THE FDH ESTIMATOR FOR PRODUCTIVITY EFFICIENCY SCORES

By Byeong U. Park, Léopold Simar, Christian Weiner. Econometric Theory, 2000

221 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/2362cffcc5081714aed7adca4b888010cee0e4e9

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Citations in the corpus

Testing Hypotheses in Nonparametric Models of Production (2016, background): “Asymptotic properties of FDH efficiency estimators are given by Park, Simar, and Weiner (2000) and Daouia, Simar, and Wilson (2015).”
Technical Efficiency of the Brazilian Municipalities: Correcting Nonparametric Frontier Measurements for Outliers (2005, methodology): “Whereas the DEA/FDH estimators are described as deterministic, recent work established the statistical properties of those estimators (Kneip et al., 1998; Park et al., 2000; Simar and Wilson, 2000) thus making inference possible either by using asymptotic results or by means of bootstrap.”
Probabilistic characterization of directional distances and their robust versions (2012, methodology): “Park et al. (2000) suggest a way to estimate this constant in the input (or output) oriented case but claim that it is only useful with large data sets (in particular if p + q increases).”
Detecting Outliers in Frontier Models: A Simple Approach (2003, background): “In Park et al. (2000) the standard deviation of the FDH estimator at a point is shown to be proportional to the inverse of the probability of observing a point near the frontier at this point: again this probability is small and difficult to estimate for border points.”
Linearly interpolated FDH efficiency score for nonconvex frontiers (2006, methodology): “Under the assumptions AI–AIII in Park et al. (2000), as n→ ∞ we have sup z>0 ∣∣∣∣∣ Pr { n1/(p+q) ( θ̂n/θ0 − 1 ) ≤ z } −Pr { m1/(p+q) ( θ̂∗n,m/θ̂n − 1 ) ≤ z ∣∣∣∣Xn } ∣∣∣∣∣ p −→ 0.”
Nonparametric frontier estimation via local linear regression (2007, methodology): “Given that 0osRo1, A2(4) and A2(5) are implied by assumption AIII in Park et al. (2000).”
Statistical inference for aggregates of Farrell-type efficiencies (2007, unknown): “1 See Blackorby and Russell (1999), Färe and Zelenyuk (2003), Färe et al.”
Non-parametric, unconditional quantile estimation for efficiency analysis with an application to Federal Reserve check processing operations (2005, unknown): “…| P) defined in (2.2) and (2.3) converge at the rate n−2/(p+q+1) (Kneip et al., 1998), while FDH estimators converge at an even slower rate, n−1/(p+q) (Park et al., 2000).9 The convergence rates become worse as dimensionality (p + q) increases, becoming quite slow for commonly used numbers of…”
How to measure the impact of environmental factors in a nonparametric production model (2012, background): “To summarize, under mild regularity conditions: n1/(p+q) ( (x0, y0)− ̂(x0, y0) ) ℒ−→ Weibull( p+q0 , p+ q), (3.3) where 0 is a constant depending on the DGP P ∈ ℙ that is described in Park et al. (2000).”
On the comparative performance of socially responsible and Islamic mutual funds (2014, background): “Thus, although most applications in the field have focused tightly on DEA, the greater flexibility of FDH, along with its asymptotic properties, are the reasons for our choice (Park et al., 2000).”
NONPARAMETRIC FRONTIER ESTIMATION: A CONDITIONAL QUANTILE-BASED APPROACH (2005, methodology): “A consistent nonparametric estimator of this unknown constant has been proposed in Park et al. (2000). Like the approach of Cazals et al.”