Occupational Prestige and Gender-Occupational Segregation

Abstract

The purpose of this article is to determine whether there is a relationship between the proportion of women working in an occupation and the prestige assigned to that occupation. Based on a representative sample of Spanish employees from the Spanish Quality of Working Life Survey, pooled-sample data (2007–2010) are used to show that occupations with larger shares of women present lower prestige, controlling for a set of objective individual and work-related variables, and self-assessed indicators of working conditions. However, the results obtained do not support the devaluation theory since an inverted-U relationship between female share and occupational prestige is observed. This conclusion holds even after passing a battery of robustness checks.

Keywords

gender differences gender-occupational segregation occupational prestige Spain

Introduction

The proportion of women in an occupation, industry or firm (i.e. the female share) has been found to be negatively correlated with pay, even after controlling for individual and occupational characteristics, and even when using longitudinal data (England et al., 2007; Levanon et al., 2009; Perales, 2013).¹ Women are largely employed in female-dominated occupations (services associated with nurturing and care), characterised by a high level of part-time work, lower promotion opportunities and lower wages, such that almost one-half of the gender pay gap can be explained by over-representation of women in low-paid jobs (Blau and Kahn, 2017; Shauman, 2006). This supports the view that women’s work is culturally and socially undervalued (i.e. a devaluation theory) (Acker, 1980; England, 1979, 1992; for a survey, see Reskin and Bielby, 2005).

Complementary indicators to earnings may be used to measure social valuation. For instance, occupational prestige, interpreted as the collective subjective consensus concerning occupational status, is an important indicator of the general valuation of occupations (Magnusson, 2009; Wegener, 1992). When considering prestige as a measure of social standing, earlier studies for the US (England, 1979; Sewell et al., 1980; Treiman and Terrell, 1975) found little gender difference in occupational prestige, with these results being disputed by more recent contributions in different countries (Crawley, 2014, in the US; Härkönen et al., 2016, in Sweden and Germany; Magnusson, 2009, in Sweden). It is this latter association that is the main focus here, in order to capture the social value of work, and not simply the individual compensation expressed in earnings. It is contended that the rewards of work are multidimensional, such that the contribution to society from work is more directly captured by an alternative and complementary indicator of social standing, such as occupational prestige.

The aim of this article is to study the association between the female share in an occupation and the prestige accorded to that occupation, using individual data for Spain, a country characterised by relatively little state intervention in the welfare sphere, with a marked gender division of paid and unpaid work, and where social care tends to be privatised within the family. These characteristics may influence the decisions on sharing domestic and family responsibilities within the household, and how to make market and non-market work compatible, thereby affecting occupational attainment. Individual information from the Spanish Quality of Working Life Survey (Encuesta de Calidad de Vida en el Trabajo, ECVT) is matched with an occupational prestige SIOPS-based, Spain-focused scale, PRESCA2 (SIOPS, Standard International Occupation Prestige Scale; Treiman, 1977). As in Magnusson (2009) and Kleinjans et al. (2015), occupational prestige is taken as an indicator of the social valuation of an occupation since individuals, and society as a whole, consider diverse characteristics, in addition to earnings or authority, as desirable in their jobs and occupations.

The preferred specification, and all the robustness checks carried out, leads to the conclusion that there is a relationship between female share in an occupation and the prestige tied to that occupation. Female-dominated occupations are the least socially valued, whereas occupations with the highest prestige are those in which the female percentage is in the range 21–60 per cent, providing no support to the devaluation theory. The results shape the relationship between female share and occupational prestige as an inverted U, with a longer and deeper right-tail. Female-dominated occupations are less socially valued than male-dominated occupations, such that women should progressively abandon low-skilled, low-prestige, female-dominated occupations and enter into integrated occupations in the expectation that women’s work becomes less undervalued, and then differences in prestige between females and males are reduced.

The remainder of the article is organised as follows. The following section reviews the prior research. After that, measures, data sources and the estimation results are presented. A series of additional exercises are then carried out to check the robustness of the results. Finally, concluding remarks close the article.

Prior research

Whereas a decreasing trend in segregation during the second half of the 20th century was observed, it has slowed, or even stalled, in the last two decades (England, 2010). As a consequence, substantial stability in male and female work is still observed, with women continuing to be employed disproportionally in lower-paid occupations (Blau and Kahn, 2017; England et al., 2007; Shauman, 2006). The causes of the existence of occupational segregation and of its persistence over time are varied (Anker, 1998). Essentially, there are three models explaining occupational segregation (i.e. allocation): (i) the human capital theory; (ii) the hypothesis of feminisation of women’s work due to gender roles, stereotypes or identity; and (iii) discrimination. These three models are advocated to argue why feminine occupations pay less (i.e. devaluation) (Levanon et al., 2009; Polavieja, 2008; Shauman, 2006).

According to the human capital theory, women seek jobs that are more suited to their personal characteristics and interests (MacPherson and Hirsch, 1995; Mincer and Polachek, 1974; Polachek, 1981; Polavieja, 2008; Tam, 1997), since they exhibit shorter and more discontinuous working lives and accumulate lower human capital. Several findings highlight the limitations of this view (Lips, 2013). Thus, gender differentials in education, experience and tenure have narrowed, and even reversed, over time (Blau and Kahn, 2017; Goldin, 2006; Perales, 2013). Similarly, whereas certain authors find empirical support to argue that women prefer jobs and occupations that allow them to balance work and family responsibilities (Becker, 1985; Bender et al., 2005; Leuze and Strauß, 2016; Magnusson, 2010; Shauman, 2006), other authors do not (Marini et al., 1996; Stier and Yaish, 2014).

A second set of models explaining occupational segregation is based on the notion that women self-allocate to occupations with which they identify (Akerlof and Kranton, 2000), or that they have internalised as feminine because of socialisation in norms, stereotypes, or gender roles (Eccles, 1994; Goldin, 2006; Lips, 2013; Ochsenfeld, 2014). In this context, gender differences in psychological traits or non-cognitive skills may influence the allocation and valuation of women’s work (Borghans et al., 2008). Men are more competitive, more self-confident, more contentious, have more self-esteem, a more internal locus of control, and put a higher value on money, whereas women are more risk-averse, more conscious, more altruistic, less prone to bargain and prefer occupations that allow for interpersonal interactions. Personal traits then emerge as relevant in the occupational choices of workers (Croson and Gneezy, 2009; Fortin, 2008; Marini et al., 1996). Finally, different kinds of discrimination may explain the concentration of women in lower-paid occupations. Economic discrimination includes prejudice or tastes of employers, co-workers, or customers (Becker, 1985); statistical discrimination (Aigner and Cain, 1977); or crowding (Bergmann, 1974). From a sociological point of view, the prevailing theory is that of devaluation (England, 1992), by which women’s work is less socially esteemed and more poorly remunerated because it is carried out by women.

These models are not exclusive and they co-exist in explaining occupational segregation and the gender wage gap, although the empirical literature has provided non-conclusive results. Whereas some research finds that devaluation theory outperforms other alternatives (England et al., 2007; Levanon et al., 2009; Perales, 2013), other studies go against this view. For Germany, Leuze and Strauß (2016) test the devaluation theory finding some support for the view that women choose occupations that provide better working-time arrangements (for Sweden, see also Magnusson, 2010). Grönlund and Magnusson (2013), with Swedish data, test three alternative theories (devaluation, crowding and human capital) and find no clear evidence in favour of any of the tested theories (see also Magnusson, 2013). The relevance of socialisation in traditional gender roles, stereotypes and identity are progressively gaining acceptance as plausible explanations of gender wage differences across occupations (Fortin, 2008; Kleinjans et al., 2015; Marini et al., 1996; Ochsenfeld, 2014). Whereas men are uncomfortable crossing boundaries to working in female-dominated occupations, women still show adherence to work in occupations associated with traditional roles, since departures from those roles generate individual costs (Crawley, 2014; England, 2010; Rudman and Phelan, 2010).²

Many of the arguments for why men and women are allocated and paid differently are the same arguments for why men and women experience different levels of prestige.³ However, in contrast to the case of earnings, the earlier literature has often found that the female share in an occupation is not significantly correlated with occupational prestige (England, 1979; Fox and Suschnigg, 1989), or only in the most prestigious occupations (Bose and Rossi, 1983). Similarly, Acker (1980), England (1979), Fox and Suschnigg (1989), Sewell et al. (1980) and Treiman and Terrell (1975) found no differences between the average prestige of men’s and women’s occupations, with Canadian and US data.⁴ These results led researchers to the abandonment of occupational prestige as a measure of social standing, in favour of other socio-economic status indicators, such as earnings, education and authority. In recent times, this process has reversed, as reflected in the following studies.

Despite the evidence showing that women earn less in the job market, it is not uncommon for women to declare greater job satisfaction than men (Clark, 1997; Zou, 2015). Zou (2015) argues that women’s greater job satisfaction could be the consequence of a better match between what they want and what their jobs offer (due to different preferences or constrained choices). Similarly, Fortin (2008) argues that women show preference for working in occupations that are deemed useful to society, even if they are paid less. Kleinjans et al. (2015) find that women are concentrated in occupations that provide them with higher social prestige. When focusing only on earnings, researchers overlook the fact that work is multidimensional and offers other kinds of reward, and interest in a particular kind of reward may differ by gender. Marini et al. (1996) show that, in a sample of US high-school seniors, intrinsic (enjoyment of work), altruistic (helping others) and social (working with people) rewards are valued more highly by women. Similarly, Grove et al. (2011) find that, in a US sample of MBAs, women exhibit higher ethical standards and prefer jobs that contribute to society. Fortin (2008) shows that women put greater importance on people and family, with men’s priority being centred on work and money. The upshot of the argument is that occupational choice is not only driven by objective rewards, such as authority or earnings, but that other compensations are also considered by workers, such as the social standing of an occupation. Since occupational prestige is interpreted as the subjective consensus concerning occupational status, it incorporates a broader notion of occupational standing that takes into account the multidimensionality of work, making it worthy of study in understanding social stratification.

Focusing on studies relating the female share and prestige, Magnusson (2009) considers that occupational prestige is an appropriate indicator to test the devaluation theory, while her results do not support this theory for Sweden. Kleinjans et al. (2015) interpret occupational prestige as an amenity and conclude that women allocate to occupations with lower wages but with greater social prestige. These two studies use national prestige scales to determine that the highest occupational prestige is observed in those occupations having at least 20 per cent of both genders (their results are robust against using the alternative Treiman SIOPS scale). Crawley (2014) carries out a lab study to show that, in contrast to the situation of 20 years ago, US college students’ perceptions of occupational status are less overtly influenced by the gender of occupation, and that gender differences in occupational prestige have diminished over time. However, the gendered perception of some aspects of occupational attainment, such as personal interest and education requirements, still exists, largely due to the significant presence of stereotypes. Härkönen et al. (2016) analyse gender inequalities in occupational careers in three birth cohorts, using growth-curve analysis with data from West Germany and Sweden, where occupational prestige is measured with the SIOPS. They observe a closing of the gender gap in prestige over time and over the life cycle for the two countries.

Measures, data and descriptive analysis

Measures of occupational prestige

Occupational status is a generic term covering prestige, socio-economic status and class measures. Among the many indicators used (see Ganzeboom and Treiman, 1996; Warren et al., 1998), the present analysis retains occupational prestige as the most important dimension in social interaction. In the sociology of work and social stratification, occupational prestige has a broader theoretical meaning than other socio-economic indices, since it encompasses many determinants other than earnings and education (Warren et al., 1998). To the extent that an occupation embodies a bundle of job characteristics that are jointly considered by individuals, prestige reflects an occupation’s contribution ‘to society’, and measures its desirability, thereby capturing the social standing given to those holding a specific occupation (Hauser and Warren, 1997; Magnusson, 2009; Powell and Jacobs, 1984). Nevertheless, the degree to which a simple score may capture all the complexity of social valuation is controversial and contested within the sociological literature (Warren et al., 1998).

Whereas prestige scales have been shown to be constant over time and space (Hauser and Warren, 1997; Hout and DiPrete, 2006), and over other characteristics, such as social class, gender and age (Ganzeboom and Treiman, 1996; Treiman, 1977), thus guaranteeing the validity of the same scale in different environments, the use of occupational prestige has been disputed – for two reasons. First, women are disadvantaged in the labour market compared to men, and a valid measure of occupational standing should reflect these gender inequalities in the labour force. As noted in the previous section, earlier studies have not found such gender differences when using prestige as an indicator of social standing. However, in the same section, several arguments have been discussed to contend that work is multidimensional and offers rewards other than earnings, and interest in a particular kind of reward may differ by gender. Taking an indicator complementary to earnings, such as prestige, that incorporates a broader notion of occupational standing, may provide an alternative view of the social valuation of women’s work. A second caveat is that prestige itself may be gender-sensitive (Acker, 1980; Bose and Rossi, 1983; Powell and Jacobs, 1984). Since the occupational prestige scale is based on the ratings of respondents, the scale will embody the prejudices and assumptions of the respondents providing the rating scores. Powell and Jacobs (1984) and Ulfsdotter Eriksson (2013), using two different laboratory experiments with US and Swedish respondents, respectively, conclude that an occupational prestige scale is actually a composite of two scales, such that measuring occupational prestige should be done for men and women separately. Whereas this kind of result is usually found in small experimental designs, or when valuations in gender-stereotyped jobs are confronted (Bose and Rossi, 1983; Fox and Suschnigg, 1989), many ‘macro-sociological’ studies find scale invariants against the gender of respondents (Treiman, 1977; Warren et al., 1998; Wegener, 1992). Furthermore, in a lab-type experiment with university students in the US, Crawley (2014) found no gender differences in the job raters.

Data sources

Occupational prestige is measured by a SIOPS-type prestige scale elaborated specifically for the Spanish case, PRESCA2, by Carabaña and Gómez-Bueno (1996). This is constructed along similar lines to the typical SIOPS scale. Specifically, surveyed individuals are asked to value different occupational categories, taking salesperson as reference with a given value of 100. Each individual is then requested to rate an occupational category according to how he/she believes that occupational category is valued by society. If one thinks that a particular occupation is considered to be twice as prestigious as the salesperson category, one may rate that occupation at 200, or 50 if one believes that society considers that an occupation is only half as prestigious as the reference category. If an occupation is believed by the individual to be socially considered a little better than salesperson one may rate it 105 or 110, or if it is a little worse, 90 or 95 (for more on the PRESCA2 scale, see Carabaña and Gómez-Bueno, 1996). Regarding the possible problem of gender bias in prestige, a subsequent study by one of the authors of the PRESCA2 scale (Gómez-Bueno, 1996) found little or no influence of the gender of the raters.

Individual information comes from the ECVT, which focuses on employment relationships and on the valuation and attitudes of employees towards work. The survey addresses employees older than 16 years as being representative of the total employed population, covers a number of issues relating to working conditions, and allows controlling for a battery of individual and job attributes, including the occupational category. The sample is constructed by pooling the last four consecutive waves, from 2007 to 2010. ECVT and PRESCA2 express occupational categories according to the 1994 Spanish Occupations National Classification (CNO-94), which follows the ISCO-88 (International Standard Classification of Occupations) guidelines. The three-digit classification is the maximum level of disaggregation provided in the ECVT, producing 216 occupations.

Table 1 shows the average values of occupational prestige, considering certain individual and job characteristics. Prestige is greater the higher the educational level, the higher the earnings, and for those working full-time, in the public sector, with a permanent contract, or a supervisory position. Comparing male and female workers, the rough average indicates that there are no differences. Looking at different characteristics, two factors stand out: first, for each educational level, average prestige for women is between three and 12 points below that of men; second, for a given income level (above the minimum interval), average prestige is between seven and 20 points higher among women than among men. These results reveal that, with a similar education, women work in less socially esteemed occupations than do men and that, in order to earn equal pay, women need to work in occupations with higher prestige. The lower part of Table 1 shows that greater social valuation is observed in those occupations where greater parity exists, whereas occupations where the female share is over 80 per cent are the least socially valued, suggesting a kind of inverted-U relationship between female share and prestige.

Table 1.

Average occupational prestige across groups of workers, by gender: 2007–2010.

	Proportion	Overall		Men		Women		Dif.^a
		Mean	SD	Mean	SD	Mean	SD
Overall		108.6	38.0	108.7	39.0	108.4	36.5	0.7
Educational level
Less than primary	3.1	81.7	20.3	83.6	20.1	77.8	20.1	4.2***
Primary	16.6	87.1	21.0	89.6	21.3	82.1	19.5	12.4***
Lower secondary	21.2	89.3	21.4	91.2	22.2	86.2	19.7	6.9***
Short vocational	10.1	103.0	26.1	105.8	29.0	99.3	20.9	7.0***
Long vocational	10.5	108.4	29.5	109.4	32.5	106.7	23.8	2.7***
High secondary	13.3	106.1	30.8	108.1	32.9	103.5	27.9	4.8***
Short bachelor	10.8	132.4	34.4	139.3	40.3	127.3	28.2	10.3***
Long bachelor	14.4	156.1	43.6	160.7	45.8	151.6	40.9	7.1***
Monthly earnings
Up to €1000	30.8	91.6	27.4	92.8	28.5	91.0	26.7	3.1***
€1001–1200	21.9	99.5	28.0	96.2	27.4	105.1	28.0	13.0***
€1201–1600	23.2	109.9	33.1	104.9	32.1	121.0	32.6	20.0***
€1601–2100	13.8	127.3	39.7	120.9	40.8	140.6	33.7	15.9***
€2100+	10.4	150.1	47.5	147.0	49.0	159.3	41.5	6.5***
Sector
Public sector	24.9	121.2	42.8	118.7	47.3	123.3	38.5	4.4***
Private sector	75.1	103.4	34.3	104.5	35.3	101.7	32.6	5.6***
Full/part-time
Full-time	86.8	110.1	38.3	108.9	39.2	112.1	36.8	8.8***
Part-time	13.2	98.7	34.0	105.9	35.9	95.8	32.8	6.7***
Contract
Permanent contract	77.5	110.8	37.5	110.7	38.9	110.8	37.5	0.3
Fixed-term contract	22.5	97.5	35.1	94.7	33.8	100.5	36.2	6.4***
Supervisory
Supervisory position	24.8	125.7	45.1	124.7	46.3	127.9	42.1	2.9***
Non-superv. position	76.2	102.9	33.9	101.9	33.1	104.1	33.7	5.1***
Female share
Women 0–20%	28.6	99.4	32.8	98.7	31.8	107.0	41.9	7.1***
Women 21–40%	13.8	123.8	45.1	123.5	44.5	124.6	46.7	0.8
Women 41–60%	16.6	128.2	44.7	128.0	45.3	128.6	44.0	0.5
Women 61–80%	28.5	111.1	23.4	110.0	23.7	111.6	23.2	3.2***
Women 81–100%	12.4	90.1	29.9	96.7	32.4	89.2	29.4	5.6***

Notes: There are 18,637 (13,538) observations for men (women) representing 58 per cent (42%) of the sample. ^aDif. is the t-statistic for equality of means by gender. ***p<0.01.

Descriptive analysis

Between 1986 and 2007, almost nine million jobs were created in Spain, of which 5.5 million were for women, increasing female participation and employment rates by around 20 percentage points. More than 80 per cent of the increase in female employment was in the services sector, characterised by high flexibility in the working day, allowing for greater compatibility of family responsibilities with paid work, more interpersonal relationships, less physical effort, and directly related to the development of ICT (Dueñas et al., 2014; García-Mainar et al., 2015).

The 15 most male- and female-dominated occupations, among the 66 corresponding to the two-digit CNO-94 classification, are chosen to illustrate the relationship between occupational gender distribution and occupational prestige. Table A1 in the Online Appendix reports, for the last year of the sample, 2010, and for each selected occupation, the female (male) share, the average prestige and the percentage of women (men) out of the total women (men) employed, respectively. The 15 most female-dominated occupations (in all of them the female share is over 55%) represent 70 per cent of total working Spanish women, indicating that a large part of female employment is allocated to a few occupations, in which women are over-represented. The 15 most male-dominated occupations, in which the female share is less than 12 per cent, represents only 34 per cent of the total employed men. There does not appear to be a clear relationship between the social prestige of an occupation and the female share in that occupation. Among the most female-dominated occupations, some surpass 140 points (teachers and nurses), while others are below 100 (clerical work and cashiers) and even 65 (cleaners). Heterogeneity across the most male-dominated occupations is much lower, with almost all of them ranking between 65 and 110 points.

A graphical approximation allows consideration of the whole set of 216 three-digit occupations. Figure 1 represents the average female share of occupations, arranged according to occupational prestige (in deciles). Occupations in the upper tail of the distribution (the most socially recognised) display higher average female shares than those in the first seven deciles, indicating that occupations with greater occupational prestige are those where the shares of women and men are more similar.

Figure 1.

Average female share by decile of prestige (216 occupations three-digit CNO-94).

Model estimation results

For a more robust assessment of the relationship between occupational prestige and the female share, and provided that the PRESCA2 scale is cardinal, ordinary least squares (OLS) regression analysis is used. Occupational prestige rates are expressed in logs since the distribution of the PRESCA scale is clearly right-skewed. They are regressed on individual variables and on the female share; first, as the proportion of women (ranging from 0 to 1) in a particular occupation, and second, in dummy variables to capture the possibility of non-linearity in the relationship (five dummies ranging from 0 to 20% up to 81 to 100%). The initial specification includes as additional regressors education and earnings variables only, expressed in dummies, as provided in the survey, with estimated coefficients being reported in the first two columns of Table 2. As expected, prestige increases with education and earnings. More importantly, the estimated coefficient for the female share is negative and statistically significant, reflecting the fact that, controlling for education and earnings, the greater the proportion of women in an occupation, the lower the prestige tied to that occupation. When expressed in dummies, high prestige is observed in occupations where the female share is between 41 and 60 per cent, with the range 21 to 40 per cent following closely, whereas occupations above 80 per cent female carry the least prestige.

Table 2.

Ordinary least squares (OLS) estimates on the relationship between the log of occupational prestige and female share.

	Linear short	Dummies short	Linear extended	Dummies extended
	Coef. (SE)	Coef. (SE)	Coef. (SE)	Coef. (SE)
Female share (in percentage)	−0.001***(0.000)		−0.002***(0.000)
Female share (in dummies)
Women 0–20%		−0.111***(0.005)		−0.056***(0.005)
Women 21–40%		−0.022***(0.005)		−0.005(0.005)
Women 41–60%
Women 61–80%		−0.060***(0.004)		−0.079***(0.004)
Women 81–100%		−0.234***(0.005)		−0.234***(0.005)
Education
Less than primary
Primary	0.053***(0.008)	0.049***(0.008)	0.034***(0.008)	0.034***(0.007)
Lower secondary	0.081***(0.008)	0.072***(0.008)	0.056***(0.008)	0.054***(0.007)
Short vocational	0.210***(0.008)	0.187***(0.008)	0.159***(0.008)	0.149***(0.008)
Long vocational	0.246***(0.008)	0.218***(0.008)	0.187***(0.008)	0.173***(0.008)
High secondary	0.231***(0.008)	0.195***(0.008)	0.164***(0.008)	0.146***(0.008)
Short bachelor	0.419***(0.009)	0.407***(0.008)	0.335***(0.008)	0.339***(0.008)
Long bachelor & above	0.544***(0.008)	0.485***(0.008)	0.437***(0.008)	0.405***(0.008)
Monthly earnings
up to €1000
€1001–1200	0.051***(0.004)	0.047***(0.004)	0.036***(0.004)	0.035***(0.004)
€1201–1600	0.097***(0.004)	0.098***(0.004)	0.060***(0.004)	0.066***(0.004)
€1601–2100	0.164***(0.005)	0.171***(0.004)	0.109***(0.005)	0.122***(0.005)
€2100	0.245***(0.005)	0.235***(0.005)	0.164***(0.006)	0.165***(0.005)
Gender (1=male)			−0.020***(0.003)	−0.016***(0.003)
Age			0.001(0.001)	0.001(0.001)
Married			0.007**(0.003)	0.007**(0.003)
Children 0–2 (dummy)			−0.001(0.004)	−0.001(0.004)
Children 3–5 (dummy)			−0.014***(0.004)	−0.013***(0.004)
Children 6–14 (dummy)			−0.016***(0.003)	−0.015***(0.003)
Father’s prestige			0.001***(0.000)	0.001***(0.000)
Seniority			0.002***(0.000)	0.001***(0.000)
Public sector			0.024***(0.004)	0.039***(0.004)
Workday			0.011***(0.004)	0.003***(0.004)
Job training			0.034***(0.003)	0.036***(0.003)
First job			0.008***(0.003)	0.011***(0.003)
Supervisory position			0.045***(0.003)	0.038***(0.003)
Teamwork			0.025***(0.003)	0.019***(0.003)
Agreement			−0.021***(0.004)	−0.013***(0.003)
Time flexibility			0.002***(0.000)	0.002***(0.000)
Stress			0.010***(0.000)	0.009***(0.000)
Monotony			−0.003***(0.000)	−0.004***(0.000)
Physical effort			−0.015***(0.000)	−0.011***(0.000)
Firm size			Yes	Yes
Sector			Yes	Yes
Region			Yes	Yes
Year 2008			0.007*(0.004)	0.005(0.004)
Year 2009			0.011***(0.004)	0.010***(0.004)
Year 2010			−0.001(0.004)	−0.003(0.004)
Constant	4.367***(0.008)	4.443***(0.008)	4.317***(0.014)	4.311***(0.014)
Observations	32,067
Adjusted R²	0.464	0.505	0.527	0.551

Notes: Female share is expressed as a proportion in linear models and five group dummies in dummy models, with the share 41–60 per cent being the reference category. There are three dummy variables for ‘Firm size’, four in ‘Sector’ and 17 corresponding to NUTS2 in ‘Region’. *p<0.1; **p<0.5; ***p<0.01.

The richness of the ECVT allows more variables to be included, thereby reducing the omitted variable bias: (i) personal and family variables, such as gender, age, marital status, dummies for children (by age group) and father’s occupational prestige; (ii) job-related variables, such as seniority and a series of dummies for public/private sector, workday, job training, working in first job, being a supervisor, working in teams and being covered by a collective agreement; (iii) indicators of individual assessment of workplace characteristics (time flexibility, stress, monotony and physical effort required); and (iv) dummies for firm size, sector, region and year. Estimated results are reported in the last two columns of Table 2. The variance explained rises to 55 per cent when the extended model with the dummy specification is used, confirming the preference for the non-linear specification. This value is in line with similar studies for other countries (Bose and Rossi, 1983; Magnusson, 2009; Sewell et al., 1980).

The male coefficient is negative, implying that, other things being equal, men receive less prestige than women. (This may be rationalised when expressed in terms of earnings, for example, as men do not need to work in an occupation with the same level of prestige as women in order to obtain higher wages.) Being married is associated with greater prestige, whereas having children is associated with lower prestige. Father’s occupational prestige, used as a proxy for the general social and financial status of the family of origin (Härkönen et al., 2016; Kleinjans et al., 2015; Treiman and Terrell, 1975), reflects the fact that original social class is directly linked to current prestige. Seniority, working in the public sector, having an uninterrupted workday, having received some training, being in the first job, a supervisor, working in teams, enjoying some flex-time and suffering stress on the job, all increase prestige, whereas being covered, feeling that work is monotonous or requiring certain physical effort reduce prestige. Finally, average prestige was higher in 2009.

The addition of new controls does not change the qualitative results. Point-estimate of the female share coefficient in the richer specifications is double (in absolute value) that in the more parsimonious specifications. That is, controlling for an ample set of personal, family and job-related variables, higher female share in an occupation is more negatively associated with occupational prestige than in the baseline specification. This makes clear that gender differences in occupational prestige exist. Looking at the estimation in dummies, the highest occupational prestige is observed when the female share is between 21 per cent and 60 per cent (differences between 21 per cent and 40 per cent, and 41 per cent and 60 per cent are not statistically significant). Again, the lowest prestige is attained when female share surpasses 80 per cent. These results resemble those of Magnusson (2009) for Sweden, in that more balanced occupations receive more prestige, and occupations with 81–100 per cent women are the least socially valued. However, one difference is that, in the case of Magnusson (2009), prestige and female share follow an inverted-U relationship, with the highest prestige in the 41–60 per cent range, decreasing, more or less symmetrically, as it moves towards the gender-dominated occupations. In this article, the inverted-U relationship is clearly right-skewed, with occupations in which the presence of women is less than 20 per cent being less valued than those in the medium-range, but more than in those occupations with an above 60 per cent participation of women.

Discussion

Results for the family variables may depend on gender. To control for this, interactions between age, marital status, children variables and gender are added in the richer specification, with estimated coefficients of the variables of interest being shown in Table 3. The estimates for the rest of the controls are much like those in Table 2 and are omitted to save space. The main results are as follows. First, the estimates of female share are robust to the specification used. Again, the prestige-female relationship is, except for the 0–20 per cent group, monotonically decreasing, with occupations above 80 per cent female carrying the least prestige. Second, age is differentially associated with prestige for men and women. Women receive the same or less prestige as they age, while men receive more prestige. This result does not change when including the variables of children by gender. Having children older than two years old increases men’s prestige and decreases women’s prestige. This may be due to the interrupted career of women, which prevents them from entering more socially valued occupations. However, if the children are younger than two years, the opposite is observed. This could result from selection, by which women in more-valued occupations are more likely, relative to those in less-valued occupations, to remain employed until their children reach school age (three years). Marriage increases prestige for both men and women. Taking these two variables together, marriage and fatherhood makes it easier for men to attain occupations with high prestige, whereas, in the case of women, marriage and motherhood go in opposite directions, with the negative effect of motherhood dominating that of marriage (a similar result is found for German and Swedish women in Härkönen et al., 2016).

Table 3.

Ordinary least squares (OLS) estimates on the relationship between the log of occupational prestige and female share, with other controls for gender.

	Coef.(SE)	Coef.(SE)	Coef.(SE)	Coef.(SE)	Coef.(SE)	Coef.(SE)
Female share(in percentage)	−0.002***(0.000)		−0.002***(0.000)		−0.002***(0.000)
Female share(in dummies)
Women 0–20%		−0.064***(0.005)		−0.058***(0.005)		−0.058***(0.005)
Women 21–40%		−0.004(0.005)		−0.007(0.005)		−0.007(0.005)
Women 41–60%
Women 61–80%		−0.076***(0.004)		−0.082***(0.004)		−0.082***(0.004)
Women 81–100%		−0.259***(0.005)		−0.241***(0.005)		−0.241***(0.005)
Variables with interactions by gender
Gender (1=male)	−0.088***(0.010)	−0.053***(0.010)	−0.565***(0.011)	−0.031***(0.011)	−0.057***(0.011)	−0.032***(0.011)
Age	−0.001***(0.000)	−0.000(0.000)	−0.001***(0.000)	−0.000(0.000)	−0.001***(0.000)	−0.000(0.000)
Age*gender	0.002***(0.000)	0.001***(0.000)	0.002***(0.000)	0.001*(0.000)	0.002***(0.000)	0.001*(0.000)
Children 0–2 (dummy)	−0.001(0.004)	−0.001(0.004)	0.017***(0.007)	0.016***(0.007)	0.015***(0.007)	0.015***(0.007)
Children 0–2*gender			−0.029***(0.007)	−0.027***(0.008)	−0.027***(0.008)	−0.029***(0.007)
Children 3–5	−0.011***(0.004)	−0.011***(0.004)	−0.013**(0.006)	−0.015**(0.007)	−0.014**(0.007)	−0.015**(0.007)
Children 3–5*gender			0.036**(0.018)	0.037**(0.018)	0.035**(0.018)	0.038**(0.018)
Children 6–14	−0.016***(0.003)	−0.015***(0.003)	−0.012***(0.005)	−0.011***(0.004)	−0.013***(0.005)	−0.012***(0.005)
Children 6–14*gender			0.046***(0.006)	0.047***(0.006)	0.045***(0.006)	0.046***(0.006)
Married			0.006*(0.003)	0.007**(0.003)	0.008**(0.004)	0.007*(0.004)
Married*gender					−0.008(0.006)	−0.004(0.006)
Observations	32,067
Adjusted R²	0.502	0.534	0.527	0.550	0.527	0.550

Notes: All other controls as in extended models of Table 2 are included but not presented. *p<0.1; **p<0.5; ***p<0.01.

Between 2007 and 2010, unemployment rates rose from less than 8 per cent (the lowest level in decades) to more than 20 per cent, with male unemployment equalling that of women, which was 5 percentage points above only five years before. To investigate the possible influence of this on the relationship between female share and prestige, the same specifications as in Table 2 are estimated separately for 2007 and 2010, with coefficients of the main variables being reported in Table A2 in the Online Appendix. Basic results remain unchanged, save for the fact that the differences in the estimated coefficients with respect to the reference category are much more marked in 2010, reflecting greater differences in prestige among the different groups of female share. Therefore, the influence of the Great Recession on the prestige–female-share relationship is limited, suggesting that this relationship has a strong structural component.

Before presenting the main conclusions of our study, note that various biases may arise in the estimation of the relationship between female percentage and occupational prestige. The cross-sectional approach prevents an analysis of causality (no other dataset in Spain in panel data form would allow it), such that whether feminised occupations are valued less because they are populated by women (as the devaluation theory suggests), or, by contrast, whether women tend to be in occupations where prestige is lower, since they are discriminated against, and they either prefer them, or are gender-socialised into them, or entry is easier, cannot properly be tested. However, other possible sources of bias due to measurement errors can be addressed. Thus, qualitative results remain unchanged when using different definitions of education and earnings; when prestige is introduced in levels; or when the reference category for the female share is not 41–60 per cent. The use of other prestige scales (Treiman, 1977; Wegener, 1992) produces very similar results (correlations between those scales and PRESCA2 are at 87% and 86%, respectively). In order to capture non-linearity in the relationship from another point of view, a three-order polynomial of the female share variable is estimated, finding that maximum occupational prestige is attained around the 30 per cent level of female participation.⁵

Finally, a cautionary note: participation rates of women in Spain are clearly lower than those of men. In order to alleviate selection bias, Table A3 in the Online Appendix presents estimated coefficients when selecting only those individuals who hold post-compulsory educational attainment since, in this group, differences in participation rates between genders are much smaller. Qualitative results remain unchanged, but it is worth noting that negative coefficients associated with female-dominated occupations are lower (in absolute value) with respect to the reference category. Thus, prestige is somewhat more homogenously distributed across occupations among the most educated, and the inverted-U relationship is less asymmetric.

Conclusions

The purpose of this article is to analyse the relationship between the percentage of women in an occupation and the prestige attached to that occupation, using Spanish data. Whereas empirical evidence across countries has consistently shown a gender wage gap, gender differences in prestige are contained. Many authors (Acker, 1980; England, 1979; Fox and Suschnigg, 1989) argued that prestige was not an appropriate index of social stratification because it failed to show that women were worse off than men. They proposed the use of such indicators as earnings, showing that occupations with higher proportions of women pay less and concluding that women’s work is undervalued.

However, because the rewards from work are multidimensional, and women do not usually report being less satisfied at work than men, altogether this leads to considering that women’s occupational choices may be driven by other work compensations, in addition to earnings. This study is based on the notion that social standing derived from work in a particular occupation is captured by occupational prestige, which provides a view of social valuation that is complementary to the much extended, one-dimensional measure of earnings.

This article is centred on Spain, a country characterised by a marked division of paid and unpaid work, in which family responsibilities are inadequately covered by the state, but basically a burden on women. The regression analysis indicates that whereas results coming from a linear specification of the female share appear to fit the devaluation view, the better adjustment provided by the non-linear specification suggests a kind of inverted-U relationship. While this is at odds with devaluation theory, since male-dominated occupations are less socially esteemed than integrated occupations, female-dominated occupations are the least socially valued, showing a certain devaluation of women’s work. The cross-sectional nature of the database and the type of information available prevents any causal analysis, such that the reasons why individuals are allocated into a particular occupation cannot be ascertained. In consequence, drawing clear-cut conclusions about whether an individual prefers a given occupation, whether he/she has been gender-socialised into it, or simply discriminated against, is not possible.

A series of robustness checks has been carried out validating the initial conclusions. Family variables affect men and women differentially, such that motherhood is penalised and fatherhood rewarded, but basic results on the prestige–female-share relationship do not change. Controlling for a different behaviour, depending on the moment of the cycle, the definition of the variables of interest, or the lower participation of women in the labour market, barely alter results.

To conclude, it is found, first, that a thorough assessment of the work-based position of women in the social hierarchy should consider as many dimensions of work as possible, and not be exclusively focused on earnings. Second, the results obtained, although in line with those found in other countries, are somewhat more unequal, suggesting some degree of devaluation of women’s work. Low-skilled women mostly populate low-prestige, traditionally female-dominated occupations, while they have avoided low-skilled, low-prestige, male-dominated occupations. High-skilled women initially entered, much later than in other developed countries, high-prestige occupations traditionally associated with female roles, such as teachers and nurses, and, only more recently, have also joined high-skilled, high-prestige, integrated occupations. As diagnosed by England (2010), the social stigma for women willing to work in occupations more typically associated with men is progressively being surmounted.

Therefore, it seems necessary to encourage and promote the participation of women in all kinds of occupations and the abandonment of the massive allocation in those feminine, low-skilled, low-prestige occupations, such as cleaners, helpers and personal services. This is not an easy task, since, first, immigrant female workers have been largely allocated into these occupations in recent years and, second, there still is more social stigma for men being interested in feminine occupations than for women being willing to work in masculine occupations (Crawley, 2014; England, 2010; Rudman and Phelan, 2010).

Footnotes

Acknowledgements

The authors would like to thank the editor and the three anonymous reviewers for their helpful comments, which greatly improved this work. In addition, we would like to thank participants at the II International Conference on Sociology of Public and Social Policies, and the XL International Conference in Regional Studies for helpful comments on earlier versions of this article.

Funding

The authors acknowledge the financial aid provided by the Spanish Women’s Institute (code 261168-190) and the Autonomous Government of Aragón (Consolidated Research Group S13).

Notes

Inmaculada García-Mainar earned her PhD at the University of Zaragoza, Spain, where she is currently working as Associate Professor in Economics. She has been interested in different topics of Labour Economics, particularly those related to Economics of the Family. Her current research focuses on two topics: differences observed between men and women in the labour market, and the relationship between personal job characteristics, job satisfaction and well-being.

Víctor M Montuenga is Associate Professor of Economics at the University of Zaragoza, Spain. He earned his PhD at the Autonomous University of Barcelona within the ENTER (European Network Training in Economic Research) programme. His main field of interest is Labour Economics, with a special focus on the relationships between human capital, productivity, wages and unemployment. Recently, he has focused on the study of gender differences in the labour market.

Guillermo García-Martín is graduated from the IE Business School and the Universidad Complutense of Madrid. He teaches at ESIC Business & Marketing School and is a PhD student in the Department of Economics at the University of Zaragoza. His PhD dissertation is devoted to the analysis of gender differences in the labour market and the role played by gender occupational segregation. He is Business Research and Knowledge Manager at Ibercaja Bank.

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