基于遗传算法的扩展Nelson-Siegel模型及实证研究

将遗传算法引入扩展Nelson-Siegel模型估计中,并将其用于国债收益率曲线的估计。实证分析表明,基于遗传算法的扩展Nelson-Siegel模型在收益率曲线拟合和估计方面明显优于基于三次样条插值的息票剥离法及基于非线性回归的扩展Nelson-Siegel模型。基于此,利用基于遗传算法的扩展Nelson-Siegel模型对所选取的三个样本交易日的收益率曲线进行估计和分析,发现金融危机中后期的收益率曲线较金融危机初期的收益率曲线有了显著变化,主要表现在收益率曲线整体水平下降,但不同部分下降的幅度不同,并且收益率曲线的斜率和曲度均明显增大。以上变化主要是金融危机背景下货币政策调整以及市场信心变化共同作用的结果。     

一种收入分布函数序列的拟合方法及扩展应用

针对收入分布函数形式选择问题,提出具有＂自适应＂能力的收入分布序列拟合思路,给出基于B-样条的收入分布函数形式,并对收入分布参数进行最小二乘估计。拟合了中国历年城镇居民收入分布序列;导出中国1996-2009年洛伦兹曲线和基尼系数;从函数角度刻画了城镇居民收入水平不断提高的同时,收入差距扩大的动态趋势;验证了城镇居民收入差距的变动轨迹体现着＂阶梯形＂扩大的特征。     

互联网消费者行为的无差异曲线研究

互联网的高速发展,带来了消费者行为的变化。文章通过对研究现状的分析,对相关学术观点展开述评。从微观经济学关于无差异曲线的假定前提出发,具体分析边际替代率递减与边际效用递减的关系、特殊的互联网消费者无差异曲线等,探讨互联网消费者行为与微观经济学理论的吻合程度。     

Application of trajectories from growth curve in identification of longitudinal biomarker for the multivariate survival data

In clinical studies, the researchers measure the patients' response longitudinally. In recent studies, Mixed models are used to determine effects in the individual level. In the other hand, Henderson et al. [3,4] developed a joint likelihood function which combines likelihood functions of longitudinal biomarkers and survival times. They put random effects in the longitudinal component to determine if a longitudinal biomarker is associated with time to an event. In this paper, we deal with a longitudinal biomarker as a growth curve and extend Henderson's method to determine if a longitudinal biomarker is associated with time to an event for the multivariate survival data.     

Testing sphericity and intraclass covariance structures under a growth curve model in high dimension

In this article, we consider the problem of testing (a) sphericity and (b) intraclass covariance structure under a growth curve model. The maximum likelihood estimator (MLE) for the mean in a growth curve model is a weighted estimator with the inverse of the sample covariance matrix which is unstable for large p close to N and singular for p larger than N. The MLE for the covariance matrix is based on the MLE for the mean, which can be very poor for p close to N. For both structures (a) and (b), we modify the MLE for the mean to an unweighted estimator and based on this estimator we propose a new estimator for the covariance matrix. This new estimator leads to new tests for (a) and (b). We also propose two other tests for each structure, which are just based on the sample covariance matrix.

To compare the performance of all four tests we compute for each structure (a) and (b) the attained significance level and the empirical power. We show that one of the tests based on the sample covariance matrix is better than the likelihood ratio test based on the MLE.     

Am I a leader? Examining leader identity development over time

The extent to which someone thinks of him- or herself as a leader (i.e., leader identity) is subject to change in a dynamic manner because of experience and structured intervention, but is rarely studied as such. In this study, we map the trajectories of leader identity development over a course of a seven-week leader development program. Drawing upon identity theory (Kegan, 1983) and self-perception theory (Bem, 1972), we propose that changes in self-perceived leadership skills are associated with changes in leader identity. Using latent growth curve modeling and latent change score analyses as our primary analytical approaches, we analyzed longitudinal data across seven measurement points (N = 98). We find leader identity to develop in a J-shaped pattern. As hypothesized, we find that these changes in leader identity are associated with, and potentially shaped by, changes in leadership skills across time.     

Optimal exact design of double acceptance sampling plans by attributes

The design of double acceptance sampling (AS) plans for attributes based on the operating characteristic curve paradigm is usually addressed by enumeration algorithms. These AS plans may be non optimal regarding the sample size to inspect as they were obtained without the requirement that the constraints at the OC curve controlled points are not violated for minimum Average Sample Number (ASN) scenarios. An approach based on mathematical programming is proposed to systematically design double AS plans for attributes, where the characteristics controlled are modelled by binomial or Poisson distributions. Specifically, Mixed Integer Nonlinear Programming (MINLP) formulations are developed and combined with an enumeration algorithm that allows finding ASN minimax optimal plans. A theoretical result is developed with the purpose of assuring the global optimum design is reached by iteration where a convenient solver is used to find local optima. To validate the algorithm, we compare our results with those of tables commonly used for practical purposes, consider different rates of risk, and setups commonly used in Lot Quality Assurance Plans (LQAS) for health monitoring programmes. Finally, we compare AS plans determined for processes described by binomial and Poisson distributions.     

Estimating Engel curves: a new way to improve the SILC-HBS matching process using GLM methods

Microdata are required to evaluate the distributive impact of the taxation system as a whole (direct and indirect taxes) on individuals or households. However, in European Union countries this information is usually distributed into two separate surveys: the Household Budget Surveys (HBS), including total household expenditure and its composition, and EU Statistics on Income and Living Conditions (EU-SILC), including detailed information about households'' income and direct (but not indirect) taxes paid. We present a parametric statistical matching procedure to merge both surveys. For the first stage of matching, we propose estimating total household expenditure in HBS (Engel curves) using a GLM estimator, instead of the traditionally used OLS method. It is a better alternative, insofar as it can deal with the heteroskedasticity problem of the OLS estimates, while making it unnecessary to retransform the regressors estimated in logarithms. To evaluate these advantages of the GLM estimator, we conducted a computational Monte Carlo simulation. In addition, when an error term is added to the deterministic imputation of expenditure in the EU-SILC, we propose replacing the usual Normal distribution of the error with a Chi-square type, which allows a better approximation to the original expenditures variance in the HBS. An empirical analysis is provided using Spanish surveys for years 2012–2016. In addition, we extend the empirical analysis to the rest of the European Union countries, using the surveys provided by Eurostat (EU-SILC, 2011; HBS, 2010).     

Local linear fitting and improved estimation near peaks

The authors look into the problem of estimating regression functions that exhibit jump irregularities in the first derivative. They investigate the behaviour of the bias in the local linear fit and show the superior performance of appropriate one‐sided versions of the local linear fit near such irregularities. They then propose an improved estimation procedure based on data‐driven selection of a conventional or one‐sided local linear fit according to a residual sum of squares type of criterion. The authors provide theoretical results and illustrate the method both on simulated and real‐life data examples. The Canadian Journal of Statistics 37: 453–475; 2009 © 2009 Statistical Society of Canada     

Changing your role models: Social learning and the Engel curve

By relating Engel curves and social learning, we explain the existence of differently shaped Engel curves—an interesting phenomenon in the theory of demand. A formal approach to cultural learning within a population of consumers accounts for some cognitive foundations of these demand patterns. We find that a changing influence of an individual's role models due to her increasing income, which entails new reference groups providing social identity, leads to the diffusion of new consumption behaviors. Thereby, the resulting Engel curves’ shape depends on the underlying learning dynamics. The approach contributes to an explanation of structural change and economic development.