Tests for the Second Order Stochastic Dominance Based on L -Statistics
Bibliographic Data
| ID | 19418282 |
|---|---|
| Authors | José R Berrendero (0000-0003-0728-7748, Universidad Autónoma de Madrid), Javier Cárcamo (0000-0002-3978-4266, Universidad Autónoma de Madrid) |
| Year | 2011 |
| Volume | 29 |
| Issue | 2 |
| Pages | 260-270 |
| Publication date | 2011-04-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1198/jbes.2010.07224 |
| OpenAlex | W1963926235 |
| Language | EN |
| Citations received | 2 |
| References cited | 16 |
We use some characterizations of convex and concave-type orders to define discrepancy measures useful in two testing problems involving stochastic dominance assumptions. The results are connected with the mean value of the order statistics and have a clear economic interpretation in terms of the expected cumulative resources of the poorest (or richest) in random samples. Our approach mainly consists of comparing the estimated means in ordered samples of the involved populations. The test statistics we derive are functions of L-statistics and are generated through estimators of the mean order statistics. We illustrate some properties of the procedures with simulation studies and an empirical example
Econometrics · Estimator · Order statistic · Statistics · Stochastic dominance · Stochastic ordering · Summary statistics · Advanced Statistical Methods and Models · Income, Poverty, and Inequality · Mathematics · Statistical Methods and Inference
Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models
Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality
Consistent Tests for Stochastic Dominance
On the measurement of inequality
Nonparametric Tests of Stochastic Dominance in Income Distributions
Ranking Income Distributions
| Citations per year | 0.67 |
|---|---|
| Citation span | 2023 - 2025 (3) |
| Highly cited | No |