The determinants of commercial banking profitability in low-, middle-, and high-income countries

Using a broad bank-level dataset and the GMM estimator technique described by Arellano and Bover (1995), this paper analyses how bank-specific characteristics, macroeconomic variables, and industry-specific factors affect the profitability of 10,165 commercial banks across 118 countries over the period from 1998 to 2012. Grouping the countries according to three income levels, we show that the determinants of bank profitability included in our model can explain existing profitability differences among commercial banks in low-, middle-, and high-income countries. The profitability determinants vary quite widely across the different levels of income in terms of significance, sign and size of the effect. The level of income has thus an important impact on the determinants of bank profitability.     

Free trade agreement and transport service trade

This study investigates the effects of free trade agreements (FTAs) on trade in transport services using OECD data from 2003 to 2006. Our analysis found that FTAs had a positive overall impact on transport services for multiple countries (i.e., 26 home and 56 partner countries). The resulting positive overall impact assures that, even with the challenges associated with different layers of services and the obstacles formed by generally low trade openness in the sector, the provisions in FTAs (e.g., national treatment and market access for goods and services) promote transport service trades. Our findings suggest that the provisions in FTAs encourage economic agents to increase engagement in transport services because of expanded openness of the physical movement of goods across international borders.     

技术创新、金融创新与经济增长——基于中国省际面板数据

本文从实证分析层面对金融创新、技术创新与经济增长之间的作用关系进行探讨。基于我国 2000~2015 年省级面板数据，采用GMM估计方法，利用动态面板模型进行实证检验。结果表明：技术创新对经济增长的影响显著为正，单独的金融创新对经济增长起抑制作用，二者的交互作用则对经济增长起显著性正向作用。脱离实体经济的金融创新将抑制经济增长，也会间接阻碍技术创新对经济增长的影响。本文结合当前经济形势，从金融机构与创新企业相接轨共同提高创新水平、培养创新型人才等角度提出建议。     

环渤海地区区域经济空间网络关联结构研究

采用网络分析方法，对1995—2014年环渤海地区区域经济空间网络关联结构进行分析，研究发现：环渤海地区区域经济空间网络关联特征显著，分为“辽宁”和“京津冀鲁”两个子网络；网络密度稳步上升，但仍然较低；核心区域的经济比重有所降低，但份额始终较大；网络效率在波动中趋降，空间溢出效应趋于显著。其中，北京、天津、济南等9地属于“主受益”板块，石家庄、保定、潍坊等19地属于“经纪人”板块，沈阳、大连、鞍山等4地属于“双向溢出”板块，而秦皇岛、承德、葫芦岛等12地属于“净溢出”板块。产业结构转型升级、控制FDI区域差异以及投资多元化等有利于环渤海地区增强区域经济空间关联。应多途径构建区域经济关联通道，打造“环型”网状关联经济，并通过产业转型升级和经济多元化发展增进区域经济空间关联。     

我国农作物秸秆综合利用现状及焚烧碳排放估算

[目的]为加快推进秸秆资源化利用工作,有效缓解因秸秆焚烧带来的环境问题。[方法]将全国划分为黄淮海区、西北区、东北区、东南区、西南区五大区域,对各类农作物秸秆进行了统计分析,研究了秸秆产生量、秸秆资源密度、秸秆利用结构、秸秆焚烧碳排放量。[结果]全国秸秆理论资源量达到10.4亿t,可收集量达到9.0亿t,玉米、水稻和小麦3类农作物秸秆占总量的79.19%,黄淮海区秸秆产量最高,占总量的33.41%。秸秆已利用量为7.21亿t,综合利用率达到80.11%,其中肥料化、饲料化、基料化、燃料化、原料化利用量占已利用量的比例分别为53.93%、23.42%、4.98%、14.27%、3.40%,形成了农用为主的利用格局,但不同秸秆种类综合利用率和利用结构存在显著差异。全国秸秆资源密度和人均占有量分别为523.57kg/667m~2和1.75 t,东北区显著高于全国平均水平,西南区和东南区则显著低于全国平均水平。根据环保部卫星遥感监测的露天焚烧火点数比例估算,2015年我国秸秆露天焚烧量约为8 110万t,总碳排放量约为3 450万t,其中东北地区约占74.1%。[结论]我国秸秆综合利用的重点和难点在东北地区,进一步推动区域秸秆实现全量利用,对于促进低碳农业发展,应对气候变化有着十分重要的意义。     

Is the protection of beach and dune vegetation compatible with tourism?

The paradox of development vs. protection and conservation of the coasts highlights the need to determine if tourism and conservation can be compatible rather than opposite activities. We analyzed the spatial and temporal changes in vegetation cover, composition and diversity in three beaches located in the state of Veracruz (Mexico) with different levels of tourism activity (Natural, Trailer Park and Hotels). We calculated tourist density and evaluated vegetation cover, species richness and diversity and analyzed the changes before and after three holiday seasons (winter, spring and summer). The Natural site had the highest vegetation cover (42.8 m²), species richness (14) and diversity (1.50), and Trailer Park the lowest (4.9 m², 8 species, and 0.897 respectively). The BACI (Before-After-Control-Design) analysis showed no significant differences before and after the holiday seasons. Our results show how low and medium density tourism can be compatible with the protection of beach and coastal dune vegetation.     

Integrating partitioned prices via computational estimation

This paper introduces computational estimation to the literature on consumers’ numerical cognition. Computational estimation involves simplifying an arithmetic problem via mathematical procedures to produce an approximate answer. Employing calculation knowledge and approximation together, consumers are likely to use computational estimation as it is relatively accurate while saving cognitive effort compared to calculating values. Three studies applied to partitioned prices in the form of a base price and a percentage discount, demonstrate that when faced with this numeric integration task, the strategy consumers undertake is dependent on the characteristics of the numerals with discounts that are round or close to round being associated with greater use of computational estimation. Further, when employing computational estimation, consumers arrive at more accurate, and lower, price estimates in which they place more confidence than when using alternative an integration strategy. As a result, discounts that are near a round value are preferred to those that are not; a result that is dependent upon the use of computational estimation.     

DSGE pileups

The sampling distribution of estimators for DSGE structural parameters tends to be non-normal and/or pile up on the boundary of the theoretically admissible parameter space. This calls into question both the reliability of asymptotic approximations and the presumption of correct specification. This paper seeks to develop a conceptual framework for understanding how these phenomena arise, and to provide pragmatic methods for dealing with them in practice. The results are presented in three examples and a medium scale DSGE model.     

Is ex-post credit risk affected by the cycles? The case of Italian banks

The objective of this research is to empirically examine if both credit and business cycle affect the ex-post credit risk (i.e. non-performing loans) in the banking system of Italy for the period 1995Q1–2014Q1. The increase in NPLs post-2008 has put into question the robustness of many European banks and the stability of the whole sector. It still remains a serious challenge, especially in Italy which is one of the countries that hit by the financial crisis. By employing fixed and random effects and a dynamic GMM estimation as econometric methodologies I find results that underline common causes for NPLs. Higher NPLs in Italy are mostly due to worse macroeconomic conditions (i.e. bad phase of business cycle) and due to excess credit. Through a Granger causality test, my arguments found even more support. Such findings can be helpful when designing macro-prudential as well as NPL resolution policies.     

基于GIS的铁路密度空间分异研究——以新疆铁路交通网络为例

城市对外交通中,铁路是发展较早的交通运输方式。本文以新疆的铁路交通网络为依据,以道路密度为指标,利用Arc GIS的叠加分析和空间分析功能,研究新疆铁路交通网络的空间分异,并分析新疆各区域人口、生产总值差异与铁路密度差异之间的相互关系。结果表明:(1)新疆铁路密度差异显著,大体呈现"南北低中部高"的趋势;(2)新疆各地区铁路密度与人口分布、生产总值高度正相关。