分布动态:空间视角

IF 1.5 3区经济学 Q2 ECONOMICS

Spatial Economic Analysis Pub Date : 2022-07-21 DOI:10.1080/17421772.2022.2095005

Margherita Gerolimetto, S. Magrini

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引用次数: 1

摘要

摘要在横断面收敛分析中，数据表现出空间相关性是很常见的。在采用分布动力学方法的文献中，作者通常选择空间预过滤。我们遵循另一条路线，并提出了一种基于条件密度均值函数估计的程序，为此我们开发了一个两阶段非参数估计器，该估计器允许通过空间相关函数的样条估计器估计空间相关性。该估计器的有限样本性能通过蒙特卡罗模拟进行评估。我们将所提出的空间非参数估计方法应用于美国各州和大都市统计区的人均个人收入数据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Distribution dynamics: a spatial perspective

ABSTRACT It is quite common in cross-sectional convergence analyses that data exhibit spatial dependence. Within the literature adopting the distribution dynamics approach, authors typically opt for spatial prefiltering. We follow an alternative route and propose a procedure based on an estimate of the mean function of a conditional density for which we develop a two-stage non-parametric estimator that allows for spatial dependence estimated via a spline estimator of the spatial correlation function. The finite sample performance of this estimator is assessed via Monte Carlo simulations. We apply the procedure that incorporates the proposed spatial non-parametric estimator to data on per capita personal income in US states and metropolitan statistical areas.

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来源期刊

Spatial Economic Analysis ECONOMICS-

CiteScore

5.40

自引率

21.70%

发文量

期刊介绍： Spatial Economic Analysis is a pioneering economics journal dedicated to the development of theory and methods in spatial economics, published by two of the world"s leading learned societies in the analysis of spatial economics, the Regional Studies Association and the British and Irish Section of the Regional Science Association International. A spatial perspective has become increasingly relevant to our understanding of economic phenomena, both on the global scale and at the scale of cities and regions. The growth in international trade, the opening up of emerging markets, the restructuring of the world economy along regional lines, and overall strategic and political significance of globalization, have re-emphasised the importance of geographical analysis.