川西藏区藏族中小学校长心理控制源的调查分析

川西藏区地处四川省西部,其特殊的历史地理环境使得这一区域成为藏、汉、羌、彝等民族的聚居地,成为多元文化相互影响、相互碰撞的交汇之地。生活在这里的个体,特别是承担着振兴民族教育事业的各位藏族中小学校长们,在面对相对艰苦的自然环境、相对贫乏的教育资源、特别是面对多种文化交互影响的过程中,在个体心理控制源上表现出怎样的特征呢?作者采用罗特(Rotter.J.B)编制的《内在—外在心理控制源量表》对126名来自四川省甘孜、阿坝和凉山地区的藏族中小学校长进行了测试。结果表明:1、该地区藏族中小学校长的心理控制源在总体上倾向于内控性;2、其内控性在性别、年龄、学校所在地这三个因素上差异不显著;3、被测试的藏族中小学校长们普遍具有较强的社会适应能力。     

Identifying Latent Structures in Panel Data

This paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized techniques. We consider both linear and nonlinear models where the regression coefficients are heterogeneous across groups but homogeneous within a group and the group membership is unknown. Two approaches are considered—penalized profile likelihood (PPL) estimation for the general nonlinear models without endogenous regressors, and penalized GMM (PGMM) estimation for linear models with endogeneity. In both cases, we develop a new variant of Lasso called classifier‐Lasso (C‐Lasso) that serves to shrink individual coefficients to the unknown group‐specific coefficients. C‐Lasso achieves simultaneous classification and consistent estimation in a single step and the classification exhibits the desirable property of uniform consistency. For PPL estimation, C‐Lasso also achieves the oracle property so that group‐specific parameter estimators are asymptotically equivalent to infeasible estimators that use individual group identity information. For PGMM estimation, the oracle property of C‐Lasso is preserved in some special cases. Simulations demonstrate good finite‐sample performance of the approach in both classification and estimation. Empirical applications to both linear and nonlinear models are presented.     

Consumption Dynamics During Recessions

Are there times when durable spending is less responsive to economic stimulus? We argue that aggregate durable expenditures respond more sluggishly to economic shocks during recessions because microeconomic frictions lead to declines in the frequency of households' durable adjustment. We show this by first using indirect inference to estimate a heterogeneous agent incomplete markets model with fixed costs of durable adjustment to match consumption dynamics in PSID microdata. We then show that aggregating this model delivers an extremely procyclical Impulse Response Function (IRF) of durable spending to aggregate shocks. For example, the response of durable spending to an income shock in 1999 is estimated to be almost twice as large as if it occurred in 2009. This procyclical IRF holds in response to standard business cycle shocks as well as in response to various policy shocks, and it is robust to general equilibrium. After estimating this robust theoretical implication of micro frictions, we provide additional direct empirical evidence for its importance using both cross‐sectional and time‐series data.     

未焊透缺陷安全尺寸的评价研究

未焊透是压力管道焊接接头常见缺陷之一,严重时会导致管道的承载能力明显降低,进而引发严重的安全事故。 目前我国的《在用工业管道定期检验规程》中对未焊透管道的定级是很保守的,为了减少对未焊透缺陷的返修,文章采 用非线性有限元分析的方法,通过简化未焊透管道的影响因素,并研究在不同载荷工况下管道失效模式与缺陷尺寸的关 系,获得了未焊透管道的极限载荷曲线簇;再运用塑性力学分析方法对有限元分析结果进行筛选,得到了焊接缺陷的安 全尺寸;最终通过试验验证极限载荷数值分析结果的合理性。研究结果表明含有超标焊接缺陷（如未焊透）的管道不通 过复杂应力计算和安全评定即可在保证安全前提下最大限度地使用。     

Robust inference for estimating equations with nonignorably missing data based on SIR algorithm

Nonresponse is a very common phenomenon in survey sampling. Nonignorable nonresponse – that is, a response mechanism that depends on the values of the variable having nonresponse – is the most difficult type of nonresponse to handle. This article develops a robust estimation approach to estimating equations (EEs) by incorporating the modelling of nonignorably missing data, the generalized method of moments (GMM) method and the imputation of EEs via the observed data rather than the imputed missing values when some responses are subject to nonignorably missingness. Based on a particular semiparametric logistic model for nonignorable missing response, this paper proposes the modified EEs to calculate the conditional expectation under nonignorably missing data. We can apply the GMM to infer the parameters. The advantage of our method is that it replaces the non-parametric kernel-smoothing with a parametric sampling importance resampling (SIR) procedure to avoid nonparametric kernel-smoothing problems with high dimensional covariates. The proposed method is shown to be more robust than some current approaches by the simulations.     

On hysteretic vector autoregressive model with applications

This paper proposes a new hysteretic vector autoregressive (HVAR) model in which the regime switching may be delayed when the hysteresis variable lies in a hysteresis zone. We integrate an adapted multivariate Student-t distribution from amending the scale mixtures of normal distributions. This HVAR model allows for a higher degree of flexibility in the degrees of freedom for each time series. We use the proposed model to test for a causal relationship between any two target time series. Using posterior odds ratios, we overcome the limitations of the classical approach to multiple testing. Both simulated and real examples herein help illustrate the suggested methods. We apply the proposed HVAR model to investigate the causal relationship between the quarterly growth rates of gross domestic product of United Kingdom and United States. Moreover, we check the pairwise lagged dependence of daily PM2.5 levels in three districts of Taipei.     

绿色增长下的导向性技术创新选择研究

针对如何正确引导 GHG 排放的气候反馈经济损失下导向性技术创新,以实现长期的绿色增长这一问题,基于 DICE 模型,重构导向性技术创新不同的动力要素及其与气候变化之间的内生关系,建立了可体现绿色增长“均衡性”、“包容性”和“可持续性”的非线性最优控制模型。数值仿真结果显示: 气候反馈经济损失不容小觑; 偏于生产的绿色技术创新导向下社会生产力强劲但存在气候环境恶化风险,偏于减排的绿色技术创新导向下气候反馈经济损失小但存在增长动力匮乏风险,二者虽均可实现长期的绿色增长,但中性的绿色技术创新导向会更稳妥; 偏于生产的绿色技术创新导向下人均消费变化率在短期内会显著提升。     

ESTIMATING A PARAMETER WHEN IT IS KNOWN THAT THE PARAMETER EXCEEDS A GIVEN VALUE

In some statistical problems a degree of explicit, prior information is available about the value taken by the parameter of interest, θ say, although the information is much less than would be needed to place a prior density on the parameter's distribution. Often the prior information takes the form of a simple bound, ‘θ > θ₁ ’ or ‘θ < θ₁ ’, where θ₁ is determined by physical considerations or mathematical theory, such as positivity of a variance. A conventional approach to accommodating the requirement that θ > θ₁ is to replace an estimator, , of θ by the maximum of and θ₁. However, this technique is generally inadequate. For one thing, it does not respect the strictness of the inequality θ > θ₁ , which can be critical in interpreting results. For another, it produces an estimator that does not respond in a natural way to perturbations of the data. In this paper we suggest an alternative approach, in which bootstrap aggregation, or bagging, is used to overcome these difficulties. Bagging gives estimators that, when subjected to the constraint θ > θ₁ , strictly exceed θ₁ except in extreme settings in which the empirical evidence strongly contradicts the constraint. Bagging also reduces estimator variability in the important case for which is close to θ₁, and more generally produces estimators that respect the constraint in a smooth, realistic fashion.     

Non-asymptotic sequential confidence regions with fixed sizes for the multivariate nonlinear parameters of regression

In this paper we consider a sequential design for the estimation of nonlinear parameters of regression with guaranteed accuracy. Non-asymptotic confidence regions with fixed sizes for the least squares estimates are used. The obtained confidence region is valid for finite numbers of data points when the distributions of the observations are unknown.     

从“凯恩斯效应”到“阿米曲线”——政府规模与经济增长关系的非线性转向

政府规模与经济增长之间的关系问题是宏观经济研究中的核心问题之一.关于两者关系的传统研究往往以线性假定为基础,所以实证结果出现了巨大的差异.这种现象促使研究者从非线性角度重新审视政府规模与经济增长之间的关系.“巴罗法则”在内生增长框架内为政府规模与经济增长关系研究提供了一个标准的分析框架,揭示了两者之间的倒“U”关系.而“Armey曲线”不仅非常直观地表达了政府规模与经济增长之间的非线性关系,同时还指出这种非对称关系的非对称性质,具有很强的总结性和政策指导意义.