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This paper examines the influence of college education on social trust at the individual level. Based on the literature of trust and social trust, we hypothesize that life experience/development since adulthood and perceptions of cultural/social structures are two primary channels in the causal linkage between college education and social trust. In the first part of the empirical study econometric techniques are employed to tackle the omitted-variable problem and substantial evidence is found to confirm the positive effect of college education. In the second part contemporary information is used to examine the hypothetical mechanisms in the causal inference. That life experience is a primary channel via which college education promotes social trust fails to find support in our examination, while individual perceptions of cultural and social structures explain up to 77% of the causal effect. (Contains 3 figures, 8 tables, and 11 footnotes.)

To assess the empirical estimates of the effect of education on social trust and social participation--the basic dimensions of individual social capital--a meta-analysis is applied, synthesizing 154 evaluations on social trust, and 286 evaluations on social participation. The publication bias problem is given special emphasis in the meta-analysis. Our statistical synthesis confirms that education is a strong and robust correlate of individual social capital. The meta-analysis provides support for the existence of a relative effect of education on social participation, and of a reciprocity mechanism between the dimensions of social capital. The analysis also suggests that the erosion of social participation during the past decades has coincided with a decrease of the marginal return to education on social capital. Finally, we find differences in the return to education between genders, between US and other nations, and variations for different education attainments. (Contains 7 tables.)

There is a small but growing literature on the determinants of social capital. Most of these studies use a measure of trust to define social capital empirically. In this paper we use three different measures of social capital: the size of the individual's social network, the extent of their social safety net and membership of unions or associations. A second contribution to the literature is that we analyze what social capital contributes to our well-being. Based on this, we calculate the compensating income variation of social capital. We find differences in social capital when we differentiate according to individual characteristics such as education, age, place of residence, household composition and health. Household income generally has a statistically significant effect. We find a significant effect of social capital on life satisfaction. Consequently, the compensating income variation of social capital is substantial.

This paper analyses the relation between two important aspects of human capital: education and health. The contribution of our paper to the literature is three-fold: some further tests for causality in the relation between education and health are provided; it is tested whether results are affected by scale of reference bias and unobserved heterogeneity; and the results are used to calculate the health returns to education. We use data from a large survey for the Netherlands to estimate the education effects on health. Calculated at the average value of GDP per capita, the implied health returns to education are 1.3-5.8%. We further test for causality in the relation between education and health and for the effects of scale of reference bias and unobserved heterogeneity. None of these appear to affect our conclusions.

A random effects ordered response model of training is estimated to analyze the existence of training tracks and time varying coefficients in training frequency. Two waves of a Dutch panel survey of workers are used covering the period 1992-1996. The amount of training received by workers increased during the period 1994-1996 compared to 1992-1994. Evidence is found for the existence of training tracks in the amount of training courses taken. It is further found that the effects of individual characteristics such as education, age and gender on training should be treated as individual varying coefficients.