2 household survey data from before, during and after the stabilization and liberalization program of the early 1990s. We conclude that there is evidence for growing inequality in rates of return to education in Brazil, but evidence that education is no longer used as a screening device in the labor market, but rather rewarded for its innate association with higher productivity. Although increases in rates of return to education have been more pronounced at the top of the earnings distribution, this has not led to increased inequality. This is because levels of education and other labor market-rewarded endowments have increased and offset the rate of return effect.

The remainder of the paper is structured as follows. Section 2 discusses the empirical method used. Section 3 describes the data source used. Section 4 presents results and section 5 concludes.

# **2. Empirical Approach**

An important issue on the productivity of education concerns whether formal education acts as a screen, separating more able (and educated) individuals from the less able (and educated). The screening hypothesis (Arrow, 1973) observes that at the point of hiring workers’ productivity is unknown to employers and argues therefore that employers use education as a proxy for latent productivity. In competitive sectors of the labor market productivity will matter and so returns to education will be higher. In non-competitive sectors of the labor market returns to subsequent education after hiring will be lower. It is therefore possible that the value of education as a screen may vary across the earnings distribution because of differing degrees of competition. In particular screening may be more important in the top of the distribution, where insider power may be more important.

The empirical literature on screening distinguishes between the weak form and strong form of the hypothesis (Psacharopoulos, 1979; Arabsheibani and Rees, 1998). The weak form states that employers will pay a higher initial salary to recruits with higher levels of education, but is agnostic about the shape of the subsequent experience-earnings profile. The strong form states that employers will continue to pay high salaries even after observing working on the job, because education continues to enhance productivity as experience on the job rises. However the experience-earnings profiles of an educated worker will converge over time with that of a non-educated worker, as the original hiring “mistake” is gradually corrected. Psacharopoulos (1979) proposes what has become known as the P(sacharopoulos) test as a method of empirical investigation.

Assume that log hourly earnings for individual _i_ , _yi_ , are determined according a Mincerian earnings function of the following form: where _S_ is years of education, _E_ is years of experience, _Z_ are other socio-economic variables affecting earnings, _aj_ and _b_ are coefficients and _u_ is a disturbance term. The inclusion of the interaction term between years of education and years of experience provides a straightforward test of convergent experience-earnings profiles under the strong screening hypothesis (Lee, 1980). If the hypothesis holds then _a_ 5 < 0, otherwise _a_ 5 ≥ 0.

Previous research has shown that modeling average earnings (i.e. OLS) fails to reveal that the effect of education on earnings is non-constant across the conditional wage