This paper makes a new attack on the old problem of measuring horizontal inequity (HI). A local measure of HI is proposed, and aggregated into a global index. Whilst other approaches have captured the welfare gain which would come from eliminating HI revenue-neutrally, our global index provides...

Just as the Gini inequality index captures people's relative deprivation [Yitzhaki (1979)], so, we show in this paper, Gini-based progressivity and horizontal inequity indices capture individual perceptions of relative fiscal harshness and ill-fortune. In fact, we find that these links between...

This paper makes a new attack on the old problem of measuring horizontal inequity (HI). A local measure of HI is proposed, and aggregated into a global index. Whilst other approaches have captured the welfare gain which would come from eliminating HI revenue-neutrally, our global index provides...

A local measure of classical horizontal inequity (HI) in an income tax or tax-benefit system is proposed and aggregated into a global index. This index expresses the revenue gain per capita that would come from eliminating HI welfare-neutrally, and also reveals the loss of vertical performance,...

Just as the Gini inequality index captures people's relative deprivation [Yitzhaki (1979)], so, we show in this paper, Gini-based progressivity and horizontal inequity indices capture individual perceptions of relative fiscal harshness and ill-fortune. In fact, we find that these links between...

Unemployment rates appear to vary widely at a subregional (e.g., local or provincial) level. Using spatial econometric models for spatial autocorrelation, this paper focuses attention on the spatial structure of regional unemployment disparities of Italian provinces. On the basis of findings...

In this paper, a set of neural network (NN) models is developed to compute short-term forecasts of regional employment patterns in Germany. NNs are modern statistical tools based on learning algorithms that are able to process large amounts of data. NNs are enjoying increasing interest in...

In this paper, a set of neural network (NN) models is developed to compute short-term forecasts of regional employment patterns in Germany. NNs are modern statistical tools based on learning algorithms that are able to process large amounts of data. NNs are enjoying increasing interest in...

An avalanche of empirical studies has addressed the validity of the rank-size rule (or Zipf's law) in a multi-city context in many countries. City size in most countries seems to obey Zipf's law, but the question under which conditions (e.g. sample size, spatial scale) this 'law' holds remained...

The geographical distribution and persistence of regional/local unemployment rates in heterogeneous economies (such as Germany) have been, in recent years, the subject of various theoretical and empirical studies. Several researchers have shown an interest in analysing the dynamic adjustment...