Definitive consensus on how to measure human capital does not exist. In general, indirect indicators are used, such as school attainment or years of schooling (Barro 2001); however these measurements do not consider quality and only capture certain aspects of human capital. Traditional models of human capital, which use only education to proxy skills, might overestimate the direct effect of education on labor participation and wages.

Several researchers, concerned with finding a better way to measure human capital by including quality of education, have used scores obtained from international assessments. While these tests cover aspects of science, language and mathematics, researchers have generally used the last two. Currently, several organizations have conducted international assessments, such as TIMSS (IEA¹), PISA (OCDE²), PIRLS (IEA) among others. These assessments were created to allow the participating nations to compare the educational achievement of students across borders. Also, some countries are including their own measurements of human capital quality, such as the MxFLS in Mexico.

Yet, similar to human capital quality, individuals’ personality may likewise result in job performance differentials, and hence the studies that do not consider personality traits might also have important limitations.

We improve on the past literature for Chile and Latin America: Using a new survey with several tests that approximate several quality characteristics of human capital.

In a recent paper we estimate a simple model of wage determination and labor participation including a reading comprehension test and psychological traits, this is the main contribution of our paper. The literacy level corresponds to the results of a reading comprehension test, conducted in 2011 by the National Council of Culture and Arts of Chile, and psychological traits are recover from several psychological tests included in the questionnaire from the same study.

What do we examine?

We examine the returns to individuals’ reading skills and psychological traits using an augmented Mincer-type earnings regression, which relates the logarithm of hourly earnings to years of schooling, the reading test and the psychological test.

Since wages are observable only for employed individuals, our sample presents a selection bias. Therefore we used Heckman’s correction procedure (Heckman 1979), modeling the wage equation jointly with the selection into the labor market.

The results were to be expected

We find that individuals with better reading comprehension skills tend to receive higher wages, confirming the hypothesis that they intrinsically have higher productivity levels. The magnitude of impact is also relevant, an additional standard deviation in the reading test is associated with an increment of 7% in hourly earnings. Therefore these skills must be taken into consideration in future human capital development policies. Interestingly, the return of education is not affected by the inclusion of the reading test.

Further the inclusion of psychological traits underline the relevance of considering other kind of abilities to better understand labor force participation. We find that the psychological traits affect the odds of participating in the labor market, even when we included years of schooling. It might be argued that an employee’s psychological traits are not observable to the employer at the beginning of an employment relationship, but these traits impacts the decision to participate in the labor market, specifically autonomy is a strong trait related to participation in the labor market.

Finally and as a recommendation for future studies, it is necessary to consider a broad range of variables, including psychological traits and quality of education. This study moves in that direction, but it may have problems of endogeneity due to the dynamics of psychological traits and labor. Future research must rely on panel data to improve the estimations and to achieve substantial improvements in the quality of evidence required for new policies.

1. TIMSS was developed by the International Association for the Evaluation of Educational Achievement (IEA).

2. The Programme for International Student Assessment (PISA) is a worldwide study by the Organisation for Economic Co-operation and Development (OECD).