经济政策不确定性、区域经济复杂度与企业创新行为

构建包含宏观经济政策不确定性指标、区域经济复杂度和上市公司特征变量“宏观-区域-企业”的实证面板数据，在理论分析经济政策不确定性对企业创新行为作用机理的基础上，以区域经济复杂度为视角，对经济政策不确定性与企业创新行为作用机制进行再检验。研究发现：经济政策不确定性对企业创新存在正向激励综合效应，同时，区域经济复杂度不仅能够促进企业创新行为，而且能够强化经济政策不确定性对企业创新行为的影响即抑制负向作用而强化正向作用。考虑内生性，通过替换核心变量检验稳健性以保证研究结论可靠，并且，研究企业特征发现，高科技企业和非高科技企业存在差异。     

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。     

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.     

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。     

Distributive cycles and endogenous technical change in a BoPC growth model

Our purpose in this paper is to expand Goodwin's (1967) distributive cycle model to an open economy framework in a way that incorporates the balance-of-payments constraint on growth. We do so by allowing technical change to be endogenous to the cyclical dynamics of the system and by adopting an independent investment function. We show that a Hopf-Bifurcation analysis establishes the possibility of persistent and bounded cyclical paths both for a 3D and a 4D extension of the model. Some numerical simulations are performed based on the analytical models developed. Motivational empirical evidence is also provided for Thirlwall's law using a sample of 16 OECD countries.     

Impact of an urban growth boundary across the entire house price spectrum: The two-stage quantile spatial regression approach

This study provides evidence for the impact of an urban growth boundary (UGB) on house prices. The study employs a two-stage quantile spatial regression method on a dataset that inventories sales transactions of single-family houses within two miles of either side of the eastern boundary of the primary UGB in King County, Washington. The results show that while the UGB decreases house prices across the entire house price spectrum, the impact is uneven; it is most pronounced for houses in the 5th to 8th decile of prices. These findings should encourage policy makers to adopt sub-housing-market-level policy approaches to address UGB and other urban and regional development policies’ potential impacts on house prices.     

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.