Does bank ownership affect lending behavior? Evidence from the Euro area

We analyze the differences in lending policies across banks characterized by different types of ownership, using micro-level data on Euro area banks during the period 1999–2011 to detect possible variations in bank lending supply responses to changes in monetary policy. Our results identify a general difference between stakeholder and shareholder banks: following a monetary policy contraction, stakeholder banks decrease their loan supply to a lesser extent than shareholder banks. A detailed analysis of the effect among stakeholder banks reveals that cooperative banks continued to smooth the impact of tighter monetary policy on their lending during the crisis period (2008–2011), whereas savings banks did not. Stakeholder banks’ propensity to smooth their lending cycles suggests that their presence in the economy has the potential to reduce credit supply volatility.     

Advocacy and political convergence under preference uncertainty

We study the formation of advocacy groups and how they can impact policy outcomes by revealing information about voters׳ preferences to uninformed political candidates. We conduct a laboratory experiment based on a two-candidate spatial electoral competition setting where the policy preferences of voters are (initially) unknown and change over time. In the control treatment candidates learn about the preferred policy of the median voter through the voting outcome of elections. In the advocacy treatments, voters can organize themselves into advocacy groups in order to reveal their policy preferences. We find that voters often overcome the collective action problem of forming an advocacy group. In fact, we observe the formation of both informative advocacy groups, which convey new information, and uninformative advocacy groups, which do not. Overall, advocacy groups significantly speed up the convergence to the preferred policy of the median voter. However, advocacy does not lead to higher earnings as the gains from faster convergence are offset by the costs of group formation.     

Rivaroxaban for non-valvular atrial fibrillation and venous thromboembolism in the Netherlands: a real-world data based cost-effectiveness analysis

Background: Non-vitamin K antagonist oral anticoagulants (NOACs) have been included in international guidelines as important alternatives to vitamin K antagonists (VKAs) for the treatment of venous thromboembolism (VTE) and stroke prevention in non-valvular atrial fibrillation (NVAF). Meanwhile, in the Netherlands, NOACs are widely used next to VKAs. The objective of this study is to estimate the cost-effectiveness of treatment with rivaroxaban compared to VKAs in NVAF and VTE patients in the Netherlands, using data from international prospective observational phase IV studies.

Methods: Two models were developed to represent NVAF and VTE patients, populated with patients from the XANTUS (NCT01606995) and XALIA (NCT01619007) international prospective observational studies. The 1-year cost-effectiveness of rivaroxaban use, compared to VKAs, was explored in a population consisting of NVAF and VTE patients (base case) as well as for four scenarios with sub-populations: NVAF patients only, VTE patients only, NVAF patients with unstable international normalized ratio (INR), and NVAF patients using an INR self-measuring device.

Results: In the base case, rivaroxaban saved €72,350 and gained 21 quality-adjusted life-years (QALYs) in a simulation of 2,000 patients over the use of VKAs. Ergo, rivaroxaban was dominant over VKAs. The probabilistic sensitivity analysis showed a probability of 85% for rivaroxaban being dominant and 100% at a willingness-to-pay threshold of €20,000/QALY. Rivaroxaban appeared to be dominant in all scenarios as well, except for the NVAF-patients-only scenario where the incremental cost-effectiveness ratio (ICER) was €157/QALY.

Conclusions: In patients with NVAF or VTE, rivaroxaban treatment is likely to be cost-effective and a potentially cost-saving alternative to VKA in the Netherlands.     

基于动态面板数据模型分析FDI的环境效应

外商直接投资在对中国经济增长起到积极推动作用的同时,我们也不可忽视其可能会对我国环境造成的影响。文章通过构建环境污染综合指数,并且以东中西部为三个横截面建立动态面板数据模型来分析外商直接投资对各个地区环境的影响。结果显示,外商直接投资和东部中部地区的环境污染指数之间有正相关关系,和西部地区的环境污染指数之间是一个负相关关系。     

基于Excel的道路工程计算技术

围绕数据组织、数据的联动检索技术、Excel高级函数、Excel自定义函数、Excel VBA程序的开发过程,系统地建立了基于Excel的道路工程计算的框架模板。     

An Application of the Dynamic Network DEA Model: The Case of Banks in Taiwan

ABSTRACT

In this study, we apply the dynamic network slack-based measure data envelopment analysis model (DNSBM) to measure the efficiency of Taiwanese banks during the period 2005–11. Using the network structure, we define intellectual capital creation capability as one of the production stages. In order to capture the dynamics of the transformation process, the nonperforming loans and loan loss reserves are defined as carryover items. This study offers sufficient information for managers to understand not only the overall performance of their banks but also the efficiency of each production stage and the dynamic changes of the overall and divisional efficiencies.     

The relevance of commuting zones for regional spending efficiency

We use data envelopment analysis (DEA) efficiency scores to show that clustering municipalities into encompassing regional clusters improves spending efficiency of single stand-alone municipalities. We propose a new geographic aggregation based on municipalities-to-municipalities commuting flows, defined using hierarchical cluster analysis. Our example for Portugal shows that from an output-oriented perspective between 83% and 98% of municipalities would increase their efficiency scores, while from an input-oriented perspective between 86% and 98% of municipalities would also be better off in terms of efficiency. Then using a linear regression model, we find that population increases positively affects the efficient scores (via scale economies). Also, increases in the share of high-educated and poorer residents leads to higher efficiency scores.     

On the measurement of investment types: Heterogeneity in corporate tax elasticities

This paper contributes to debates about the appropriate characterisation of heterogeneous investment types and to what extent different investment motives affect the responsiveness to corporate taxation. In particular, we employ and refine a methodology to better evaluate the tax elasticity of investment types. Using a combination of both firm‐specific information and sector‐specific information from input–output tables, we discuss how to classify investment as non‐related, horizontal, vertical and complex types. First, we point out to what extent the resulting classification depends on assumptions made by the researcher. Second, we employ an ample set of classifications and find that non‐related investment reacts stronger to corporate taxation, whereas horizontal investment is less responsive, though, significant negative tax semi‐elasticities turn out for the subset of manufacturing industries. To address inherent characteristics of vertical and complex investment, we extend the methodology and find that, by and large, stronger business motives reduce the tax responsiveness of investment to a larger extent. Given the current debates about substantial corporate tax reforms, it is all the more important to recognise that corporate tax effects can vary fundamentally between countries, driven by country‐specific differences in their composition of industries and investment types.     

移动网络数据中大数据处理的关键技术探索

最近几年以来,我国科技水平持续提升,计算机网络技术也逐渐在各行各业中获得了广泛运用,这也使得信息技术的深度融合发展受到一定的促进,数据规模愈发庞大,在此背景下,开始演变成大数据供不应求的状况。为此,国内陆续推出了一系列相关的管理法规与条例,同时扩大了对大数据的探究创新力度,有效提升了移动通信网络处理数据的速度,这同时促使国内移动通信网络中有关大数据的研究内容更为明晰,由此可知,针对大数据的相关研究具有一定必要性。