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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 present a spatial nonparametric analysis of local multipliers. Following Moretti (2010), we estimate the effect of an exogenous shock in the employment of the tradable sector on the employment in either the nontradable sector or the rest of the tradable sector using a...

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...

This paper contributes to the normative literature on mitigation and adaptation by framing the question of their optimal policy balance in the context of catastrophic climate risk. The analysis uses the WITCH integrated assessment model with a module that models the endogenous risk of...

This paper contributes to the normative literature on mitigation and adaptation by analyzing their optimal policy balance in the context of climate catastrophic risk. The investigation enriches an integrated assessment model introducing the endogenous link between the probability of experiencing...

Instrumental variables estimation is classically employed to avoid simultaneous equations bias in a stable environment. Here we use it to improve upon ordinary least-squares estimation of cointegrating regressions between non-stationary and/or long memory stationary variables where the...