Shanghai University of Finance and Economics

In ecology and conservation biology, the number of species counted in a biodiversity study is a key metric but is usually a biased underestimate of total species richness because many rare species are not detected. Moreover, comparing species richness among sites or samples is a statistical challenge because the observed number of species is sensitive to the number of individuals counted or the area sampled. For individual-based data, we treat a single, empirical sample of species abundances from an investigator-defined species assemblage or community as a reference point for two estimation objectives under two sampling models: estimating the expected number of species (and its unconditional variance) in a random sample of (i) a smaller number of individuals (multinomial model) or a smaller area sampled (Poisson model) and (ii) a larger number of individuals or a larger area sampled. For sample-based incidence (presence-absence) data, under a Bernoulli product model, we treat a single set of species incidence frequencies as the reference point to estimate richness for smaller and larger numbers of sampling units.

Abstract At present, more and more attention is paid to the sustainable development of enterprises. In particular, in the context of frequent financial crises and COVID‐19 pandemic, how the performance of listed companies' environmental, social, and governance (ESG) affects the company's market value has attracted widespread attention. Different from existing studies, this paper takes financial performance as a mediating variable and constructs linear regression model and mediating effect model based on analyzing the relationship between ESG performance, financial performance, and company market value and their influencing mechanism. The ESG rating data of Chinese listed companies newly developed by SynTao Green Finance from 2014 to 2019 were selected for empirical test. The results show that the improvement of ESG performance of listed companies can improve the market value of the company, and the financial performance of the company presents an obvious mediating effect. At the same time, operational capacity is an important mediating way for ESG performance to affect the company's market value. Further research shows that ESG performance of state‐owned listed companies exerts a stronger mediating effect on corporate operating capacity. Finally, this paper provides relevant suggestions for regulators, listed companies, and investors.

This article is concerned with screening features in ultrahigh-dimensional data analysis, which has become increasingly important in diverse scientific fields. We develop a sure independence screening procedure based on the distance correlation (DC-SIS). The DC-SIS can be implemented as easily as the sure independence screening (SIS) procedure based on the Pearson correlation proposed by Fan and Lv. However, the DC-SIS can significantly improve the SIS. Fan and Lv established the sure screening property for the SIS based on linear models, but the sure screening property is valid for the DC-SIS under more general settings, including linear models. Furthermore, the implementation of the DC-SIS does not require model specification (e.g., linear model or generalized linear model) for responses or predictors. This is a very appealing property in ultrahigh-dimensional data analysis. Moreover, the DC-SIS can be used directly to screen grouped predictor variables and multivariate response variables. We establish the sure screening property for the DC-SIS, and conduct simulations to examine its finite sample performance. A numerical comparison indicates that the DC-SIS performs much better than the SIS in various models. We also illustrate the DC-SIS through a real-data example.

As organizational environments become increasingly dynamic, complex, and competitive, leaders are likely to face intensified contradictory, or seemingly paradoxical, demands. We develop the construct of “paradoxical leader behavior” in people management, which refers to seemingly competing, yet interrelated, behaviors to meet structural and follower demands simultaneously and over time. In Study 1, we develop a measure of paradoxical leader behavior in people management using five samples from China. Confirmatory factor analyses support a multidimensional measure of paradoxical leader behavior with five dimensions: (1) combining self-centeredness with other-centeredness; (2) maintaining both distance and closeness; (3) treating subordinates uniformly, while allowing individualization; (4) enforcing work requirements, while allowing flexibility; and (5) maintaining decision control, while allowing autonomy. In Study 2, we examine the antecedents and consequences of paradoxical leader behavior in people management with a field sample of 76 supervisors and 516 subordinates from 6 firms. We find that the extent to which supervisors engage in holistic thinking and have integrative complexity is positively related to their paradoxical behavior in managing people, which, in turn, is associated with increased proficiency, adaptivity, and proactivity among subordinates.

Climate change is expected to cause mass human migration, including immigration across international borders. This study quantitatively examines the linkages among variations in climate, agricultural yields, and people's migration responses by using an instrumental variables approach. Our method allows us to identify the relationship between crop yields and migration without explicitly controlling for all other confounding factors. Using state-level data from Mexico, we find a significant effect of climate-driven changes in crop yields on the rate of emigration to the United States. The estimated semielasticity of emigration with respect to crop yields is approximately -0.2, i.e., a 10% reduction in crop yields would lead an additional 2% of the population to emigrate. We then use the estimated semielasticity to explore the potential magnitude of future emigration. Depending on the warming scenarios used and adaptation levels assumed, with other factors held constant, by approximately the year 2080, climate change is estimated to induce 1.4 to 6.7 million adult Mexicans (or 2% to 10% of the current population aged 15-65 y) to emigrate as a result of declines in agricultural productivity alone. Although the results cannot be mechanically extrapolated to other areas and time periods, our findings are significant from a global perspective given that many regions, especially developing countries, are expected to experience significant declines in agricultural yields as a result of projected warming.

Although green growth has become the economic development strategy of many countries in the world, and studies have analyzed the influencing factors of green growth from multiple angles, there are few literatures devoted to the impact of fintech and green finance on green growth. From the perspective of fintech development, this paper tries to construct a comprehensive index to evaluate the green growth of regional economy based on the in-depth analysis of the influence mechanism of green finance on green growth. At the same time, China's provincial panel data from 2011 to 2018 are selected to test the impact of fintech innovation and green finance on green growth, and its mechanism. It turns out that fintech and green finance significantly promotes green economic growth. At the same time, the impact of fintech and green finance on green growth has obvious regional heterogeneity, that is, the impact in eastern China is significantly stronger than that in central and western China. Further research shows that fintech innovation mainly promotes green economic growth through green credit and green investment. Therefore, fintech innovation can promote green economic growth by improving the development level of green finance, which has great reference significance for most countries.

From 1996 to 1998, listed companies in China were required to achieve a minimum return on equity (ROE) of 10 percent in each of the previous three years before they could apply for permission to issue additional shares. As a result of this rule, there was a heavy concentration of ROEs in the area just above 10 percent. We show that the Chinese regulators appear to have scrutinized firms using excess amounts of nonoperating income to reach the 10 percent hurdle. In addition, their ability to do so seems to have improved over time, which allows them to be better able to identify firms that subsequently performed better. However, many firms were still able to gain rights issue approval through excess nonoperating income. We show that these firms subsequently underperformed other approved firms that did not use the same practice, indicating that the Chinese regulators' objective of guiding capital resources toward the well-performing sectors is partially compromised by earnings management.

This paper examines why credit constraints for domestic and exporting firms arise in a setting where banks do not observe firms' productivities. To maintain incentive compatibility, banks lend below the amount that firms need for optimal production. The longer time needed for export shipments induces a tighter credit constraint on exporters than on purely domestic firms. In our application to Chinese firms, we find that the credit constraint is more stringent as a firm's export share grows, as the time to ship for exports is lengthened, and as there is greater dispersion of firms' productivities, reflecting more incomplete information.

China is the world's largest energy consumer and CO2 emitter. Cities contribute 85% of the total CO2 emissions in China and thus are considered as the key areas for implementing policies designed for climate change adaption and CO2 emission mitigation. However, the emission inventory construction of Chinese cities has not been well researched, mainly owing to the lack of systematic statistics and poor data quality. Focusing on this research gap, we developed a set of methods for constructing CO2 emissions inventories for Chinese cities based on energy balance table. The newly constructed emission inventory is compiled in terms of the definition provided by the IPCC territorial emission accounting approach and covers 47 socioeconomic sectors, 17 fossil fuels and 9 primary industry products, which is corresponding with the national and provincial inventory. In the study, we applied the methods to compile CO2 emissions inventories for 24 common Chinese cities and examined uncertainties of the inventories. Understanding the emissions sources in Chinese cities is the basis for many climate policy and goal research in the future.

This paper estimates the effects on rural education of the send-down movement during the Cultural Revolution, when about 16 million urban youth were mandated to resettle in the countryside. Using a county-level dataset compiled from local gazetteers and population censuses, we show that greater exposure to the sent-down youths significantly increased rural children’s educational achievement. This positive effect diminished after the urban youth left the countryside in the late 1970s but never disappeared. Rural children who interacted with the sent-down youths were also more likely to pursue more-skilled occupations, marry later, and have smaller families than those who did not. (JEL I21, J13, J24, N35, O15, P36, R23)

Abstract Previous studies on the effect of International Financial Reporting Standards (IFRS) on accounting quality often have difficulties to control for confounding factors on accounting quality. As a result, the observed changes in accounting quality could not be attributed mainly to IFRS. We use a unique research setting to address this issue by comparing the accounting quality of publicly listed companies in 15 member states of the European Union (EU) before and after the full adoption of IFRS in 2005. We use five indicators as proxies for accounting quality. We find that the majority of accounting quality indicators improved after IFRS adoption in the EU. That is, there is less of managing earnings toward a target, a lower magnitude of absolute discretionary accruals, and higher accruals quality. But our results also show that firms engage in more earnings smoothing and recognize large losses in a less timely manner in post‐IFRS periods. In addition, we examine the effects of institutional variables on financial reporting quality. Our contribution to the literature is that we show the improved accounting quality is attributable to IFRS, rather than changes in managerial incentives, institutional features of capital markets, and general business environment, etc.

Abstract The impact of environmental regulation on enterprise innovation is closely related to the competitiveness of the enterprise and sustainable development of the regional economy, but existing research does not provide a consistent view. This paper summarizes the impacts of environmental regulation on enterprise innovation from the perspectives of technological innovation, product innovation, system innovation and ecological innovation. We find that the impacts of environmental regulation on enterprise innovation behaviour are complex, and that the impacts can be reflected together by the four aspects above and even by their interaction. Moreover, the impacts are not limited to the creation of new technologies, products, and systems but also include their adoption and application. In particular, whether the Porter hypothesis is true and which versions of the Porter hypothesis environmental regulation causes in enterprise innovation depend on enterprise characteristics, means of environmental regulation, and enterprises' strategic behaviours in an enterprise ecosystem. Finally, we propose five potential research directions: quantifying the degree of enterprise innovation caused by environmental regulation, the impacts of environmental regulation on sustainable economic development from an enterprise ecosystem perspective, the impacts of enterprise innovation on environmental regulation, the role of enterprise initiative in the relationship between environmental regulation and enterprise innovation, and social security issues and the integration of eliminated enterprises resulting from environmental regulation.

With the recent explosion of scientific data of unprecedented size and complexity, feature ranking and screening are playing an increasingly important role in many scientific studies. In this article, we propose a novel feature screening procedure under a unified model framework, which covers a wide variety of commonly used parametric and semiparametric models. The new method does not require imposing a specific model structure on regression functions, and thus is particularly appealing to ultrahigh-dimensional regressions, where there are a huge number of candidate predictors but little information about the actual model forms. We demonstrate that, with the number of predictors growing at an exponential rate of the sample size, the proposed procedure possesses consistency in ranking, which is both useful in its own right and can lead to consistency in selection. The new procedure is computationally efficient and simple, and exhibits a competent empirical performance in our intensive simulations and real data analysis.

emissions for 182 Chinese cities, decomposed into 17 different fossil fuels, 46 socioeconomic sectors, and 7 industrial processes. We find that more affluent cities have systematically lower emissions per unit of gross domestic product (GDP), supported by imports from less affluent, industrial cities located nearby. In turn, clusters of industrial cities are supported by nearby centers of coal or oil extraction. Whereas policies directly targeting manufacturing and electric power infrastructure would drastically undermine the GDP of industrial cities, consumption-based policies might allow emission reductions to be subsidized by those with greater ability to pay. In particular, sector-based analysis of each city suggests that technological improvements could be a practical and effective means of reducing emissions while maintaining growth and the current economic structure and energy system. We explore city-level emission reductions under three scenarios of technological progress to show that substantial reductions (up to 31%) are possible by updating a disproportionately small fraction of existing infrastructure.

This paper presents theory and evidence from disaggregated Chinese data that tariff reductions induce a country’s producers to upgrade the quality of their exports. We first document stylized facts regarding the effect of trade liberalization on export prices. Next, we develop an analytic framework that relates a firm’s choice of quality to its access to imported intermediates. In the model, a reduction in import tariffs induces a firm to increase export quality and raise its export price in industries where the scope for quality differentiation is large and lower its export price in industries where the scope is small. The predictions are consistent with the stylized facts and are highly robust econometrically.

Differential abundance analysis is at the core of statistical analysis of microbiome data. The compositional nature of microbiome sequencing data makes false positive control challenging. Here, we show that the compositional effects can be addressed by a simple, yet highly flexible and scalable, approach. The proposed method, LinDA, only requires fitting linear regression models on the centered log-ratio transformed data, and correcting the bias due to compositional effects. We show that LinDA enjoys asymptotic FDR control and can be extended to mixed-effect models for correlated microbiome data. Using simulations and real examples, we demonstrate the effectiveness of LinDA.

Recent technological advances in online and mobile communications have enabled collaborative consumption or product sharing among consumers on a massive scale. Collaborative consumption has emerged as a major trend as the global economic recession and social concerns about consumption sustainability lead consumers and society as a whole to explore more efficient use of resources and products. We develop an analytical framework to examine the strategic and economic impact of product sharing among consumers. A consumer who purchased a firm’s product can derive different usage values across different usage periods. In a period with low self-use value, the consumer may generate some income by renting out her purchased product through a third-party sharing platform as long as the rental fee net of transaction costs exceeds her own self-use value. Our analysis shows that transaction costs in the sharing market have a nonmonotonic effect on the firm’s profits, consumer surplus, and social welfare. We find that when the firm strategically chooses its retail price, consumers’ sharing of products with high marginal costs is a win-win situation for the firm and the consumers, whereas their sharing of products with low marginal costs can be a lose-lose situation. Furthermore, in the presence of the sharing market, the firm will find it optimal to strategically increase its quality, leading to higher profits but lower consumer surplus. This paper was accepted by J. Miguel Villas-Boas, marketing.

abstract The study reported here examined the relationship between workplace ostracism and employee psychological distress (i.e. job tension, emotional exhaustion, and depressed mood at work) by focusing on the joint moderating effects of ingratiation and political skill. Data from a two‐wave survey of 215 employees in two oil and gas firms in China indicated that as predicted, workplace ostracism was positively related to psychological distress. Moreover, the findings showed that when employee political skill was high, ingratiation neutralized the relationship between workplace ostracism and psychological distress, but when it was low, ingratiation exacerbated the relationship.

The emergence of Alibaba’s Taobao (e-commerce) Villages in remote China has challenged the assumption that rural, underserved communities must always be the recipients of aid to stimulate ICT-enabled development. Based on an in-depth case study of two remote villages in China, this research note shows how ICT (e-commerce) can empower a marginalized community, giving rise to a rural e-commerce ecosystem that can aid self-development. We propose the concept of digital empowerment to explicate our findings in the exploration of community-driven development: first, we identify the critical actors of a rural e-commerce ecosystem and how they use ICTs; second, we illustrate how the same ICT can be used for different affordances by the actors in the evolution of a rural e-commerce ecosystem. The paper also presents unintended consequences of rural e-commerce development. We conclude with suggestions on how to make ICT useful for rural development and, in doing this, challenge some of the prevailing theoretical arguments about this process.

We introduce the large portfolio selection using gross-exposure constraints. We show that with gross-exposure constraint the empirically selected optimal portfolios based on estimated covariance matrices have similar performance to the theoretical optimal ones and there is no error accumulation effect from estimation of vast covariance matrices. This gives theoretical justification to the empirical results in Jagannathan and Ma (2003). We also show that the no-short-sale portfolio can be improved by allowing some short positions. The applications to portfolio selection, tracking, and improvements are also addressed. The utility of our new approach is illustrated by simulation and empirical studies on the 100 Fama-French industrial portfolios and the 600 stocks randomly selected from Russell 3000.