Drivers and barriers to cross-border e-commerce: Evidence from Spanish individual behavior

This paper explores the determinants of the individual's decision to perform cross-border e-commerce (CBeC). The European Union (EU) is especially interested in the promotion of CBeC because it is an important tool in its strategy to achieve the Digital Single Market in Europe. In this paper official data is used from a representative survey of 16,209 individuals on ICT usage by households and individuals that was carried out in Spain by the National Institute of Statistics (INE) for the year 2016. Using a standard neoclassical utility maximization framework, and logistic regression techniques, the results show that being a male is positively related to the probability of practicing CBeC. Education is positively and significantly related to the probability of being involved in CBeC with EU countries. Computer and Internet Skills are significant and positive factors in explaining CBeC (either with EU countries or with the rest of the world). The variable “how often the consumer sees other customer reviews before buying online”, has a positive effect. Foreign nationality also increases the likelihood of using CBeC. To promote CBeC in Spain measures towards developing digital skills, Internet trust and use of online information reviews of goods and services are discussed.     

A hybrid information approach to predict corporate credit risk

This study proposes a hybrid information approach to predict corporate credit risk. In contrast to the previous literature that debates which credit risk model is the best, we pool information from a diverse set of structural and reduced‐form models to produce a model combination based on credit risk prediction. Compared with each single model, the pooled strategies yield consistently lower average risk prediction errors over time. We also find that while the reduced‐form models contribute more in the pooled strategies for speculative‐grade names and longer maturities, the structural models have higher weights for shorter maturities and investment grade names.     

Data-based mechanistic modelling and forecasting globally averaged surface temperature

The main objective of this paper it to model the dynamic relationship between global averaged measures of Total Radiative Forcing (RTF) and surface temperature, measured by the Global Temperature Anomaly (GTA), and then use this model to forecast the GTA. The analysis utilizes the Data-Based Mechanistic (DBM) approach to the modelling and forecasting where, in this application, the unobserved component model includes a novel hybrid Box-Jenkins stochastic model in which the relationship between RTF and GTA is based on a continuous time transfer function (differential equation) model. This model then provides the basis for short term, inter-annual to decadal, forecasting of the GTA, using a transfer function form of the Kalman Filter, which produces a good prediction of the ‘pause’ or ‘levelling’ in the temperature rise over the period 2000 to 2011. This derives in part from the effects of a quasi-periodic component that is modelled and forecast by a Dynamic Harmonic Regression (DHR) relationship and is shown to be correlated with the Atlantic Multidecadal Oscillation (AMO) index.     

我国农村产业融合发展的效率评价

[目的]为了进一步提升农村产业融合发展效率,提升农业质量效益和竞争力、增强农村发展活力、促进农民持续增收,[方法]文章根据我国农村产业融合发展的投入产出指标数据,利用DEA方法对我国31个省(自治区、直辖市)农村产业融合效率进行了科学的分析与测算,[结果]研究表明,我国农村产业融发展的总体效率偏低。从综合效率看,仅有天津等7个省(自治区、直辖市)的综合效率值高于0. 5;从纯技术效率看,仅有江苏等8个省(自治区、直辖市)的纯技术效率高于0. 5;从规模效率看,西藏、甘肃、青海3个省(自治区)的规模效率低于0. 5。提升农村产业融合发展效率仍有较大的空间。[结论]应从进一步加大对农村产业融合发展的资金投入力度、着力优化农村产业融合发展的资金投入结构、建立农村产业融合发展效率考评制度等方面提升农村产业融合发展效率,促进农村产业融合快速发展。     

A nowcasting model for Ecuador: Implementing a time-varying mean output growth

We propose a model to nowcast the annual growth rate of real GDP for Ecuador, whose economy lacks timely macroeconomic information for some key variables and has gone through unstable periods due to its dependence on oil exports. Our specification combines monthly information for 30 macroeconomic and financial variables with quarterly information for real GDP in a mixed-frequency approach. Our setup includes a time-varying coefficient on the mean annual growth rate of output to allow the model to incorporate prolonged periods of low or high growth. The model produces more accurate nowcasts of real output growth in pseudo out-of-sample exercises than a nowcasting model that assumes a constant mean real GDP growth rate. We also conduct sensitivity analyses on our nowcasting model within the time-varying mean setup and find that including financial variables can be detrimental to the performance of the proposed model.     

The cointegrated vector autoregressive model with general deterministic terms

In the cointegrated vector autoregression (CVAR) literature, deterministic terms have until now been analyzed on a case-by-case, or as-needed basis. We give a comprehensive unified treatment of deterministic terms in the additive model $X_t=\gamma Z_t+Y_t$, where $Z_t$ belongs to a large class of deterministic regressors and $Y_t$ is a zero-mean CVAR. We suggest an extended model that can be estimated by reduced rank regression, and give a condition for when the additive and extended models are asymptotically equivalent, as well as an algorithm for deriving the additive model parameters from the extended model parameters. We derive asymptotic properties of the maximum likelihood estimators and discuss tests for rank and tests on the deterministic terms. In particular, we give conditions under which the estimators are asymptotically (mixed) Gaussian, such that associated tests are ${\chi }^2$-distributed.     

Does e-government performance actually boost citizen use? Evidence from European countries

For many years, it was believed that higher-performing e-government features would boost citizen use of e-services. However, this straightforward proposition had never been tested. Using a survey of over 28,000 citizens across 32 European countries, we examined the effect of e-government performance on citizen use. Theoretically, a better-designed and maintained government website should be used more, but it was reject by multilevel model estimates. We found that performance was negatively related to citizen use of e-information and e-services, while e-participation use was insignificant. The implications of our findings on future efforts to increase the uptake of e-government are also discussed.     

山东省耕地后备资源变化及驱动因素分析

[目的]揭示耕地后备资源变化规律及其驱动因素是进行耕地后备资源合理保护、开发利用的重要基础,但目前对于耕地后备资源变化及驱动因素的研究较为匮乏。[方法]文章以山东省为例,基于2003年和2015年两期耕地后备资源数据库,在分析耕地后备资源时空变化的基础上,采用空间回归模型分析了其变化的驱动因素。[结果]2003~2015年期间,山东省集中连片耕地后备资源减少了30.81万hm~2,其中可开垦土地减少24.97万hm~2,可复垦土地减少5.84万hm~2。[结论]总人口、文盲率、农民人均纯收入、建设用地扩张速度、第一产业产值占总产值比重等是山东省耕地后备资源变化的显著性驱动因素,并且总人口和建设用地扩张的驱动作用最大,受教育程度和产业结构调整的作用次之,农民人均纯收入变化对耕地后备资源变化的影响最小。"宏观统筹协调,异地代补"是解决"耕地后备资源空间分布不均衡、供需不匹配",实现耕地占补平衡、高效合理的开发利用耕地后备资源的必经之路。但异地代补的数量比例和质量应严格控制,并注重对补充耕地地区的经济补偿和政策倾斜,逐步缩小与发达地区之间的差距。     

农民宅基地退出差异性受偿意愿及其影响因素分析

研究目的:宅基地退出工作能否顺利推进与退地补偿息息相关,研究宅基地退出中农民差异性受偿意愿及其影响因素,以服务决策。研究方法:基于重庆市890份农民实地调查数据,应用多元离散选择模型(Logit)进行定量研究。研究结果:(1)传统农区的农民更愿意选择货币补偿;城乡结合部(街道办)的农民更愿意选择安置补偿;农民修建补偿选择率总体偏低,区位差异并不明显;(2)农民货币受偿意愿影响因素主要包括受教育程度、家庭主要成员是否定居城镇、非农务工收入、新居住地适应性;(3)农民安置受偿意愿影响因素主要包括年龄、农房是否自住、退地补偿是否有截留、村基础设施状况;(4)农民修建受偿意愿影响因素主要包括农房造价、农房是否新建、退地补偿是否有截留;(5)影响农民受偿意愿的因素存在较大差异,同一因素可能对农民选择受偿意愿产生不同的影响,但没有一个自变量同时对三个因变量产生显著影响。研究结论:应针对农民受偿意愿差异及其影响因素,实行产异化的补偿措施,在经济发展相对滞后的传统地区,强化村落基础设施建设的同时,加大现金补偿力度。对于经济较为发达、区位条件较好的城乡结合部地区,应加大安置补偿力度,以保障退地农民的居住权。