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.     

Measuring benefits from spatially-explicit surface water quality improvements: The roles of distance,scope, scale,and size

Programs to improve water quality do not improve all water bodies equally. Evaluation of the benefits of such programs must account for where improvements occur and the relative magnitude of improvements that occur in different places. This study uses a choice experiment survey to explore how the value to a household of a surface water quality improvement varies as a function of (i) the distance between the household and the affected streams and rivers, (ii) the degree to which the quality of the water has been improved, (iii) how many stream and river miles have been improved, and (iv) the sizes of the affected streams and rivers. Results show evidence that value declines with distance in an approximately linear way, weak evidence that large rivers are worth more than small rivers, and no evidence that willingness-to-pay is nonlinear in either the degree of water quality improvement or the number of stream miles improved. These results indicate that it may be defensible in applied work to value small, spatially-explicit water quality improvement projects independently and then sum over projects.     

科技服务业产出测算：指标确立、数据收集与未来预测

科技服务业产出测算是对科技服务业产出数据的统计与分析,加强科技服务业产出数据的规范统计和应用分析可为我国政府调整产业政策提供重要数据支撑。以科技服务业产出测算为研究对象,结合学者观点、国家标准及各级政府相关产业政策,提出将分支产业作为初始指标的横向统计思路,构建科技服务业产出测算指标体系。在数据收集方面,强调要做好“收”与“填”两个基本工作;在指标确立和数据收集基础上,进一步提出未来预测的两种方法,以此作为科技服务业产出数据预测的初步探索;提出应从统一数据统计标准、完善数据调查与公开制度、加强数据资源开发3个方面建立健全我国科技服务业产出数据测量与管理体制机制。     

经济开放与货币需求:国际金融风险及持币成本的测度

在中国开放经济体制下的基准货币需求模型中,本文将源于国际金融市场的持币成本设为遗漏潜变量,并构建特定的国际金融综合指数(CIFI)作为该潜变量的测度。借鉴机器学习与测度理论,本文利用对数误差修正模型提出了分步降维的CIFI构造算法,构造了长期CIFI和短期CIFI。结果表明,CIFI构造中的无监督降维步骤有助于减少高维金融数据中的冗余信息。实证分析发现,国际机会成本对中国货币需求具有规律性的前导影响,而在2007至2008年国际金融危机期间,央行的应急措施对长期CIFI所代表的非均衡冲击起到明显的阻截效果,对短期CIFI的影响基本是持续不变的。通过综合指数构造与宏观货币需求模型的算法连接,可以利用CIFI的构成结构从前导时间与影响强度两方面追踪冲击货币需求的国际金融风险的具体来源,这为宏观决策者监测国际金融市场提供了颇有规律的信息。在方法论上,本研究为如何利用模型监测国际金融市场影响宏观经济开辟了一条新路。     

为何言路难开?领导拒谏构念维度与形成机理探究

员工谏言不仅具有建设性,而且具有挑战性和结果的不确定性,使得领导者可能纳谏也可能拒谏。然而,现有研究主要关注员工谏言与领导纳谏,却忽略了领导拒谏。本研究在回顾员工谏言及相关研究的基础上发现,领导者会对员工谏言进行建设性评估和威胁性评估,具有建设性和防御性两种行为目的。基于此,首先,从领导者的双元行为目的出发探讨了领导拒谏的概念与维度,依据发展视角、人际视角和防御视角将领导拒谏划分为:指导员工驱动的拒谏、维持关系驱动的拒谏、保证权威驱动的拒谏。其次,分析了领导拒谏的形成机理,从谏言内容、谏言员工和谏言行为三方面考察领导者对员工谏言的认知评估过程,详细讨论了组织距离如何通过领导注意间接影响领导拒谏,并探讨了权力距离在领导注意与领导拒谏之间所具有的调节作用。本研究有助于推动领导拒谏的理论构建,拓展认知评估理论的应用,而且能为组织管理实践给予一定的参考与借鉴。     

European systemic credit risk transmission using Bayesian networks

The analysis of systemic credit risk is one of the most important concerns within the financial system. Its complexity lies in adequately measuring how the transmission of systemic default spreads through assets or financial markets. The transmission structure of systemic credit risk across several European sectoral CDS is studied by dynamic Bayesian networks. The new approach allows for a more advanced analysis of systemic risk transmission, including long-term and more complex relationships. The modelling reveals as relevant only relationships between the original series and one- and two-lagged series. Network structure learning displays a robust and stationary underlying risk transmission structure, pointing to a consolidated transmission mechanism of systemic credit risk between CDSs. Between 5 % and 40 % of sectoral CDS series variances are explained by the network relationships. The modelling allows us to ascertain which relationships between the CDS series show positive (amplifier) and negative (reducer) effects of systemic risk transmission.     

Impact of the Fast Track Land Reform Programme (FTLRP) on agricultural production: A tobacco success story in Zimbabwe?

The study ascertained the impact of the Fast Track Land Reform Programme (FTLRP) in Zimbabwe on tobacco production. The Chow Test, Vector Error Correction Model (VECM) and the Vector Error Granger-Causality Test were applied. The results reveal that there was a structural break in tobacco sales in the year 2000. Furthermore, in the long-run, area under tobacco production had a positive impact whilst number of tobacco producers had a negative impact on tobacco sold pre-FTLRP. Post-FTLRP, area of tobacco and number of tobacco producers had negative impact. In addition, the FTLRP induced an 8.94 % increase in the speed of adjustment in correcting the long-run equilibrium in tobacco sales. In the short-run, the FTLRP caused a percentage increase in the area of tobacco production and number of tobacco producers to induce a 0.65 % and 0.76 % increase in the tobacco sales, respectively. Area of tobacco production and number of tobacco producers Granger-caused tobacco sales in the pre-FTLRP period. Post-FTLRP, the number of tobacco growers Granger-caused tobacco sales. It is concluded that the FTLRP had an impact on tobacco sales, mainly through the number of tobacco growers. The study recommends the specialisation and training of the new farmers to improve productivity.     

Predicting bank insolvencies using machine learning techniques

Proactively monitoring and assessing the economic health of financial institutions has always been the cornerstone of supervisory authorities. In this work, we employ a series of modeling techniques to predict bank insolvencies on a sample of US-based financial institutions. Our empirical results indicate that the method of Random Forests (RF) has a superior out-of-sample and out-of-time predictive performance, with Neural Networks also performing almost equally well as RF in out-of-time samples. These conclusions are drawn not only by comparison with broadly used bank failure models, such as Logistic, but also by comparison with other advanced machine learning techniques. Furthermore, our results illustrate that in the CAMELS evaluation framework, metrics related to earnings and capital constitute the factors with higher marginal contribution to the prediction of bank failures. Finally, we assess the generalization of our model by providing a case study to a sample of major European banks.     

Is heterogeneous capital depreciation important for estimating firm-level productivity? Evidence from Chinese manufacturing firms

This paper contributes to the existing literature on estimating firm-level production functions. Using Chinese manufacturing survey data, we employ the firm-level heterogeneous capital depreciation rate to measure firms’ investment and assess its role using Olley and Pakes (1996) (OP) production function estimation technique. Although there is some ongoing debate on the econometric soundness of the OP technique, we argue quantitatively that the heterogeneous depreciation rate muffles the measurement error associated with the key input demand investment. In our sample, it significantly narrows the gap of total factor productivity (TFP) estimates between the OP technique and a state-of-the-art estimation method that works without investment. We further reveal that the improved performance primarily originates from the dynamic evolution in the distribution of the capital depreciation rate.     

新会计准则中公允价值计量的探析

我国新颁布的企业会计准则中第一次大量引用了公允价值计量,引起了会计学界的广泛争议。本文重点分析了公允价值计量引入新会计准则的逻辑分析、具体表现、特点和应对措施。意在理论研究和实务操作方面更好地把握公允价值计量这一引人入胜的观念。