Full Likelihood Inference in Normal-Gamma Stochastic Frontier Models

The paper takes up inference in the stochastic frontier model with gamma distributed inefficiency terms, without restricting the gamma distribution to known integer values of its shape parameter (the Erlang form). The paper shows that Gibbs sampling with data augmentation can be used in a computationally efficient way to explore the posterior distribution of the model and conduct inference regarding parameters as well as functions of interest related to technical inefficiency.     

社会经济调查中整群抽样的应用及误差处理方法

本文从技术上探讨了整群抽样在社会经济调查中的适应性及其基本运用,重点分析了整群抽样在实施过程中的误差问题,指出并分析了总体的变异效应、群体效应、单位比率变异度的效应、群体规模效应和偏差效应等五种因素对整群抽样的误差的影响方式和特点,并分析了各种情况下的具体处理方法。     

Stochastic model specification search for Gaussian and partial non-Gaussian state space models

Model specification for state space models is a difficult task as one has to decide which components to include in the model and to specify whether these components are fixed or time-varying. To this aim a new model space MCMC method is developed in this paper. It is based on extending the Bayesian variable selection approach which is usually applied to variable selection in regression models to state space models. For non-Gaussian state space models stochastic model search MCMC makes use of auxiliary mixture sampling. We focus on structural time series models including seasonal components, trend or intervention. The method is applied to various well-known time series.     

INVARIANCE OF THE UNORDERED BEST ESTIMATOR IN THE T,–CLASS FOR MIDZUNO'S AND FOR IKEDA–SEN'S SAMPLING PROCEDURES

MIDZUNO'S sampling procedure is considered where the first (n – 1) draws are carried out with simple random sampling without replacement and the nth draw with varying probabilities. It is shown that for this scheme, the best estimator in the HORVITZ–THOMPSON (1952) T_t–class of linear estimators exists and rejects the last draw. When MURTHY'S technique of unordering of an ordered estimator is employed, the rejected draw is restored and the unordered estimator is obtained. Surprisingly, this unordered estimator is the same as the unordered best estimator in the T₁–class, derived for IKEDA–SEN'S sampling procedure.     

Identification and estimation with contaminated data: When do covariate data sharpen inference?

Contaminated or corrupted data typically require strong assumptions to identify parameters of interest. However, weaker assumptions often identify bounds on these parameters. This paper addresses when covariate data—variables in addition to the one of interest—tighten these bounds. First, we construct the identification region for the distribution of the variable of interest. This region demonstrates that covariate data are useless without knowledge about the distribution of erroneous data conditional on the covariates. Then, we develop bounds both on probabilities and on parameters of this distribution that respect stochastic dominance.     

The Limit Distribution of the Bootstrap for the Unit Root Test Statistic when the Residuals are Dependent

In this article, the unit root test for the AR(1) model with dependent residuals is considered. We adopt a bootstrap procedure to bootstrap the residuals with bootstrap sample size m less than the size n of the original sample. Under the assumptions that m → ∞ and m/n → 0, the convergence in probability of the bootstrap distribution function is established. Research supported by National Natural Science Foundation of China (No. 10471126)     

Technical,quality and environmental efficiency of the olive oil industry

This paper studies the level of technical efficiency in the olive oil industry from a multi-output perspective, and examines olive oil production in quantitative and qualitative terms. The study also covers the environmental impact of the production process. These are key issues due to the current environmental, organoleptic and food traceability requirements of the EU Common Agricultural Policy (CAP). Furthermore, product differentiation is sought after in today’s ever more demanding markets. The production of olive oil in Andalusia (Spain) is the most important agricultural food industry in the whole region and it represents 30% of world olive oil production. Three data sources have been used: a comprehensive survey to a sample of olive oil producers, their financial reports, and the opinion of a group of experts in olive oil production techniques interviewed by means of the Delphi survey. With this data and after the construction of indicators, a production frontier is elaborated by applying an extension of the Data Envelopment Analysis (DEA) technique. This will allow for the measuring of the relative technical efficiency indices and set specific efficiency indices for both the quality of the oil produced and the environmental impact of the production process. Those factors impacting on efficiency are determined by a truncated regression model with bootstrap. The results show a medium–high level of relative technical efficiency and highlight the importance of efficiency factors involving production and marketing associations.     

连续批计数抽样检验中的跳批抽样技术

文章介绍了跳批抽样的基本原理、适用范围、条件以及一般程序。文章主要对GB／T2828．3《计数抽样检验程序第3部分跳批抽样程序》技术内容进行了解读和介绍,帮助实际应用者正确运用跳批抽样程序,以达到预期目的。     

负荷管理系统交流采样扩展箱功能原理及应用

对当前供电企业面临的窃电问题进行了分析,介绍了辽阳电力负荷管理系统交流采样的功能原理,通过无线电负荷管理系统功能扩展工程实践,在用户终端和主站端增加技术防窃电功能,并可在主站端监视到窃电行为发生后,电能计量曲线的变化情况,具有一定的先进性、经济性和实用性。     

Comparing risk attitudes of organic and non-organic farmers with a Bayesian random coefficient model

Organic farming is usually considered to be more risky thanconventional farming, but the risk aversion of organic farmerscompared with that of conventional farmers has not been studied.Using a non-structural approach to risk estimation, a Bayesianrandom coefficient model is used to obtain individual Arrow–Prattcoefficients of absolute risk aversion for a sample of Dutchorganic and non-organic arable farmers. The model is estimatedusing Gibbs sampling. The results indicate that organic farmersare significantly less risk averse than their non-organic colleagues.