Léopold Simar
Biographic Data
| ID | 8920938 |
|---|---|
| NAME | Léopold Simar |
| GIVEN NAMES | Léopold |
| FAMILY NAME | Simar |
| SIGNATURE | SIMAR L |
| AFFILIATIONS | UCLouvain |
| ORCID | 0000-0003-0791-8490 |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 11 |
| EDITOR COUNT | 1 |
| FIRST PUBLICATION YEAR | 1985 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Proportional incremental cost probability functions and their frontiers
Nonparametric, Stochastic Frontier Models with Multiple Inputs and Outputs
Stochastic frontier models along the lines of Aigner et al. are widely used to benchmark firms’ performances in terms of efficiency. The models are typically fully parametric, with functional form specifications for the frontier as well as both the noise and the inefficiency processes. Studies such as Kumbhakar et al. have attempted to relax some of the restrictions in parametric models, but so far all such approaches are limited to a univariate …
Predicting recessions with a frontier measure of output gap: An application to Italian economy
Despite the long and great history, developed institutions, and high level of physical and human capital, the Italian economy has been fairly stagnant during the last three decades. In this paper, we merge two streams of literature: nonparametric methods to estimate frontier efficiency of an economy, which allows us to develop a new measure of output gap, and nonparametric methods to estimate probability of an economic recession. To illustrate th…
Testing Hypotheses in Nonparametric Models of Production
Data envelopment analysis (DEA) and free disposal hull (FDH) estimators are widely used to estimate efficiency of production. Practitioners use DEA estimators far more frequently than FDH estimators, implicitly assuming that production sets are convex. Moreover, use of the constant returns to scale (CRS) version of the DEA estimator requires an assumption of CRS. Although bootstrap methods have been developed for making inference about the effici…
Specifying Statistical Models: From Parametric to Non-Parametric, Using Bayesian or Non-Bayesian Approaches
Two-stage DEA: Caveat emptor
Estimation and inference in two-stage, semi-parametric models of production processes
Introducing Environmental Variables in Nonparametric Frontier Models: A Probabilistic Approach
Nonparametric frontier estimation: A robust approach
A general methodology for bootstrapping in non-parametric frontier models
The Data Envelopment Analysis method has been extensively used in the literature to provide measures of firms' technical efficiency. These measures allow rankings of firms by their apparent performance. The underlying frontier model is non-parametric since no particular functional form is assumed for the frontier model. Since the observations result from some data-generating process, the statistical properties of the estimated efficiency measures…
Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models
Efficiency scores of production units are generally measured relative to an estimated production frontier. Nonparametric estimators (DEA, FDH, ⋯) are based on a finite sample of observed production units. The bootstrap is one easy way to analyze the sensitivity of efficiency scores relative to the sampling variations of the estimated frontier. The main point in order to validate the bootstrap is to define a reasonable data-generating process in t…
Alternative Approaches to Time Series Analysis
No prominent works on this page.
Alternative Approaches to Time Series Analysis
Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models
Efficiency scores of production units are generally measured relative to an estimated production frontier. Nonparametric estimators (DEA, FDH, ⋯) are based on a finite sample of observed production units. The bootstrap is one easy way to analyze the sensitivity of efficiency scores relative to the sampling variations of the estimated frontier. The main point in order to validate the bootstrap is to define a reasonable data-generating process in t…
A general methodology for bootstrapping in non-parametric frontier models
The Data Envelopment Analysis method has been extensively used in the literature to provide measures of firms' technical efficiency. These measures allow rankings of firms by their apparent performance. The underlying frontier model is non-parametric since no particular functional form is assumed for the frontier model. Since the observations result from some data-generating process, the statistical properties of the estimated efficiency measures…
Nonparametric frontier estimation: A robust approach
Introducing Environmental Variables in Nonparametric Frontier Models: A Probabilistic Approach
Estimation and inference in two-stage, semi-parametric models of production processes
Two-stage DEA: Caveat emptor
Specifying Statistical Models: From Parametric to Non-Parametric, Using Bayesian or Non-Bayesian Approaches
Testing Hypotheses in Nonparametric Models of Production
Data envelopment analysis (DEA) and free disposal hull (FDH) estimators are widely used to estimate efficiency of production. Practitioners use DEA estimators far more frequently than FDH estimators, implicitly assuming that production sets are convex. Moreover, use of the constant returns to scale (CRS) version of the DEA estimator requires an assumption of CRS. Although bootstrap methods have been developed for making inference about the effici…
Predicting recessions with a frontier measure of output gap: An application to Italian economy
Despite the long and great history, developed institutions, and high level of physical and human capital, the Italian economy has been fairly stagnant during the last three decades. In this paper, we merge two streams of literature: nonparametric methods to estimate frontier efficiency of an economy, which allows us to develop a new measure of output gap, and nonparametric methods to estimate probability of an economic recession. To illustrate th…
Proportional incremental cost probability functions and their frontiers
Nonparametric, Stochastic Frontier Models with Multiple Inputs and Outputs
Stochastic frontier models along the lines of Aigner et al. are widely used to benchmark firms’ performances in terms of efficiency. The models are typically fully parametric, with functional form specifications for the frontier as well as both the noise and the inefficiency processes. Studies such as Kumbhakar et al. have attempted to relax some of the restrictions in parametric models, but so far all such approaches are limited to a univariate …
Computer Science (11 works) · Econometrics (11 works) · Mathematics (10 works) · Statistics (10 works) · Efficiency Analysis Using DEA (9 works) · Economics (7 works) · Monetary Policy and Economic Impact (7 works) · Nonparametric statistics (7 works) · Economic Growth and Productivity (6 works) · Estimator (6 works)