Showing 1 - 10 of 5,660
healthcare systems of WHO members with regard to spatial dependencies while distinguishing between heterogeneity and inefficiency …
Persistent link: https://www.econbiz.de/10010593578
In a panel data model with fixed effects, possible cross-sectional dependence is investigated in a spatial autoregressive setting. An Edgeworth expansion is developed for the maximum likelihood estimate of the spatial correlation coefficient. The expansion is used to develop more accurate...
Persistent link: https://www.econbiz.de/10011268329
extended to incorporate heterogeneity in the responses of health to the explanatory variables. We illustrate our method with an … there is an important degree of heterogeneity in the association of health to explanatory variables across birth cohorts and …
Persistent link: https://www.econbiz.de/10005771946
extended to incorporate heterogeneity in the responses of health to the explanatory variables. We illustrate our method with an … there is an important degree of heterogeneity in the association of health to explanatory variables across birth cohorts and …
Persistent link: https://www.econbiz.de/10005708010
Inference using difference-in-differences with clustered data requires care. Previous research has shown that t tests based on a cluster-robust variance estimator (CRVE) severely over-reject when there are few treated clusters, that different variants of the wild cluster bootstrap can...
Persistent link: https://www.econbiz.de/10011428007
Inference using difference-in-differences with clustered data requires care. Previous research has shown that, when there are few treated clusters, t-tests based on cluster-robust variance estimators (CRVEs) severely overreject, and different variants of the wild cluster bootstrap can either...
Persistent link: https://www.econbiz.de/10011962945
When there are few treated clusters in a pure treatment or difference-in-differences setting, t tests based on a cluster-robust variance estimator (CRVE) can severely over-reject. Although procedures based on the wild cluster bootstrap often work well when the number of treated clusters is not...
Persistent link: https://www.econbiz.de/10011939455
Inference using difference-in-differences with clustered data requires care. Previous research has shown that, when there are few treated clusters, t-tests based on cluster-robust variance estimators (CRVEs) severely overreject, and different variants of the wild cluster bootstrap can either...
Persistent link: https://www.econbiz.de/10012431053
Inference using difference-in-differences with clustered data requires care. Previous research has shown that t tests based on a cluster-robust variance estimator (CRVE) severely over-reject when there are few treated clusters, that different variants of the wild cluster bootstrap can...
Persistent link: https://www.econbiz.de/10011583198
This paper proposes an approach to specify and estimate multiple input, multiple output production frontiers and technical efficiency using a stochastic ray frontier production model A possible model extension is to incorporate a technical efficiency effects model to allow estimation of the...
Persistent link: https://www.econbiz.de/10005423780