中国城市居民收入和储蓄增长对家庭能耗碳排放的区域异质性及政策应对

估计和预测城市居民收入变化对家庭能源消费碳排放的影响,对城市家庭消费部门构建低碳能源供应体系,应对气候变化具有重要意义。论文首先估计了中国284个地级以上城市的家庭三类能源消费的直接碳排放量,建立了面板固定效应模型来识别城市家庭能耗碳排放增长和变化的驱动因素。研究结果表明:城市居民收入的快速增长与储蓄水平的提高对于家庭碳排放有显著影响;城市家庭收入和储蓄的增加会抑制家庭燃气碳排放的产生,但对于城市家庭用电碳排放和城市家庭采暖碳排放,则表现出显著的推动作用。此外,研究还发现了家庭碳排放的影响因素存在显著的区域异质性。     

Observability and incentive in organizations

The paper shows that producer-owned firms are more efficient in quality provision than investor-owned firms if input quality is observable, while they are less efficient when the input quality is unobservable and the size of the organization is large.     

Pace of work and piece rates

Using cross-industry survey data, I examine how the determinants of the pace of work affect the probability of using piece rates. Internal determinants raise the likelihood of piece rates, while response to external needs lowers the probability.     

黄龙洞旅游开发对洞内生态环境和人的影响研究

通过对黄龙洞年内不同季节定点测定，同时与对旅游影响还不大的龙王洞对比测定，作者发现黄龙滑滑内空气CO2浓度的明显变化主要受客流量的影响。旅游旺季和黄金周客流量急剧增长带来的洞内空气CO2浓度大幅度增长，有利于岩溶作用，但洞内黑暗、高湿、低温的生态环境，对洞内工作人员身体健康有害。洞穴内岩溶景观的变化，主要受漫长的自然岩溶过程的影响，与洞内开发旅游活动的关系不大，但与洞顶山地植被保护状况有密切关系。     

中国各地区集约经济运营绩效的DEA评价

DEA方法是进行相对有效性评价的一种方法。其最先提出并被广泛应用的C2R模型可同时判断决策单元是否同时满足技术有效和规模有效。通过利用DEA模型对我国30个地区的集约经营效率进行了分析评价,并探讨了制约我国各地区集约经济发展的重要因素及其对策问题。     

出口企业更清洁吗？——基于微观企业数据的再考察

基于工业企业数据以及环境统计数据,构建1998-2007年面板数据实证分析出口对企业二氧化硫排放强度的影响。回归结果显示：相较于非出口企业,出口企业二氧化硫排放强度较低;企业出口强度越高时二氧化硫排放强度越低。异质性分析发现：企业所属行业以及企业所在地区差异均会对二氧化硫排放强度产生影响。具体表现为,污染密集型制造业行业中,出口企业比非出口企业更为清洁;相较于其他地区而言,东部地区企业出口对二氧化硫排放强度的降低幅度更为显著。在排除两控区环境规制因素对回归结果的影响,并且通过IV(2SLS)以及PSM-DID等方法处理内生性问题后,本文的回归结果依然稳健。机制分析表明：出口企业一方面通过提高新产品产值——R D,另一方面通过提高全要素生产率,降低了企业的二氧化硫排放强度。此外,通过对企业出口状态的改变(广延边际)和企业出口强度的改变(集约边际)的比较发现,出口企业二氧化硫排放强度低的主要驱动因素在于广延边际而非集约边际。     

维格列汀与二甲双胍合用治疗糖尿病的药物经济学研究

目的比较维格列汀、吡格列酮、格列美脲分别与二甲双胍合用治疗2型糖尿病时的效果、成本及成本-效果。方法运用Markov模型对三种治疗方案的终身治疗成本及效用（期望寿命、质量调整寿命年）进行经济学评价,通过文献资料和专家问卷咨询获得临床、生命质量、并发症年治疗成本等数据,进行敏感度分析。结果维格列汀、吡格列酮、格列美脲分别与二甲双胍合用治疗2型糖尿病分别延长11.02、10.96、10.90个质量调整生命年,而生命周期中三种治疗方案的治疗费用分别为124892元、134135元、126010元。敏感度分析证明了结果的可靠性。结论与吡格列酮、格列美脲合并二甲双胍质量相比,维格列汀合并二甲双胍治疗获得的健康效果更好,而治疗成本更低。     

Empirical study on the determinants of CO2 emissions: evidence from OECD countries

This article empirically investigates the Environmental Kuznets Curve (EKC) for CO₂ emissions in the cases of 11 OECD countries by taking into account the role of nuclear energy in electricity production. The autoregressive distributed lag approach to cointegration is employed as the estimation method. Our results indicate that energy consumption has a positive impact on CO₂ emissions in most countries in the study. However, the impact of trade is not statistically significant. The results provide evidence for the role of nuclear power in reducing CO₂ emissions only in some countries. Additionally, although the estimated long-run coefficients of income and its square satisfy the EKC hypothesis in Finland, Japan, Korea and Spain, only Finland's EKC turning point is inside the sample period of the study, providing poor evidence in support of the EKC hypothesis.     

Time-varying correlations in oil,gas and CO2 prices: an application using BEKK,CCC and DCC-MGARCH models

Previous literature has identified oil and gas prices as being the main drivers of CO₂ prices in a univariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) econometric framework (Alberola et al., 2008; Oberndorfer, 2009). By contrast, we argue in this article that the interrelationships between energy and emissions markets shall be modelled in a Vector Autoregressive (VAR) and Multivariate GARCH (MGARCH) framework, so as to reflect the dynamics of the correlations between the oil, gas and CO₂ variables overtime. Using the Baba–Engle–Kraft–Kroner (BEKK), Constant Conditional Correlation (CCC) and Dynamic Conditional Correlation MGARCH (DCC-MGARCH) models on daily data from April 2005 to December 2008, we highlight significant own-volatility, cross-volatility spillovers, and own persistent volatility effects for nearly all markets, indicating the presence of strong Autoregressive Conditional Heteroscedasticity (ARCH) and GARCH effects. Besides, we provide strong empirical evidence of time-varying correlations in the range of [?0.3;?0.3] between oil and gas, [?0.05;?0.05] between oil and CO₂, and [?0.2;?0.2] between gas and CO₂, that have not been considered by previous studies. These findings are of interest for traders and utilities in the energy sector, but also for a broader applied economics audience.     

The heterogeneity of carbon Kuznets curves for advanced countries: comparing homogeneous,heterogeneous and shrinkage/Bayesian estimators

We investigate Carbon Kuznets Curves (CKC) relationships for advanced countries grouped in policy relevant groups – North America and Oceania, South Europe, North Europe – by means of various homogeneous, heterogeneous and shrinkage/Bayesian panel estimators. We try to provide an answer to the question ‘how sensitive are the CKC estimates to changes in the level of parameters' heterogeneity?’. We do find that in coherence with their ‘policy and economic’ commitment to carbon reductions and environmental market-based instruments implementation, bell shapes are present only for northern EU, which leads the group of advanced countries. The other two lag behind. We show for the first time that CKC shapes are present if we net out Europe of the southern and less developed countries. This is coherent with the Kuznets paradigm. The negative side of the tale is that they characterize a bunch of few countries. Other advanced countries lag behind and are far from reaching a CKC dynamics. Heterogeneous and Bayesian estimators clearly show this, with the EU presenting turning points closely around $13?000 per capita Gross Domestic Product (GDP). Heterogeneous panel estimates also show that for lagging countries presumed bell shapes turn into linear relationships. The stability of outcomes across models is stronger when we compare heterogeneous rather than homogeneous models. If it is compared with other studies, our analysis highlights a relative lower variability across specifications.