工业劳动力流动、资本创造与经济地理空间均衡

资本创造模型（CC模型）忽视了要素流动对产业空间分布的影响。而发展的新的资本创造模型则认为资本集聚的过程必然伴随着工业劳动力的流动过程。另外，是资本的实际收益而不是名义收益决定资本是否创造。研究结果表明，随着贸易自由度、工业品支出份额及资本贴现率的变大，替代弹性及资本折旧率的变小，将降低对称结构的稳定性，而提高中心-外围结构的稳定性；经济地理空间的产业均衡是集聚力和分散力相互作用的结果。当企业生产工业品的规模报酬递增程度足够显著，或者工业品支出份额很高时，市场拥挤效应将彻底消失，并转化成为促进产业集聚的动力；突破点与持续点的大小比较可以形成不同的关系，这意味着随着贸易自由度的变化，本文发展的资本创造模型可以体现出多样化的产业空间动态演化行为。     

Rényi entropy of m-generalized order statistics

Abstract

Characterizing relations via Rényi entropy of m-generalized order statistics are considered along with examples and related stochastic orderings. Previous results for common order statistics are included.     

The Eurasian Economic Union: Development Prospects and Possible Obstacles

This article analyzes the development prospects and problems for the Eurasian Economic Union (EAEU). It examines issues of integration within the EAEU, as well as interactions with other countries, both CIS (Commonwealth of Independent States) and non-CIS. The main problem of integration within the EAEU is the dominance of redistributive motives over productive ones. This article assesses the extent of Russian oil and gas transfers to EAEU partners and the impact of tax maneuvers on their size. It shows that the creation of mechanisms for redistributing profits within the EAEU will allow a positive economic effect to materialize from free trade agreements with non-CIS countries. The article assesses the risks for the EAEU related to Russia’s introduction of a unilateral ban on food imports from countries on the sanctions list and to the possible establishment of tariffs on trade with Ukraine.     

On the Convergence of the Monte Carlo Maximum Likelihood Method for Latent Variable Models

While much used in practice, latent variable models raise challenging estimation problems due to the intractability of their likelihood. Monte Carlo maximum likelihood (MCML), as proposed by Geyer & Thompson (1992 ), is a simulation-based approach to maximum likelihood approximation applicable to general latent variable models. MCML can be described as an importance sampling method in which the likelihood ratio is approximated by Monte Carlo averages of importance ratios simulated from the complete data model corresponding to an arbitrary value of the unknown parameter. This paper studies the asymptotic (in the number of observations) performance of the MCML method in the case of latent variable models with independent observations. This is in contrast with previous works on the same topic which only considered conditional convergence to the maximum likelihood estimator, for a fixed set of observations. A first important result is that when is fixed, the MCML method can only be consistent if the number of simulations grows exponentially fast with the number of observations. If on the other hand, is obtained from a consistent sequence of estimates of the unknown parameter, then the requirements on the number of simulations are shown to be much weaker.     

林业投资均衡性的理论分析

我国林业投资体制的改革面临着许多新的课题,研究市场经济条件下林业投资状况十分必要。首先,从均衡理论出发,在分析宏观经济政策对林业的影响和林业投资现状基础上,对形成这种状况的主要原因进行了探讨;其次,以林业投资对象为主体,对其微观经济行为的成本与收益问题进行了分析;最后,提出深化林业投资体制改革要促进投资主体多元化,给予林业更多的政策扶持,进一步完善林业法律法规,以促进我国林业持续稳定地发展。     

管理贸易的制度经济学分析

各国开展对外贸易是为了能充分、有效配置国内外资源 ,并从中获得最大利益 ,但在追求最大利益的过程中 ,各国所采取的贸易政策都不尽相同。这些不同的贸易政策大体分为自由贸易与保护贸易两类。 2 0世纪 80年代初 ,一种既不同于自由贸易 ,也不同于保护贸易 ,但又兼有两者特点的新型的贸易制度开始出现 ,这便是“管理贸易”。管理贸易是自由贸易与保护贸易博弈的结果 ,是各国在无法达到最佳目标模式时所能选择的次佳目标模式 ,其本质是有组织的自由和协调的保护。一些西方国家先后采取管理贸易并获得了有效的实践效果。我国应正视这一新情况、新趋势进行贸易制度变迁与创新———实行偏保护的管理贸易政策     

Statistical and Combinatorial Aspects of Comparative Genomics*

Abstract. This document presents a survey of the statistical and combinatorial aspects of four areas of comparative genomics: gene order based measures of evolutionary distances between species, construction of phylogenetic trees, detection of horizontal transfer of genes, and detection of ancient whole genome duplications.     

一种嵌入式GUI软件结构实现方案

综合比较了嵌入式GUI的几种实现方式,结合嵌入式系统的特点,研究了嵌入式GUI中的关键技术,分析了嵌入式GUI与普通GUI系统的不同之处,提出一种通用的嵌入式图形用户界面系统的设计思想和体系结构,这种嵌入式GUI实现方案具有轻型、占用资源少、可剪裁等特点。     

HEAVY-TAILED-DISTRIBUTED THRESHOLD STOCHASTIC VOLATILITY MODELS IN FINANCIAL TIME SERIES

To capture mean and variance asymmetries and time‐varying volatility in financial time series, we generalize the threshold stochastic volatility (THSV) model and incorporate a heavy‐tailed error distribution. Unlike existing stochastic volatility models, this model simultaneously accounts for uncertainty in the unobserved threshold value and in the time‐delay parameter. Self‐exciting and exogenous threshold variables are considered to investigate the impact of a number of market news variables on volatility changes. Adopting a Bayesian approach, we use Markov chain Monte Carlo methods to estimate all unknown parameters and latent variables. A simulation experiment demonstrates good estimation performance for reasonable sample sizes. In a study of two international financial market indices, we consider two variants of the generalized THSV model, with US market news as the threshold variable. Finally, we compare models using Bayesian forecasting in a value‐at‐risk (VaR) study. The results show that our proposed model can generate more accurate VaR forecasts than can standard models.     

The analysis of incomplete data using stochastic covariates

In the development of many diseases there are often associated random variables which continuously reflect the progress of a subject towards the final expression of the disease (failure). At any given time these processes, which we call stochastic covariates, may provide information about the current hazard and the remaining time to failure. Likewise, in situations when the specific times of key prior events are not known, such as the time of onset of an occult tumour or the time of infection with HIV-1, it may be possible to identify a stochastic covariate which reveals, indirectly, when the event of interest occurred. The analysis of carcinogenicity trials which involve occult tumours is usually based on the time of death or sacrifice and an indicator of tumour presence for each animal in the experiment. However, the size of an occult tumour observed at the endpoint represents data concerning tumour development which may convey additional information concerning both the tumour incidence rate and the rate of death to which tumour-bearing animals are subject. We develop a stochastic model for tumour growth and suggest different ways in which the effect of this growth on the hazard of failure might be modelled. Using a combined model for tumour growth and additive competing risks of death, we show that if this tumour size information is used, assumptions concerning tumour lethality, the context of observation or multiple sacrifice times are no longer necessary in order to estimate the tumour incidence rate. Parametric estimation based on the method of maximum likelihood is outlined and is applied to simulated data from the combined model. The results of this limited study confirm that use of the stochastic covariate tumour size results in more precise estimation of the incidence rate for occult tumours.