Intergenerational Mobility in Spain: 2005-2019

Third Prize in the "Nada es Gratis" - NeG Competition for the Dissemination of Master's Theses in Economics

Cite: Muñoz-Terroba, L. (2023) Movilidad intergeneracional a partir de un indicador multidimensional de bienestar socioeconómico de los padres: 2005-2019, WEIPO-01, Universidad de Alcalá

Over the past two decades, developed economies have exhibited a persistent rise in income and wealth inequality, as documented in the World Inequality Report (2022). This trend has generated considerable concern regarding its implications for equality of opportunity, motivating substantial academic inquiry into the intergenerational transmission of socioeconomic advantages. Seminal contributions to this literature are Becker and Tomes (1985), Roemer (1993), Chetty et al. (2014), and Corak (2016).

Intergenerational mobility indicates the extent to which economic outcomes are decoupled from parental socioeconomic status. High levels of mobility imply that individuals' economic prospects are less constrained by their familial background, indicative of greater equality of opportunity. Conversely, low mobility signals persistent structural barriers that sustain inequality across generations. To assess this phenomenon, scholars often employ measures such as the Intergenerational Elasticity (IGE), which quantifies the influence of parental income on children’s income, and the Intergenerational Rank Association (IRA) or Rank-Rank Slope (RRS), which evaluates correlations in socioeconomic rank between generations. Unlike IGE, IRA provides a robust assessment of relative mobility by mitigating the effects of distributional changes in income over time.

We study the relationship between parental socioeconomic conditions and the economic outcomes of their children in Spain between 2005 and 2019, comparing with  Italy, Poland, and the Netherlands using the information of the Intergenerational Transmission of Poverty modules from the European Union Statistics on Income and Living Conditions (EU-SILC) survey. We adopt a multidimensional framework to approximate parental socioeconomic status, extending beyond traditional income measures to incorporate dimensions such as parental education and occupational status, enabling a more comprehensive analysis when direct income data for parents is unavailable.

To approximate parental socioeconomic status, we use a Principal Component Analysis (PCA)-based index, constructed from three key variables: the household’s financial conditions during the respondent’s adolescence, the educational attainment of parents, and their primary occupation. This methodology adopts a household dominance approach, choosing the highest educational or occupational attainment between both parents. Our index is then normalized and standardized to facilitate cross-country comparisons, ensuring a consistent scale between 0 and 1 to represent relative socioeconomic positioning. Our research focuses on relative mobility, examining the likelihood of transitioning from the lowest to the highest income quintiles across generations. High relative mobility reflects the significant potential for individuals born into economically disadvantaged households to achieve higher economic status than their parents. In contrast, low mobility points to the persistence of socioeconomic well-being between parents and children.

This study highlights the methodological importance of a multidimensional approach to socioeconomic status, particularly in contexts where income alone may not capture the full extent of familial advantage or disadvantage. Building on the work of Avram and Cantó (2017), this framework integrates indicators of education, occupation, and financial conditions to identify parental socioeconomic origin. Such an approach is particularly beneficial in cross-country analyses, where differing social and economic structures need flexible but comparable indicators of socioeconomic status. In adopting this multidimensional perspective, the study contributes to a deeper understanding of how socioeconomic background shapes adult economic outcomes. By leveraging comprehensive data and robust methodologies, the research offers critical insights into the dynamics of intergenerational mobility, providing a foundation for policymakers to develop strategies aimed at enhancing equality of opportunity and mitigating the persistence of inequality across generations.

Figure 1 depicts a detailed distribution of the multidimensional socioeconomic index segmented into quartiles, distinguishing between data collected in 2005, 2011, and 2019. The analysis of quartile distributions reveals significant patterns concerning family socioeconomic status. Over the years studied and across the countries analyzed (Spain, Italy, Poland, and the Netherlands), the index shows a general upward trend, indicating a decline in the proportion of individuals in the lowest quartile, partially attributable to improvements in educational attainment. However, notable cross-country differences emerge. While Spain, Italy, and Poland exhibit similar distributional patterns, the Netherlands stands out with a significantly higher concentration of individuals in the fourth quartile and a markedly lower proportion in the first quartile. This disparity highlights the relatively higher socioeconomic status of parents in the Netherlands compared to those in the other countries analyzed, reflecting variations in family socioeconomic structures across nations.

The multidimensional index of parental socioeconomic status was further divided into 100 percentiles, enabling a detailed comparison of the socioeconomic position distribution across countries. The equivalent disposable income of the household was employed to approximate the economic standing of the offspring. This metric, which adjusts total income for transfers, taxes, and household size, provides a more equitable measure of individual economic well-being by accounting for available resources on a per-member basis. Given the inherent asymmetry in income distributions—frequently characterized by right-skewed long tails due to a small number of individuals with exceptionally high incomes—a logarithmic transformation was applied to the equivalent disposable income variable. This transformation mitigates skewness, enhances data distribution, and facilitates interpretation and comparison.

Intergenerational mobility was analyzed through two primary approaches. The first involved estimating intergenerational elasticity (IGE), which captures the extent to which parental socioeconomic status influences offspring income. The second employed the intergenerational rank association (IRA), also referred to as the Rank-Rank Slope estimator (RRS). Unlike IGE, the IRA method evaluates the relationship between relative socioeconomic positions independently of changes in the marginal income distributions of parents and offspring. Since IGE is sensitive to the standard deviations of the marginal distributions, its values can vary over time across countries. To address this, the IRA estimation was utilized, derived from the slope of the regression linking the offspring's income percentile to the parent's socioeconomic percentile. This methodology, widely adopted in the literature (e.g., Chetty et al., 2014; Leites et al., 2022), relies on percentiles rather than absolute income values. Consequently, it enables a more nuanced assessment of the disparities in socioeconomic potential between the least and most advantaged families.

The adoption of percentiles in IRA offers several methodological advantages. First, it resolves issues arising from zero-income values, facilitating a linear relationship between the variables. Second, it standardizes the distributions of both generations, ensuring uniformity with equivalent standard deviations. By complementing the intergenerational elasticity estimates, this measure provides a more comprehensive view of intergenerational mobility.

The IRA shown in Table 1 confirms its robustness against temporal changes in parental and offspring income distributions. A higher IRA or rank-rank slope value indicates lower relative mobility. On average, in Spain and Poland, a one-percentile increase in parental socioeconomic position correlates with a 0.27-percentile increase in offspring income. In contrast, the Netherlands exhibits a lower correlation, with a one-percentile parental increase corresponding to only a 0.14-percentile rise in offspring income, indicating higher relative mobility in this context.

To visually represent intergenerational mobility, IRA estimates are presented by country and offspring characteristics. These graphical depictions plot each parental socioeconomic percentile (X-axis), ranging from the lowest (0) to the highest (100), against the mean income percentile of their offspring (Y-axis), offering a comparative and graphical perspective on intergenerational mobility dynamics.

Figure 2 presents the results by country, highlighting the significant differences in intergenerational mobility between Poland and the other countries analyzed. In the Netherlands, the trend curve is notably flatter, reflected in a lower IRA or RRS coefficient, indicating a weaker correlation between the economic well-being of parents and their offspring compared to the other countries, which exhibit a more pronounced and similar trend. On the other hand, Figure 3 illustrates the analysis of intergenerational mobility in Spain over the years 2005, 2011, and 2019. The results reveal a negative trend in social mobility for children from lower socioeconomic backgrounds during this period, suggesting a growing persistence of disadvantage among families of less favorable origins.

To better identify cohort effects, the sample was divided by the birth decade of offspring, ranging from the 1940s to the 2000s. The results, presented in Figure 4, suggest a clear decline in intergenerational mobility as the year of birth increases, with a particularly pronounced decrease among individuals born between 1980 and 1990. This reduction in mobility by cohort is most concentrated in the lower tail of the parental socioeconomic percentile distribution, whereas differences across cohorts are much smaller in other parts of the distribution. Notably, this marked disparity between generations becomes particularly evident beginning with those born in the 1980s.

A revealing example of this dynamic is observed among children born in the 1990s. When originating from families in the lowest 20% of the socioeconomic distribution, these individuals largely fail to surpass the 30th percentile of average income. This stark discrepancy is highlighted when comparing current generations to earlier ones. For instance, the cohort born in the 1940s exhibits an intergenerational mobility index of approximately 0.232, roughly half the estimate for the 1990 cohort. It is plausible that income differences experienced by younger individuals during their formative years contribute to these generational discrepancies. One approach to address this issue without altering the methodology—such as by making percentiles relative to the birth decade, as suggested by Chetty et al. (2014)—is to examine whether these differences persist when restricting the sample to individuals aged 25–35 years, enabling comparisons across birth cohorts at a similar life stage. This approach, as illustrated in Figure 5, confirms that intergenerational mobility differences remain persistent among young individuals aged 25–35 at the time of observation. These disparities are especially pronounced when comparing those born in the 1990s with earlier cohorts.

This study has examined intergenerational mobility in Spain within a comparative framework, utilizing data from the EU-SILC survey and focusing on three distinct economic periods. The research aimed to understand how intergenerational opportunities have evolved and differ across countries, employing two straightforward estimators of intergenerational mobility. The first, the Intergenerational Elasticity (IGE), assesses the relationship between the logarithm of a multidimensional measure of parental socioeconomic background—incorporating educational attainment, parental occupation, and household socioeconomic conditions at age 14—and the logarithm of adult offspring income. The second, the Intergenerational Rank Association (IRA) or Rank-Rank Slope (RRS), evaluates the relationship between the ranks of these variables, thereby minimizing the influence of temporal changes in their dispersion.

The selection of these countries provided insight into the critical role of welfare systems, institutional structures, and cultural factors in shaping the intergenerational transmission of opportunities. Mediterranean countries, such as Spain and Italy, exhibit similar patterns, sharing with Poland relatively lower intergenerational mobility compared to the Netherlands. The analysis, spanning a substantial time, highlighted how the Great Recession impacted intergenerational mobility. Observations from the pre-crisis (2005), the crisis (2011), and post-crisis (2019) periods revealed a decline in intergenerational mobility in Spain, Italy, and Poland, signaling the enduring effects of the economic downturn. In contrast, the Netherlands experienced an increase in mobility over the same period.

Furthermore, the findings underscore the role of offspring age in the transmission of parental socioeconomic status. Younger offspring tend to exhibit levels of economic well-being closely aligned with their parents, particularly among those from lower socioeconomic backgrounds. This trend suggests declining mobility in Spain for children from the lower end of the socioeconomic spectrum, posing significant barriers to upward mobility, especially for those born in the 1990s and later. These findings point to persistent structural challenges in ensuring equitable access to opportunities across generations.

References

• Avram, S., and Cantó, O. (2017). Labour Outcomes and Family Background: Evidence from the EEU during the Recession. Equalitas WP nº 41 and ECINEQ WP nº 414.

• Björklund, A., and Jäntti, M. (2007). Intergenerational income mobility and the role of family background. Handbook of Economic Inequality.

• Bowles, S., Gintis, H., and Osborne Groves, M. (2005). Unequal changes: Family Background and Economic Success,. Princeton University Press.

• Chetty, R., Hendren, N., Kline, P., and Saez, E. (2014). Where is the Land of Opportunity? The Geography of Intergenerational Mobility in the United States. Quarterly Journal of Economics, 129 (4), 1553-1623. 

• Corak, M. (2013). Income Inequality, Equality of Opportunity, and Intergenerational Mobility. Journal of Economic Perspectives—Volume 27, Number 3, 79–102.

• Corak, M. (2016). Inequality from Generation to Generation: The United States in Comparison. Institute for the Study of Labor.

• Leites, M., Ramos, X., Rodriguez, C., and Vilá, J. (2022). Intergenerational mobility along the income distribution: estimates using administrative data for a developing country. Instituto de economía, Serie documentos de trabajo.