EMPIRICAL BAYES TEST PROBLEMS OF VARIANCE COMPONENTS IN RANDOM EFFECTS MODEL

Bayes decision rule of variance components for one-way random effects model is derived and empirical Bayes (EB) decision rules are constructed by kernel estimation method. Under suitable conditions, it is shown that the proposed EB decision rules are asymptotically optimal with convergence rates near O(n-1/2). Finally, an example concerning the main result is given.

Bootstrap inference of the skew-normal two-way classification random effects model with interaction

In this paper,we consider the statistical inference problems for the fixed effect and variance component functions in the two-way classification random effects model with skewnormal errors.Firstly,the exact test statistic for the fixed effect is constructed.Secondly,using the Bootstrap approach and generalized approach,the one-sided hypothesis testing and interval estimation problems for the single variance component,the sum and ratio of variance components are discussed respectively.Further,the Monte Carlo simulation results indicate that the exact test statistic performs well in the one-sided hypothesis testing problem for the fixed effect.And the Bootstrap approach is better than the generalized approach in the one-sided hypothesis testing problems for variance component functions in most cases.Finally,the above approaches are applied to the real data examples of the consumer price index and value-added index of three industries to verify their rationality and effectiveness.

Bias and Mean Square Error of Reliability Estimators under the One and Two Random Effects Models: The Effect of Non-Normality

The coefficient of reliability is often estimated from a sample that includes few subjects. It is therefore expected that the precision of this estimate would be low. Measures of precision such as bias and variance depend heavily on the assumption of normality, which may not be tenable in practice. Expressions for the bias and variance of the reliability coefficient in the one and two way random effects models using the multivariate Taylor’s expansion have been obtained under the assumption of normality of the score (Atenafu et al. [1]). In the present paper we derive analytic expressions for the bias and variance, hence the mean square error when the measured responses are not normal under the one-way data layout. Similar expressions are derived in the case of the two-way data layout. We assess the effect of departure from normality on the sample size requirements and on the power of Wald’s test on specified hypotheses. We analyze two data sets, and draw comparisons with results obtained via the Bootstrap methods. It was found that the estimated bias and variance based on the bootstrap method are quite close to those obtained by the first order approximation using the Taylor’s expansion. This is an indication that for the given data sets the approximations are quite adequate.

Bootstrap Inference on the Variance Component Functions in the Two-Way Random Effects Model with Interaction

In this paper,using the Bootstrap approach and generalized approach,the authors consider the one-sided hypothesis testing problems for variance component functions in the two-way random effects model.Firstly,the test statistics and confidence intervals for the sum of variance components are constructed.Next,the one-sided hypothesis testing problems for the ratio of variance components are also discussed.The Monte Carlo simulation results indicate that the Bootstrap approach is better than the generalized approach in most cases.Finally,the above approaches are applied to the real data examples of mice blood p H and molded plastic part’s dimensions.

Agents’ Behavior in Market Bubbles： Herding and Information Effects

This paper explores some behavioral factors that may explain the formation of speculative bubbles in financial markets. The study adopts an experimental approach focused on the agents’ behavior when facing a “true” bubble and is incentivized to herd and/or receive information about the market sentiment. For this purpose, a straightforward laboratory experiment that reproduces the dotcom market bubble and asks subjects to forecast asset prices in a true dynamic information scenario. The experiment was conducted in the laboratory of the Faculty of Economics at the University of Salamanca and involved 137 undergraduate students in the degree of economics. The results show that incentives to the herding behavior increase the forecasted volatility and thus contribute to the bubble inflation. Nevertheless, this effect may be offset by giving information to the agents about the expected market trend. Therefore, under herding effects, it is the absence of clear signals about market sentiments what inflates the bubble.

The Sources of Economic Growth in Sub-Saharan African IDB Member Countries

The economic growth in Sub-Sahara African （SSA） IDB member countries has been encouraging over the last decade; however, it is still not high enough to enable these countries to overcome the persistent poverty. There is thus a need to raise substantially real GDP growth rates on a sustained basis, both through the productivity channel and factor accumulation such as labor and capital. This study focuses on ＂the source of economic growth in SSA IDB member countries＂ with the objective of identifying the main driving factors of economic growth in the region using the growth accounting framework and extending the existing analysis both by country and time coverage. The paper is expected to be useful for the policymakers in the region to have a clear picture on the main sources of growth, and thus help them in identifying strategic reform areas of intervention in line with the most binding factors of growth. The data used in this study cover 20 Sub-Sahara African countries covering the period 1990-2012. The data set includes real GDP, labor force, and capital stock. The source of data is the various version of the World Economic Outlook, IMF. Capital stock is estimated using perpetual inventory method and the base year is 1970. In estimating growth accounting model, a translog production function is applied using panel data and random effects model. Empirical results show that the capital accumulation is the most important individual factor in GDP growth （52%） followed by workforce accumulation （39%） while total factor productivity （TFP） accounts for meagre 8%. This suggests that, on average, real GDP growth in Sub-Sahara African countries was driven primarily by factor accumulation with a low level of TFP. In addition, the elasticity of labor was lower than that of capital indicating that the labor played very little role in GDP growth most likely due to unskilled labor force or mismatch of labor skills with the production process. Furthermore, this also adversely affects both the TFP growth and the share of capital growth to the GDP growth. The results indicate that the critical constraint to the economic growth appears to be poor labor skills that lead to both low labor productivity and under-utilization of capital stock.

Safety Analysis of Riding at Intersection Entrance Using Video Recognition Technology

To study riding safety at intersection entrance,video recognition technology is used to build vehicle-bicycle conflict models based on the Bayesian method.It is analyzed the relationship among the width of nonmotorized lanes at the entrance lane of the intersection,the vehicle-bicycle soft isolation form of the entrance lane of intersection,the traffic volume of right-turning motor vehicles and straight-going non-motor vehicles,the speed of right-turning motor vehicles,and straight-going non-motor vehicles,and the conflict between right-turning motor vehicles and straight-going nonmotor vehicles.Due to the traditional statistical methods,to overcome the discreteness of vehicle-bicycle conflict data and the differences of influencing factors,the Bayesian random effect Poisson-log-normal model and random effect negative binomial regression model are established.The results show that the random effect Poisson-log-normal model is better than the negative binomial distribution of random effects;The width of non-motorized lanes,the form of vehicle-bicycle soft isolation,the traffic volume of right-turning motor vehicles,and the coefficients of straight traffic volume obey a normal distribution.Among them,the type of vehicle-bicycle soft isolation facilities and the vehicle-bicycle traffic volumes are significantly positively correlated with the number of vehicle-bicycle conflicts.The width of non-motorized lanes is significantly negatively correlated with the number of vehicle-bicycle conflicts.Peak periods and flat periods,the average speed of right-turning motor vehicles,and the average speed of straight-going non-motor vehicles have no significant influence on the number of vehicle-bicycle conflicts.

Joint Modeling of Failure Time Data with Transformation Model and Longitudinal Data When Covariates are Measured with Errors

Semiparametric transformation models provide a class of flexible models for regression analysis of failure time data. Several authors have discussed them under different situations when covariates are time- independent （Chen et al., 2002; Cheng et al., 1995; Fine et al., 1998）. In this paper, we consider fitting these models to right-censored data when covariates are time-dependent longitudinal variables and, furthermore, may suffer measurement errors. For estimation, we investigate the maximum likelihood approach, and an EM algorithm is developed. Simulation results show that the proposed method is appropriate for practical application, and an illustrative example is provided.

A study of inadequate consumer demand among Chinese residents --based on data for urban and rural areas in different provinces

Using panel data from both urban and rural areas in China＇s thirty provinces, autonomous regions and municipalities （Tibet excluded） from 1995 to 2005 and applying the random effects model, we conducted a quantitative analysis of factors influencing urban and rural consumer demand. The findings show the per capita disposable income of Chinese residents is highly correlated with their per capita consumption expenditure and the consumption function of urban and rural residents was relatively stable over the eleven years under study. On the basis of these findings, this paper further makes use of data in China＇s funds flow statements （physical transactions） from 1992 to 2004 to explain one of the reasons for the continuing under-consumption since 1997-1998; that is, in the course of national income distribution and redistribution the government has gained an ever increasing share of total and disposable income while the share of Chinese residents shows a continuous decline.