This paper analyses the determinants of spatial wage disparities in the US context for the period 1980-2000. Agglomeration benefits are estimated based on city productivity premia which are computed after controlling for the skills distribution among metropolitan areas as well as industry fixed...

The paper investigates how the spatial evolution of core-based city regions affects the dynamics of income disparities across Metropolitan Statistical Areas in the United States between 1971 and 2010. Treating initially non-metropolitan counties as part of the functional economic system for the...

This paper analyzes the impact of immigration on the dynamics of the cross-sectional distribution of GSP per capita and per worker. To achieve this we combine different approaches: on the one hand, we establish via Instrumental Variable estimation the effect of the inflow of foreign-born workers...

Internet and near-instant communication services have had a strong impact on the way people communicate and exchange information since the end of the 1990s. The COVID-19 pandemic shock is likely to provide a dramatic boost to this phenomenon. In the world that will emerge from lockdown, digital...

One of the most important drawbacks of the existing literature on convergence is that it largely ignores the effect of aggregate fluctuations on the evolution of income disparities. To the extent that regional income disparities follow a distinct cyclical pattern in the short-run, moving either...

The analysis of synchronization among regional or national business cycles has recently been attracting a growing interest within the economic literature. Far less attention has instead been devoted to a closely related issue: given a certain level of synchronization, some economies might be...

Conditional distributions for the analysis of convergence are usually estimated using a standard kernel smoother but this is known to be biased. Hyndman et al. (1996) thus suggest a conditional density estimator with a mean function specified by a local polynomial smoother, i.e. one with better...

In this paper we present a new procedure for nonparametric regression in case of spatially dependent data. In particular, we extend usual local linear regression (along the lines of Martins-Filho and Yao, 2009) and propose a two-step method where information on spatial dependence is incorporated...

In this paper we analyse some bootstrap techniques to make inference in INAR(p) models. First of all, via Monte Carlo experiments we compare the performances of these methods when estimating the thinning parameters in INAR(p) models. We state the superiority of sieve bootstrap approaches on...