Performance of microfinance institutions in Europe—Does social capital matter?

This paper investigates performance drivers of microfinance suppliers in Europe. As such suppliers, in contrast to advanced microfinance suppliers in developing economies, typically focus on uncollateralized microcredit services to individuals at the margins of society and of labor markets, we draw on the theory of social capital and empirically investigate the role that social capital may play in the overall performance of European microfinance suppliers. We build a unique, unbalanced panel data set of 302 microfinance service providers in Europe covering the years 2008–2015, and measure their performance in terms of credit risk, financial and social performance, and efficiency. Pursuing an econometric approach, we test a series of hypotheses using various measures of conditions conducive to building social capital on both the institutional and the country level, such as the client base of a microfinance supplier and the level of cultural fractionalization in a society. Our findings confirm that a higher intensity of social capital is positively associated with all areas of the performance of microfinance suppliers in Europe. Our conclusions could help in the design and launch of microfinance institutions in those European countries in which microfinance markets are developed not at all or only to a very limited extent. Our paper thus contributes to the nascent literature on microfinance in developed economies by applying and extending the theoretical framework and empirical models on social capital and microfinance that were originally elaborated for developing economies.     

The relative income hypothesis

Despite its theoretical dominance, the empirical case in favor of the permanent income hypothesis is weak. Contrary to one of its basic implications, a growing body of evidence suggests that rich households save a higher proportion of their permanent income than poor households. We propose an overlapping-generations economy where households care about relative consumption. As a result, an individual's consumption is driven by the comparison of his lifetime income and the lifetime income of his reference group; a permanent income version of Duesenberry's (1949) relative income hypothesis. Across households the savings rate increases with income while aggregate savings are independent of the income distribution.     

The effect of stabilization fund to rescue stock market based on expected return-capita circulation equation

This paper builds an expected return-capital circulation equation to explore the impact of using the stabilization fund to rescue the stock market when it crashes. We find that the stock stabilization fund buying the underlying stocks can restrain the sharp decline of the stock index, but it is also easy to promote the fluctuation in prices of small-cap stocks. Therefore, we suggest that the government in use of stock stabilization fund to take control of the stock market crash should not only buy underlying stocks in the index but also pay attention to prevent implicit stock disaster in the market.     

Research on the time-varying effects among green finance markets in China: A fresh evidence from multi-frequency scale perspective

Green finance is an essential instrument for achieving sustainable development. Objectively addressing correlations among different green finance markets is conducive to the risk management of investors and regulators. This paper presents evidence on the time-varying correlation effects and causality among the green bond market, green stock market, carbon market, and clean energy market in China at multi-frequency scales by combining the methods of Ensemble Empirical Mode Decomposition Method (EEMD), Dynamic Conditional Correlation (DCC) GARCH model, Time-Varying Parameter Vector Autoregression with Stochastic Volatility Model (TVP-VAR-SV), and Time-varying Causality Test. In general, the significant negative time-varying correlations among most green finance markets indicate a prominent benefit of risk hedging and portfolio diversification among green financial assets. In specific, for different time points and lag periods, the green finance market shock has obvious time-varying, positive and negative alternating effects in the short-term scales, while its time delay and persistence are more pronounced in the medium-term and long-term scales. Interestingly, a positive event shock will generate positive connectivity among most green finance markets, whereas a negative event including the China/U.S. trade friction and the COVID-19 pandemic may exacerbate the reverse linkage among green finance markets. Furthermore, the unidirectional causality of “green bond market - carbon market - green stock and clean energy markets” was established during 2018–2019.     

Assessment of the sustainable development of rural minority settlements based on multidimensional data and geographical detector method: A case study in Dehong,China

In a developing country, paying attention to the sustainable development of rural areas is conducive to the development of the entire country. Ethnic minority areas are an important part of China's economic and social development. Owing to a lack of relevant statistical data, most previous studies in this area have focused on the sustainable development of rural areas or the development of ethnic minorities, but have not studied the sustainable development of rural ethnic minorities. The development of rural ethnic minorities is worthy of attention. In this study, we took Dehong as the study area. First used toponyms to accurately identify the rural minority areas and then calculated a grid of settlement density. Second, we considered the digital number (DN) value of the visible infrared imaging radiometer suite (VIIRS) as a measure of the development of the region and digital elevation model (DEM), net primary productivity (NPP), normalized difference vegetation index (NDVI), and gross domestic product (GDP) data as the indicators of terrain, climate, ecological, and economic factors, respectively. Finally, linear regression and the geographical detector method were used to determine the weight of the factors for constructing a sustainable development index (SDI) to quantitatively analyze the sustainable development and influencing factors of each minority nationality. The factors evaluated using linear regression and the geographical detector method were ranked as follows: NDVI > elevation > GDP > slope > NPP > settlement density. The results demonstrate that of the five main ethnic minorities in Dehong, Dai and Jingpo have higher SDI, followed by Achang, Lisu and De'ang. In addition, we provide some suggestions for ethnic minorities in Dehong.     

A data-driven decision support system with smart packaging in grocery store supply chains during outbreaks

The unexpected emergence of the COVID-19 pandemic has changed how grocery shopping is done. The grocery retail stores need to ensure hygiene, quality, and safety concerns in-store shopping by providing “no-touch” smart packaging solutions for agri-food products. The benefit of smart packaging is to inform consumers about the freshness level of a packaged product without having direct contact. This paper proposes a data-driven decision support system that uses smart packaging as a smart product-service system to manage the sustainable grocery store supply chain during outbreaks to prevent food waste. The proposed model dynamically updates the price of a packaged perishable product depending on freshness level while reducing food waste and the number of rejected customers and maximising profit by increasing the inventory turnover rate of grocery stores. The model was tested on a hypothetical but realistic case study of a single product. The results of this study showed that stock capacities, freshness discount rate, freshness period, and quantity discounts significantly affect the performance of a grocery store supply chain during outbreaks.     

The era of Omni-learning: Frameworks and practices of the expanded human resource development

According to the ever-changing organizational environment, we also adopt an ever-expanding HRD in contents and scope. Focusing on the drivers of the recent HRD reforms, the growing demand for organizational agility and holistic capabilities of human resources is driving the need for change, and the pandemic crisis is pushing the revolutionary changes of HRD. Such trends of the expanded HRD can be characterized as a ‘march toward Omni-learning’. In specific, there are at least four noticeable and intertwined waves of HRD reforms toward Omni-learning: (1) embracing holistic capabilities such as benchmarking, modeling, forecasting, and backcasting (BMFB); (2) integrating working and learning by promoting on-the-job learning (OJL), on-the-life learning (OLL), and on-the-life training (OLT); (3) standardizing communication tools such as LMF (logic tree; multi-dimensional matrix/map; flowchart) and EEOSP (everything/everyone on the same page); and (4) diversifying communication space-time across diverse places (close; remote) and times (synchronized; a-synchronized). And all the HRD waves are commonly facilitated and promoted by technological breakthroughs of artificial intelligence (AI) and the metaverse. Beyond the current innovations of HRD, no one would be certain about the answer to the question “What’s next?”. But what is certain is that HRD will continue to be deepened and widened as long as human resources are needed to respond to the ever-changing organizational environment.     

Twitter’s daily happiness sentiment,economic policy uncertainty,and stock index fluctuations

This research applies quantile Granger causality and impulse-response analyses to evaluate the causal linkages among Twitter’s daily happiness sentiment, economic policy uncertainty (EPU), and S&P 500 indices across the U.S. stock market cycles. We present notable evidence of bi-directional causality among cyclical components of Twitter’s daily happiness sentiment, economic policy uncertainty, and S&P 500 indices for most quantiles. The causal linkage of Twitter’s daily happiness sentiment and S&P 500 indices identified in this study reconciles the so-called Easterlin Paradox and Easterlin Illusion arguments from previous studies on income-happiness relationship. Moreover, given a high (low) EPU level, the positive (negative) impulse-response effects between the Twitter’s daily happiness sentiment and the S&P 500 indices are justified during a stock market bust cycle, but the signs of these correlations change to negative (positive) during a stock market boom cycle. These findings imply that investors’ hedging strategies can be linked to the surveillance of the Twitter’s daily happiness sentiment index.     

Advancing purchasing as a design science: Publication guidelines to shift towards more relevant purchasing research

Due to rapidly changing business environments, purchasing and supply management (PSM) organisations are constantly confronted with new problems impacting organisational performance. PSM research can address these problems through design science research. Design science is also regarded as the science of the artificial. Design science research is a methodology that aims to systematically generate knowledge for the design, synthesis, testing, and evaluation of human-made artefacts (e.g., tools, interventions, policies) that solve practical problems. PSM artefacts such as the purchasing portfolio matrix invented by Kraljic (1983) represent a valuable opportunity to solve problems in the PSM discipline. However, our artificial-intelligence (AI)-based analysis of the discipline's flagship journal, the Journal of Purchasing and Supply Management (JPSM), indicates that design-oriented publications in PSM are underrepresented, accounting for less than 4% of the total publications. We argue that existing PSM research should be complemented with more design-oriented research, and address the following research question: How can PSM scholars publish more design-oriented research? Our objectives are to (1) provide arguments for advancing PSM as a design science, (2) nurture a better understanding of design science research as a methodology, and (3) propose publication guidelines that enable researchers to present design-oriented research in a management journal.     

Orchestrating distributed data governance in open social innovation

Open Social Innovation (OSI) involves the collaboration of multiple stakeholders to generate ideas, and develop and scale solutions to make progress on societal challenges. In an OSI project, stakeholders share data and information, utilize it to better understand a problem, and combine data with digital technologies to create digitally-enabled solutions. Consequently, data governance is essential for orchestrating an OSI project to facilitate the coordination of innovation. Because OSI brings multiple stakeholders together, and each stakeholder participates voluntarily, data governance in OSI has a distributed nature. In this essay we put forward a framework consisting of three dimensions allowing an inquiry into the effectiveness of such distributed data governance: (1) openness (i.e., freely sharing data and information), (2) accountability (i.e., willingness to be held responsible and provide justifications for one's conduct) and (3) power (i.e., resourceful actors' ability to impact other stakeholder's actions). We apply this framework to reflect on the OSI project #WirVsVirus (“We versus virus” in English), to illustrate the challenges in organizing effective distributed data governance, and derive implications for research and practice.     

Public spending and economies of scale in partial fiscal decentralized governments: The case of Chile

This article evaluates economies of scale in local public spending in Chile, emphasizing the country's geographical features and high fiscal heterogeneity. We leverage balanced panel data for ten years and 307 municipalities in order to estimate the population level at which a reduction in the average cost of local public goods provision occurs and to differentiate between levels of market potential. We follow a theoretical model of cost efficiency that considers spatial interactions and spillover effects among neighboring jurisdictions. Our findings suggest that Chilean municipalities reach an optimum population level at around 700,000 inhabitants, which is high considering that only two cities qualify. When differentiating for levels of economies of scale according to levels of market potential, municipalities with a low potential reach their optimum at around 28,000 inhabitants, those with a medium potential reach it at approximately 124,000, and those with a high potential reach it at approximately 680,000.     

Who Gains from the Demographic Dividend? Forecasting Income by Age

Changes in the population age structure are known to influence the total income per person, but little is known about whether the changes are equally shared across the population or are concentrated on particular age groups and/or birth cohorts. The answer to this question has potentially important implications for income inequality, human capital investment, and fertility decision-making. We propose a new model of intergenerational transfers which distinguishes between the effects of changes in population structure and the effects of changes in family age structure. Using age-specific data from annual income and expenditure surveys of Taiwan between 1978 and 1998, we show that changes in age structure have had a very favorable effect on Taiwan's income growth. The gains are not equally shared by all age groups, however. Children and young adults have benefited the most, while the elderly have benefited the least. The population and family age structures have independent effects on per capita income; the effect of the population age structure is most important. Generational differences in per capita income are closely related to intergenerational differences in earnings, suggesting only a weak form of altruism. Finally, we predict that, on average, population aging will adversely influence the per capita income growth in Taiwan in the coming decades.     

Can innovation improve income inequality? Evidence from panel data

Income inequality is a source of social instability and armed conflict, which in turn are detrimental to economic development. This study examines the role of innovation in income inequality in twenty-three developed countries, using a panel mean group estimator that takes cross-sectional dependence into consideration. Three income inequality indicators are used: the Standardized World Income Inequality Database (SWIID), the University of Texas Inequality Project (UTIP), and the Estimated Household Income Inequality (EHII). The innovation indicators are patent applications and patents granted. The empirical results based on the common correlated effect mean group (CCEMG) reveal that innovation widens income inequality. We also investigate whether the innovation–income inequality nexus is subject to a country’s level of globalization and financial development. The findings suggest that the interaction terms between innovation with these two variables have positive effects on income inequality, whereas innovation failed to reduce income inequality. Globalization and financial development are found to drive income inequality. The empirical results are robust to different income inequality and innovation measures as well as estimation techniques.     

Foreign capital inflows and poverty linkages in South Asia: Do the forms of capital inflows matter?

The relationship between foreign direct investment and poverty reduction has received modest attention in the empirical literature. However, little is known about the relative significant impact of different forms of capital inflows on poverty reduction. This study attempts to investigate the impact of different forms of capital inflows (foreign direct inflows, portfolio equity and portfolio debt inflows) on poverty reduction in major South Asian economies during the post-reform period. The capital inflows-poverty nexus is explored using panel econometric methods robust to cross-sectional dependence. Our empirical results show that while portfolio equity inflows exert a favorable impact on poverty reduction, foreign direct inflows and debt inflows fail to influence poverty. The panel causality results demonstrate that portfolio equity inflows also support poverty alleviation via stimulating economic growth and trade openness. The findings of our study highlight the importance of considering the differential welfare impacts of different forms of capital inflows while implementing capital account liberalization.     

Debt financing and maintenance expenditure: Theory and evidence on government-operated toll roads in China

Transportation infrastructure is the foundation of economic growth, and the existence of high-quality roads is inseparable from their durable maintenance. However, the burden of heavy debt has brought risks to maintenance management and distorted resource allocation. This study builds a two-stage optimal theoretical model under different debt-financing constraints in China, who has the longest expressway mileage of any country in the world. We establish the two principles of “spend-and-debt” and “debt-and-spend” to demonstrate the substitution effect and the complementary effect of debt financing on maintenance, respectively. Furthermore, we use a time-varying differences-in-differences approach to estimate the effect of the financing of tollway bonds on maintenance and further discuss the mechanism. The results provide evidence that there is a significant improvement in the relationship between tollway bonds and maintenance expenditure, mainly due to the reduction of debt costs and the passive propelling of the government’s spending responsibility. Our proposed theoretical and empirical framework sheds new light on transportation infrastructure research. More specifically, the impetus for public expenditure comes from a decrease of the substitution effect, which not only alleviates the burden of debt scale on the public sector but also provides a reference for developing countries to balance infrastructure construction and maintenance.     

Optimal fiscal policy under learning

This paper characterizes optimal fiscal policy when agents learn about future taxation. A benevolent and fully rational government chooses taxes on labor income and state-contingent bonds to finance public spending, considering that private agents form their expectations through a learning algorithm. Facing a trade-off between distortionary taxes and distorted expectations, the Ramsey planner chooses the policy that minimizes the total cost of distortions. The analysis produces two main results. First, the government will use fiscal variables to manipulate expectations, reducing taxes and issuing debt at times of pessimism and doing the opposite at times of optimism. This speeds up learning. Second, the expectation-dependent fiscal plan is also history-dependent, and it prescribes taxes that are not as smooth and more persistent than under rational expectations. These findings are robust to alternative learning algorithms.     

Growth,deficits and uncertainty: Theoretical aspects and empirical evidence from a panel of 27 countries

We examine the relationship between fiscal deficits and per-capita income growth in a panel of 27 European countries, allowing for perceived risks, in terms of fiscal sustainability, associated with additional government spending. Such risks are proxied by the conditional variability of manufacturing production and stock market returns and by the unconditional variability of two survey-based economic-sentiment indicators. To help clarifying how fiscal variables impact on growth and to provide a point of reference for the interpretation of the empirical results a structural growth model is first identified. We find evidence of an asymmetric relationship, in that fiscal deficits give rise to adverse growth effects if they coincide with high uncertainty regarding the prospects of the economy and no significant negative growth effects in the low-uncertainty case.     

The effect of minimum wage hikes on employment: Evidence from regional panel data from Romania

Minimum wage hikes aim to increase the income of low-wage workers and improve their labour market participation. However, there are concerns that large increases may reduce employment, especially in countries where minimum wages increased quickly and whose competitiveness depends, at least partly, on low production costs. This study examines the employment effect of large increases in the minimum wage in Romania between 2008 and 2016. It uses regional (NUTS III) data and dynamic panel methods. The results do not support the hypothesis that minimum wage hikes reduce employment. They are robust to the use of different econometric methods, plausible variations of the specification and definitions of the key variables. Moreover, the results suggest insignificant effects even for low wage, less developed or high unemployment regions.     

Powerful CEOs,debt financing,and leasing in Chinese SMEs: Evidence from threshold model

This study investigates the impacts of CEO power on firm financing policies (i.e. debt financing and operating leasing) using the Caner and Hansen (2004) instrumental variable threshold regressions approach. The sample consists of a panel of 297 Chinese listed small and medium sized enterprises (SMEs) over the period 2009–2012. The empirical results indicate that there are threshold effects in the CEO power-debt relationship and CEO power-operating lease relationship. In particular, we find that firms tend to use more debt financing (and operating leasing) when CEO power index below a certain threshold level; beyond the threshold level, CEO tends to manipulate firm capital structure to pursue their own interests, thus using less debt financing and operating leasing. In addition, our estimation results suggest a positive relationship between debt and operating leases when CEO power is smaller than certain threshold, while it becomes negative if the power index exceeds the threshold level.     

Is corruption bad for economic growth? Evidence from Asia-Pacific countries

This study utilizes the bootstrap panel Granger causality approach, which incorporates both cross-sectional dependence and heterogeneity across countries, to investigate whether corruption negatively impacts economic growth in thirteen Asia-Pacific countries over the 1997–2013 period. The empirical results show that there is a significantly positive causality running from corruption to economic growth in South Korea, a significantly positive causality running from economic growth to corruption in China and no significant causality between corruption and economic growth for the remaining countries. According to the empirical results, we do not support the common perception that corruption is bad for economic growth for all thirteen Asia-Pacific. On the contrary, results of this study suggest that the “grease the wheels” hypothesis is supported for South Korea. Additionally, results of this study indicate that for most Asia-Pacific countries, policy makers’ use of anti-corruption policies to promote a country's economic development may not be effective. Finally, results of this study also suggest that for China, increase in economic growth leads to an increase in corruption.