nwxtregress: Network regressions in Stata

William Grieser, Morad Zekhnini and Jan Ditzen
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William Grieser: Texas Christian University
Morad Zekhnini: Michigan State University

German Stata Users' Group Meetings 2022 from Stata Users Group

Abstract: Network analysis has become critical to the study of social sciences. While several Stata programs are available for analyzing network structures, programs that execute regression analysis with a network structure are currently lacking. We fill this gap by introducing the nwxtregress command. Building on spatial econometric methods (LeSage and Pace 2009), nwxtregress uses MCMC estimation to produce estimates of endogenous peer effects, as well as own-node (direct) and cross-node (indirect) partial effects, where nodes correspond to cross-sectional units of observation, such as firms, and edges correspond to the relations between nodes. Unlike existing spatial regression commands (for example, spxtregress), nwxtregress is designed to handle unbalanced panels of economic and social networks as in Grieser et al. (2021). Networks can be directed or undirected with weighted or unweighted edges, and they can be imported in a list format that does not require a shapefile or a Stata spatial weight matrix set by spmatrix. Finally, the command allows for the inclusion or exclusion of contextual effects. To improve speed, the command transforms the spatial weighting matrix into a sparse matrix. Future work will be targeted toward improving sparse matrix routines, as well as introducing a framework that allows for multiple networks.

Date: 2022-06-10
New Economics Papers: this item is included in nep-geo, nep-net and nep-ure
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http://repec.org/dsug2022/germany22_ditzen.pdf presentation materials (application/pdf)

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Working Paper: nwxtregress: Network regressions in Stata (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:boc:dsug22:03

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