Thermodynamics and process analysis for future economic scenarios

Economists are increasingly interested in forecasting future costs and benefits of policies for dealing with materials/energy fluxes, polluting emissions and environmental impacts on various scales, from sectoral to global. Computable general equilibrium (CGE) models are currently popular because they project demand and industrial structure into the future, along an equilibrium path. But they are applicable only to the extent that structural changes occur in or near equilibrium, independent of radical technological (or social) change. The alternative tool for analyzing economic implications of scenario assumptions is to use Leontief-type Input-Output (I-O) models. I-O models are unable to endogenize structural shifts (changing I-O coefficients). However, this can be a virtue when considering radical rather than incremental shifts. Postulated I-O tables can be used independently to check the internal consistency of scenarios. Or I-O models can be used to generate scenarios by linking them to econometric macro-drivers (which can, in principle, be CGE models). Explicit process analysis can be integrated, in principle, with I-O models. This hybrid scheme provides a natural means of satisfying physical constraints, especially the first and second laws of thermodynamics. This is important, to avoid constructing scenarios based on physically impossible processes. Process analysis is really the only available tool for constructing physically plausible alternative future I-O tables, and generating materials/energy and waste emissions coefficients. Explicit process analysis also helps avoid several problems characteristic of pure CGE or I-O models, viz. (1) aggregation errors (2) inability to handle arbitrary combinations of co-product and co-input relationships and (3) inability to reflect certain non-linearities such as internal feedback loops.     

基于复杂性科学观的区域创新网络研究

复杂性科学打破了新古典经济学的简单性、稳定性和线性的均衡范式,开创了一种建立在复杂性、动态性和非线性基础上的演化范式。区域创新网络由于具有非线性、动态性和不可逆性等特征,更适合纳入到复杂性科学的范式中来研究。根据区域创新网络的复杂性特征,归纳出其实质上是一种复杂性适应系统,进而运用复杂性科学对其进行了阐释,最后得出了基于高新区培育和发展区域创新网络的几点启示。     

区域发展中地理势能的初步研究

从区域发展的各个主要相关要素，初步探讨区域发展的地理势能。把地理区域作为一个系统，当一个区域相对于其它区域在地理位置、区际差异、区域结构和环境质量等方面，所显示出发展的综合优势即是该区域在这一系统中的地理势能。这种地理势能的大小受自然环境基础的深刻影响，并可随着不同的历史阶段、科学技术的发展而转化。一个地区的地理位置对比优势的态势为地理位置势能。地理位置和区位在自然条件上的势能促使其获得政策上的势能，并直接影响到产业结构的形成。地域间环境条件、生态功能、产业优势的潜在影响力为地理区际势能，如各种环境条件以及这些条件合理匹配的所谓地理地带性规律，决定了传统的农业生产。区际的差异还体现在区域发展的历史过程上，历史悠久的区域往往具有较高的地理区际势能。区域自然环境结构对于区域发展优势的影响力为区域结构势能。环境质量势能是环境质量对于区域发展优势的态势。生态环境脆弱、土地退化、自然灾害、环境污染等，大大减弱了区域环境质量势能。地理势能遵循能量守恒定律，势能转化的动力来源于自然与社会两方面。     

管理文化演进的规律性探究

管理文化是指人类在管理活动中共同创造、共同维持、共同发展的物质财富和精神财富的总和。它包括四个层次的内容:一是管理物质文化,二是管理制度文化,三是管理意识文化,四是管理心理文化。管理文化的演进是按照这四个层次由低到高依次循环进行的。现代管理文化近百年的演进历程可分为三个大的周期。     

区域经济一体化的最优货币区理论分析

欧盟是迄今为止运行最为成功的区域经济一体化组织,欧元的出现以及成功运行标志着区域经济一体化进入货币一体化的更高层次。作者首先阐述了区域经济一体化理论的产生与发展以及蒙代尔教授提出的最优货币区理论,并提出了从最优货币区理论的角度来分析区域经济一体化理论的观点,然后探讨了在一个经济区域内建立最优货币区的标准的问题,最后用 GG-LL模型分析了区域内各经济体与最优货币区的关系,从而最终建立了分析区域经济一体化本质的新视野。     

发展现代物流 提升城市功能

分析了武汉市物流业的现状及存在的问题，论述了武汉发展物流业具有一定优势，并提出了发展区域性物流中心的正确定位，在此基础上合理规划城市交通设施和网络设施等物流活动的支撑体系，建立配套的相关政策，推动武汉区域物流中心的建设。     

从“其他绿地”到“区域绿地”： 城市非建设用地下的绿地规划转型 与优化

新版《城市绿地分类标准》(CJJ/T 85—2017)以“区域绿地”代替“其他绿地”，这为城市非建设用地下绿地的保护利用提出了新的要求和目标。解读新标准指导下城市非建设用地中的绿地建设发展要求并进行科学合理的规划，是响应当前城市绿色发展新形势和满足人民日益增长的美好生活新需求所面临的重要课题之一。聚焦从“其他绿地”到“区域绿地”的分类调整，分析新标准下区域绿地的内涵和特征。以河北省承德市为例，结合城乡发展需求，阐述区域绿地规划的核心转型思路。并从目标、内容、方法和评价等方面，论述区域绿地设定下城市非建设用地中绿地规划的具体内容和方向。最后从空间政策、发展引导、部门合作和大众参与等方面，提出了规划实施保障优化的策略。以“区域绿地”的解读为源，聚焦当前城市建设用地内外绿地规划建设割裂的现状问题，提出区域绿地规划的转型优化措施和实践经验，以期为新时代中国城市绿色空间的拓展与优化提供参考。     

东部地区在区域经济协调发展中要发挥更大作用

“八五”以来，我国东部沿海地区充分利用区位优势和现实经济条件，依靠科技力量，致力于产业结构升级换代，积极转变经济增长方式，形成了一批现代化的企业集团和企业家队伍，经济增长方式上完成了由劳动密集型向资本、技术密集型的转变，积累了大量的资本，为东西部地区协调发展创造了条件。     

Seasonality and Markov switching in an unobserved component time series model

It is generally acknowledged that the growth rate of output, the seasonal pattern, and the business cycle are best estimated simultaneously. To achieve this, we develop an unobserved component time series model for seasonally unadjusted US GDP. Our model incorporates a Markov switching regime to produce periods of expansion and recession, both of which are characterized by different underlying growth rates. Although both growth rates are time-varying, they are assumed to be cointegrated. The analysis is Bayesian, which fully accounts for all sources of uncertainty. Comparison with results from a similar model for seasonally adjusted data indicates that the seasonal adjustment of the data significantly alters several aspects of the full model. First Version Received: January 2001/Final Version Received: February 2002 Send offprint requests to: Rob Luginbuhl?Correspondence to: Rob Luginbuhl     

Pro-cyclical effect of sovereign rating changes on stock returns: a fact or factoid?

This article examines the effect of changes in sovereign credit ratings and their outlook on the stock market returns of European countries at different phases of business cycle. Using standard four-factor model, it records a significant average marginal effect of credit rating announcements on stock market returns. Both magnitude and significance of the effect vary with business cycle and across announcement types. However, we do not find evidence of pro-cyclical effect of sovereign rating and outlook changes on stock returns. Our results show that stock markets react more negatively to rating downgrades in recovery phases and more positively to rating upgrades in contractionary period. Both results are statistically significant and robust to various sensitivity tests.