Spatial Inequality in Mortality in France over the Past Two Centuries

Abstract

This article analyzes the evolution of spatial inequalities in mortality across 90 French territorial units since 1806. Using a new database, we identify a period from 1881 to 1980 when inequalities rapidly shrank while life expectancy rose. This century of convergence across territories was mainly due to the fall in infant mortality. Since 1980, spatial inequalities have levelled out or occasionally widened, due mainly to differences in life expectancy among the elderly. The geography of mortality also changed radically during the century of convergence. Whereas in the 19th century high mortality occurred mainly in larger cities and along a line from North‐west to South‐east France, it is now concentrated in the North, and Paris and Lyon currently enjoy an urban advantage.

An Evaluation of the Innovation Tax Credit

“…In 1950, only 10% were above this threshold. This interdepartmental convergence is similar to the process analysed by Bonnet & d'Albis (2020) for life expectancy but contrasts with the process described by Combes et al (2011) for value added. This sheds light on the role played by public transfers in levelling standards of living, more than compensating for the divergent force resulting from the concentration of economic activities in certain areas of France, in particular the large metropolitan areas.…”

“…When the departmental income is related not to the number of people aged 20 and above but to the department's surface area, the measure of inequality accounts for the department's density (Figure V). With this approach, the inequality level firstly appears to be much higher, which is due to the fact that the French population has concentrated to a very significant extent over the last century (Bonnet, 2019). We also see an overall upward shift in inequality until the end of the 1950s, which was erased over the following two decades.…”

Where Do People Live Longer in Russia in the 21st Century? Life Expectancy across Urban and Rural areas

“…First, because of the country's history of centralization, Moscow has the most advanced and the most numerous healthcare facilities, as many of the federal medical centers that cater to the whole country are situated there. Second, it is a prime destination for Russian and international migrants (mostly from former Soviet republics) whose health is probably better than the health of the receiving population because of the “healthy migrant effect.” Although the LE advantage of Moscow is large, it is common for the capitals of countries to have LE values that exceed the national average (Minton and McCartney 2018; Bonnet and d'Albis 2020).…”

Redistributive Effects of the Taxation of Couples and Families: A Microsimulation Study of Income Tax

“…We have based our work on a new database of average tax income in each department of metropolitan France since 1922, developed from the digitisation of the archives of the Ministry of Finance. These fiscal data on income tax, combined with Bonnet & Sotura's (2021) database on the income distribution of each department and Bonnet's (2020) database on the population of each department broken down by age, allow us to measure average standards of living in each department in a new and more direct way. Based on the average tax income per department calculated using a regression before and after payment of income tax for each year since 1922, we develop indicators of inequality across departments that allow us to analyse the change in inequality over the last century.…”

“…Using administrative archives produced by the tax services, the authors estimated the distribution of tax income in each department and for each year of the following periods: 1960-1969, 1986-1998 and 2001-2015. We have used the total tax income (excluding capital gains) of each department. The second statistical source is the database built by Bonnet (2020), which provides an annual estimate of the population of each department broken down by age. Combining these two sources therefore gives us the average tax income for each department for the years 1960-1969, 1986-1998 and 2001-2015. Furthermore, we also gathered new data for our estimation.…”