Estimation under length-bias and right-censoring: an application to unemployment duration analysis for married women

In this work we analyse unemployment duration for married women in Spain, using the Labour Force Survey (LFS) of the Spanish Institute for Statistics, 1987-1997. Consistent non-parametric estimation of the unemployment survival function is provided. Since the available data are length- biased, a suitable correction of the Kaplan-Meier product-limit estimator is motivated and used for the referred analysis. The accuracy of parametric models is checked by means of goodness-of-fit plots--a graphical tool that requires preliminary estimation of the survival. Structural features of the associated hazard (as monotonicity and unimodality) are explored.     

The demographic situation in Poland in 1987

Demographic trends in Poland in 1987 are reviewed using data from official sources. The author notes that the population growth rate for 1987 was 0.5 percent, compared to 0.8 percent for the 1980s as a whole.     

Bias corrected MLEs under progressive type-II censoring scheme

ABSTRACT

Censoring frequently occurs in survival analysis but naturally observed lifetimes are not of a large size. Thus, inferences based on the popular maximum likelihood (ML) estimation which often give biased estimates should be corrected in the sense of bias. Here, we investigate the biases of ML estimates under the progressive type-II censoring scheme (pIIcs). We use a method proposed in Efron and Johnstone [Fisher's information in terms of the hazard rate. Technical Report No. 264, January 1987, Stanford University, Stanford, California; 1987] to derive general expressions for bias corrected ML estimates under the pIIcs. This requires derivation of the Fisher information matrix under the pIIcs. As an application, exact expressions are given for bias corrected ML estimates of the Weibull distribution under the pIIcs. The performance of the bias corrected ML estimates and ML estimates are compared by simulations and a real data application.     

Zur Weitergabe von ?lteren amtlichen Mikrodaten an die Wissenschaft

Zusammenfassung: Der Beitrag diskutiert dieMöglichkeit derWeitergabe von amtlichen Mikrodaten, die vor 1987 erhoben wurden, an die Wissenschaft in Form von sogenannten Scientific–use–files auf der Grundlage des Bundesstatistikgesetzes von 1987.

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Summary: The paper discusses possibilities to release official microdata, collected before 1987, to social scientists as scientific–use–files based on the Federal Act on Statistics of 1987.

     

The population of the USSR

Official population data for the USSR for 1986 and 1987 are presented. Tables are included on age and sex distribution; rural and urban population; birth, death, and natural increase rates, 1970-1986; fertility and mortality by sex, 1970-1986; birth order; age-specific birth rates by rural and urban area and Union republic; age-specific death rates, 1970-1986; infant mortality, 1970-1986; life expectancy, 1926-1986; life tables; marriage and age at marriage; and divorce.     

基于贝叶斯SDM模型的中国城镇居民收入收敛性分析

随着中国经济的高速增长,中国区域间贫富差距也日渐加大,在此背景下对中国城镇居民收入是否收敛进行检验并探究其影响原因十分必要。基于一个包括物质资本和人力资本投入的新古典增长模型,根据中国31个省市的1987—2013年数据,利用SDM模型和贝叶斯MCMC统计分析方法,研究城镇居民收入的收敛性问题,结果发现:中国城镇居民人均收入具有显著的空间差异,且在1987—2008年为发散、在2008—2013年以及1987—2013年为存在β收敛的变化趋势;物质资本对中国城镇居民收入增长的β收敛具有正向促进作用,而人力资本对其具有反向促进作用,增加物质资本投入有利于缩小地区收入差距,二者的不匹配可能是导致中国收入增长差距的原因。     

Varying Dispersion Diagnostics for Inverse Gaussian Regression Models

Homogeneity of dispersion parameters is a standard assumption in inverse Gaussian regression analysis. However, this assumption is not necessarily appropriate. This paper is devoted to the test for varying dispersion in general inverse Gaussian linear regression models. Based on the modified profile likelihood (Cox & Reid, 1987), the adjusted score test for varying dispersion is developed and illustrated with Consumer- Product Sales data (Whitmore, 1986) and Gas vapour data (Weisberg, 1985). The effectiveness of orthogonality transformation and the properties of a score statistic and its adjustment are investigated through Monte Carlo simulations.     

美国九大客源市场旅游本底趋势线及危机评估

美国是当今世界出入境旅游大国,1987年以来突发事件频繁发生,对美国入境旅游的发展产生了重大影响。依据1987—2007年统计数据,建立了4大洲9个国家入境旅游本底趋势线,定量分析突发事件对各客源市场入境美国客流量的影响。结果发现：1998年亚洲金融危机和2001年“9．11”恐怖袭击事件是美国入境旅游发展的一个拐点,西欧、东亚主要客源市场入境客流量出现停滞或绝对衰退的趋势。另外,以所建的9条本底趋势线为参照系,定量测定了多个危机事件对9个国家入境美国客流量的影响,为突发事件旅游危机后评价研究提供了新的事实。     

A stopping rule for structure-preserving variable selection

A stopping rule is provided for the backward elimination process suggested by Krzanowski (1987a) for selecting variables to preserve data structure. The stopping rule is based on perturbation theory for Procrustes statistics, and a small simulation study verifies its suitability. Some illustrative examples are also provided and discussed.     

Women in the USSR

This is a selection of statistical data on women in the USSR; it covers the period 1970-1989. Tabular data are provided on the number of women by Union republic; the number of women and men by age group and rural or urban area; women's educational levels, sources of income, and occupations; family size for the whole country and for rural and urban areas; women's marital status by age; marriages and divorces; divorce by women's education, age, and number of children; birth rate by Union republic and by nationality; abortion and childbirth for selected years and by Union republic; maternal deaths by Union republic; infant deaths; and female life expectancy.     

Women in the nation

A selection of statistical data on women in the former Soviet Union is presented for the years 1979, 1989, 1990, and 1991. The data concern number of women by republic and by age group; marriage, divorce, and birth rates; number of household members and singles; infant mortality; abortion and natality; life expectancy; single mothers; education; and employment.     

Comment

Using postwar annual data through 1987 from 46 countries, we confirm our earlier finding that the maximum impact (χ) of monetary shocks on real output is negatively correlated across countries with the variance of such shocks (σ ) [the Lucas proposition (LP)]. This holds whether the time series specification for each country is the one we reported in Kormendi and Meguire (1984) (KM), one selected by a Bayesian pretest (BPT) suggested by Poirier's results, or a uniform specification that nests both. Using the LP to restrict the coefficients of monetary shocks in the real output equation significantly improves forecasts of real output growth over the period 1978–1987. Over the same period, predictions of money and real output growth made from the BPT specifications often do not outperform comparable predictions made from the KM specifications.     

On the experience of projecting the family composition of the population of the USSR

The joint efforts in the USSR by the Central Planning Commission and the State Statistical Commission to develop projections of family characteristics of the Soviet population are described. The projections, based on official data for the rural and urban populations in 1987, are for the years 1991, 1996, 2001, and 2006.     

Bootstrap adjustments for empirical bayes interval estimates of small-area proportions

Empirical Bayes approaches have often been applied to the problem of estimating small-area parameters. As a compromise between synthetic and direct survey estimators, an estimator based on an empirical Bayes procedure is not subject to the large bias that is sometimes associated with a synthetic estimator, nor is it as variable as a direct survey estimator. Although the point estimates perform very well, naïve empirical Bayes confidence intervals tend to be too short to attain the desired coverage probability, since they fail to incorporate the uncertainty which results from having to estimate the prior distribution. Several alternative methodologies for interval estimation which correct for the deficiencies associated with the naïve approach have been suggested. Laird and Louis (1987) proposed three types of bootstrap for correcting naïve empirical Bayes confidence intervals. Calling the methodology of Laird and Louis (1987) an unconditional bias-corrected naïve approach, Carlin and Gelfand (1991) suggested a modification to the Type III parametric bootstrap which corrects for bias in the naïve intervals by conditioning on the data. Here we empirically evaluate the Type II and Type III bootstrap proposed by Laird and Louis, as well as the modification suggested by Carlin and Gelfand (1991), with the objective of examining coverage properties of empirical Bayes confidence intervals for small-area proportions.     

Optimum group limits for estimation in scaled log-logistic distribution from a grouped data

The well known logistic distribution is considered. A transformation of the logistic variate in terms of exponential function results in a new distribution called log-logistic distribution suggested by Balakrishnanet al (1987). Estimation of its scale parameter from a grouped data is presented. Optimal group limits in the case of equispaced as well as unequispaced groupings so as to have a maximum asymptotic relative efficiency are worked out. The grouping correction in the case of equispaced grouped data with a mid point type estimator is also suggested. The results are expalined by an example.     

Testing non-nested log-linear models with pseudo estimator

As the number of random variables for the categorical data increases, the possible number of log-linear models which can be fitted to the data increases rapidly, so that various model selection methods are developed. However, we often found that some models chosen by different selection criteria do not coincide. In this paper, we propose a comparison method to test the final models which are non-nested. The statistic of Cox (1961, 1962) is applied to log-linear models for testing non-nested models, and the Kullback-Leibler measure of closeness (Pesaran 1987) is explored. In log-linear models, pseudo estimators for the expectation and the variance of Cox's statistic are not only derived but also shown to be consistent estimators.     

A Stochastic Volatility Model With Markov Switching

This article presents a new way of modeling time-varying volatility. We generalize the usual stochastic volatility models to encompass regime-switching properties. The unobserved state variables are governed by a first-order Markov process. Bayesian estimators are constructed by Gibbs sampling. High-, medium- and low-volatility states are identified for the Standard and Poor's 500 weekly return data. Persistence in volatility is explained by the persistence in the low- and the medium-volatility states. The high-volatility regime is able to capture the 1987 crash and overlap considerably with four U.S. economic recession periods.     

Bayesian inference for Birnbaum–Saunders distribution and its generalization

We present a Bayesian approach for parameter inference of the Birnbaum–Saunders distribution [Birnbaum ZW, Saunders SC. A new family of life distributions. J Appl Probab. 1969;6:319–327], as well as the generalized Birnbaum–Saunders distribution developed by Owen [A new three-parameter extension to the Birnbaum–Saunders distribution. IEEE Trans Reliab. 2006;55:475–479], in the presence of random right-censored data. To handle the instance of commonly occurred censored observations, we utilize the data augmentation technique [Tanner MA, Wong WH. The calculation of posterior distributions by data augmentation. J Amer Statist Assoc. 1987;82(398):528–540] to circumvent the arduous expressions involving the censored data in posterior inferences. Simulation studies are carried out to assess performance of these methods under different parameter values, with small and large sample sizes, as well as various degrees of censoring. Two real data are analysed for illustrative purpose.     

Multivariate Dispersion Models Generated From Gaussian Copula

In this paper a class of multivariate dispersion models generated from the multivariate Gaussian copula is presented. Being a multivariate extension of Jørgensen's (1987a) dispersion models, this class of multivariate models is parametrized by marginal position, dispersion and dependence parameters, producing a large variety of multivariate discrete and continuous models including the multivariate normal as a special case. Properties of the multivariate distributions are investigated, some of which are similar to those of the multivariate normal distribution, which makes these models potentially useful for the analysis of correlated non-normal data in a way analogous to that of multivariate normal data. As an example, we illustrate an application of the models to the regression analysis of longitudinal data, and establish an asymptotic relationship between the likelihood equation and the generalized estimating equation of Liang & Zeger (1986).