Estimating flow data models of international trade: dual gravity and spatial interactions

IF 0.8 4区 经济学 Q3 ECONOMICS
Fei Jin, Lung-fei Lee, Jihai Yu
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引用次数: 1

Abstract

Abstract This article investigates asymptotic properties of quasi-maximum likelihood (QML) estimates for flow data on the dual gravity model in international trade with spatial interactions (dependence). The dual gravity model has a well-established economic foundation, and it takes the form of a spatial autoregressive (SAR) model. The dual gravity model originates from Behrens et al., but the spatial weights matrix motivated by their economic theory has a feature that violates existing regularity conditions for asymptotic econometrics analysis. By overcoming the limitations of existing asymptotic theory, we show that QML estimates are consistent and asymptotically normal. The simulation results show the satisfactory finite sample performance of the estimates. We illustrate the usefulness of the model by investigating the McCallum “border puzzle” in the gravity literature.
国际贸易流量数据模型估算:双重重力与空间相互作用
摘要本文研究了具有空间相互作用(依赖)的国际贸易中双重力模型流量数据的拟最大似然估计的渐近性质。双重重力模型有着坚实的经济基础,它采用了空间自回归(SAR)模型的形式。二重引力模型起源于Behrens等人,但由他们的经济理论驱动的空间权重矩阵具有违反渐近计量经济学分析现有规则性条件的特征。通过克服现有渐近理论的局限性,我们证明了QML估计是一致的和渐近正态的。仿真结果表明,有限样本估计具有令人满意的性能。我们通过研究引力文献中的麦卡勒姆“边界谜题”来说明该模型的有用性。
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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来源期刊
Econometric Reviews
Econometric Reviews 管理科学-数学跨学科应用
CiteScore
1.70
自引率
0.00%
发文量
27
审稿时长
>12 weeks
期刊介绍: Econometric Reviews is widely regarded as one of the top 5 core journals in econometrics. It probes the limits of econometric knowledge, featuring regular, state-of-the-art single blind refereed articles and book reviews. ER has been consistently the leader and innovator in its acclaimed retrospective and critical surveys and interchanges on current or developing topics. Special issues of the journal are developed by a world-renowned editorial board. These bring together leading experts from econometrics and beyond. Reviews of books and software are also within the scope of the journal. Its content is expressly intended to reach beyond econometrics and advanced empirical economics, to statistics and other social sciences.
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