Heteroscedastic Weibull-Normal Mixture Models: A Bayesian Approach

In this article, we propose Bayesian methodology to obtain parameter estimates of the mixture of distributions belonging to the normal and biparametric Weibull families, modeling the mean and the variance parameters. Simulated studies and applications show the performance of the proposed models.     

Digital Age Discoverability: A Collaborative Organizational Approach

Abstract

The tumultuous changes in the scholarly communications ecosystem have disrupted traditional library assumptions and established new workflows and user expectations. In response, the Auraria Library at the University of Colorado Denver initiated a collaborative design (co-design) initiative to re-invent structures, processes, services, and roles throughout the entire organization. Fostered by appreciative inquiry, enabled by social learning, and furthered by shared leadership, redesign initiated sustainable information exchange, reflective dialog, and knowledge creation practices.

The case study highlights accomplishments of technical services staff members who successfully engaged co-workers in selection, implementation, and enhancement of a Web-scale discovery service. Continuing support of the full discovery layer lifecycle illustrates evolving information practices and workplace outcomes at the Auraria Library. Concluding reflections offer transferable insights to other organizations aspiring to co-design workplace environments that enliven creativity, discovery, and exploration.     

Moments of L-Statistics: A Divided Differences Approach

The derivation of the distributions of linear combinations of order statistics or L-statistics and the computation of their moments has been approached in the literature several ways. In this paper we use the properties of divided differences to obtain expressions for moments of some order statistics that arise as special cases of L-statistics. Expectations of some well-known L-statistics such as the trimmed mean and the winsorised mean for the pareto distribution are computed. The study also undertakes the computation of L-moments that are expectations of certain linear combinations of order statistics. The algorithms have been implemented using some well-known continuous distributions as examples.     

Scientific Periodicals in Iran: A Systems Approach

Scientific periodicals fulfill a significant role in the communication, exchange, and sharing of scientific findings. In recent years, the Iranian Ministry of Science, Research, and Technology (MSRT) has concentrated on non-medical, scientific periodicals. The present paper offers a short history of scientific periodicals and their role in Iran. The authors further examine the current status in the Iranian Ministry of Science, Research, and Technology by using a systems approach. Scientific periodicals in Iran involve four external entities and six major subsystems, including resources, format, content, publication, refereeing, and structure. Investigation of the current failings of the periodicals in the MSRT reveals that the main orientation of the system does not facilitate scientific communication, ease of starting new periodicals, and promotion of natural development of these periodicals. The authors suggest ways to improve the status of scholarly periodicals in Iran.     

A Novel Regression Approach: Least Squares Ratio

Regression Analysis (RA) is one of the frequently used tool for forecasting. The Ordinary Least Squares (OLS) Technique is the basic instrument of RA and there are many regression techniques based on OLS. This paper includes a new regression approach, called Least Squares Ratio (LSR), and comparison of OLS and LSR according to mean square errors of estimation of theoretical regression parameters (mse ß) and dependent value (mse y).     

Digital Age Discoverability: A Collaborative Organizational Approach

The tumultuous changes in the scholarly communications ecosystem have disrupted traditional library assumptions and established new workflows and user expectations. In response, the Auraria Library at the University of Colorado Denver initiated a collaborative design (co-design) initiative to re-invent structures, processes, services, and roles throughout the entire organization. Fostered by appreciative inquiry, enabled by social learning, and furthered by shared leadership, redesign initiated sustainable information exchange, reflective dialog, and knowledge creation practices.     

Multivariate Process Capability Indices: A Directional Approach

We propose a unified, universal, natural, and very intuitive way how to obtain new multivariate and tool wear extensions of univariate process capability indices by means of projection pursuit. We also illustrate the methodology in detail of the popular precision and accuracy indices, generalize the latter in a few different ways in the same spirit, add some personal insight, discuss the computational issues involved, and demonstrate the advantages of our approach in a small data example.     

A Nonparametric Test for Autoregressive Conditional Heteroscedasticity: A Markov-Chain Approach

In this article we propose a nonparametric test for autoregressive conditional heteroscedasticity based on finite-state Markov chains. A simple Monte Carlo experiment suggests that in finite samples it performs comparably to the Lagrange multiplier test under conditional normality and is superior for the t, lognormal, and exponential distributions. As an illustration, we apply both tests to Canadian/U.S. forward foreign exchange data.     

基于多变量动态模型的产出缺口估算

 本文运用多变量动态模型系统下的Beveridge-Nelson分解方法和贝叶斯Gibbs抽样估计,估算了1985年1季度至2008年2季度期间中国的产出缺口,并且与传统的单变量估计方法测算的结果在统计属性和对货币政策调节的预测效果方面进行了比较。实证结果表明,不同产出缺口的统计属性存在差别,并且只有基于多变量系统测算的产出缺口对货币政策具有显著预测效果。这说明多变量模型估计出的产出缺口更全面地考虑了经济产出与其他相关变量的互动效应,含有的信息更为丰富,从而对宏观政策调整具有更重要的参考价值。     

Indexing the Federal Tax System: A Cost-of-Living Approach

In this article, we analyze the indexation of federal taxes, using an approach based on cost-of-living measurement. We use our Tax and Price Index methodology and data base to study an indexed system historically, comparing indexation with the Consumer Price Index (CPI) to actual tax policy, a tax system with constant parameters, and an “exact” indexing scheme. We reach three main conclusions: (a) The sequence of tax reductions implemented between 1967 and 1985 have fallen short of mimicking indexation, (b) wealthier households would have benefited relatively more than lower-income households from indexation, and (c) CPI indexation would not have completely eliminated bracket creep.     

工资收入差异的解释：基于分位数回归的经验研究

利用CHNS2006年的数据,通过分位数回归方法从教育回报率、性别和工作部门的差异三个方面对中国工资收入差异进行研究,得出与以往研究不同的结论。结果表明：教育回报率在工资收入分布上的变动趋势是不定的。在工资收入分布的两端,大专以上学历对工资收入差距的影响相对较大。对不同性别间工资收入差异的分解表明劳动力市场上存在明显的性别歧视,而对部门间工资差异的分解表明在整个工资分布区间,这种差异呈倒＂U＂型走势。     

Conditional Asymmetries in Real GNP: A Seminonparametric Approach

Two critical assumptions are often made in empirical research regarding the relationship between economic variables and economic disturbances—linearity and Gaussianity. Together, these two assumptions place strong restrictions on the time series behavior of a model. Most important, these restrictions imply conditional symmetry. Using seminonparametric (SNP) techniques, this article presents evidence that real gross national product growth displays conditional asymmetry. Although these results confirm related results of Brock and Sayers, Sichel, and Hamilton, the SNP approach is novel in that it emphasizes the relationship between common modeling assumptions and the restrictions that these assumptions place on data.     

Inflationary Expectations in Israel: A Multiple Indicators Approach

This article derives unobservable short-term inflationary expectations in Israel from their postulated effects on the velocity of demand deposits and the nominal interest rate. A multiple-indicators model is estimated to assess the impact of inflationary expectations on these variables. The expectations-formation mechanism is estimated using a multiple indicators–multiple causes (MIMIC) model. This methodology allows us to test for the structural stability of the model and estimate the relative variances of the postulated error components. Moreover, this procedure contains a built-in specification test of the chosen expectations-formation mechanism.     

Treatment Effects With Unobserved Heterogeneity: A Set Identification Approach

We propose the sharp identifiable bounds of the potential outcome distributions using panel data. We allow for the possibility that statistical randomization of treatment assignments is not achieved until unobserved heterogeneity is properly controlled for. We use certain stationarity assumptions to obtain the sharp bounds. Our approach allows for dynamic treatment decisions, where the current treatment decisions may depend on the past treatments or the past observed outcomes. As an empirical illustration, we study the effect of smoking during pregnancy on infant birthweight. We find that for the group of switchers the infant birthweight of a smoking mother is first-order stochastically dominated by that of a nonsmoking mother.     

Conditional VAR and Expected Shortfall: A New Functional Approach

We estimate two well-known risk measures, the value-at-risk (VAR) and the expected shortfall, conditionally to a functional variable (i.e., a random variable valued in some semi(pseudo)-metric space). We use nonparametric kernel estimation for constructing estimators of these quantities, under general dependence conditions. Theoretical properties are stated whereas practical aspects are illustrated on simulated data: nonlinear functional and GARCH(1,1) models. Some ideas on bandwidth selection using bootstrap are introduced. Finally, an empirical example is given through data of the S&P 500 time series.     

Demand Systems Estimation With Microdata: A Censored Regression Approach

Demand systems estimation increasingly makes use of household-level microdata, mainly to measure the effects of demographic variables. Data based on these household-expenditure surveys present a major estimation problem. For any given household, many of the goods have zero consumption, implying a censored dependent variable. Techniques which do not take this censored dependent variable into account will yield biased results. We utilize a censored regression approach that is computationally simple, consistent, and asymptotically efficient. The results are then presented and compared with those obtained using an uncensored technique.     

Determinants of Contraceptive Use in Egypt: A Multilevel Approach

The increasing use of family planning methods seems to be the intermediate determinant which mostly influences the fertility decline in developing countries, and in particular in those countries which are in an advanced phase of demographic transition such as Egypt. Moreover large countries, like Egypt, are characterized by very different geographical realities and even by strong regional heterogeneities. The aim of this study is the analysis of the determinants of contraceptive use in Egypt, with particular reference to the differentials due to the socio-economic context and to the area of residence. To estimate each individual and regional factors’ effect on contraceptive use, a logistic two-level random intercept model is fitted to EDHS 2000 data; the use of a multilevel analysis is suggested by the two-level data structure: the first level units are the women, the second level units are their regions of residence.