Detection and estimation of block structure in spatial weight matrix
Clifford Lam and
Pedro Souza ()
LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library
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.
Keywords: spatial weight matrix; LASSO penalization; zero-block consistency; spatial lag/error model; Nagaev-type inequality (search for similar items in EconPapers)
JEL-codes: C31 C33 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ure
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Published in Econometric Reviews, 2015. ISSN: 0747-4938
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:59898
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