Evaluating the Move to a Linear Tax System in Germany and Other European Countries

This paper proposes a comparison of the results of tax policy analysis obtained on the basis of unitary and collective representations of the household. We first generate labour supplies consistent with the collective rationality, by use of a model calibrated on microdata as described in Vermeulen et al. [Collective Models of Household Labor Supply with Nonconvex Budget Sets and Nonparticipation: A Calibration Approach (2006)]. A unitary model is then estimated on these collective data and unitary and collective responses to a tax reform are compared. We focus on the introduction of linear taxation in Germany. The exercise is replicated for other European countries and other topical reforms. Distortions due to the use of a unitary model turn out to be important in predicting labour supply adjustments, in the design of tax revenue neutral reforms, and in predicting a reform’s welfare implications.

河北省普通高校影视课程调查研究

对河北省20所普通高校的影视课程进行调查研究,发现主要存在课程目标各不相同、课程内容各自为政、教学方法贫乏单一、课程考核简单随意、课程评估形同虚设五方面的问题,为了促进河北省普通高校影视课程的建设和完善,必须统一课程目标、规范课程内容、丰富教学方法、细化课程考核、改进课程评估。     

A robust regression model for a first-order autoregressive time series with unequal spacing: application to water monitoring

Summary.  Time series arise often in environmental monitoring settings, which typically involve measuring processes repeatedly over time. In many such applications, observations are irregularly spaced and, additionally, are not distributed normally. An example is water monitoring data collected in Boston Harbor by the Massachusetts Water Resources Authority. We describe a simple robust approach for estimating regression parameters and a first-order autocorrelation parameter in a time series where the observations are irregularly spaced. Estimates are obtained from an estimating equation that is constructed as a linear combination of estimated innovation errors, suitably made robust by symmetric and possibly bounded functions. Under an assumption of data missing completely at random and mild regularity conditions, the proposed estimating equation yields consistent and asymptotically normal estimates. Simulations suggest that our estimator performs well in moderate sample sizes. We demonstrate our method on Secchi depth data collected from Boston Harbor.     

Conditional Uncertainty Analysis and Implications for Decision Making: The Case of WIPP

Uncertainty analyses and the reporting of their results can be misinterpreted when these analyses are conditional on a set of assumptions generally intended to bring some conservatism in the decisions. In this paper, two cases of conditional uncertainty analysis are examined. The first case includes studies that result, for instance, in a family of risk curves representing percentiles of the probability distribution of the future frequency of exceeding specified consequence levels conditional on a set of hypotheses. The second case involves analyses that result in an interval of outcomes estimated on the basis of conservative assumptions. Both types of results are difficult to use because they are sometimes misinterpreted as if they represented the output of a full uncertainty analysis. In the first case, the percentiles shown on each risk curve may be taken at face value when in reality (in marginal terms) they are lower if the chosen hypotheses are conservative. In the second case, the fact that some segments of the resulting interval are highly unlikely—or that some more benign segments outside the range of results are quite possible—does not appear. Also, these results are difficult to compare to those of analyses of other risks, possibly competing for the same risk management resources, and the decision criteria have to be adapted to the conservatism of the hypotheses. In this paper, the focus is on the first type (conditional risk curves) more than on the second and the discussion is illustrated by the case of the performance assessment of the Waste Isolation Pilot Plant in New Mexico. For policy-making purposes, however, the problems of interpretation, comparison, and use of the results are similar.     

A Bayesian analysis of directional data using the projected normal distribution

This paper presents a Bayesian analysis of the projected normal distribution, which is a flexible and useful distribution for the analysis of directional data. We obtain samples from the posterior distribution using the Gibbs sampler after the introduction of suitably chosen latent variables. The procedure is illustrated using simulated data as well as a real data set previously analysed in the literature.     

浅谈中职社团活动对促进学生就业的作用

学生社团活动由于适合中职学生的发展特点,比如组织的自主性等,社团活动越来越受到学生的欢迎。文章通过分析中职社团活动对于中职学生就业以及自身发展等各方面的影响,提出目前社团活动的不足以及优点,得出中职社团活动的发展机制。     

Tests based on weighted rankings in complete blocks: exact distribution and monte carlo simulation

Quade (1972, 1979) proposed a family of nonparametric tests based on weighted within-block rankings, for testing the hypothesis of no treatment effects in a complete randomized blocks layout. In this paper we give a table of the exact null distribution of these tests when the number of treatments is 3, the number of blocks is less than or equal to 14 and the block scores are linear. Moreover, a Monte Carlo study was performed to compare the powers of these tests with parametric and nonparametric competitors