, the lowest per unit contribution is observed in the bottom quintile. Here, women’s earnings are found to reduce income inequality. Finally, in the top quintile, women’s earnings slightly increase inequality.¹²
To complete the picture, we briefly turn to the non-wage component of income and the earnings contributed by other members. The non-wage income contributes a surprisingly low 31.3% to inequality even though it accounts for 35% of income. Given the way the proportionate contributions are defined, this must have to do with the distribution of this component. Apparently, those households that have the largest total income are not the ones with the highest non-wage income figures. The contribution of other individuals to household income other than working age adults is minimal at 1.4%. However, the distribution of this source is rather unequal so that its contribution reaches 9.4%.
--- Insert Table 11 about here. ---
7. Conclusions
The various policy documents produced on the Turkish labor market discuss the need to integrate more women into the labor market, especially in urban areas. Official documents such as the 5-year development plans of Turkey also recognize this need and call for appropriate measures to be taken. To date, the Turkish government has not formulated a comprehensive program geared toward increasing the participation of women and improving the labor market conditions of active participants. This is expected to change in the near future as the Joint Assessment of Employment Priorities in Turkey (expected to be signed by the end of 2006), prepared in accordance with the provision of the partnership accession with the EU, recognizes the low participation rate of women and commits the government to take action to increase it.
A related concern that does not get spelled out as much in the policy documents has to do with the observed diversity among working women. In this paper, we demonstrated this diversity by way of examining various indicators by employment status. We showed that not all employment categories are open to women, especially to those with little education. We also demonstrated that women’s earnings show variations within and across these employment categories and draw attention to the especially disadvantaged status of those women who occupy the lower ranks of their respective distributions. Policy initiatives geared toward increasing women’s labor market participation need to carefully consider the form of employment they want to promote and the consequences of such a policy choice. These consequences have to do with, among other things, individual and household well-being - as measured by women’s earnings and their contribution to household income which we have shown to be sizeable -, though the magnitude changes with employment status.
Although the impact of female earnings on household income inequality is found to be ambiguous in the sense that the two methods employed yielded conflicting results, both methods clearly showed an equalizing effect in the bottom quintile. Hence, helping women in lower income ranks attain a higher status in the labor market is likely to improve the income distribution and diminish the gender earnings gap. As discussed in the text, women with low earnings typically suffer from a number of handicaps, low levels of educational attainment being one of these. Another important handicap is the high demand from the household on women’s time stemming from a large number of dependents, and the social norms that make the needs of these dependents the sole responsibility of women. Neither of these obstacles can be easily eliminated. However, creating an enabling environment for women by way of facilities and services that can decrease women’s work burden at home, increasing their access to financial and human capital, as well as establishing women’s networks that can offer guidance and counseling, can help attract more women to the labor market and enable their fuller participation in it.
As stated in the literature on female labor supply, an equally strong link as the one between education and labor force participation is observed between education and fertility. In this respect, promoting women’s education emerges as an important long-term policy objective. The recent emphasis placed on girl’s education will in no doubt bear fruit in the years to come. However, more needs to be done to change the perceptions of women about themselves and of the society as to what women can and cannot do. The finding that there are so few employer women and that none of the highly educated employers are in manufacturing (in a country where manufacturing industry contributes significantly to the GDP) is very illuminating and goes to indicate that there are limits to what even the most educated women can achieve in the workplace.

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Figure 1: Empirical CDF’s of male and female annual earnings



Table 1: Distribution of men and women into various work categories in urban areas

	Female share (%)	Male		Female		Total
		No. employed (‘000)	Column share (%)	No. employed (‘000)	Column share (%)	No. employed (‘000)
Regular wage earner	20.66	5,842	64.99	1,521	65.02	7,363
Casual wage earner	34.30	730	8.12	381	16.28	1,110
Employer	3.31	810	9.01	28	1.18	837
Self-employed	10.49	1,297	14.43	152	6.50	1,449
Unpaid family worker	45.36	311	3.46	258	11.02	569
Total	100	8,988	100	2,340	100	11,328