Heterogeneous spatial dynamic panels with an application to US housing data

IF 1.5 3区经济学 Q2 ECONOMICS

Spatial Economic Analysis Pub Date : 2022-10-26 DOI:10.1080/17421772.2022.2118363

Yong Bao, Xiao Zhou

引用次数: 1

Abstract

ABSTRACT This paper proposes two models that incorporate both heterogeneity and multiple sources of spatial correlation for dynamic panels. One uses convex combinations of them to form a single weight matrix. The second one includes explicitly different spatial weight matrices to form a higher order model. We use a Bayesian scheme for model estimation by deriving the full conditional distributions of heterogeneous parameters. Our Monte Carlo experiments demonstrate their finite-sample performance relative to a baseline model. In our empirical study we find the importance of including both geographical and non-geographical information in capturing correlations in real house price growth in the United States.

查看原文本刊更多论文

应用于美国住房数据的异质空间动态面板

摘要本文提出了两个模型，这两个模型结合了动态面板的异质性和多个空间相关性来源。使用它们的凸组合来形成单个权重矩阵。第二个模型包括明确不同的空间权重矩阵以形成更高阶模型。我们通过推导异质参数的全条件分布，使用贝叶斯方案进行模型估计。我们的蒙特卡罗实验证明了它们相对于基线模型的有限样本性能。在我们的实证研究中，我们发现包括地理和非地理信息在捕捉美国实际房价增长相关性方面的重要性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

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.