Premium
Non‐linearities in regional growth: A non‐parametric approach
Author(s) -
SansoNavarro Marcos,
VeraCabello María
Publication year - 2015
Publication title -
papers in regional science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.937
H-Index - 64
eISSN - 1435-5957
pISSN - 1056-8190
DOI - 10.1111/pirs.12112
Subject(s) - econometrics , endowment , economics , context (archaeology) , human capital , novelty , estimator , dimension (graph theory) , kernel (algebra) , semiparametric model , productivity , parametric statistics , kernel regression , mathematics , economic geography , geography , nonparametric statistics , statistics , macroeconomics , economic growth , psychology , political science , archaeology , law , social psychology , combinatorics , pure mathematics
Abstract This paper analyses the determinants of regional economic growth in the E uropean U nion adopting a non‐parametric approach. Although the local‐linear kernel estimator applied does not explicitly take into account the spatial dimension of the data, it is found to be consistent in our context. In addition, the geographically weighted regression turns out to be less efficient. We obtain evidence of a non‐linear relationship between regional growth and its determinants in the form of parameter heterogeneity and threshold effects. These non‐linearities mainly affect the initial productivity of labour, the human capital endowment and, as a novelty, the level of infrastructures.