Investments,Credit, and Corporate Financial Distress: Evidence from Central and Eastern Europe

Although they are instrumental for economic development, productivity-enhancing corporate investments may increase the financial vulnerability of companies, especially in an economic and financial crisis. We employ an instrumental probit model with the aim of finding evidence for the investment and credit patterns that led companies into financial distress during the global financial crisis 2009–2010. The company-level micro-data for our study on three Central and East European countries—Hungary, Bulgaria, Romania and two Baltic countries, Latvia and Lithuania—originates from two independent surveys, the Business Environment and Enterprise Performance Survey conducted in 2008 and the Financial Crisis Survey conducted in 2009/2010. Both were carried out jointly by the EBRD and the World Bank. Our results emphasize a substantial adverse impact from investment intensity and debt financing on company financial soundness during a crisis. On top of that, we discover a strong non-linear pattern in the sensitivity of company distress to its investment-financing nexus.     

Globalization and Outward Foreign Direct Investment

While recent research into foreign direct investment (FDI) has focused on examining the importance of institutions, corruption, money laundering, and tax havens, the role of globalization on FDI has not yet been explored. This research investigates the impacts of globalization on outward FDI. We find that both overall globalization and its economic and social dimensions significantly positively influence outward FDI flows. We also demonstrate that beyond the level of globalization, corruption, money laundering, and the status of a country as a tax haven, cross-country similarity also plays an important role. Accordingly, policies specifically designed to increase the transparency of outward FDI flows should be required to address money laundering and the existence of tax havens.     

Export Sophistication: A Dynamic Panel Data Approach

In this article, we analyze export sophistication based on a large panel dataset (2001–2015; 101 countries) and using various estimation algorithms. Using Monte Carlo simulations, we evaluate the bias properties of estimators and show that GMM-type estimators outperform instrumental-variable and fixed-effects estimators. Based on our analysis we document that GDP per capita and the size of the economy exhibit significant and positive effects on export sophistication; weak institutional quality exhibits negative effect. We also show that export sophistication is path-dependent and stable even during a major economic crisis, which is especially important for emerging and developing economies.     

The Role of Total Factor Productivity Growth in Middle-Income Countries

We examine the importance of total factor productivity (TFP) growth in middle-income countries (MICs) based on cross-country panel data for the period of 1975–2014. We find that TFP growth contributed significantly to a country’s upward transition from middle-income to high-income country group. The TFP growth model reveals that the catch-up effect, human capital, smaller population, weak currency, and research and development growth are significant sources of TFP growth. We do not find a systematic difference in the TFP growth models for MICs. In analyzing the role of factors influencing TFP growth at different income stages, strengthening innovative activities and building innovative capacities are important in overcoming the challenges that MICs face when transitioning to the high-income group. Governments of upper MICs need to initiate reform to motivate innovation by optimizing national R&D systems, and redesigning the educational system to target promoting innovation.     

Risk Awareness of Interpersonal Trust and Entrepreneurship in China: Evidence from Survey Data

This paper aims to build a theoretical framework for the influence of risk awareness of interpersonal trust (RAIT) on entrepreneurship, and explores the influence of RAIT on entrepreneurship with the micro survey data from the Chinese General Social Survey (CGSS) 2010–2013. The study found that, individuals with higher level of RAIT, their probability of starting new business will increase significantly, and with every increase of RAIT level, the probability of business venturing increase almost 4.0%. No mediation effects of information screening and cooperative mechanism are found in the relationship between RAIT and entrepreneurship. Moreover, during the venturing process, risks accompanying interpersonal trust cannot be reduced by social input; the reduction occurs only in eastern China where the economic system and the industrial development standards are more comprehensive and mature. This paper contributes to the literatures in the following two areas: it provides new evidence on how to deal with risks in the entrepreneurship process that accompanying interpersonal trust; meanwhile, it provides an explanatory mechanism on how the risk awareness affects business venturing.     

中国经济波动的产出和通胀效应 ——基于供求冲击相关的SVAR模型分析

本文结合产出缺口-通胀形式的菲利普斯曲线（AS曲线）,构建了产出缺口和通 胀率的SVAR模型,并将识别结果同B-Q约束条件下的识别结果进行比较,以此来探究我国近 三十多年来宏观经济系统中需求冲击和供给冲击对产出和通胀动态的效应。主要得出以下结 论：第一,供求冲击之间高度相关;第二,需求冲击是我国通胀波动的决定性因素,并且存在 持久稳定的效应。第三,供给冲击是我国经济增长的绝对主导力量。第四,我国存在相对陡峭 的菲利普斯曲线（AS曲线）。第五,产出缺口与同比CPI对我国经济状况的拟合效果最好。     

“丝路经济带”九省市经济金融竞争力评价

深入剖析丝绸之路沿线国内段九省市的综合发展实力,探索不同发展战略定位下省 区市竞合协同发展路径,对全面发展丝绸之路经济带具有重要意义。本文从经济发展竞争力、 环境设施与可持续发展竞争力、科技创新与财富竞争力、金融发展竞争力、对外开放竞争力五 个维度建立指标评价体系,运用分类主成分分析法全面衡量九个省市经济金融发展的分项和综 合竞争力,将九省市分为三个发展梯度,形成资源聚集与要素流动的直观剖析。在此基础上,利 用聚类分析法得出丝绸之路经济带区域经济关联的着力点与经济发展的增长极,并最终得出处 于不同梯度省区市间开展基于优势竞争力的产业间合作的三大有效路径。     

Optimizing the credit term decisions in supply chain finance

We study a credit term determination problem in the context of a supplier-buyer supply chain. The supplier's credit term decision is simultaneously made with its production and inventory decisions, and most importantly, it is impacted by the buyer's order quantity. We present a new game-theoretic framework to model this problem, which captures the interaction between the supplier's credit term decision and the buyer's order decision in a multi-period setting. An exact method based on nonlinear programming is implemented to obtain the optimal solutions. We apply our methodologies on a real world case. The computational results show that our approach significantly outperforms the heuristics with fixed credit terms, and either a short or a long credit term can be sub-optimal for the supplier in profitability. Our work offers the first data-driven model and solution approach that assists purchasing and supply managers to make optimal dynamic credit term decision in conjunction with production, ordering and inventory decisions in a game-theoretic setting.     

Do monetary subjective well-being evaluations vary across space? Comparing continuous and discrete spatial heterogeneity

Using subjective well-being estimations, this study analyzes whether compensating variations vary across space using a cross-sectional data set from Chile. To achieve this goal, it describes and compares two econometric ways of modelling unobserved spatial heterogeneity. Both approaches allow compensating variations to vary across spatial units by assuming some distribution a priori. One method assumes that the spatial heterogeneity can be represented by a discrete distribution (a group of regions that share the same coefficient) and the other that the preferences can be represented by a continuous distribution (each region has a different coefficient). The results show that focusing just on the average estimates of compensating variations, as the applied studies have done so far, masks useful local variation. More empirical studies are needed to assess the advantages and disadvantages of both econometric approaches and how their results compare across a wide range of conditions and samples.     

Innovation performance and the role of clustering at the local enterprise level: a fuzzy-set qualitative comparative analysis approach

ABSTRACT

This study, utilizes an innovative methodological approach, fuzzy-set Qualitative Comparative Analysis (fsQCA), investigating the drivers of heterogeneous geographies characterizing English Local Economic Partnerships (LEPs). The fsQCA technique offers a novel configurational alternative to regression-based approaches investigating the effects of clustering in conjunction with firm-level innovation, university third-sector activity (TSA) and entrepreneurship, on LEPs innovation performance. The findings, offer contributions to the theories of industrial clusters and innovation, regional innovation systems, knowledge spillovers and entrepreneurial university innovation within LEPs. First, supporting fsQCAs, no individual variable generates either a positive/negative innovation outcome. Second, while all positive innovation recipes include presence of the cluster variable, for negative innovation recipes, only one does not identify absence of clustering as relevant. Given that the cluster variable does not appear in any recipes without at least one of the other variables suggests activity concentration does not exist in isolation to generate innovation outcomes without other localized conditions existing, e.g. firm-level innovation. Third, there is evidence for the non-cluster-based aspects of knowledge spillover theory of entrepreneurship with respect to university activity and the entrepreneurial university concept. Instead, roles of entrepreneurship and university TSA, while important, appear to be more peripheral and geographically context specific.