Central Limit Theorems and Uniform Laws of Large Numbers for Arrays of Random Fields.

Central Limit Theorems and Uniform Laws of Large Numbers for Arrays of Random Fields.
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DOI:
10.1016/j.jeconom.2009.02.009
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发表时间:
2009-05
影响因子:
6.3
通讯作者:
Prucha IR
Prucha IR
中科院分区:
经济学2区
文献类型:
--
作者:
Jenish N;Prucha IR

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在过去的几十年里,空间相互作用模型在经济学中得到越来越多的应用。然而,一个足够普遍的非线性空间模型的渐近理论的发展一直受到阻碍,缺乏相关的中心极限定理(CLTs),一致大数定律(ULLN)和逐点大数定律(LLNs)。这些极限定理形成了发展M-估计量的渐近理论的基本组成部分,包括最大似然估计量和广义矩估计量。本文建立了一个CLT,ULLN和LLN的空间过程或随机场,应该适用于广泛的数据处理。
Over the last decades, spatial-interaction models have been increasingly used in economics. However, the development of a sufficiently general asymptotic theory for nonlinear spatial models has been hampered by a lack of relevant central limit theorems (CLTs), uniform laws of large numbers (ULLNs) and pointwise laws of large numbers (LLNs). These limit theorems form the essential building blocks towards developing the asymptotic theory of M-estimators, including maximum likelihood and generalized method of moments estimators. The paper establishes a CLT, ULLN, and LLN for spatial processes or random fields that should be applicable to a broad range of data processes.
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