山高皇帝远:地理距离与上市公司股价崩盘风险的经验证据

鉴于信息不对称程度、制度实施成本和心理文化差异，文章提出"监管距离"假说，认为监管者和被监管者之间距离远近可以影响监管效果。实证分析中国沪深上市公司数据，文章从非对称风险视角出发，研讨了上市公司注册地距所在地中国证监会派出机构的地理距离对公司层面的股价崩盘风险的影响。我们发现，监管机构与上市公司总部的地理距离越远，该上市公司股价的崩盘风险越大。进一步分析发现，如果开通高铁或者上市公司所在地社会信任水平足够高，那么监管距离和崩盘风险的正相关关系是不显著的；如果监管负担严重或政府效率低下，那么监管距离和崩盘风险之间正相关关系更为显著。文章认为，地理距离具有监管信息效应、监管威慑效应和监管执行效应，能够影响股价崩盘风险。也就是说，"山高皇帝远"可以改变上市公司行为，提高金融监管效率不应忽视非正式制度的影响。     

Business-to-business selling in the post-COVID-19 era: Developing an adaptive sales force

The COVID-19 pandemic has changed how salespeople interact with customers and with business-to-business (B2B) organizations. Organizations must confront the shifts in how their salespeople operate. Recent research recommends firms develop an adaptive sales force to address disruptions like a pandemic and be prepared to meet such challenges in the future. Based on interviews with marketing and sales executives, we explore how firms have responded to these interconnected changes during the COVID-19 pandemic and offer insight into best practices deployed across industries.     

How have the dependence structures between stock markets and economic factors changed during the COVID-19 pandemic?

This study investigates how the dependence structures between stock markets and economic factors have changed during the COVID-19 pandemic using the dynamic model averaging approach. A series of economic factors such as commodity markets, cryptocurrency, monetary policy, international capital flows, and market uncertainty indices are considered. We find that the importance of economic variables and the sign and size of their coefficients are significantly different from those before the COVID-19 pandemic. The stock markets are most influenced by economic factors during the COVID-19 outbreak.     

Multi-criteria analysis of economic complexity transition in emerging economies: The case of Paraguay

Like many emerging economies, the productive structure of the Paraguayan economy is not complex. It relies extensively on low value-added activities in the primary sector such as agriculture and cattle ranching. These activities have a lower return in terms of economic and social benefits than other potential productive activities and do not contribute to increasing capability accumulation. In this paper we present a tool to support the identification of strategic sectors and products which if taken advantage of, could leverage development through the accumulation of productive capabilities. Our guiding question is: Which productive sectors should be promoted to foster economic development in Paraguay through a transition towards a more complex economy? To answer this question, we use concepts from the Economic Complexity theory to identify new products and cluster them based on the Product Space methodology for the determination of potential products and combine it with the Analytic Hierarchy Process (AHP) for multicriteria analysis considering multiple criteria. In doing so, our proposed methodology contributes to both the Economic Complexity and the AHP literature. Through this combination, we tackle the multiplicity of juxtaposed criteria, which should be considered at the prioritization stage in the crafting of economic restructuring measures according to the country's capabilities. Our evaluation showed that the combination of the approaches is useful, and for Paraguay's case, it helped identify sectors, which, if promoted by policymakers, could help boost economic development through complexity and capability accumulation.     

Threshold effects of terms of trade on Latin American growth

This paper investigates nonlinear relationships between terms of trade volatility (totvol) and economic growth in 14 Latin American economies from 1997 to 2014. In the 2000s, Latin American countries experienced accelerated economic growth often attributed to commodity price booms. We split the sample into two regimes based on totvol thresholds determined by bootstrap techniques. Fixed effects, instrumental variable and dynamic panel regressions address endogeneity in trade growth, subject to traditional economic channels such as domestic investment, population growth, exchange rate, government size, and institutions. We find statistically significant thresholds and stronger trade-growth links during the 2000s commodity boom and in larger economies.     

BEYOND THE STARS

It is frequent to hear in economic seminars or read in academic papers that an effect is economically significant or economically important. Yet, the economic literature is vague on what economic importance means and how it should be measured. In this paper, I show that existing measures of economic importance are flawed and misused. I derive a new metric that measures, in percentage terms, the contribution of each explanatory variable to deviations in the dependent variable, ceteris paribus. As an illustration, the method is applied to study the determinants of migration and the determinants of fertility.     

长江经济带中三角地区农业结构的分析与优化对策

[目的]从宏观、中观和微观3个层面深入分析长江经济带中三角地区湖北、湖南和江西3省的农业产业结构及其各产业差异性和相对优势及其竞争力。[方法]在宏观层面运用了传统的基尼系数分析3个省份历史发展上的地区经济水平差异,判断3个地区经济发展是否存在虹吸效应;从中观层面运用区位熵指数分析法分析区域农业产业结构,从农畜林渔等方面判断各区域产业专业化水平程度;从微观层面运用偏离—份额分析法(SSM)分离出3个地区的各部门产业的优势及其竞争力。[结果]区域内的经济差异变化呈不断增大的趋势,基尼系数不断扩大;湖北的种植业、渔业和农林牧渔服务业,湖南的种植业、林业、畜牧业和农林牧渔服务业,江西的林业、渔业都较中三角地区对应的子产业的区位熵指数高;江西木材和竹加工业和烟草业具有较大的产业竞争优势,湖北的茶叶、水产和瓜果疏菜产业优势明显,湖南地区农业产业综合优势主要在于烟草、水果、肉类以及木材和竹类加工业。[结论]通过比较地区农业产业竞争优势,提出发展地区产业特色,合理布局全域农业产业,提高农产品附加收益,稳固对结构优化的资金支持等对策建议。     

成渝经济区生态农业对区域经济影响分析

[目的]区域经济发展反映经济各个方面的综合发展状况,探讨其影响因素以确定区域未来经济的发展方向,为进一步规划发展提供科学依据。[方法]先构建生态农业评价指标体系再采用层析分析法确定权重,结合线性加权和函数计算生态农业评价指数,通过相关分析法分析生态农业各个指标与区域经济的关系,最终确定生态农业对成渝经济区经济的影响程度。[结果]生态农业指标中评价指数大于0.9是森林覆盖率,介于0.8~0.7的包括投入产出比、土地生产率、农业科技贡献率、万人拥有的科技人员、劳动生产率、化肥施用量。且生态农业中各个指标与GDP都正相关,其中森林覆盖率、人均收入增长率、农业科技贡献率和万人拥有的科技人员与GDP显著相关,对区域经济的影响最大。[结论]成渝经济区经济受生态农业的影响,进一步选取更多生态农业相关因素,对于全面促进区域经济持续发展具有十分的重要现实意义。     

能源效率、环境污染与中国经济发展方式转变

以往研究虽然关注了能源效率与经济发展之间的关系,但却忽略了能源利用过程中环境污染的改善对经济发展方式转变的影响。本文将环境变量纳入能源效率分析框架内,采用EBM-DEA模型测算了中国各地区能源效率,并利用动态空间面板模型,实证考察了环境约束下的能源效率对中国经济发展方式转变的影响。研究结果显示,中国经济发展方式具有明显的空间相关性和路径依赖性;与未考虑环境污染相比,环境约束下的能源效率对经济发展方式转变的影响更为明显,这也在一定程度上表明,如果不考虑能源效率提升的环境污染改善效应,将会低估其对经济发展方式转变的影响。本文结论为提升中国能源效率水平,加快经济发展方式转变提供政策启示。     

Economic forecasting with evolved confidence indicators

We present a machine-learning method for sentiment indicators construction that allows an automated variable selection procedure. By means of genetic programming, we generate country-specific business and consumer confidence indicators for thirteen European economies. The algorithm finds non-linear combinations of qualitative survey expectations that yield estimates of the expected rate of economic growth. Firms’ production expectations and consumers’ expectations to spend on home improvements are the most frequently selected variables – both lagged and contemporaneous. To assess the performance of the proposed approach, we have designed an out-of-sample iterative predictive experiment. We found that forecasts generated with the evolved indicators outperform those obtained with time series models. These results show the potential of the methodology as a predictive tool. Furthermore, the proposed indicators are easy to implement and help to monitor the evolution of the economy, both from demand and supply sides.