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Background: There is absence of national data to estimate the prevalence and the hospitalization costs of long-term diabetic complications among hospitalized patients with diabetes in China. Methods: Using the national Hospital Quality Monitoring System (HQMS) database, we identified inpatients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) via ICD-10 code and calculated the proportion of inpatients with microvascular complications and macrovascular complications 2013-2017. We then investigated the changes of hospitalization costs before, during and after the year when the complications occurred. Findings: A total of 92,413 inpatients with T1DM and 6,094,038 inpatients with T2DM were identified 2013-2017. The proportions of inpatients with microvascular complications in inpatients with T1DM and T2DM increased from 29·9% and 19·0% in 2013 to 31·6% and 21·0% in 2017, respectively. The proportions of inpatients with macrovascular complications in inpatients with T1DM and T2DM increased from 7·3% and 14·5% in 2013 to 13·2% and 18·4% in 2017, respectively. Compared with the average annual hospitalization costs before the occurrence of kidney transplantation, dialysis, acute myocardial infarction, stroke, diabetic foot, nephropathy, retinopathy and neuropathy among inpatients with T2DM, the hospitalization costs of the year when the long-term complications occurred increased by 249·0%, 120·9%, 172·0%, 61·3%, 61·5%, 34·0%, 22·9% and 24·6%, respectively. The growth of hospitalization costs of inpatients with T1DM after the occurrence of long-term complications were 339·8%, 197·2%, 347·5%, 106·3%, 22·5%, 33·9%, 26·8% and 109·5%, respectively. Interpretation: The proportions of long-term complications of inpatients with diabetes in China increased 2013-2017. The hospitalization costs of inpatients with diabetes in China increased significantly after the occurrence of long-term complications. Funding: China-World Health Organization Biennial Collaborative Projects Declaration of Interest: None to declare. Ethical Approval: This study was approved by the Ethics Committees of the First Affiliated Hospital of Sun Yat-sen University.

ESG is the core concept in the field of green finance that has attracted much attention in recent years. Based on traditional financial indicators, ESG aims to integrate environmental, social, and governance factors. By examining the potential for long-term and sustainable value growth of the company, it can effectively help prevent and control downside risks, obtain long-term returns, and discover economic growth. However, there are currently many international ESG rating systems, lacking a unified framework, transparency of their rating methodologies, data sources, and a consensus on how to evaluate the ESG related risk profiles. This research intends to find how ESG Rating is constructed from company performance. In the study, we mainly did the review and illustration of MSCI & RepRisk ESG Rating. We can identify limited mechanisms that could hinder us to simulate ESG rating under various circumstances. For RepRisk, we could only identify the formula in the last step of generating RepRisk Rating: Scale RRR = 0.5 𑁦 (country sector aver+|||| peak RRI). For MSCI, we could only identify the rating construction methodologies based on various factors. However, we believe that the blockchain is supportive of eliminating these limitations, and we aim to explore the possibility of constructing an ESG rating system for blockchain for our next step.

We propose a new perspective based on the individualism vs. collectivism (IC) cultural distinction to understand the diverging early-stage transmission outcomes of COVID-19 between countries. To provide a fair comparison for different countries, we use the date when the total cases per million capita reach one as the starting point of each country's outbreak. With data of sixty days after the outbreak, we find the COVID-19 spread much faster in the early stage in more individualistic societies than in more collectivistic societies. We further use pronoun drop and absolute latitude as the instruments for IC to solve reverse causality and omitted variable bias. We find a significant impact of IC cultural distinction on the early-stage transmission outcome of COVID-19. The results are robust to different measures of COVID-19 outcomes, different measures of IC, other cultural dimensions, and different sub-samples. We propose to take into account the role of IC not only for understanding the current pandemic but also for thinking about the future trend of the world.

Currently, there are no convincing proxies for the fundamentals of cryptocurrency assets. We propose a new market-to-fundamental ratio, the price-to-utility (PU) ratio, utilizing unique blockchain accounting methods. We then proxy various fundamental-to-market ratios by Bitcoin historical data and find they have little predictive power for short-term bitcoin returns. However, PU ratio effectively predicts long-term bitcoin returns. We verify PU ratio valuation by unsupervised and supervised machine learning. The valuation method informs investment returns and predicts bull markets effectively. Finally, we present an automated trading strategy advised by the PU ratio that outperforms the conventional buy-and-hold and market-timing strategies.

We provide a new perspective to understand poverty traps by researching the effect of psychological poverty on economic decisions. Our innovative sample consists of two pools of subjects: impoverished students and normal students from the same university. Subjects were first randomly assigned either to a treatment group that induced them to think about finances or to a control group. Then all subjects performed three tasks of economic decisions. Our results show that priming in general significantly intensifies the poor’s choices, with fewer total payoffs, higher response times, and favoring “pinching pennies” over “making money,” all of which can perpetuate poverty traps.

This research constructs a simple dynamic model to illustrate the micro-mechanism of industrial upgrading along the global value chains. Our model demonstrates the following results. (1) Firms in the value chains manage to upgrade from downstream to upstream stages by acquiring higher profitability if and only if the following 3 conditions are satisfied. First, the increasing rate of sunk cost (including R&D expenditure) over sequential stages of production cannot be sufficiently large (endogenous sunk cost effect). Second, the decreasing rate of change of intermediate input demand with respect to the price set by firms at a production stage cannot be sufficiently high (intermediate input price effect). Third, the decreasing rate of change of intermediate input demand with respect to the pricing dynamics over the sequential stages of production cannot be sufficiently large (sequential pricing uncertainty effect). (2) The level of total cost islower when firms climb from downstream stages to relatively more upstream stages in the value chains if and only if the decreasing rate of change of input demand with respect to the price set by firms at a production stage is sufficiently large. (3) The output level is higher when the downstream firms move towards relatively more upstream stages if and only if the decreasing rate of change of input demand with respect to the price set by firms at a production stage is not sufficiently high. (4) The price level decreases when a firm at a production stage moves from downstream to relatively more upstream stages. At the end of this paper, we also apply our theoretical framework into the current debate on the rise of the unbundling production pattern as well as a nation’s industrial development during this era of an increasingly globalized world with reference to some empirical evidence focusing on China.

Substantial evidence in field, lab and thought experiments in multiple disciplines, shows that decision makers often choose a dominated strategy, which contradicts with current economic theory. To bridge this gap between theory and evidence, first, we propose two alternative axiomatic approaches, formalizing a distinct defect in human reasoning and tying together a broad range of evidence for the choice of dominated strategies. Second, we extend the theory to game theory and mechanism design, where we identify a rich class of mechanisms that successfully achieve desirable goals even with boundedly rational agents or agents who mistrust the market makers. Third, we test and verify our theory and its implications by a laboratory experiment. Finally, we address how our approach contributes to accomplishing two goals simultaneously in modelling bounded rationality: stimulating transdisciplinary conversations and providing a unified framework.