软预算约束与国企改革：从要素投入的视角分析

论文运用动态模型对软预算约束的形成路径进行了理论研究,并对中国国有企业改革的路径选择进行实证研究。研究结果表明软预算约束起源于企业要素投入与生产模式的匹配模式,而中国国有企业改革路径选择的结果是使要素投入和生产模式满足弱匹配条件。     

Bayesian model comparison via parallel model output

Bayesian estimation via MCMC methods opens up new possibilities in estimating complex models. However, there is still considerable debate about how selection among a set of candidate models, or averaging over closely competing models, might be undertaken. This article considers simple approaches for model averaging and choice using predictive and likelihood criteria and associated model weights on the basis of output for models that run in parallel. The operation of such procedures is illustrated with real data sets and a linear regression with simulated data where the true model is known.     

Books on probability ideas are reviewed

In this paper, semiparametric methods are applied to estimate multivariate volatility functions, using a residual approach as in [J. Fan and Q. Yao, Efficient estimation of conditional variance functions in stochastic regression, Biometrika 85 (1998), pp. 645–660; F.A. Ziegelmann, Nonparametric estimation of volatility functions: The local exponential estimator, Econometric Theory 18 (2002), pp. 985–991; F.A. Ziegelmann, A local linear least-absolute-deviations estimator of volatility, Comm. Statist. Simulation Comput. 37 (2008), pp. 1543–1564], among others. Our main goal here is two-fold: (1) describe and implement a number of semiparametric models, such as additive, single-index and (adaptive) functional-coefficient, in volatility estimation, all motivated as alternatives to deal with the curse of dimensionality present in fully nonparametric models; and (2) propose the use of a variation of the traditional cross-validation method to deal with model choice in the class of adaptive functional-coefficient models, choosing simultaneously the bandwidth, the number of covariates in the model and also the single-index smoothing variable. The modified cross-validation algorithm is able to tackle the computational burden caused by the model complexity, providing an important tool in semiparametric volatility estimation. We briefly discuss model identifiability when estimating volatility as well as nonnegativity of the resulting estimators. Furthermore, Monte Carlo simulations for several underlying generating models are implemented and applications to real data are provided.     

Detection and correction of artificial shifts in climate series

Summary.  Many long instrumental climate records are available and might provide useful information in climate research. These series are usually affected by artificial shifts, due to changes in the conditions of measurement and various kinds of spurious data. A comparison with surrounding weather-stations by means of a suitable two-factor model allows us to check the reliability of the series. An adapted penalized log-likelihood procedure is used to detect an unknown number of breaks and outliers. An example concerning temperature series from France confirms that a systematic comparison of the series together is valuable and allows us to correct the data even when no reliable series can be taken as a reference.     

Merging information for semiparametric density estimation

Summary.  The density ratio model specifies that the likelihood ratio of m −1 probability density functions with respect to the m th is of known parametric form without reference to any parametric model. We study the semiparametric inference problem that is related to the density ratio model by appealing to the methodology of empirical likelihood. The combined data from all the samples leads to more efficient kernel density estimators for the unknown distributions. We adopt variants of well-established techniques to choose the smoothing parameter for the density estimators proposed.     

Kernel adjusted nonparametric regression

In this paper we propose and study a new kernel regression estimator in which the kernel is taken from a properly adapted location-scale family of the design distribution. We show that, while the original smoothing may be performed with sub-optimal bandwidths, adaptation of proper scale parameters yields overall optimal estimators. Unlike traditional smoothing methodology, our approach does not aim at estimating pivotal higher order derivatives.     

丹东市城市居民居住区位选择调查研究

以内外因相结合的辨证思维方法为指导,构建影响丹东市城市居民居住区位选择的因子体系,通过问卷调查与数理统计分析相结合的方法,对丹东市城市居民居住区位选择的影响因素进行调查,分析了丹东市城市居民居住区位选择的主要影响因素和动力机制。希望为城市规划调整、开发商的适居住宅的建设、居民的住址选择提供帮助。     

双重合约论————基于对外部性的新解释

外部性的新定义是：没有参与订立特定相关合约的其他人所给予上述合约订立人的影响。上述订立的特定相关合约就是内部合约。所谓影响或某种控制,都是经过一致同意达成合约实现的。上述“其他人”不参加内部合约从而不受它控制,但对内部合约订立人产生影响,必定是同内部合约订立人达成了另外的合约即外部合约。上述内外合约组合成双重合约,这是一个普遍存在的事实。在拥有完全退出权的条件下,所有合约包括内外合约,都是每个参与人通过收益成本计算而一致同意达成的,其中包括为降低决策成本而一致同意采取各种授权方式达成的合约。内外合约的联系即相互之间的影响是双向的,其中外部合约作为外部选择点,由于条件的不同,或是可以保障内部合约的达成与稳定,或是可以替代内部合约参与人使其退出并改变内部合约。但上述退出权的实现取决于退出效用是否不小于退出成本。公共选择、合作博弈、讨价还价和一般均衡等理论同样可以解释双重合约。     

企业新闻发言人：秘书职业发展的新选择

从企业秘书职业发展的角度,锁定企业新闻发言人这一新兴职业,通过比较企业新闻发言人和秘书工作两者之间的很多共通的素质能力要求,揭示出两者的天然贴近性,进而提出企业新闻发言人可以成为企业中高级秘书职业发展的一个新选择。     

后金融危机时期东北地区开放型经济新优势的培育和发展

金融危机对东北地区进出口贸易、外商投资和对外经济合作都造成了显著影响.在后金融危机时期,世界经济存在再度衰退风险,外部需求总体上继续保持低迷,我国与其他国家贸易竞争不断加剧,外贸结构调整难度加大.东北地区发展开放型经济必须致力于培育新的经济增长点和新的比较优势.具体来说,在进出口贸易方面,应该重点培育进出口竞争新优势、扶持本土企业“走出去”拓展新兴市场;在外资利用方面,应该重点扩大招商规模,提高外资利用质量;在特殊区域建设方面,应该充分发挥综合保税区的创新平台作用和区域带动作用;同时,要加强对外投资风险防控.