Topic
Variable (computer science)
About: Variable (computer science) is a research topic. Over the lifetime, 7479 publications have been published within this topic receiving 160725 citations. The topic is also known as: assignable & mutable variable.
Papers published on a yearly basis
1 / 3
Papers
TL;DR: The CCR ratio form introduced by Charnes, Cooper and Rhodes, as part of their Data Envelopment Analysis approach, comprehends both technical and scale inefficiencies via the optimal value of the ratio form, as obtained directly from the data without requiring a priori specification of weights and/or explicit delineation of assumed functional forms of relations between inputs and outputs as mentioned in this paper.
Abstract: In management contexts, mathematical programming is usually used to evaluate a collection of possible alternative courses of action en route to selecting one which is best. In this capacity, mathematical programming serves as a planning aid to management. Data Envelopment Analysis reverses this role and employs mathematical programming to obtain ex post facto evaluations of the relative efficiency of management accomplishments, however they may have been planned or executed. Mathematical programming is thereby extended for use as a tool for control and evaluation of past accomplishments as well as a tool to aid in planning future activities. The CCR ratio form introduced by Charnes, Cooper and Rhodes, as part of their Data Envelopment Analysis approach, comprehends both technical and scale inefficiencies via the optimal value of the ratio form, as obtained directly from the data without requiring a priori specification of weights and/or explicit delineation of assumed functional forms of relations between inputs and outputs. A separation into technical and scale efficiencies is accomplished by the methods developed in this paper without altering the latter conditions for use of DEA directly on observational data. Technical inefficiencies are identified with failures to achieve best possible output levels and/or usage of excessive amounts of inputs. Methods for identifying and correcting the magnitudes of these inefficiencies, as supplied in prior work, are illustrated. In the present paper, a new separate variable is introduced which makes it possible to determine whether operations were conducted in regions of increasing, constant or decreasing returns to scale in multiple input and multiple output situations. The results are discussed and related not only to classical single output economics but also to more modern versions of economics which are identified with "contestable market theories."
17,387 citations
TL;DR: In this paper, variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available, such as t...
Abstract: Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available. These areas include t...
7,076 citations
TL;DR: The authors tried to answer the question: When is a random variable Y "more variable" than another random variable X "less variable" by asking when a variable X is more variable than another variable Y.
4,223 citations
TL;DR: In this paper, the authors develop attractive functional forms and simple quasi-likelihood estimation methods for regression models with a fractional dependent variable, and apply these methods to a data set of employee participation rates in 401 (k) pension plans.
Abstract: SUMMARY We develop attractive functional forms and simple quasi-likelihood estimation methods for regression models with a fractional dependent variable. Compared with log-odds type procedures, there is no difficulty in recovering the regression function for the fractional variable, and there is no need to use ad hoc transformations to handle data at the extreme values of zero and one. We also offer some new, robust specification tests by nesting the logit or probit function in a more general functional form. We apply these methods to a data set of employee participation rates in 401 (k) pension plans. I. INTRODUCTION Fractional response variables arise naturally in many economic settings. The fraction of total weekly hours spent working, the proportion of income spent on charitable contributions, and participation rates in voluntary pension plans are just a few examples of economic variables bounded between zero and one. The bounded nature of such variables and the possibility of observing values at the boundaries raise interesting functional form and inference issues. In this paper we specify and analyse a class of functional forms with satisfying econometric properties. We also synthesize and expand on the generalized linear models (GLM) literature from statistics and the quasi-likelihood literature from econometrics to obtain robust methods for estimation and inference with fractional response variables. We apply the methods to estimate a model of employee participation rates in 401 (k) pension plans. The key explanatory variable of interest is the plan's 'match rate,' the rate at which a firm matches a dollar of employee contributions. The empirical work extends that of Papke (1995), who studied this problem using linear spline methods. Spline methods are fiexible, but they do not ensure that predicted values lie in the unit interval. To illustrate the methodological issues that arise with fractional dependent variables, suppose that a variable y, O^y^l, is to be explained by a 1 x/^ vector of explanatory variables \ = {Xi,X2 XK), with the convention that Xi = l. The population model
3,689 citations
Posted Content•
TL;DR: In this paper, simple quasi-likelihood methods for estimating regression models with a fractional dependent variable and for performing asymptotically valid inference are proposed, and they apply these methods to a data set of employee participation rates in 401(k) pension plans.
Abstract: We offer simple quasi-likelihood methods for estimating regression models with a fractional dependent variable and for performing asymptotically valid inference. Compared with log-odds type procedures, there is no difficulty in recovering the regression function for the fractional variable, and there is no need to use ad hoc transformations to handle data at the extreme values of zero and one. We also offer some new, simple specification tests by nesting the logit or probit function in a more general functional form. We apply these methods to a data set of employee participation rates in 401(k) pension plans.
3,562 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2022 | 3 |
| 2021 | 314 |
| 2020 | 354 |
| 2019 | 384 |
| 2018 | 355 |
| 2017 | 377 |