 Identification and Estimation of Treatment Effects in the Presence of Neighbourhood InteractionsCERIS Working Paper from CNR-IRCrES Research Institute on Sustainable Economic Growth - Torino (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY Abstract: This paper presents a parametric counter-factual model identifying Average Treatment Effects (ATEs) by Conditional Mean Independence when externality (or neighbourhood) effects are incorporated within the traditional Rubin’s potential outcome model. As such, it tries to generalize the usual control-function regression, widely used in program evaluation and epidemiology, when SUTVA (i.e. Stable Unit Treatment Value Assumption) is relaxed. As by-product, the paper presents also ntreatreg, an author-written Stata routine for estimating ATEs when social interaction may be present. Finally, an instructional application of the model and of its Stata implementation through two examples (the first on the effect of housing location on crime; the second on the effect of education on fertility), are showed and results compared with a no-interaction setting. Keywords: ATEs; Rubin’s causal model; SUTVA; neighbourhood effects; Stata command. JEL Codes: C21; C31; C87 (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:csc:cerisp:201404 Access Statistics for this paper More papers in CERIS Working Paper from CNR-IRCrES Research Institute on Sustainable Economic Growth - Torino (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY Contact information at EDIRC. |
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