共查询到20条相似文献,搜索用时 15 毫秒
1.
In productivity analysis an important issue is to detect how external (environmental) factors, exogenous to the production process and not under the control of the producer, might influence the production process and the resulting efficiency of the firms. Most of the traditional approaches proposed in the literature have serious drawbacks. An alternative approach is to describe the production process as being conditioned by a given value of the environmental variables (Cazals, C., Florens, J.P., Simar, L., 2002. Nonparametric Frontier estimation: A robust approach. Journal of Econometrics 106, 1–25; Daraio, C., Simar, L., 2005. Introducing environmental variables in nonparametric Frontier models: A probabilistic approach. Journal of Productivity Analysis 24(1), 93–121). This defines conditional efficiency measures where the production set in the input × output space may depend on the value of the external variables. The statistical properties of nonparametric estimators of these conditional measures are now established (Jeong, S.O., Park, B.U., Simar, L., 2008. Nonparametric conditional efficiency measures: Asymptotic properties. Annals of Operations Research doi: 10.1007/s10479-008-0359-5). These involve the estimation of a nonstandard conditional distribution function which requires the specification of a smoothing parameter (a bandwidth). So far, only the asymptotic optimal order of this bandwidth has been established. This is of little interest for the practitioner. In this paper we fill this gap and we propose a data-driven technique for selecting this parameter in practice. The approach, based on a Least Squares Cross Validation procedure (LSCV), provides an optimal bandwidth that minimizes an appropriate (weighted) integrated Squared Error (ISE). The method is carefully described and exemplified with some simulated data with univariate and multivariate environmental factors. An application on real data (performances of Mutual Funds) illustrates how this new optimal method of bandwidth selection works in practice. 相似文献
2.
《Stochastic Processes and their Applications》2005,115(1):155-177
We consider the estimation of a regression functional where the explanatory variables take values in some abstract function space. The principal aim of the paper is to establish the asymptotic normality of such estimates for dependent functional data. 相似文献
3.
Testing for the independence between two categorical variables R and S forming a contingency table is a well-known problem: the classical chi-square and likelihood ratio tests are used. Suppose now that for each individual a set of p characteristics is also observed. Those explanatory variables, likely to be associated with R and S, can play a major role in their possible association, and it can therefore be interesting to test the independence between R and S conditionally on them. In this paper, we propose two nonparametric tests which generalise the chi-square and the likelihood ratio ideas to this case. The procedure is based on a kernel estimator of the conditional probabilities. The asymptotic law of the proposed test statistics under the conditional independence hypothesis is derived; the finite sample behaviour of the procedure is analysed through some Monte Carlo experiments and the approach is illustrated with a real data example. 相似文献
4.
Jacobo de Uña-Álvarez M. Carmen Iglesias-Pérez 《Annals of the Institute of Statistical Mathematics》2010,62(2):323-341
In this paper we consider the problem of estimating a conditional distribution function in a nonparametric way, when the response
variable is nonnegative, and the observational procedure is length-biased. We propose a proper adaptation of the estimate
to right-censoring provoked by limitation in following-up. Large sample analysis of the introduced estimator is given, including
rates of convergence, limiting distribution, and efficiency results. We show that the length-bias model results in less variance
in estimation, when compared to methods based on observed truncation times. Practical performance of the proposed estimator
is explored through simulations. Application to unemployment data analysis is provided. 相似文献
5.
Toshio Honda 《Annals of the Institute of Statistical Mathematics》2010,62(6):995-1021
We consider nonparametric estimation of conditional medians for time series data. The time series data are generated from two mutually independent linear processes. The linear processes may show long-range dependence. The estimator of the conditional medians is based on minimizing the locally weighted sum of absolute deviations for local linear regression. We present the asymptotic distribution of the estimator. The rate of convergence is independent of regressors in our setting. The result of a simulation study is also given. 相似文献
6.
Fuzzy integrals and conditional fuzzy measures 总被引:1,自引:0,他引:1
Rudolf Kruse 《Fuzzy Sets and Systems》1983,10(1-3):309-313
7.
Hannes Hoffmann Thilo Meyer-Brandis Gregor Svindland 《Mathematics and Financial Economics》2018,12(3):413-444
We consider families of strongly consistent multivariate conditional risk measures. We show that under strong consistency these families admit a decomposition into a conditional aggregation function and a univariate conditional risk measure as introduced Hoffmann et al. (Stoch Process Appl 126(7):2014–2037, 2016). Further, in analogy to the univariate case in Föllmer (Stat Risk Model 31(1):79–103, 2014), we prove that under law-invariance strong consistency implies that multivariate conditional risk measures are necessarily multivariate conditional certainty equivalents. 相似文献
8.
A. Baltrūnas 《Lithuanian Mathematical Journal》1991,31(4):395-400
Institute of Mathematics and Informatics, Lithuanian Academy of Sciences. Published in Litovskii Matematicheskii Sbornik (Lietuvos Matematikos Rinkinys), Vol. 31, No. 4, pp. 577–583, October–December, 1991. 相似文献
9.
The traditional approach to multivariate extreme values has been through the multivariate extreme value distribution G, characterised by its spectral measure H and associated Pickands’ dependence function A. More generally, for all asymptotically dependent variables, H determines the probability of all multivariate extreme events. When the variables are asymptotically dependent and under the assumption of unit Fréchet margins, several methods exist for the estimation of G, H and A which use variables with radial component exceeding some high threshold. For each of these characteristics, we propose new asymptotically consistent nonparametric estimators which arise from Heffernan and Tawn’s approach to multivariate extremes that conditions on variables with marginal values exceeding some high marginal threshold. The proposed estimators improve on existing estimators in three ways. First, under asymptotic dependence, they give self-consistent estimators of G, H and A; existing estimators are not self-consistent. Second, these existing estimators focus on the bivariate case, whereas our estimators extend easily to describe dependence in the multivariate case. Finally, for asymptotically independent cases, our estimators can model the level of asymptotic independence; whereas existing estimators for the spectral measure treat the variables as either being independent, or asymptotically dependent. For asymptotically dependent bivariate random variables, the new estimators are found to compare favourably with existing estimators, particularly for weak dependence. The method is illustrated with an application to finance data. 相似文献
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11.
We consider in this paper the use of Monte Carlo simulation to numerically approximate the asymptotic variance of an estimator
of a population parameter. When the variance of an estimator does not exist in finite samples, the variance of its limiting
distribution is often used for inferences. However, in this case, the numerical approximation of asymptotic variances is less
straightforward, unless their analytical derivation is mathematically tractable. The method proposed does not assume the existence
of variance in finite samples. If finite sample variance does exist, it provides a more efficient approximation than the one
based on the convergence of finite sample variances. Furthermore, the results obtained will be potentially useful in evaluating
and comparing different estimation procedures based on their asymptotic variances for various types of distributions. The
method is also applicable in surveys where the sample size required to achieve a fixed margin of error is based on the asymptotic
variance of the estimator. The proposed method can be routinely applied and alleviates the complex theoretical treatment usually
associated with the analytical derivation of the asymptotic variance of an estimator which is often managed on a case by case
basis. This is particularly appealing in view of the advance of modern computing technology. The proposed numerical approximation
is based on the variances of a certain truncated statistic for two selected sample sizes, using a Richardson extrapolation
type formulation. The variances of the truncated statistic for the two sample sizes are computed based on Monte Carlo simulations,
and the theory for optimizing the computing resources is also given. The accuracy of the proposed method is numerically demonstrated
in a classical errors-in-variables model where analytical results are available for the purpose of comparisons. 相似文献
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13.
《European Journal of Operational Research》2001,132(2):326-342
We propose to relax the standard convexity property used in Data Envelopment Analysis (DEA) by imposing additional qualifications for feasibility of convex combinations. We specifically focus on a condition that preserves the Koopmans efficiency classification. This yields an efficiency classification preserving conditional convexity property, which is implied by both monotonicity and convexity, but not conversely. Substituting convexity by conditional convexity, we construct various empirical DEA approximations as the minimal sets that contain all DMUs and are consistent with the imposed production assumptions. Imposing an additional disjunctive constraint to standard convex DEA formulations can enforce conditional convexity. Computation of efficiency measures relative to conditionally convex production set can be performed through Disjunctive Programming (DP). 相似文献
14.
Nondiscretionary environmental inputs are critical in explaining relative efficiency differences and productivity changes in public sector applications. For example, the literature on education production shows that school districts perform better when student poverty is lower. In this paper, we extend the nonparametric approach to decompose the Malmquist Productivity Index suggested by Färe et al. (American Economic Rewiew 84:66–83, 1994) into efficiency, technological and environmental changes. The approach is applied to analyze educational production of Ohio school districts. Applying the extended approach in an analysis of the educational production of 604 school districts in Ohio, we find changes in environmental harshness are the primary drivers in productivity changes of underperforming school districts, while technical progress drives the performance of top performing school districts. 相似文献
15.
We consider the Barndorff-Nielsen and Cox (1994, p. 319) method of modifying an estimative prediction interval to obtain an improved prediction interval with better conditional coverage properties. The parameter estimator, on which this improved interval is based, is assumed to have the same asymptotic distribution as the conditional maximum likelihood estimator. This improved interval depends strongly on the asymptotic conditional bias of this estimator, which can be very sensitive to small changes in this estimator. We show, however, that the asymptotic efficiency of this improved prediction interval does not depend on this bias. 相似文献
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I. I. Malofeev 《Doklady Mathematics》2016,94(2):493-497
We obtain broad sufficient conditions for the existence of proper conditional probabilities measurably depending on a parameter in the case of parametric families of measures and mappings. 相似文献
19.
《Bulletin des Sciences Mathématiques》2001,125(6-7):583-604
Based on quasi-invariance properties of the Gaussian process and the gamma process, we give certain formal expressions of their laws on infinite-dimensional spaces. They are also consistent with some identities of conditional probabilities which are shown to be equivalent to the quasi-invariance properties. 相似文献