A missing link? Cultural capital as a source of human capital: evidence from Italian regional data

Abstract

We apply a 2SLS approach to panel data from Italian regions, 2004–2014, to investigate the relationship between cultural and human capital. We find that cultural participation, as a proxy of cultural capital, has positive impact on two proxies of human capital, tertiary education and lifelong learning. Due to structural differences between North Central and Southern Italy, we separately analyse the two macro-regions, highlighting differences in cultural participation and human capital endowment, finding positive relations between the two types of capital in all areas. The relationship between cultural and human capital is mediated by the heterogeneity of regional socio-economic orientations towards education, learning, and cultural participation.

Appendix

1.1 The Mazziotta–Pareto procedure

The first computational step consists in standardizing the observed values. All the elementary values are rescaled, around a mean of 100, in the approximate range of (70, 130), meaning that at least 89% of the rescaled values will fall within that interval. Assume X is an n × m matrix, whose elements {x_ij} are the elementary values. The n rows represent the regions, whereas the m columns are the variables. In order to standardize, compute the vertical variability

$$ M_{j} = \frac{1}{n} \sum\limits_{i = 1}^{n} {x_{ij} } \quad S_{j} = \sqrt {\frac{1}{n} \sum\nolimits_{i = 1}^{n} {(x_{ij} - M_{j} )^{2} } } $$

Consider now matrix Z, whose elements are {z_ij}

$$ z_{ij} = 10*\frac{{x_{ij} - M_{j} }}{{S_{j} }} \pm 100 $$

(5)

The sign in (5) depends on the interpretation of the indicator. If high values are to be read as a positive phenomenon, then the sign is positive. In our case, the variables that build both the indicator of human capital and that of cultural capital are to be considered positive (e.g. an increase in TE and LL is intended as a positive phenomenon, and likewise for all the cultural capital variables that end up in the indicator of cultural capital).

To capture the horizontal variability, define

$$ M_{j} = \frac{1}{m} \sum\limits_{i = 1}^{n} {z_{ij} } \quad S_{j} = \sqrt {\frac{1}{m} \sum\nolimits_{i = 1}^{n} {(z_{ij} - M_{i} )^{2} } } $$

The variation coefficient cv_i is the ratio between S_i and M_i. The composite indicator for unit i is then computed as

$$ {\text{MPI}} = M_{i} \pm S_{i} {\text{cv}}_{i} $$

(6)

This indicator basically adjusts the mean by subtracting an amount which is proportional to the mean square error (penalty). Using this aggregation method, we build up two indicators, both with positive sign: the IHC and the ICC.