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Detection and estimation of block structure in spatial weight matrix

Lam, Clifford and Souza, Pedro C.L. (2015) Detection and estimation of block structure in spatial weight matrix. Econometric Reviews. ISSN 0747-4938

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Identification Number: 10.1080/07474938.2015.1085775

Abstract

In many economic applications, it is often of interest to categorize, classify or label individuals by groups based on similarity of observed behavior. We propose a method that captures group affiliation or, equivalently, estimates the block structure of a neighboring matrix embedded in a Spatial Econometric model. The main results of the LASSO estimator shows that off-diagonal block elements are estimated as zeros with high probability, property defined as “zero-block consistency”. Furthermore, we present and prove zero-block consistency for the estimated spatial weight matrix even under a thin margin of interaction between groups. The tool developed in this paper can be used as a verification of block structure by applied researchers, or as an exploration tool for estimating unknown block structures. We analyzed the US Senate voting data and correctly identified blocks based on party affiliations. Simulations also show that the method performs well.

Item Type: Article
Official URL: http://www.tandfonline.com/toc/lecr20/current
Additional Information: © 2015 Taylor and Francis
Divisions: Economics
Statistics
Subjects: H Social Sciences > HA Statistics
Q Science > QA Mathematics
JEL classification: C - Mathematical and Quantitative Methods > C3 - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors > C31 - Cross-Sectional Models; Spatial Models; Treatment Effect Models
C - Mathematical and Quantitative Methods > C3 - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors > C33 - Models with Panel Data
Sets: Departments > Economics
Departments > Statistics
Collections > Economists Online
Date Deposited: 21 Oct 2014 13:15
Last Modified: 20 Feb 2019 11:11
URI: http://eprints.lse.ac.uk/id/eprint/59898

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