On the optimum number of levels in the one-way model with random effects

The optimal number of levels is studied for the one-way random model with normally distributed effects. The optimum criteria used are based on the variances of the traditional analysis of variance estimators of the variance components. Exact solutions are compared to earlier results based on lower bounds of the sampling variances. Comparisons are also made to the large-sample variances of the estimates based on restricted maximum likelihood. Received February 2002     

Estimation of variances in orthogonal finite discrete spectrum linear regression models

The Invariant Quadratic Estimators, the Maximum Likelihood Estimator (MLE) and Restricted Maximum Likelihood Estimator (REML) of variances in an orthogonal Finite Discrete Spectrum Linear Regression Model (FDSLRM) are derived and the problems of unbiasedness and consistency of these estimators are investigated.Acknowledgement. The research was supported by the grants 1/0272/03, 1/0264/03 and 2/4026/04 of the Slovak Scientific Grant Agency VEGA.     

A Review of Simultaneous Painvise Multiple Comparisons

Abstract  A Review of Simultaneous Pairwise Multiple Comparisons. Simultaneous pairwise comparisons can be accomplished with numerous multiple comparison procedures. The methods differ in two essential ways: the choice of critical value and the specification of the estimated standard error of the mean difference. Those methods that assume homogeneous variances are not robust to violations of this assumption. The methods are contrasted via a numerical example. Results of recent Monte Carlo work are described. A choice between the G ames -H owell , D unnett , and C ochran procedures is recommended.     

The impact of intellectual property rights protection on trade: The role of a “third country” in market power and market expansion effects

This study analyzes the impact of increased protection of intellectual property rights (IPRs) in importing countries on the inventing countries’ exports in the presence of “third countries.” In this study, “third countries” include all countries that compete with the inventing countries in exporting similar products to the importing countries. The most significant contribution of this study is to develop an alternative empirical approach for analyzing the impact of IPRs on trade flows. This approach considers three players (the inventing/exporting country, the importing country, and “third countries”) and thus is tentatively called the “three-country model.” The findings confirm that our “three-country model” provides important insights into the impact of IPR protection on international trade, especially in the context of increasingly fierce competition in international trade. We found that the emergence of a third country restrains the market power effects and stimulates market expansion effects. Specifically, when a third country appears, the increased protection of IPRs in the importing countries encourages the inventing countries to increase their exports. However, the export elasticity of IPR protection is highest for primary products and lowest for technology-intensive and human capital–intensive products.     

Analysis of a mixed model for ordinal data by iterative re-weighted REML

An estimation procedure will be presented for a class of threshold models for ordinal data. These models may include both fixed and random effects with associated components of variance on an underlying scale. The residual error distribution on the underlying scale may be rendered greater flexibility by introducing additional shape parameters, e.g. a kurtosis parameter or parameters to model heterogeneous residual variances as a function of factors and covariates. The estimation procedure is an extension of an iterative re-weighted restricted maximum likelihood procedure, originally developed for generalized linear mixed models. This procedure will be illustrated with a practical problem involving damage to potato tubers and with data from animal breeding and medical research from the literature.     

Small-sample Properties of Panel Spatial Autoregressive Models: Comparison of the Bayesian and Maximum Likelihood Methods

Abstract

This article considers autoregressive (SAR) models. We method to estimate the parameters of likelihood (ML) method. Our Bayesian by the Monte Carlo studies. We found the efficient as the ML estimators.     

样本数据缺失情形下泊松过程的强度估计和检验

文章讨论了样本数据缺失情形下泊松过程的强度估计和检验问题。用极大似然估计、矩估计法和最小二乘估计法对强度进行估计,分别得出了极大似然估计强度的迭代方法,矩估计值及最小二乘估计值。证明了矩估计值和最小二乘估计值的无偏性和相合性,导出了其统计量的极限分布。最后,对两个Poisson过程的差异进行了假设检验同时给出渐近置信区间。     

浅谈似然函数的两种不同定义

本文通过两个具体例题表明当连续型总体可能的取值范围不是(-∞,+∞)时,利用第一种似然函数的定义解决点估计问题,学生不仅能够很容易地掌握最大似然估计法,同时对样本来自总体且估计离不开样本这一统计思想加深了理解。     

Analytical quasi maximum likelihood inference in multivariate volatility models

Quasi maximum likelihood estimation and inference in multivariate volatility models remains a challenging computational task if, for example, the dimension of the parameter space is high. One of the reasons is that typically numerical procedures are used to compute the score and the Hessian, and often they are numerically unstable. We provide analytical formulae for the score and the Hessian for a variety of multivariate GARCH models including the Vec and BEKK specifications as well as the recent dynamic conditional correlation model. By means of a Monte Carlo investigation of the BEKK–GARCH model we illustrate that employing analytical derivatives for inference is clearly preferable to numerical methods.     

Scaling for Residual Variance Components of Ordered Category Responses in Generalised Linear Mixed Multilevel Models

A method is proposed that enables changes in variance components to be computed from the results of fitting ordered response generalised models with multilevel and random effects. This deals with the rescaling of the response that occurs as we add new features to a developing model.     

Urban agglomeration, wages and selection: Evidence from samples of siblings

The large and significant relationship between city population and wages has been well-established in the agglomeration literature, and the influence of selection effects on this wage premium is important. This paper contributes new evidence to the understanding of this premium by using two different data sets of siblings in order to estimate the agglomeration premium while controlling for unobserved heterogeneity with a family-specific fixed effect. The inclusion of a familial fixed effect into the regression framework makes the city size wage premium insignificant, and there is a large return to a variable representing the correlation between familial ability and residence in an urban area in all of the data sets used in the analysis. The results are discussed in the context of the existing literature, and they demonstrate the importance of family background and selection effects for interpreting the agglomeration premium, which is small in the fixed effects regression.     

Consistent estimation of the fixed effects stochastic frontier model

In this paper we consider a fixed-effects stochastic frontier model. That is, we have panel data, fixed individual (firm) effects, and the usual stochastic frontier analysis (SFA) composed error.     

Fixed and Random Effects in Stochastic Frontier Models

Received stochastic frontier analyses with panel data have relied on traditional fixed and random effects models. We propose extensions that circumvent two shortcomings of these approaches. The conventional panel data estimators assume that technical or cost inefficiency is time invariant. Second, the fixed and random effects estimators force any time invariant cross unit heterogeneity into the same term that is being used to capture the inefficiency. Inefficiency measures in these models may be picking up heterogeneity in addition to or even instead of inefficiency. A fixed effects model is extended to the stochastic frontier model using results that specifically employ the nonlinear specification. The random effects model is reformulated as a special case of the random parameters model. The techniques are illustrated in applications to the U.S. banking industry and a cross country comparison of the efficiency of health care delivery.JEL classification: C1, C4