Global inequality and national inequality: Is there a trade-off?

The objective of this paper is to show that there is a trade-off between global inequality (between countries) and national inequality (within countries). We observed that when the former declines, the latter increases. Empirically, it is possible to observe a shift from higher global inequality to lower global inequality levels (and higher national inequality levels) since the last quarter of the previous century. From a historical perspective, my thesis is that when the main drivers of economic growth are technology and means of transportation, inequality is mostly between countries (higher global inequality). In contrast, when the main driver of economic growth is labour (and related factors such as human capital, skills, knowledge exploitation), then inequality is mostly within countries (higher national inequality). Limitations of data availability did not allow for testing these historical trends. However, the trends of global and national inequalities over the last three to four decades confirm such a thesis.

Does a Rise in Income Inequality Lead to Rises in Transportation Inequality and Mobility Practice Inequality?

Social and economic inequalities have sharpened in the late 20^th century. During this period, Europe has witnessed a rising unemployment rate, a declining wages for the least qualified workers, a slowing of income growth, and an increasing gap between the richest and the poorest. Based on the hypothesis of the relation between socio-economic condition and mobility behaviour, it is necessary to ask how these socio-economic inequalities manifest themselves in transportation: does a rise in income inequality lead to a rise in transportation inequality and mobility practice inequality? This question is particularly relevant today as some European countries are facing high socio-economic inequalities following the financial crisis that started in 2008. Using results from transport, car ownership and mobility surveys as well as household surveys from the Paris (Île-de-France) region between eighties and late nineties, this paper tries to answer this question. The results show how inequalities in transportation and mobility practice have decreased during the period in spite of an increase in income inequalities. We find that the evolution of socio-economic inequality, most specifically income inequality was simply one of the determining factors of the evolution of inequalities in transportation and mobility practice. In fact, the most important role in that evolution is not played by the evolution of income inequality but by the evolution of elasticity between transportation and income. Reducing the effects of this elasticity should be the main target of transport policies to diminish inequality in transportation and mobility practice.

Concentration on the Discrete Torus Using Transportation

The sub-Gaussian constant of a graph arises naturally in bounding the moment-generating function of Lipschitz functions on the graph, with a given probability measure on the set of vertices. The closely related spread constant of a graph measures the maximal variance over all Lipschitz functions on the graph. As such they are both useful (as demonstrated in the works of Bobkov, Houdré and Tetali and Alon, Boppana and Spencer) for describing the concentration of measure phenomenon in product graphs. An equivalent formulation of the sub-Gaussian constant using a transportation inequality, introduced by Bobkov and Götze, is investigated here in depth, leading to a new way of bounding the sub-Gaussian constant. A tight concentration result for the discrete torus is given as a concrete application. An infinite family of graphs is also provided here to demonstrate that, typically, the spread and the sub-Gaussian constants differ by an order of magnitude.