Iteratively Weighted Least Squares in Stochastic Frontier Estimation: Applied to the Dutch Hospital Industry

Iteratively Weighted Least Squares in Stochastic Frontier Estimation: Applied to the Dutch Hospital Industry

Blank, J.L.T.
Meesters, A.J.

Technology, Policy and Management

Values Technology and Innovation

2013-03-01

This paper proposes an alternative class of stochastic frontier estimators. Instead of making distributional assumptions about the error and efficiency component in the econometric specification of a cost function model (or any other model), this class is based on the idea that some observations contain more information about the true frontier than others. If an observation is likely to contain much information, it is assigned a large weight in the regression analysis. In order to establish the weights, we propose an iterative procedure. In each step, the weights are updated and a next stage weighted least squares (WLS) regression is carried out. The advantages of this approach are its high transparency, it’s easy application to a model that includes a cost function and its corresponding share equations and its flexibility to the use of several alternative weighting functions and the easiness of testing for the sensitivity of the outcomes. The model was applied to a set of Dutch hospital data comprising about 550 observations. The outcomes are promising. The model converges rather quickly and presents reliable estimates of the parameters, the cost efficiencies and the error components

weighted least squares
frontier analysis
efficiency
hospitals

http://resolver.tudelft.nl/uuid:e01dec41-39f7-4ce9-bef3-4c29d01b4256

Delft University of Technology

978-94-6186-167-2

IPSE Sudies

Institutional Repository

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