江淮汽车成功开拓哈萨克斯坦市场的经验与启示

产能合作是当前和未来促进中哈两国经济协同发展的核心方式,江淮汽车成功进入哈萨克斯坦,对于推进两国制造业产能合作具有重要意义.充分利用国家政策、对接哈萨克斯坦汽车工业发展战略和市场需求、选择恰当国际市场进入模式和营销策略、培植核心竞争力以及积极应对哈萨克斯坦市场的激烈竞争是江淮汽车成功进入哈萨克斯坦市场的关键因素.我国企业应有效对接哈萨克斯坦经济战略,积极参与中哈产能合作;精准目标市场定位,优化产品结构;选择合适的市场进入模式,积极开展本地化生产;不断提升企业的核心竞争力.     

湿热地区精装住宅室内甲醛和TVOC污染调查及分析

对宁波精装修后未入住的76户住宅进行甲醛和TVOC浓度检测.统计发现,甲醛和TVOC平均超标率为52.5％和59.1％,儿童房室内污染最严重,高温高湿气候加速甲醛释放,人造板家具比实木家具的污染超标率高3.4倍.     

MODELING SOVEREIGN RISKS: FROM A HYBRID MODEL TO THE GENERALIZED DENSITY APPROACH

Motivated by the European sovereign debt crisis, we propose a hybrid sovereign default model that combines an accessible part taking into account the evolution of the sovereign solvency and the impact of critical political events, and a totally inaccessible part for the idiosyncratic credit risk. We obtain closed‐form formulas for the probability that the default occurs at critical political dates in a Markovian setting. Moreover, we introduce a generalized density framework for the hybrid default time and deduce the compensator process of default. Finally, we apply the hybrid model and the generalized density to the valuation of sovereign bonds and explain the significant jumps in long‐term government bond yields during the sovereign crisis.     

Exchange Rate Pass-Through to Consumer Prices: The Increasing Role of Energy Prices

Open Economies Review - A number of researchers have found that the rate of exchange rate pass-through (ERPT) to domestic prices has declined substantially over the last few decades. We revisit...     

Brexit: How Will UK Agriculture Fare?

There is little doubt that Brexit would have significant implications for UK agriculture, a sector with strong trade links to the EU and strong reliance on CAP income support. This article reports preliminary results from employing a Computable General Equilibrium Model, a Partial Equilibrium Model and Farm Level Models to explore selected trade and domestic policy scenarios post‐Brexit. These allow for the estimation of changes in producer prices, production and farm incomes against a baseline scenario of continued EU membership. Under a Free Trade Agreement with the EU, agricultural impacts are relatively modest. By contrast, unilateral removal of import tariffs has significant negative impacts on prices, production and incomes. Adoption of the EU's WTO tariff schedule for all imports favours net importers (e.g. dairy) and harms net exporters (e.g. sheep). Given the strong dependence of most UK farms on direct payments, their removal worsens negative impacts of new trade arrangements and offsets positive impacts. Impacts vary across different types and sizes of farm, but also regionally. However, the period of adjustment to new trade and domestic policy conditions may prove very challenging for a large number of farm businesses.     

北方县级海绵城市建设模式研究 ——以迁安海绵城市建设为例

我国北方缺水县级海绵城市建设的深入推进是实施海绵城市建设工作的重要内容,但目前我国北方缺水县级市的海绵城市建设工作还处于探索创新阶段.迁安依托海绵城市建设契机,在坚持政府主导、专家团队支持、社会资本运作、群众参与、发展区域产业优势等方面,首创了"一三一"模式,并取得了探索性经验,为其他北方缺水县级城市的海绵建设提供了有益启示和经验借鉴.     

施工进度管理与控制研究

目前国内一些施工工程因为进度不达标而不得不推迟工期,产生工期延误现象,进而就会造成项目不必要的工期和经济损失.施工工程延期的影响因素复杂,作为建筑工程项目管理三大控制中的一环,进度控制直接对工程造价、建筑经济以及项目社会效益产生影响,文章在对工程项目进度一般理论研究的基础上,分析人为、环境、资源、资金等影响因素,并提出适应性解决方案,为工程项目的进度管理研究提供理论基础.     

水文地质调查在地热资源勘查中的应用

在经济的发展和城市化推进的过程中,不可避免地会对自然环境造成污染与破坏,因此,有必要对污染环境进行勘察与研究,进而解决其中存在的问题,保障人们长远的生存与发展利益.其中,污染环境的地质水文勘察工作,是环境管理与保护工作中的重要环节、关键内容,更是后续工作开展的重要先决条件.本文通过对污染环境地质水文勘察技术的分析与探讨,总结分析出更有利于开展这一工作的方法与策略,提高污染环境地质水文勘察技术的应用水平.     

Improving forecasting performance using covariate-dependent copula models

Copulas provide an attractive approach to the construction of multivariate distributions with flexible marginal distributions and different forms of dependences. Of particular importance in many areas is the possibility of forecasting the tail-dependences explicitly. Most of the available approaches are only able to estimate tail-dependences and correlations via nuisance parameters, and cannot be used for either interpretation or forecasting. We propose a general Bayesian approach for modeling and forecasting tail-dependences and correlations as explicit functions of covariates, with the aim of improving the copula forecasting performance. The proposed covariate-dependent copula model also allows for Bayesian variable selection from among the covariates of the marginal models, as well as the copula density. The copulas that we study include the Joe-Clayton copula, the Clayton copula, the Gumbel copula and the Student’s $t$-copula. Posterior inference is carried out using an efficient MCMC simulation method. Our approach is applied to both simulated data and the S&P 100 and S&P 600 stock indices. The forecasting performance of the proposed approach is compared with those of other modeling strategies based on log predictive scores. A value-at-risk evaluation is also performed for the model comparisons.