Externality

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Externality

The cost or benefits of a transaction to parties who do not directly participate in it. Externality can be either positive or negative. For example, a merger can lead to higher share prices and bonuses for employees, benefiting shareholders and employees at the two companies merging, This can create wealth and positively impact a community. On the other hand, the merger can drive a competitor out of business, which results in layoffs and reduced wealth, which can hurt a community. Externality is also called spillover or the neighborhood effect. See also: External benefit, External cost.
References in periodicals archive ?
However, when steps are taken to control for unobserved heterogeneity, the neighborhood effects become insignificant.
Plotnick and Hoffman use PSID sisters to identify neighborhood effects, concluding that family fixed effects eliminate the impact of neighborhoods on postsecondary schooling, teen births, and welfare recipiency.
I modeled the probability the individual was attributed in the current year, based on current age, gender, plan enrollment, and neighborhood effects, and based on the prior year's health status to avoid having current health status confound current patterns of care-seeking.
Finally, we control for neighborhood residential stability because a neighborhood's homeownership rate is plausibly linked to residential stability (Rohe and Stewart 1996), and we want to determine whether it is neighborhood homeownership or neighborhood stability that is responsible for neighborhood effects on children's outcomes.
Section III will review the literature on technology diffusion and present a conceptual framework for analyzing the neighborhood effect.
Great American city: Chicago and the enduring neighborhood effect.
Reflections about neighborhood effect and youth social exclusion in European cities
And as has been extensively documented in the scholarly literature, in the US the quality of schools is largely determined by the very neighborhood effect that Sampson makes so much of, wherein low-income communities of color are spatially and racially concentrated, thus radically affecting their life chances (see Duncan and Murname, 2011).
The evaluation framework makes a clear distinction between (i) program effects from intent-to-treat and treatment-on-the-treated parameters and (ii) neighborhood effects from local-average-treatment-effect parameters.
On the other hand, the statistical models help to obtain visions of spatial heterogeneity effects and neighborhood effects, but these models are able to express the medium effects on the existing data.
As argued by Lopez-Bazo (2002), Overman and Puga (2002) and Niebuhr (2003), these two effects can be characterized as the neighborhood effect variable and the spillover effect variable, respectively.

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