Abstract
This article aims to provide insights into the intergenerational social mobility of Spanish workers, comparing the occupational prestige of sons and daughters to that of their fathers when the offspring were aged sixteen. We used a pooled-sample for the years 2007–2010, from a nationally representative data base, the Spanish Quality of Working Life Survey, to compute transition matrices, and to estimate the intergenerational elasticity of occupational prestige, considering differences by gender and age group. Our results confirmed that mobility in Spain is in the medium range, from an international perspective, and is slightly higher for daughters than for sons. By age, the younger generation presents an upward jump in prestige with respect to the older generation, along with lower values of intergenerational elasticity. This suggests that the father’s effect may be weakening across generations. It is notable that our conclusions held after passing a series of robustness checks.
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Notes
SIOPS: The Standard International Occupation Prestige Scale (Treiman 1977). The main advantage of PRESCA2 over SIOPS is that the former provides a cardinal measure of occupational prestige, whereas the latter is merely ordinal. See “Data sources” section, for more details.
In Nordic countries and, to a lesser extent, in certain Continental countries, a re-emergence of mobility based on meritocracy seems to be observed (Esping-Andersen and Wagner 2012).
Although female participation has markedly increased during recent decades, notable differences still exist between men and women in participation: interruptions due to maternity and child rearing are almost exclusively borne by mothers, hence likely influencing participation and future prospects in career achievement.
Temporary, part-time, and unemployment rates are, respectively, 26.0%, 9.5% and 12.5%, for men and 27.7%, 27.6% and 15.8% for women (Labour Force Survey, 2019: II quarter). According to the 2014 wave of the Wage Structural Survey, average hourly wages were €16.68 and €13.12 for men and women, respectively. As for 2017, the Gini index for income inequality was 0.35 (0.31 for the Eurozone, World Bank), whereas the Duncan index for occupational segregation was 0.50, and over-education was above 25% (Garcia-Mainar et al. 2015).
Information for parents’ occupation was not present in previous waves.
In the section devoted to discussion, occupational prestige of mothers was also included in estimations as an additional sensitivity analysis.
The reasons for the absence of father’s occupation were unknown. It could be due to non-working fathers (unemployed, non-active, retired); non-response; or non-existence (absent, dead, etc.…). It supposed missing less than 10% of the initial sample.
The Appendix presents a comparison with data drawn from the Labour Force Survey for the same time period. The sample proportion of 41% women resembles the population percentage of working women.
Sample descriptive statistics for the whole set of variables used in the analysis are reported in the Appendix.
This is the standard approach to compute intergenerational elasticity. Studies attempting to investigate the mechanism through which parental background is reproduced in children’s outcomes add mediators to this simple specification. The most clear example is education (see, for instance, Raitano and Vona 2015a, b; or Palomino et al. 2019).
The ranking indices were (1) a simple summation of the elements of the leading diagonal; (2) the summation of the elements below the leading diagonal; (3) the summation of the elements above the leading diagonal; (4) the summation of the elements above and below the leading diagonal; (5) the Shorrocks index, computed, for a given (square) matrix A of dimension n, as (n − traceA)/(n − 1); (6) a weighted mobility index due to Bartholomew that, if aij is the proportion of daughters or sons in quantile j whose parents were in quantile i, is defined by (1/n)ΣiΣjaij |i − j| and (7) an adjusted version computed by (1/n)ΣiΣjaij (i − j)2. In all cases, except (1), the larger the index size, the higher the mobility. See Dearden et al. (1997), Hirvonen (2008) and De Pablos and Gil (2016) for description and discussion of the mobility indices.
An initial exercise was to estimate a pooled sample with a dummy for gender (1 = son, 0 = daughter), included on its own, and interacted with all the other regressors, to test whether differences by gender were statistically significant (this has been done in this and in all subsequent specifications). In nearly all cases, the hypothesis of gender equality in coefficients was rejected. In particular, the gender dummy was positive and statistically significant, which reveals a distinct intergenerational association across genders (estimated coefficient for model I was 0.028 and standard deviation 0.012). Results not shown but available upon request.
In contrast, if individuals who remained in the sample had parents with higher occupational prestige than those individuals who dropped out of the sample because of the persistence being studied, then the estimated elasticity may not be so overestimated.
As in the case of children, occupational prestige may vary during the life-cycle of parents. Ideally, adding a polynomial of father’s age would help to control for this. However, there was no information in the survey on father’s age. Notwithstanding that, although the life-cycle bias for fathers may appear, it is expected to be smaller in our study than in the general case. Since fathers’ reported occupational prestige corresponded to that when the respondent was sixteen, variation in fathers’ age is not expected to be as large as it would be if individuals reported the occupational prestige of their fathers at the moment of the survey.
The age that maximizes prestige is attained from the expression α2 + 2α 3(Agei/100) = 0.
Although some more recent scales have been proposed, none is as disaggregated by occupations as PRESCA2. Carabaña and Gomez-Bueno (1996) show little or no influence of the gender of the raters, so that gender bias in prestige is at a minimum.
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Acknowledgements
We thank Bryan Brooks for providing language help and proof reading the article. The authors would like to thank participants at the Journal of Youth Studies Conference in Copenhagen, 2015; and II International Conference of Sociology of Public and Social Policies in Zaragoza, 2015.
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This work was supported by the Autonomous Government of Aragon (Research Group S32-17R), co-financed by ERDF 2014–2020, and University of Zaragoza (Grant UZ2018-SOC-01).
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Appendix
Table 9 compares sample data with those of the Spanish Labor Force Survey averaged for the same period as in our analysis. Since ECVT is a sample of workers only, employment rates could not be computed. The first columns of Table 9 show that the female employment rate was near 55%, 15 percentage points below that of males. The proportion of male/female in the sample resembled that of the active population, even though the age distribution differed to a certain extent between both samples (the younger were somewhat under-represented and the older over-represented).
Descriptive statistics in Table 10 show that sons’ average prestige was essentially the same as for daughters, both being higher than fathers’ average prestige and much higher than mothers’ average prestige. Average differences between son-father were larger than between daughter–father. A working mother was more frequently observed in the case of daughters than in the sons. Daughters were, on average, a bit younger and, clearly, better educated.
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García-Mainar, I., Montuenga, V.M. Occupational Prestige and Fathers’ Influence on Sons and Daughters. J Fam Econ Iss 41, 706–728 (2020). https://doi.org/10.1007/s10834-020-09677-w
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DOI: https://doi.org/10.1007/s10834-020-09677-w