A modified two-stage randomized response model for estimating the proportion of stigmatized attribute

The survey related to stigmatized characteristics leads to the non-response problem if it is conducted according to classical (direct) methods, especially, developed for non-sensitive issues; therefore, it needs to be applied appropriate survey methodology to get a reliable response from respondents in incriminating issues. Randomized response model is one of the most recent methods which is attracting the attention of survey practitioners to deal with the problems of non-response because it protects the privacy of individuals in order to acquire the truthful response. The present work proposes a new two-stage randomized response model to get rid of misleading response or non-response due to the stigmatized nature of attribute under the study. The proposed randomized response model results in the unbiased estimator of population proportion possessing the sensitive attribute. The properties of the resultant estimator have been studied and empirical comparisons are performed to show its dominance over existing estimators. Suitable recommendations have been put forward to the survey practitioners.     

Revealing age-specific past and future unrelated costs of pneumococcal infections by flexible generalized estimating equations

We aimed to study the excess health-care expenditures for persons with a known positive isolate of Streptococcus pneumoniae. The data set was compiled by linking the database of the largest Belgian Sickness Fund with data obtained from laboratories reporting pneumococcal isolates. We analyzed the age-specific per-patient cumulative costs over time, using generalized estimating equations (GEEs). The mean structure was described by fractional polynomials. The quasi-likelihood under the independence model criterion was used to compare different correlation structures. We show for all age groups that the health-care costs incurred by diagnosed pneumococcal patients are significantly larger than those incurred by undiagnosed matched persons. This is not only the case at the time of diagnosis but also long before and after the time of diagnosis. These findings can be informative for the current debate on unrelated costs in health economic evaluation, and GEEs could be used to estimate these costs for other diseases. Finally, these results can be used to inform policy on the expected budget impact of preventing pneumococcal infections.     

基于自相关视角的弱平稳过程之间的伪回归分析

随机干扰项之间的未知形式自相关是导致相互独立的弱平稳过程之间伪回归的主要原因.通过理论分析和一系列的蒙特卡罗模拟,揭示了数据过程本身的持久性、样本容量T和随机干扰项自相关之间的内在联系.研究发现随机干扰项往往呈现出与数据过程阶数相同的自相关.进一步研究表明,运用广义差分法和Cochrane- Orcutt迭代法虽然能大大减少伪回归概率,但在有些情况下,即使当样本容量较大时,较高阶的Cochrane- Orcutt迭代法仍然无法避免伪回归的发生.     

Inference on locally ordered breaks in multiple regressions

We consider issues related to inference about locally ordered breaks in a system of equations, as originally proposed by Qu and Perron (2007 Qu, Z., Perron, P. (2007). Estimating and testing structural changes in multivariate regressions. Econometrica 75:459–502.[Crossref], [Web of Science ®] , [Google Scholar]). These apply when break dates in different equations within the system are not separated by a positive fraction of the sample size. This allows constructing joint confidence intervals of all such locally ordered break dates. We extend the results of Qu and Perron (2007 Qu, Z., Perron, P. (2007). Estimating and testing structural changes in multivariate regressions. Econometrica 75:459–502.[Crossref], [Web of Science ®] , [Google Scholar]) in several directions. First, we allow the covariates to be any mix of trends and stationary or integrated regressors. Second, we allow for breaks in the variance-covariance matrix of the errors. Third, we allow for multiple locally ordered breaks, each occurring in a different equation within a subset of equations in the system. Via some simulation experiments, we show first that the limit distributions derived provide good approximations to the finite sample distributions. Second, we show that forming confidence intervals in such a joint fashion allows more precision (tighter intervals) compared to the standard approach of forming confidence intervals using the method of Bai and Perron (1998 Bai, J., Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica 66:47–78.[Crossref], [Web of Science ®] , [Google Scholar]) applied to a single equation. Simulations also indicate that using the locally ordered break confidence intervals yields better coverage rates than using the framework for globally distinct breaks when the break dates are separated by roughly 10% of the total sample size.     

Hybrid tripartite randomized response technique

In this paper, a new randomized response technique has been proposed that combines the unrelated question randomized response technique and tripartite randomized response technique. The relative efficiency of the newly proposed Randomized Response technique over the existing Randomized Response technique was obtained. It was observed that the relative efficiency of the proposed technique over the tripartite RRT increases with increase in π_A and π_U. The applicability of the proposed technique was also shown. However, it has been shown that the proposed technique performs better than the conventional ones.     

扇形探测器光电特性的修正方法

研究了扇形自扫描光电二极管列阵(SSPD)的光电特性,分析了器件的特殊结构和非线性转换特性,提出了一种快速、准确的修正方法。     

Support for state opting out and stateless national identity in the Basque Country

Preferences for state opting out are thought of as being the expression of underpinning conflicts of states national identity, empirical evidence on its underlying behavioural processes is scarce. This paper draws upon evidence form the Basque Country to examine the support for a hypothetical opting out from the Spanish State in the light of a reformulation of [Ackerlof, G.A., Kranton, R.E., 2000. Economics and Identity. Quarterly Journal of Economics, 115, 715–753]. We use representative survey data from the Spanish Institute of Sociological Research for the Basque Country. To adjust our empirical specification to the prevalent hypothesis we employ a recursive seemingly unrelated probit approach. Our results suggest evidence for a simultaneous and endogenous influence of national identity on political preferences for the opting out of the Basque Country from Spain. We find evidence consistent with an instrumental conception of identity as motivating preferences for nation-state opting out, and status quo bias.     

全要素生产率会影响成本函数估计吗

不同于传统的成本函数实证研究,本文关注的是企业间异质的全要素生产率对成本函数估计的影响。为此,本文首次从CES生产函数推导出一个包含全要素生产率的完整的成本函数模型,并以中国大型重化工企业的2003-2007年样本进行回归,同时使用传统模型与SFA模型回归,以进行方法论上的比较分析。结果表明,全要素生产率确实对成本函数估计产生了重要影响,改良前的传统模型可能出现“遗漏变量”问题,使似不相关回归产生内生性问题。三种方法的回归结果表明：非国有企业的规模经济效应是显著的,但国有企业的规模经济检验结果却不稳健——不同方法的测度结果不一致。因此,政府在制定规制、扶持与补贴等政策前,规模经济的测度应该尽量考虑到企业异质性,并使用多种检验方法,以保证政策干预的有效性。     

Seemingly unrelated regression tree

Nonparametric seemingly unrelated regression provides a powerful alternative to parametric seemingly unrelated regression for relaxing the linearity assumption. The existing methods are limited, particularly with sharp changes in the relationship between the predictor variables and the corresponding response variable. We propose a new nonparametric method for seemingly unrelated regression, which adopts a tree-structured regression framework, has satisfiable prediction accuracy and interpretability, no restriction on the inclusion of categorical variables, and is less vulnerable to the curse of dimensionality. Moreover, an important feature is constructing a unified tree-structured model for multivariate data, even though the predictor variables corresponding to the response variable are entirely different. This unified model can offer revelatory insights such as underlying economic meaning. We propose the key factors of tree-structured regression, which are an impurity function detecting complex nonlinear relationships between the predictor variables and the response variable, split rule selection with negligible selection bias, and tree size determination solving underfitting and overfitting problems. We demonstrate our proposed method using simulated data and illustrate it using data from the Korea stock exchange sector indices.     

Contributions to-asymptotic theory in regression models with linear covariance structure 1

Asymptotic results are .presented- for estimating the parameters in variance-components models both with linear and with nonlinear regression functions.