Spatial error regressions for testing the Cancer-EKC
Tommaso Luzzati (),
Angela Parenti () and
Discussion Papers from Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy
Why do we observe increasing rates of new cancers cases? Is this mainly the outcome of higher life expectancy and better life conditions brought about by economic development? Do environmental degradation and changes in life-styles play also a role? To answer these questions we empirically assessed the relationship between per capita income and new cancer cases (incidence) by using a cross-sectional dataset from 121 countries. When looking at the overall incidence rate (i.e., all-sites cancer), we found no support for a cancer-EKC hypothesis (inverted-U relationship). Actually, incidence increases with per capita income, even after controlling for population ageing, improvement in cancer detection, and omitted spatially correlated variables. Hence, a role in cancer occurrence has to be attributed also to changes in lifestyles and to deterioration of environmental quality brought about by economic growth. Looking at the eight most common site-specific cancers not only confirms the existing evidence of different patterns in rich and poor countries, but also helps understanding the estimated relationship for the overall incidence rates.
Keywords: Economic development; Cancer; Environmental Kuznets Curve; Environmental degradation; Spatial error models. (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-env and nep-hea
Note: ISSN 2039-1854
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:pie:dsedps:2017/218
Access Statistics for this paper
More papers in Discussion Papers from Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy Contact information at EDIRC.
Bibliographic data for series maintained by ().