scholarly journals SLACK AND NET TECHNICAL EFFICIENCY MEASUREMENT: A BOOTSTRAP APPROACH

2005 ◽  
Vol 04 (03) ◽  
pp. 395-410 ◽  
Author(s):  
J. RICHMOND
Keyword(s):  
Confidence Intervals ◽  
Technical Efficiency ◽  
Small Component ◽  
Empirical Application ◽  
Use Of Resources ◽  
Bootstrap Techniques ◽  
Bootstrap Approach ◽  
Efficiency Estimation ◽  
Downward Bias ◽  
Cautious Interpretation

Statistical properties of DEA methods for efficiency estimation are poorly understood and currently the best way forward must be to use bootstrap techniques. The article seeks to extend bootstrap methods to allow investigation of the properties of estimates of inefficiencies due to the slack in the use of resources as well as technical efficiency. In an empirical application, it is found that inefficiency due to slack is a small component of the overall inefficiency and that the DEA technical efficiency estimates have a small downward bias, with confidence intervals that are wide enough to suggest cautious interpretation.

scholarly journals Analyzing the performance of the Major League Baseball Teams by using the Data Envelopment Analysis

2021 ◽  
pp. 1-13
Author(s):  
Yanzhi Bi
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Major League Baseball ◽  
Scale Effects ◽  
Competitive Environment ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Use Of Resources ◽  
Major League ◽  
Reasonable Use

Abstract Professional teams are commercial and recreational organizations, and team managers always set their goals to be playing well and benefitting more in a highly competitive environment. In order to measure the ability of the professional teams to make reasonable use of resources and create various outputs, this study employs the Data Envelopment Analysis (DEA) model to measure the efficiencies of 30 Major League Baseball (MLB) teams. The results showed that the inefficiencies were due to pure technical inefficiencies rather than scale effects, and the scale efficiency on average is more higher than the other efficiencies, applying the managers in the Major League Baseball Teams have higher ability of controlling the scale change. Keywords: Major League Baseball, Data Envelopment Analysis, Technical efficiency, Pure technical efficiency, Scale efficiency.

Confidence intervals for the ratio of two independent Poisson rates: Parametric bootstrap, modified asymptotic, and approximate-estimate approaches

2019 ◽  
Vol 29 (8) ◽  
pp. 2140-2150
Author(s):  
Mahmood Kharrati-Kopaei ◽  
Raziye Dorosti-Motlagh
Keyword(s):  
Confidence Intervals ◽  
Coverage Probability ◽  
Ad Hoc ◽  
Rare Events ◽  
Average Length ◽  
Parametric Bootstrap ◽  
Asymptotic Results ◽  
Approximate Estimate ◽  
Bootstrap Approach ◽  
Estimate Method

We propose four confidence intervals for the ratio of two independent Poisson rates. We apply a parametric bootstrap approach, two modified asymptotic results, and we propose an ad-hoc approximate-estimate method to construct confidence intervals. We justify the correctness of the proposed methods asymptotically in the case of non-rare events (when the Poisson rates are large). We also compare the proposed confidence intervals with some recommended ones in the case of rare events (when the Poisson rates are small) via an extensive simulation study. The results show that the proposed modified asymptotic and the approximate-estimate confidence intervals perform reasonably well in terms of coverage probability and average length.

Using Bootstrapped Confidence Intervals for Improved Inferences with Seemingly Unrelated Regression Equations

1996 ◽  
Vol 12 (3) ◽  
pp. 569-580 ◽  
Author(s):  
Paul Rilstone ◽  
Michael Veall
Keyword(s):  
Monte Carlo ◽  
Regression Model ◽  
Confidence Intervals ◽  
Seemingly Unrelated Regression ◽  
Regression Coefficients ◽  
Standard Errors ◽  
Regression Equations ◽  
Unrelated Regression ◽  
Seemingly Unrelated Regression Model ◽  
Downward Bias

The usual standard errors for the regression coefficients in a seemingly unrelated regression model have a substantial downward bias. Bootstrapping the standard errors does not seem to improve inferences. In this paper, Monte Carlo evidence is reported which indicates that bootstrapping can result in substantially better inferences when applied to t-ratios rather than to standard errors.

scholarly journals Efficient Bootstrap Estimates for Tail Statistics

2016 ◽  
Author(s):  
Øyvind Breivik ◽  
Ole Johan Aarnes
Keyword(s):  
Confidence Intervals ◽  
Temporal Resolution ◽  
Small Subset ◽  
High Temporal Resolution ◽  
Data Set ◽  
Empirical Distributions ◽  
Bootstrap Techniques ◽  
Entire Sequence ◽  
Bootstrap Estimates ◽  
Return Value

Abstract. Bootstrap resamples can be used to investigate the tail of empirical distributions as well as return value estimates based on the extremal behaviour of the distribution. Specifically, the confidence intervals on return value estimates or bounds on in-sample tail statistics can be estimated using bootstrap techniques. However, bootstrapping from the entire data set is expensive. It is shown here that it suffices to bootstrap from a small subset consisting of the highest entries in the sequence to make estimates that are essentially identical to bootstraps from the entire sequence. Similarly, bootstrap estimates of confidence intervals of threshold return estimates are found to be well approximated by using a subset consisting of the highest entries. This has practical consequences in fields such as meteorology, oceanography and hydrology where return estimates are routinely made from very large gridded model integrations spanning decades at high temporal resolution. In such cases the computational savings are substantial.

scholarly journals A Re-Evaluation of the Swiss Hail Suppression Experiment Using Permutation Techniques Shows Enhancement of Hail Energies When Seeding

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1623
Author(s):  
Armin Auf der Maur ◽  
Urs Germann
Keyword(s):  
Confidence Intervals ◽  
Silver Iodide ◽  
New Method ◽  
Raw Data ◽  
Hail Suppression ◽  
Bootstrap Techniques

Grossversuch IV is a large and well documented experiment on hail suppression by silver iodide seeding. The original 1986 evaluation remained vague, although indicating a tendency to increase hail when seeding. The strategy to deal with distributions of hail energy far from normal was not optimal. The present re-evaluation sticks to the question asked and avoids both misleading transformations and unsatisfactory meteorological predictors. The raw data show an increase by about a factor of 3 for the hail energy when seeding. This is the opposite of what seeding is supposed to do. The probability to obtain such a result by chance is below 1%, calculated by permutation and bootstrap techniques applied on the raw data. Confidence intervals were approximated by bootstrapping as well as by a new method called “correlation imposed permutation” (CIP).

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