Fitting semiparametric accelerated failure time models for nested case–control data

A nested case–control (NCC) study is an efficient cohort-sampling design in which a subset of controls are sampled from the risk set at each event time. Since covariate measurements are taken only for the sampled subjects, time and efforts of conducting a full scale cohort study can be saved. In this paper, we consider fitting a semiparametric accelerated failure time model to failure time data from a NCC study. We propose to employ an efficient induced smoothing procedure for rank-based estimating method for regression parameters estimation. For variance estimation, we propose to use an efficient resampling method that utilizes the robust sandwich form. We extend our proposed methods to a generalized NCC study that allows a sampling of cases. Finite sample properties of the proposed estimators are investigated via an extensive stimulation study. An application to a tumor study illustrates the utility of the proposed method in routine data analysis.     

An LM-type test for idiosyncratic unit roots in the exact factor model with integrated factors

We consider an exact factor model with integrated factors and propose an LM-type test for unit roots in the idiosyncratic component. We show that, for a fixed number of panel individuals (N) and when the number of time points (T) tends to infinity, the limiting distribution of the LM-type statistic is a weighted sum of independent Chi-square variables with one degree of freedom, and when T tends to infinity followed by N tending to infinity, the limiting distribution is standard normal. The results should contribute to the challenging task of deriving likelihood-based unit-root tests in dynamic factor models.     

《墨西哥气候变化法》及其对中国气候安全立法的启示

《墨西哥气候变化法》是在特殊的国际、国内立法背景下通过的,是在遵循气候正义、气候公平等法理基础上制定的,有广泛的国际、国内法律基础.该法规定了一系列应对气候变化的原则、规则和相应的实施机制,具有注重“协调与参与”、“透明与责任”制度性设计等特点.中国与墨西哥同为发展中国家,中国在参考和借鉴《墨西哥气候变化法》合理成分的基础上,应采取诸如制定综合性气候变化应对法、加强气候变化应对能力建设、进行减缓性与适应性立法等措施,以应对全球气候变化带来的挑战.     

非监禁刑乃刑罚轻缓之必然

非监禁刑是在监狱之外对犯罪人适用的刑罚,犯罪是一种复杂的社会现象,犯罪的原因既有个人的,也有社会的,刑罚不是对抗犯罪的唯一的有效的手段,社会的文明要求刑罚应由严酷到缓和,由以监禁刑为主向以非监禁刑为主发展,这与中国传统“慎刑恤狱”的法律文化思想是相符合的,它是人性的需要,也是社会发展的必然,是节约刑罚成本的需要,也是实现刑罚目的需要,也利于罪犯重新回归社会,我国现行的刑罚是以监禁刑为主的重刑结构,所以,必须完善立法、加强司法,逐步实现刑罚的非监禁化。     

自然资源资产审计的风险识别与应对措施——以EG公司为例

自然资源资产审计是处于起步期的审计新领域。透过审计人员对EG公司自然资源资产的风险识别与分析,探讨了自然资源资产审计的风险应对措施。     

DOUBLE LENGTH ARTIFICIAL REGRESSIONS FOR TESTING SPATIAL DEPENDENCE

This paper derives two simple artificial Double Length Regressions (DLR) to test for spatial dependence. The first DLR tests for spatial lag dependence while the second DLR tests for spatial error dependence. Both artificial regressions utilize only least squares residuals of the restricted model and are therefore easy to compute. These tests are illustrated using two simple examples. In addition, Monte Carlo experiments are performed to study the small sample performance of these tests. As expected, these DLR tests have similar performance to their corresponding LM counterparts.     

对影响货币乘数内在因素的实证分析和几点思考

1985年我国确立了中央银行体制下的货币供给管理体制.该体制中的三要素--基础货币、货币乘数和货币供应量之间的相互独立、相互依存的关系开始形成.它为我们从统计实证角度分析影响货币供给的内在因素提供了制度基础;1998年中央银行取消了信贷规模控制,提出了健全和完善以间接调控为主的货币政策工具,这对我们结合中国实际,从理论上分析我国基础货币的控制及货币乘数的稳定,提出了客观要求.     

A Locally Most Mean Powerful Based Score Test for ARCH and GARCH Regression Disturbances

This article considers the twin problems of testing for autoregressive conditional heteroscedasticity (ARCH) and generalized ARCH disturbances in the linear regression model. A feature of these testing problems, ignored by the standard Lagrange multiplier test, is that they are onesided in nature. A test that exploits this one-sided aspect is constructed based on the sum of the scores. The small-sample-size and power properties of two versions of this test under both normal and leptokurtic disturbances are investigated via a Monte Carlo experiment. The results indicate that both versions of the new test typically have superior power to two versions of the Lagrange multiplier test and possibly also more accurate asymptotic critical values.     

Interaction Between Autocorrelation and Conditional Heteroscedasticity: A Random-Coefficient Approach

In applied econometrics, we tend to tackle specification problems one at a time rather than considering them jointly. This has serious consequences for statistical inference. One example of this is considering autocorrelation and autoregressive conditional heteroscedasticity (ARCH) separately. In this article we consider a linear regression model with random coefficient autoregressive disturbances that provides a convenient framework to analyze autocorrelation and ARCH simultaneously. Our stationarity conditions and testing results reveal the strong interaction between ARCH and autocorrelation. An empirical example of testing the unbiasedness of experts' expectations of inflation demonstrates that neglecting conditional heteroscedasticity or misspecifying the autocorrelation structure might result in unreliable inference.     

某自锚式悬索桥减震性能研究

以某自锚式悬索桥为研究对象，采用非线性时程分析方法，对整体式减隔震装置铅芯橡胶支座对自锚式悬索桥的减震性能进行研究。通过对在辅助墩上布置铅芯橡胶支座和普通橡胶支座的自锚式悬索桥的抗震性能对比分析，得到在辅助墩上布置铅芯橡胶支座对自锚式悬索桥的地震效应减震效果明显的结论。