Juncal Cuñado, Ph., D, Quantitative Methods, University of Navarra, Campus Universitario, Pamplona, Navarra, Spain, Pamplona, 31080, Spain and Fernando Pérez de Gracia, Ph., D, Economics, University of Navarra, Campus Universitario, Pamplona, Navarra, Spain, Pamplona, 31080, Spain.
Quality of life has emerged over the last decades as an important policy and intellectual preoccupation. How to best measure quality of l, however, remains an open question. Since, as early as in the 1950s and 1960s, it has become clear that, in spite of its widespread use, monetary socio-economic indicators (such as per capita GNP) are an insufficient measure of the well-being of citizens (e.g., United Nations, 1954; Erikson, 1993), and the current consensus even among economists is that the employment of monetary indicators to measure welfare is far from perfect (e.g., Ng, 1997; Frey and Stutzer, 2000, 2002; Gowdy, 2004). Over the last decades, subjective well-being indicators have emerged as a valid measure of individual welfare, opening the door to a new paradigm for policy-making which sets people’s happiness, rather than national income, as the goal that policy makers should try to maximise. In this context the understanding of the determinants of happiness or life satisfaction becomes critical to evaluate the success of European countries at promoting the personal and social well-being of their citizens.The first objective of this paper is to examine for the Spanish economy the impact on happiness of a number of factors, such as: socio-demographic characteristics of individuals, such as age, gender and marital status, and socio-economic and macroeconomic characteristics, such as income, unemployment and inflation. The second objective is to describe how the impact of these variables varies among the different regions of.
The main data source will be the European Social Survey (ESS) (www.europeansocialsurvey.org). The ESS provides rich data on individuals’ subjective well-being, political interests, trust, electoral participation, party allegiance, socio-political orientations, environmental attitudes and demographic and socio-economic characteristics required to control for individual heterogeneity (age, gender, education, employment status, marital status, number of children, income, etc.).