China’s GDP: Examining provincial disparities (1952–1998)

Accompanying rapid economic growth in China, there have been provincial disparities. This article presents and analyzes the evolution of Chinas provincial GDP per capita disparity between 1952 and 1998. First, an examination of some basic indicators of disparity is carried out, and a test for unconditional convergence is performed to explore the dispersion features. Then, a more comprehensive regression analysis, allowing insights into the evidence of conditional convergence and highlighting the main determinants of growth in two main periods of the recent history of China (i.e., prereform and postreform) is presented. Finally, a discussion and conclusion are provided.     

论我国酌定不起诉权行使的条件

从立法机关对检察机关的酌定不起诉权的态度和《刑法》的相关规定分析,"犯罪情节轻微"是我国检察机关行使酌定不起诉权的前提条件,而将"犯罪情节"理解为量刑情节则有助于充分实现酌定不起诉权的积极功能。     

实践性·具体性·系统性--全面贯彻"三个代表"重要思想的方法论原则探论

要使"三个代表"重要思想真正成为全党在实际工作中长期坚持的指导思想,就必须正确解决实现"三个代表"重要思想的科学方法论问题,切实按照马克思主义的实践性、具体性、系统性原则的要求,在贯彻"三个代表"重要思想过程中,始终做到"务实"与"务虚"、"共性"与"个性"、"部分"与"整体"的有机统一.     

Asymptotic risk comparisions of restricted and unrestricted maximum likelihood estimators

Conditions for choosing between restricted and unrestrieted maximum likelihood estimators based on various asymptotic risk oriteria are derived. These conditions involve the non-centrality parameters of classical and specification test statistics, and are generlizations of well known results for the linear regression model.     

Approximate Likelihoods for Generalized Linear Errors-in-variables Models

When measurement error is present in covariates, it is well known that naïvely fitting a generalized linear model results in inconsistent inferences. Several methods have been proposed to adjust for measurement error without making undue distributional assumptions about the unobserved true covariates. Stefanski and Carroll focused on an unbiased estimating function rather than a likelihood approach. Their estimating function, known as the conditional score, exists for logistic regression models but has two problems: a poorly behaved Wald test and multiple solutions. They suggested a heuristic procedure to identify the best solution that works well in practice but has little theoretical support compared with maximum likelihood estimation. To help to resolve these problems, we propose a conditional quasi-likelihood to accompany the conditional score that provides an alternative to Wald's test and successfully identifies the consistent solution in large samples.     

Does work during childhood affect the health of Guatemalan adults?

The diversity of potential relationships between child labor and health makes the empirical disentanglement of the causal relationship a difficult exercise. This paper examines the long run impact of child labour on health by controlling for unobserved household specific characteristics. In order to control for the unobserved households specific effect, we estimate a conditional fixed effect model using data on siblings constructed from the Guatemalan National Survey of Living Condition. The estimation results reinforce the conventional wisdom that child labor is harmful for health in the long run. The results can be interpreted as a lower bound of the true impact since healthier children are most likely to offer themselves for employment and to be appointed. The views expressed in this paper are those of the authors and do not necessarily represent those of IMF and IMF policy.     

A Discrete Variable Chain Graph for Applicants for Credit

A bank offering unsecured personal loans may be interested in several related outcome variables, including defaulting on the repayments, early repayment or failing to take up an offered loan. Current predictive models used by banks typically consider such variables individually. However, the fact that they are related to each other, and to many interrelated potential predictor variables, suggests that graphical models may provide an attractive alternative solution. We developed such a model for a data set of 15 variables measured on a set of 14 000 applications for unsecured personal loans. The resulting global model of behaviour enabled us to identify several previously unsuspected relationships of considerable interest to the bank. For example, we discovered important but obscure relationships between taking out insurance, prior delinquency with a credit card and delinquency with the loan.     

Measuring the complexity of generalized linear hierarchical models

Measuring a statistical model's complexity is important for model criticism and comparison. However, it is unclear how to do this for hierarchical models due to uncertainty about how to count the random effects. The authors develop a complexity measure for generalized linear hierarchical models based on linear model theory. They demonstrate the new measure for binomial and Poisson observables modeled using various hierarchical structures, including a longitudinal model and an areal‐data model having both spatial clustering and pure heterogeneity random effects. They compare their new measure to a Bayesian index of model complexity, the effective number p_D of parameters (Spiegelhalter, Best, Carlin & van der Linde 2002); the comparisons are made in the binomial and Poisson cases via simulation and two real data examples. The two measures are usually close, but differ markedly in some instances where p_D is arguably inappropriate. Finally, the authors show how the new measure can be used to approach the difficult task of specifying prior distributions for variance components, and in the process cast further doubt on the commonly‐used vague inverse gamma prior.     

Testing parameter of the power series distribution of a zero inflated power series model

The Zero Inflated Power Series Distribution (ZIPSD) contains two parameters. The first parameter indicates inflation of zero and the other parameter is that of the Power Series distribution. We provide three asymptotic tests for testing the parameter of Power Series distribution, using an unconditional (standard) likelihood approach, a conditional likelihood approach and a test based on sample mean, respectively. The performance of these three tests has been studied for Zero Inflated Poisson Distribution (ZIPD). Asymptotic Confidence Intervals for the parameter are also provided.     

Exact inference for a simple step-stress model with competing risks for failure from exponential distribution under Type-II censoring

In reliability analysis, accelerated life-testing allows for gradual increment of stress levels on test units during an experiment. In a special class of accelerated life tests known as step-stress tests, the stress levels increase discretely at pre-fixed time points, and this allows the experimenter to obtain information on the parameters of the lifetime distributions more quickly than under normal operating conditions. Moreover, when a test unit fails, there are often more than one fatal cause for the failure, such as mechanical or electrical. In this article, we consider the simple step-stress model under Type-II censoring when the lifetime distributions of the different risk factors are independently exponentially distributed. Under this setup, we derive the maximum likelihood estimators (MLEs) of the unknown mean parameters of the different causes under the assumption of a cumulative exposure model. The exact distributions of the MLEs of the parameters are then derived through the use of conditional moment generating functions. Using these exact distributions as well as the asymptotic distributions and the parametric bootstrap method, we discuss the construction of confidence intervals for the parameters and assess their performance through Monte Carlo simulations. Finally, we illustrate the methods of inference discussed here with an example.