One size does not fit all: quantile regression estimates of cross-country risk of poverty and social exclusion in Europe

Using a macro panel of 31 European countries, this paper shows that the application of a QR procedure to the estimation of poverty risk offers a picture of poverty determinants and cross-country poverty differences more reliable than that emerging from conditional mean estimations. The extent and significance of interquartile differences of estimated coefficients suggest that economic growth, income distribution, public expenditure, and investment, as well as education and the labour share of social product — a proxy for class struggle — have strong but differentiated effects on poverty reduction. However, technical development does not have a similar effect. Low institutional quality exemplified by high public sector corruption has a significant concomitant adverse effect and interacts with economic cofactors in determining interquartile differences of estimated coefficients. Hence, definition and implementation of any European policy against poverty should consider cross-country interquartile differences and avoid a one size fits all uniform philosophy.