By Gilles Duranton, Vernon Henderson, William Strange
Developments in methodologies, agglomeration, and quite a number utilized matters have characterised contemporary advances in nearby and concrete experiences. quantity five concentrates on those advancements whereas treating conventional matters similar to housing, the prices and merits of towns, and coverage concerns past nearby inequalities. participants make a behavior of mixing conception and empirics in each one bankruptcy, guiding study amid a development in utilized economics in the direction of structural and quasi-experimental techniques. truly exclusive from the recent monetary Geography lined via quantity four, those articles function a global procedure that positions fresh advances in the self-discipline of economics and society at large.
- Emphasizes advances in utilized econometrics and the blurring of "within" and "between" towns
- Promotes the combination of conception and empirics in so much chapters
- Presents new examine on housing, specifically in macro and foreign finance contexts
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Additional resources for Handbook of Regional and Urban Economics
Causal Inference in Urban and Regional Economics they would not be good measures of individual ability. These observations are made by De La Roca and Puga (2014) using Spanish data and Baum-Snow and Pavan (2012) using US data in their assessments of the effects of city size on wages. Absent some source of randomization in treatment, the literature has heretofore been only partially successful at handling the potential endogeneity of moves without the use of a structural model, as in Baum-Snow and Pavan (2012).
These assumptions are sometimes called “selection on observables” because they allow selection into treatment to be fully predicted by X, but not by U. This assumption implies TT(x) ¼ ATE(x), but not necessarily that TT ¼ ATE. Provided that the data set being used is rich with observables, there is information in the propensity score coupled with treatment status about whether unobservables correlated with the treatment may be an important source of bias. If there is very little overlap in the range of the propensity score in which both treated and untreated observations exist, this indicates that since treatment and control groups differ on observables, they may be more likely to differ on unobservables as well.
Denote the set of exogenous variables as Z ¼ [Z1X]. 13) are sufficiently different from 0 in a statistical sense. We sometimes use the “reduced form” of this two-equation system, which is as follows: yi ¼ Zi1 ϕ1 + Xi ϕ2 + ψ i : If there is just one excluded instrument per endogenous variable, one simple way to esti^1OLS mate β is through indirect least squares (ILS): b β ILS ¼ ϕ . This is an intuitive object ^ ζ 1OLS which shows how the first-stage coefficient rescales the reduced form effect of the instrument on the outcome.