Knowledge of Catalan, Public/Private Sector Choice and Earnings: Evidence from a Double Sample Selection Model

Abstract

This paper explores the earnings return to Catalan knowledge for public and private workers in Cat alonia. In doing so, we allow for a double simultaneous selection process. We consider, on the one hand, the nonrandom allocation of workers into one sector or another, and on the other, the potential selfselection into Catalan proficiency. In addition, when correcting the earnings equations, we control for the correlation between the two selectivity rules. Our findings suggest that the apparent higher lan guage return for public sector workers is entirely accounted for by selection effects, whereas knowl edge of Catalan has a significant positive return in the private sector, which is somewhat higher when the selection processes are taken into account.

The impact of host language proficiency across the immigrants’ earning distribution in Spain

“…In contrast, low-educated individuals may be precluded from entering high-paying occupations, regardless of their knowledge of the host language. 7 This explanation is consistent with previous research by Di Paolo (2011), who finds that education and not Catalan language proficiency is the main channel for entering high-skilled occupations in the Spanish region of Catalonia. Moreover, in Spain, a country with historically above average unemployment rates, language knowledge may determine the sorting of immigrants between employment and unemployment, whereas education may act as a screening device to access high-skilled occupations.…”

WHAT HAS 20 YEARS OF PUBLIC–PRIVATE PAY GAP LITERATURE TOLD US? EASTERN EUROPEAN TRANSITIONING vs. DEVELOPED ECONOMIES

“…Finally, in Spain, DiPaolo () estimated that private sector workers who were more likely to be selected in the public sector performed in 2006 worse in terms of monthly earnings than a random private sector worker.…”

Wage returns to interregional mobility among Ph.D graduates: Do occupations matter?

“…To outline this procedure, we follow the notation proposed by Di Paolo (). Assuming a standard Becker‐Mincer equation for earnings augmented to estimate returns of mobility ( M ) across occupations ( J ) that are matched ( J = 1) or not ( J = 0), we can write: where w is wage, X is a matrix of exogenous variables, M is the vector of the dummy for mobility, β is a coefficient vector, δ is the coefficient of the wage effect of mobility varying across matched occupations ( J = 1) or non‐matched ones ( J = 0) and ( υ ) denotes the error term normally distributed with mean zero.…”

“…In the second step, we estimate the wage equation including the above parameters as supplementary independent variables in order to control for the selectivity of mobility and sector choice; the wage equation is finally estimated by OLS. 3 To outline this procedure, we follow the notation proposed by Di Paolo (2011). Assuming a standard Becker-Mincer equation for earnings augmented to estimate returns of mobility (M) across occupations (J) that are matched (J = 1) or not (J = 0), we can write:…”

“…In the notable contribution of Aldashev, Gernandt, and Thomsen (), language ability did not impact on earnings once the selectivity bias due to the simultaneous self‐selection of individual into economic sector and occupation according to language fluency was taken into account. Finally, a recent work by Di Paolo () showed that the language earnings premium was attributable in its totality to occupational selection; also in this case, the estimation was carried out by a double sample selection model. As this brief survey states clearly, this estimation procedure proved to be efficient to correct estimates in several contexts.…”