Network regressions in Stata

Jan Ditzen, William Grieser and Morad Zekhnini
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William Grieser: Free University of Bozen-Bolzano
Morad Zekhnini: Free University of Bozen-Bolzano

UK Stata Conference 2023 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. 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. A special focus of the presentation will be put on the construction of the spatial weight matrix and integration with Python to improve speed.

Date: 2023-09-10
New Economics Papers: this item is included in nep-net and nep-ure
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http://repec.org/lsug2023/Stata_UK23_Ditzen.pdf

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Working Paper: Network regressions in Stata (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:boc:lsug23:21

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