不同经济发展水平下创新要素对产业创新绩效的影响及政策启示

基于不同经济发展水平研究视角，选取新一代信息技术产业为研究对象，采用改进的Griliches-Jaffe知识生产函数模型，运用面板数据回归分析方法，利用《中国高技术产业统计年鉴》（2007-2017年）中电子及通信设备制造业统计数据进行实证研究，探究创新要素投入与创新绩效的关系。结果发现：对于新一代信息技术产业，在不同经济发展水平地区投入相同创新要素对创新绩效的影响存在一定差异，尤其体现在技术投入要素作用效果上。这就意味着，对经济发展水平不同地区使用相同的创新要素推动产业创新发展是低效的；不同发展水平地区有针对性地分配创新要素，对于实现创新要素最大效率、推动战略性新兴产业布局与发展尤其关键。最后，提出相应政策启示及建议。     

Operating efficiency in Chinese universities: An extended two-stage network DEA approach

The result shows that it accepts the null hypothesis. Namely, there is no significant difference in the operating efficiency of universities in different regions. That is to say, although the efficiency of the central and western universities is slightly better than that of the eastern universities in terms of the average efficiency, there is no significant efficiency difference among the eastern, central, and western regions statistically. Therefore, it shows a balanced development trend for the efficiency of universities in different regions.     

Using Machine Learning for measuring democracy: A practitioners guide and a new updated dataset for 186 countries from 1919 to 2019

We provide a comprehensive overview of the literature on the measurement of democracy and present an extensive update of the Machine Learning indicator of Gründler and Krieger (2016). Four improvements are particularly notable: First, we produce a continuous and a dichotomous version of the Machine Learning democracy indicator. Second, we calculate intervals that reflect the degree of measurement uncertainty. Third, we refine the conceptualization of the Machine Learning Index. Finally, we significantly expand the data coverage by providing democracy indices for 186 countries in the period from 1919 to 2019.     

An application of data envelopment analysis to evaluate the efficiency level of the operational cost of Brazilian electricity distribution utilities

This paper shows efficiency indices for 60 Brazilian electricity distribution utilities. The efficiency scores are gauged by three DEA models. For both models, these quantities are evaluated under different contexts. One treats with respect to the regulator perspective. The others examine an alternative approach based on cluster analysis and restrictions on factor weights. It is worth pointing out that these developments can reduce the information asymmetry and improve the regulator's skill to compare the performance of the utilities, a fundamental in incentive regulation schemes.     

Pattern mining in tourist attraction visits through association rule learning on Bluetooth tracking data: A case study of Ghent,Belgium

The rapid evolution of information and positioning technologies, and their increasing adoption in tourism management practices allows for new and challenging research avenues. This paper presents an empirical case study on the mining of association rules in tourist attraction visits, registered for 15 days by the Bluetooth tracking methodology. This way, this paper aims to be a methodological contribution to the field of spatiotemporal tourism behavior research by demonstrating the potential of ad-hoc sensing networks in the non-participatory measurement of small-scale movements. An extensive filtering procedure is followed by an exploratory analysis, analyzing the discovered associations for different visitor segments and additionally visualizing them in ‘visit pattern maps’. Despite the limited duration of the tracking period, we were able to discover interesting associations and further identified a tendency of visitors to rarely combine visits in the center with visits outside of the city center. We conclude by discussing both the potential of the employed methodology as well as its further issues.     

农村减贫效率及其空间差异研究——基于DEA-ESDA模型的分析

[目的]通过对2011~2015年间全国以及各区域层面的农村减贫效率进行测度,探讨其空间差异及变化特征。[方法]文章采用投入导向的DEA-BCC模型测算农村减贫效率值,并借助探索性数据分析法(ESDA)对农村减贫效率的空间差异和变化展开分析。[结果](1)我国农村减贫综合技术效率相对较低,未能充分挖掘现有资源投入的潜力,纯技术效率整体偏小是造成综合技术效率较低的重要原因;(2)省际农村减贫效率在2011~2015年整体呈现出先减后增的趋势,并表现出西高东低的阶梯形空间布局;(3)农村减贫的综合技术效率存在正自相关性,高高聚集的区域主要集中在西部地区,低低聚集区域呈现由东北向京津都市区移转的趋势;(4)减贫综合技术效率的热点区域主要集中在西北与西南两大区域,且具有较强的稳定性;冷点区域主要分布在江西、安徽及东部沿海地区,较为稳定的冷点区域主要集中在东北及环渤海地区。[结论]我国农村减贫效率存在显著的空间异质性的特征,需要精准地识别出局部性致贫因素,因地制宜地制定出具有区域联动特点的空间扶贫开发策略。     

Efficiency,total factor productivity and returns to scale in a sustainable perspective: An analysis in the European Union at farm and regional level

For global sustainability it is imperative to find a balance across the three main components of sustainable development which are the economic, social and environmental aspects. However, it is not a simple task to make these contexts compatible, usually because of economic pressures which transform them into opposed objectives. This framework occurs across several dimensions within society and the economy, where the agricultural sector is not an exception. The objective of this study is to analyse the efficiency, total factor productivity and returns to scale in an economic, social and environmental perspective in farms of the European Union (EU) regions through Data Envelopment Analysis (DEA) approaches. The research concerning the returns to scale will be complemented by the Keynesian models. Data obtained from the European Union Farm Accountancy Data Network (FADN) was considered. The results show that in maintaining or improving the levels of production in farms, it is often possible to greatly reduce, in some cases, the consumption of fertilizers and crop protection products. On the other hand, from a social perspective, some European Union regions are more generous in the salaries paid to farming workers and absorb more labour, which in a European context of unemployment, may be an interesting way to realistically look at and be engaged in the agricultural planning in a sustainable way, founding a balanced trade-off among the economic, social and environmental dimensions.     

An adaptive approach to forecasting three key macroeconomic variables for transitional China

The macroeconomic forecasts for emerging economies often suffer from the constraints of instability and limited data. In light of these constraints, we propose the use of a local autoregressive (LAR) model with a data-driven estimation window, i.e., a local homogenous interval, that is adaptively identified to strike a balance between information efficiency and stability. When applied to three key macroeconomic variables of China, the LAR model substantially outperforms the alternative models for various forecast horizons of 3 to 12 months, with forecast error reductions of between 4% and 64% for the IP growth, and between 1% and 68% for the inflation rate. The one-quarter ahead performance of the LAR model matches that of a well-known survey forecast. The patterns of the identified local intervals also coincide with the characteristic evolution of the gradual reforms and monetary policy shifts in China. In short, the LAR model is suitable for not only forecasting, but also the real-time monitoring of the effects of regime and policy changes in emerging economies.     

On estimating long-run effects in models with lagged dependent variables

A common procedure in economics is to estimate long-run effects from models with lagged dependent variables. For example, macro panel studies frequently are concerned with estimating the long-run impacts of fiscal policy, international aid, or foreign investment.Our analysis points out the hazards of this practice. We use Monte Carlo experiments to demonstrate that estimating long-run impacts from dynamic models produces unreliable results.Biases can be substantial, sample ranges very wide, and hypothesis tests can be rendered useless in realistic data environments. There are three reasons for this poor performance. First, OLS estimates of the coefficient of a lagged dependent variable are downwardly biased in finite samples. Second, small biases in the estimate of the lagged, dependent variable coefficient are magnified in the calculation of long-run effects. And third, and perhaps most importantly, the statistical distribution associated with estimates of the LRP is complicated, heavy-tailed, and difficult to use for hypothesis testing. While many of the underlying problems have been long-known in the literature, the continued widespread use of the associated empirical procedures suggests that researchers are unaware of the extent and severity of the estimation problems. This study aims to illustrate their practical importance for applied research.