Digitalization is nowadays one of the fastest developing processes. The adoption of digital technologies can provide innumerous opportunities for the organizations to evolve and gain competitive advantage by leveraging of technologies to respond to dynamic expectations and demands. Information about the country digitalization level is essential to decision makers in both public and private organizations. It can present insights on which areas need the most investment, and furthermore to gain feedback on the outcomes of these investments. For companies, it can create a certain predictability on which products and services will be required the most. To assess the evolution of this process in different countries, various indexes were proposed and employed by different corporations. The Digital Economy and Society Index (DESI) and ICT Development Index (IDI) are used by public organizations. Digitalization Index (DiGiX) and Cisco Digital Readiness Index (CISCO) are used by private companies. Comparing two sectors highlights the most common factors of digital evaluation. Indexes are analyzed thoroughly by their structure, coverage, weights, methodology and ranking. The result of the practical work is a equivalence table which shows the percentage of their similarity. Additionally, a new digitalization index is proposed, based on the result of the previous comparison, which can be applied to analyze both public and private sector of the country’s digitalization level.

Because of the complexity of indirect financial intermediary services (FISIM) accounting, the traditional price index deflation method can no longer meet its accounting needs. The manual of price and volume measurement suggests that the stock deflation method and output index method should be used to calculate the volume of FISIM. Comparing the two accounting frameworks, it can be found that the key to the implementation of the stock deflation method is to set a scientific and reasonable deflation index from two aspects of service price and the service quantity, while the key of the output index method is the selection of the output index and the determination of weight. This paper compares the application cases of stock deflation method and output index method in practice, summarizes the similarities, differences, advantages and disadvantages of each case in index construction, index selection and weight determination, and further provides a reference for China FISIM volume accounting.

The signing of RCEP has created new opportunities for the development of China's export trade, and international logistics capacity is an important factor affecting the conduct of international trade. This paper qualitatively describes and analyzes the LPI index and its sub-indicators of RCEP member countries, and empirically investigates the impact of logistics performance level on China's export trade through an extended gravity model. The study shows that there are large differences in logistics performance levels among RCEP member countries, especially in South Asia, where the quality of logistics infrastructure and customs efficiency are the most lagging behind, which are the key factors pulling down the logistics performance index; the signing of RCEP has effectively promoted China's foreign trade level, but there are great differences in export amounts to different countries, and the logistics performance levels of importing countries and China's export trade are significant positive correlation, the improvement of logistics performance is conducive to promoting China's export trade to RCEP member countries, and from the viewpoint of logistics links, the role of logistics infrastructure quality is the strongest, and the influence of cargo transportation timeliness is the weakest.

This paper specifically underscores the disparities among various ESG rating systems in China, highlighting their varied interpretations and emphasis on corporate financial factors. Analyzing data on Chinese listed firms from 2009-2022, we observe that while company size and leverage ratio uniformly correlate with ESG scores across rating agencies such as Bloomberg, Huazheng, Wind, and Hexun, the influence of factors like return on assets, cash flow, company age, and Tobin's Q is markedly inconsistent among these agencies. For instance, while operational cash flow and company age are positively associated with ESG ratings from Bloomberg, Huazheng, and Wind, they hold an inverse relationship with Hexun's ratings. This divergence underscores the unique data collection, weighting, and evaluation methodologies employed by each rating system. The study emphasizes the criticality of comprehending the nuances of each rating agency's approach when interpreting ESG scores and crafting ESG strategies. Moreover, it advocates for integrating insights from multiple rating systems to cater to the diverse expectations of stakeholders.

The clean energy revolution is a global concern. Cross-border collaboration is crucial for sharing knowledge, pooling resources, and tackling complex challenges on a global scale. International partnerships can accelerate innovation by drawing on diverse knowledge and experience from different regions. Access to capital is a key driver of innovation and entrepreneurship in clean energy. Institutional investors and financial institutions increasingly recognize the potential for high returns from the clean energy sector. This research aimed to understand whether "dirty" energies, such as the Brent Crude Spot, WTI, FTSE 350 Oil, Gas & Coal, EURO STOXX Oil & Gas, influence the formation of sustainable energy prices, namely Geothermal Index, Solar Energy Index, NASDAQ OMX Bio Clean Fuels Index, Wind Energy Index, WilderHill Clean Energy Index, during the 2020 Covid-19 pandemic and the Russian invasion of Ukraine in 2022. When comparing the two sub-periods, the results show that the level of autocorrelation in price formation has increased, i.e., the mean rhoDCCA went from 32 to 45, the weak correlation coefficients without trend decreased from 30 to 19, and the anti-persistence has also decreased from 8 to 4. The strong rhoDCCA increased from 2 to 4; during the Tranquil period, the FTSE 350 / EURO STOXX Oil index pairs had a rhoDCCA of 0.76. While in the Stress subperiod, the NASDAQ OMX Bio / Solar Energy pairs had a slope of 0.70, and the FTSE 350 / EURO STOXX Oil indices had a rhoDCCA of 0.91. Evidence shows a notable dissociation between fossil energy prices and sustainable energy sources. This dissociation is characterized by various degrees of influence between fossil energy prices and sustainable energy indices, from low to moderate. This dissociation between fossil energy prices and sustainable energy prices suggests that investments in sustainable energy can offer diversification opportunities.

Stock indexes are used as a barometer of economic health, and fluctuations in these markets can have a substantial influence on the economy. For example, the Covid-19 pandemic caused severe economic disruption, as reflected in stock market indexes. Similarly, Russia's invasion of Ukraine has geopolitical implications that might undermine global trade and economic stability, impacting stock market indexes. Considering these developments, the purpose of this article is to examine the co-movements of the stock markets of Austria (ATX), Poland (WIG), the Czech Republic (PX Prague), Hungary (BUX), Croatia (CROBEX), Serbia (BELEX 15), Romania (BET), and Slovenia (SBI TOP) from February 16, 2018, to February 15, 2023. To achieve the research objectives, the aim is to answer the following research question: i) Have the events of 2020 and 2022 accentuated the co-movements between the stock markets in Central Europe? The results show the presence of 21 shocks between markets (out of a potential 56) during the Tranquil subperiod, with the WIG stock index having a greater predictive influence on the behavior of its peers (4 shocks out of 7 possible). During the Stress subperiod, 45 shocks were confirmed (out of 56 possible). The markets that triggered the most market shocks (7 out of 7 possibilities) were BET, BUX, CROBEX, and SBI TOP. The research question was validated based on the conclusion supplied, as all markets increased their movements, showing a considerable effect of the 2020 and 2022 events on these markets.

This research evaluates the efficacy of survival models in forecasting startup failures and investigates their economic implications. Several machine learning survival models, including Kernel SVM, DeepSurv, Survival Random Forest, and MTLR, are assessed using the concordance index (C-index) as a measure of prediction accuracy. The findings reveal that more sophisticated models, such as Multi-Task Logical Regression (MTLR) and Random Forest, outperform the standard Cox and Kaplan Meier (K-M) models in terms of predicted accuracy.

Based on the empirical data of 6110 listed export companies in China from 2010 to 2019, this paper studies the impact of China's economic policy uncertainty (EPU) index on the profitability of listed companies from the specific perspective of export companies, and analyzes the moderating effects of different factors on this impact. The results show that China's EPU index has a significant negative impact on the profitability of listed export companies, and the increase in R&D investment and wage returns will aggravate this negative impact. In addition, listed export enterprises with different enterprise characteristics have different responses to EPU. State-owned enterprises and enterprises located in coastal areas are relatively less negatively affected by EPU.

Understanding the economic trends and demographic dynamics of a country is crucial for policymakers and researchers to formulate effective strategies and policies. This study aims to examine the GDP trends and aging index dynamics in Portugal from 2011 to 2021, with a focus on regional disparities and their implications for demographic challenges. The findings highlight the relationship between regional GDP and the aging index, indicating that regions with higher GDP values tend to have a relatively younger population, while regions with lower GDP values have a relatively older population. The study contributes to the existing literature on population aging by providing insights into the demographic, economic, and social implications of an aging society. It provides valuable insights into the demographic, economic, and social implications of population aging in Portugal. The findings contribute to the existing literature and can inform policymakers and stakeholders in developing targeted strategies and policies to address the specific challenges faced by each region.

Poland has experienced a very sharp rise in income and wealth inequality after the economic transition. We measure the relative persistence of income inequality and intra-generational income mobility in Poland during the period 2008-2015. Our research is based on the panel survey data, our subsample includes 501 households. To measure the persistence of income inequality we calculate Shorrocks’s R coefficient. We find that if inequality is measured by the Gini index the relative persistence of income inequality in Poland is similar to Western Europe. In the case of the Theil index and the Mean Log Deviation (MLD), the relative persistence is higher than in a majority of Western Europe countries and similar to the United Kingdom or the United States. The income distribution in Poland is rather stable. Income mobility is lowest at the bottom and at the top of the income distribution. In the middle (3rd) quintile upward mobility is higher than downward mobility. The short-term income mobility in Poland has not changed during and after the Great Financial Crisis and is still medium in comparison with the rest of Europe.

Green-biased technological progress takes into account the influence of energy input and pollution emissions, which is of great significance to China's green development. This paper decomposes technological progress into two categories: green input-biased technological progress (IBTC) and green output-biased technological progress (OBTC), using the Slacks-based measure integrating (SBM) model. The factor bias in technological progress is determined based on data from 34 industries in China from 2000 to 2015. The results show that green-biased technological progress exists significantly in the industry, and most of it promotes the growth of green total factor productivity. IBTC first tends to consume energy to pursue capital between capital input and energy input, while it tends to save energy after the Eleventh Five-Year Plan. Between labor input and energy input, it is biased towards saving labor and consuming resources. OBTC is biased towards promoting industrial growth and curbing pollution emissions. Medium and light-polluting industries are biased toward promoting industrial growth and curbing pollution emissions, while heavy-polluting industries are biased towards emitting more pollution.

The stages of liver fibrosis can reflect the severity of chronic viral hepatitis and the probability of liver cancer. Biopsy is still regarded as the reference for staging fibrosis, but the invasive method is not suitable for first-line screening. In recent years, noninvasive methods for detecting virus-driven liver fibrosis have been developed rapidly, which mainly include biological (serum biomarkers indexes) and physical (imaging assessment of liver stiffness) strategies. In this review, we introduce these noninvasive methods, enumerate their diagnosis performances and discuss the role of ferroptosis. At last, we propose directions for future researches.

We extend the Shariah-compliant digital assets and Islamic Fintech literature through exploring the time-frequency associations between the volatility index (VIX) and cryptocurrencies (both Islamic and traditional). Employing wavelet-based technique, we find that Islamic cryptocurrencies demonstrate low or no coherency with stock market volatility compared to traditional cryptocurrencies (except Tether) during the whole time and frequency bands, highlighting the hedging capabilities of Islamic cryptocurrencies. Tether also serves the same against VIX, as there is a low or favorable link between these variables. Finally, our findings would be prolific to digital currency traders and investors in designing the portfolio strategies.

With the daily data from Nov 20, 2019 to Oct 31, 2022, this paper examines the dynamic nonlinear effects of RCEP on Dual Circulation and Greater Bay Area stock market from a quantile perspective. The rolling window quantile regressions detect the positive effects of RCEP on Dual Circulation and Greater Bay Area stock markets with significant time-varying characteristics. Meanwhile, QQ results show that the impacts from RCEP index are more significant under extreme conditions. In addition, we further use a nonparametric QC test to provide evidence on the predictive power of RCEP for Dual Circulation and Greater Bay Area with stock market.

Population, as a fundamental element in urban development, often reflects a city's economic development pattern through its spatial distribution and dynamic changes. Studying population spatial distribution is pivotal for bolstering the economic activity capacity in urban agglomerations and guiding regional economic health. Using the Changsha-Zhuzhou-Xiangtan urban agglomeration as a case study, this paper analyzes its overall spatial structure and the spatiotemporal evolution of population at the district and county levels. This analysis utilizes population density, population redistribution index, and population geographic concentration as key indices. Additionally, a spatial econometric model is constructed to assess the impact of economic, social, and environmental factors on population spatial patterns. Findings reveal several key points: (1) Furong District serves as the primary central area, boasting a population geographic concentration of 25.1% in 2021. Tianxin District, Kaifu District, Yuhua District, Shifeng District, Yuelu District, and Hetang District constitute the secondary central areas, while Yutang District, Tianyuan District, Lusong District, Yuhu District, Wangcheng District, and Changsha County form the tertiary level areas. (2) Population density within the Changsha-Zhuzhou-Xiangtan urban agglomeration gradually decreases from Furong District outward. The first central area and sub-central areas experience increasing population density, highlighting a polarization trend in the population distribution. (3) The overall Moran's index for the spatial distribution of population in the Changsha-Zhuzhou-Xiangtan urban agglomeration is significantly positive, indicating a strong spatial autocorrelation and a deepening spatial agglomeration of population distribution. (4) Per capita disposable income, financial expenditure, and education level positively influence the geographical concentration of population in the urban agglomeration, while GDP per capita, road area per capita, and environmental quality exert a negative impact. Notably, the most influential factors shaping population spatial distribution are GDP per capita, disposable income per capita, and air quality.

This study explores the cause and effect of endogenous risk aversion in land pricing, where state intervention through taxation remains a general practice. Using a consumption-based asset pricing model incorporating taxation, it is shown that high taxation, due to the indexation effect, supporting land prices and reducing individuals' risk expectations, could lead to an endogenous decrease in risk aversion, which could result in market dysfunction because risk aversion plays a key role in the market mechanism. China, with its wholly state-owned land and the general use of land sales to cover financial deficits, is a typical case for empirical tests. The tests confirm that there, the rise in land prices was driven by the increase in reserve prices set by local governments, a strong means of taxation, and not by the market, indicating the endogenous decrease in risk aversion.

The sensitive nature of interest rate has spurred empirical interests on the factors that determine it. This paper examined the joint impact of exchange rate and foreign direct investment inflows on interest rate in Nigeria over the period from 1981-2022. The study made use of the auto regressive distributed lag (ARDL) bounds test and results of findings reveal that in both the short-run and the long-run the impact of the interaction between FDI inflows and exchange rate on real interest rate was negative and significant. Also, while credit to the private sector was found to have significant positive impact on real interest rate in both the time horizons, the impact of consumer price index was negative only in the short. Oil revenue was found to impact positively on real interest rate only in the long-run, but the impact of broad money supply was negative and significant in both the short-run and the long-run. The study suggests that policies to regulate domestic interest rate should focus on joint regulation of both exchange rate and FDI inflows and this requires a synergy between monetary and fiscal policies.

Excessive volatility in financial markets can disrupt economic activity, affect investor and consumer confidence, and potentially lead to financial crises in an economy. Due to this backdrop, this study examined the link between asset class volatility and the output gap in Nigeria. The asset classes were categorized into stock, crude, gold, and bitcoin. The study adopted the GARCH and Bayesian VAR approach and found that all share index has an initial negative impulse with output gap while other asset classes have a positive impulse on output gap. The outcome of this study revealed to both policymakers and economists the potential risks and vulnerabilities of asset class volatility in the economy. Based on this result, recommendations are made amongst which is the strengthening of the Nigerian stock market to help with the inflationary pressures this is because the Nigerian stock market hurt the output gap also, the government should prioritize investing in crude, gold, and bitcoin to push the actual output to full capacity, which brings about employment.

With the continuous advancement of technological revolution and industrial transformation, digital finance supported by big data and artificial intelligence has become an important engine for promoting carbon neutrality. We measured the industrial structure transformation index (ISU) of 30 provinces in China, and discussed the spatial spillover effect and transmission mechanism between digital finance and ISU using the spatial Durbin model. The research results demonstrate that the digital finance development can significantly improve the local ISU. Interestingly, the impact of digital finance on the ISU of adjacent areas has a significantly negative spatial spillover effect, which still exists under the different spatial weight matrix. Digital finance can improve ISU by improving green technology innovation, upgrading industrial structure, and alleviating capital allocation. We also found that the higher degree of marketization and environmental regulation can increase the positive influences of digital finance on ISU. This research proves the effectiveness of the digital finance in improving energy efficiency, and it encourages policymakers around the world to rely on digital finance to promote ecological governance and achieve high-quality economic development.

Based on fully considering the actual differences in statistical indicators between Hong Kong, Macao, and the nine cities in the Pearl River Delta, this paper constructs a high-quality urban development evaluation system that is suitable for the actual development of the Guangdong-Hong Kong-Macao Greater Bay Area. The Entropy Weighted TOPSIS two-step method is used to process data and systematically investigate the changes in the high-quality development index of 11 cities in the Guangdong-Hong Kong-Macao Greater Bay Area from 2013 to 2020. The study found that the Guangdong-Hong Kong-Macao Greater Bay Area has thoroughly implemented the new development concept, and the level of high-quality development has continued to improve. The profound integration effect of the Guangdong-Hong Kong-Macao Greater Bay Area has appeared, and it has promoted the high-quality development of the region in coordination. The construction of the Guangdong-Hong Kong-Macao Greater Bay Area has strongly promoted the great practice of "one country, two systems" to achieve stability and prosperity.