There is a considerable amount of debate on the impact of capital liberalization on economic performance. Using Three-Stage Least Squares (3SLS) estimation technique introduced by Zellner and Theil (1962), we synthesize studies on the determinants of governance and capital flows. We find evidence of a revolving door relationship. Foreign aid has a negative impact on governance and, thereby reduces capital inflows since bad governance hinders capital inflows. The need to fill the gap created by private capital outflows encourages inflow of foreign aid, which in turn harms governance. Therefore, capital liberalization could grease a revolving door and undermine economic development in the aid receiving countries.

In the context of the continuous deepening reform of the foreign investment negative list system and the increasing pressure on financial risk prevention and resolution, it is of great significance to study the impact of the foreign investment negative list system on banking risks. This study is conducted on the basis of systematically sorting out the mechanism of the foreign negative list system affecting the risks of domestic banks. Based on the panel data of 27 provinces (cities, districts) in China from 2006 to 2016, and comprehensively adopting the synthetic control method, the difference-in-difference (DID) model, mediating effect model, and other methods, this article systematically examines the impact of the foreign negative list system on Shanghai banking risks. The study found that the implementation of the foreign investment negative list system has significantly reduced the credit risk of the Shanghai banking industry, and this reduction effect has gradually strengthened over time. Additionally, the implementation of the foreign investment negative list system will also significantly reduce the liquidity risk of the Shanghai banking industry; However, the effect of this positive influence is short-lived and subsequently weakens. The analysis of the mechanism of action indicates that the foreign investment negative list system primarily reduces the risk of Shanghai's banking industry by stimulating the inflow of foreign capital and reducing government intervention. However, the effect of improving the level of the rule of law to mitigate commercial bank risk is not apparent. Regarding other influencing factors, the growth of local government financial resources and the increase in new loans have significantly reduced banking risks, while the rise in residents' leverage has substantially increased the level of banking risks.

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.

Spence’s signaling model (Spence, 1973) suggests that education can signal workers’ unobserved ability to employers thereby mitigating discrimination. There have been several studies concerning education’s impact on labor market discrimination against minority or disadvantaged groups. Our approach in this inquiry is unique in that we utilize the data of PhD recipients, a group of people with the highest education attainment, to test Spence’s theory. Another novelty of this paper is that in addition to examining possible discrimination against women and foreign-born, as has been done in previous studies, we further explore possible discrimination against the physically challenged individuals. Our baseline results show conflicting results that Ph.D. education can reduce discrimination against disability and foreign-born but not against gender. Further analysis by the Blinder-Oaxaca Decomposition shows that the wage gaps of gender and disability come more from the unobserved part than the explained part, while the foreign-born wage gap come more from the observable human capital differences. Since prejudice is an unobserved factor and we know that the disadvantaged groups are likely to suffer from prejudice (Oaxaca, 1973; Blinder, 1973; Montes-Rojas et al., 2017; Deshpande and Khanna, 2018), we conjecture that prejudice might be attributable to the unexplained part of the wage gaps. Furthermore, prejudice might be deeply rooted in one’s mind, thus difficult to remove even with the influence of education. Hence, our results reveal that it would be hard for Ph.D. education to eradicate the discrimination against gender and disability, but not against foreign-born.

This study considers the effects of disclosure conditions on firms' investment decisions when facing an identical competitor in multiple markets. Assuming that there are congestion costs between multiple investments to reduce marginal cost for each market, this study focuses on the cases where the disclosure conditions may differ by market. Like previous studies on single Cournot competition, these results show that firms invest more in the observable investment markets than in the unobservable markets under symmetric disclosure conditions. However, firms invest more in the unobservable market if there are asymmetric disclosure conditions.

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 answer to how to stop economic growth must be political rather than economic. Economic growth made by men has an impetus which can only be stopped by a deliberate choice. It takes national and international decisions to stop it. In order to organize a moratorium on economic growth (which eventually must lead to a stop on growth) I suggest to create blocks of nations in the world. The European Union can function as a model for such a block. The E.U. is on its way of becoming a supra-national government which was created to ensure a level playing field for its members. Now it is meant to create economic growth for its members, in the future its administration should be used to stop it. Blocks should agree on the targets to reach a durable economy. Globally or between certain more advanced blocks a date should be set to stop economic growth after that date. Each block should implement the goals to reach a durable economy and prevent products reaching its market that violate the goals of durability. Blocks in developing countries cannot be expected to stop economic growth. They need that growth for two reasons. Eventually they must reach the level of existence in the more advanced block and secondly they must have the time to improve the standard for durability of their products. They need the aid of the developed countries to reach a higher but also more durable level of production, but this aid comes with a quid pro quo, In the meantime they must do their utmost to stop wars in their regions and conduct a responsible population-policy to reduce the growth of their population and let it reduce on the long term.

The primary goal of this research is to examine how different types of energy are used in South Asian countries and how they affect the environment and economic growth. From 1990 through 2021, this research employed Panel Data from multiple sources covering the South Asian countries of Pakistan, India, Bangladesh, Sri Lanka, Nepal, Bhutan, Maldives, and Afghanistan. The results are determined by using the Fixed Effect Regression (FEM) technique in both models. Several significant findings are supported by the data. First, while using renewable energy flattens carbon dioxide effusion, using non-renewable energy sources increases it. CO2 emissions are affected negatively by gross domestic product but positively by gross domestic product square. These results provide credence to the idea that South Asian countries do experience an Environment Kuznets Curve. Furthermore, foreign direct investment has a beneficial effect on CO2 emissions, lending credence to the Pollution Haven Hypothesis. Model 2 instead finds that both renewable and non-renewable energy consumption contributes to economic expansion. Gross Fixed Capital Formation and foreign direct investment also contribute to economic growth in this area. Finally, Inflation retards economic expansion.

Public diplomacy is a significant factor in promoting policy communication, people-to-people bonds, and the protection of foreign assets between two nations, but there is little research on the economic worth of public diplomacy. Python was used to crawl the daily search frequency of "China", "African countries", and related terms to construct the heat index of China-Africa public diplomacy during 2011-2019, and a two-way fixed effect model was developed to examine the impact of public diplomacy on China’s outward foreign direct investment (OFDI) in Africa. The empirical results show that public diplomacy has a considerable favorable effect on China’s OFDI in Africa, and after a series of robustness tests, the basic conclusion still holds. Heterogeneity tests show the investment promotion effect of public diplomacy is more pronounced in sub-Saharan Africa and that the promotion mechanism exhibits the characteristics of poverty alleviation and risk aversion. In addition, the promotion effect of public diplomacy on China’s OFDI becomes greater as time goes on. In terms of impact mechanisms, public diplomacy may promote OFDI by enhancing financing capacity and improving national governance. The research conclusion has policy implications for promoting China-Africa public diplomacy and investment cooperation in the new era.

College choice and choice of major are the most important decisions for future earnings. It is still unclear, however, what makes a greater difference—college or major—or whether a choice of college matters more for some majors, but not the others. Using cross-classified models and College Scorecard data, I show that a discipline is more consequential for future earnings than a college. The effect of STEM is substantial but is less pronounced at institutions with higher overall median earnings. The effect of college selectivity on earnings is more pronounced for non-STEM disciplines. Institutional characteristics—such as tuition, shares of graduates receiving different forms of financial aid, institutional size and location, and type of college—correlate with earnings of graduates. Racial and gender composition of an educational program correlate with expected earnings of its graduates even after control for other institutional and disciplinary characteristics. Models presented here provide a better understanding of the effect of college and major choices on future earnings.

The paper is motivated by the growth of the electronic payments system and its relevance in enhancing the banking industry's earnings. Consequently, the paper examines the causal relationship between the electronic payments system and the banking industry's returns in Nigeria. The paper offers some important contributions to the literature involving the use of an approach that allows for data-driven identification of the change points in the electronic payments system and the banking industry's returns nexus. The paper discovered three important findings. First, the causal relationship between the electronic payments system and the banking industry's returns in Nigeria changes with time changes. Second, there is evidence of causality between the electronic payments system and returns on assets and equity, however, the causality was more evident under the recursive window. Third, the causal relationship was more evident in some specific periods such as 2020Q4, all quarters of 2015 to 2016, and 2020 to the end of 2023. The paper recommends that policymakers should revisit and reinvigorate the specific cashless policies instituted in 2012-2016 that aided higher returns to the banking industry. Similarly, the Central Bank of Nigeria and other banking industry players should intensify efforts to encourage the use of electronic payments due to their usefulness and ability to enhance the banking industry's earnings.

The objective of this research is to investigate, using time series data ranging from 1992 to 2021, the effects of information and communication technologies (ICTs) and foreign direct investment (FDI) on economic growth (GDP) in India. The stationarity of the data was examined by employing unit root tests, and an autoregressive distributed lag (ARDL) technique was used to investigate the link between the factors, taking both the long- and the short-run into consideration. According to the findings, an increase of one percent in both ICT and FDI will result in an increase of 0.56% and 0.71% in GDP over the long term, in addition to an increase of 0.11% and 0.29% over the short term. The findings of the investigation are of particular significance to policymakers because they can be utilized to establish sensible policymaking for long-term economic success, in addition to advancing the ICT sector and boosting FDI.

Gravity Energy Storage (GES) systems are recently being considered as a viable solution for storing intermittent renewable energy power, specifically in high curtailment zones. While a few studies have analyzed the material costs of GES systems, there is a paucity of literature on analyzing the socioeconomic costs of GES systems. This study analyzes the location-dependent costs of GES plants using a multi-factor spatial parameterization model for evaluating the existence of a point of minimum cost in a suburban mountainous geography. A case study of 500x500 points in a 50x50km2 area in the suburban area of Fukuoka city in Japan is performed. It is found that the cost of material transportation and transmission is more dominant in determining the position of an optimal cost location than factors of excavation and land costs. The position of the minima is also related to the principal urban area in that the line connecting the Center Business District (CBD) and suburban flat areas (line 1) is where the potential minima lie. The intersection point of an orthogonal to the line connecting the CBD with a substation nearest to the flat area with line 1, is the potential zone of minima location. The findings of this study are critical for urban energy planners and reveals how socioeconomic cost factors can aid in geolocation a suitable GES installation site.

Foreign direct investment (FDI) is widely viewed as a key driving force behind China’s exceptional growth performance in the last four decades. This paper investigates several questions posed by China’s success in capturing gains from FDI. What explains that success? Can other countries replicate it, or is it unique to China? What lessons are from China for other countries? China indeed has advantages in attracting FDI such as huge market and cheap labor, the well-designed policy and strategy, however, seem to play more important role in the successful story. Our empirical estimates support on four hypotheses: FDI and GDP growth in China positively interact each other; FDI is helpful to China’s technological progress, FDI promotes China’s industrial development, and FDI stimulates China’s manufactured exports.

The dawn of the Artificial Intelligence (AI) era presents a plethora of new possibilities for analyzing regional economic development. The present article provides an in-depth exploration of the methods employed in this field, highlighting the immense opportunities that AI offers while also addressing potential challenges. The role of AI is crucial in complex data handling, enabling efficient analyses of intricate regional economic patterns. This capacity is paramount in shaping economic policies and strategies that are reflective of each region's unique needs and potential. The article firstly explores various AI methods used in economic analysis, including but not limited to machine learning, deep learning, and natural language processing. It delves into the application of these methods in discerning development trends, predicting economic shifts, and identifying strategic economic drivers unique to various regions. Subsequently, the potential of AI to transform regional economic analysis is discussed, encompassing its capability to process large and complex datasets, its power to predict future trends based on past and present data, and its ability to aid in strategic decision-making. However, this new era of AI-driven economic analysis is not without challenges. The latter part of this article thus confronts the issues related to data privacy, ethical use of AI, and the necessity of interdisciplinary skills in AI and economics. This exploration contributes to a broader understanding of how AI is transforming the landscape of regional economic development analysis, illuminating both its present use and future implications. By understanding these dynamics, we can better harness the potential of AI to advance economic prosperity in various regions around the globe.

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 examines the impact of COVID-19 on Small and medium-sized enterprises (SMEs) deposits across 13 African nations from 2016 to 2022, using a seven-year dataset and Ordinary Least Squares estimator. Notably, it uncovers a significant positive link between the pandemic and SMEs deposits, indicating heightened reserves amidst economic uncertainty, potentially driven by risk mitigation or government support. Associations between gross domestic product (GDP), inflation, unemployment, foreign direct investment (FDI), exchange rates, and SMEs deposits were evident, showcasing higher GDP aligning with increased deposits, while inflation and unemployment linked to reduced ones. FDI showed a positive influence, and exchange rate fluctuations notably affected SMEs deposits, especially for those in international trade. These findings emphasize policy reconsideration for crisis strategies supporting SMEs reserves during uncertainty and interventions addressing inflation, unemployment, and exchange rate risks. Future research exploring regional nuances and global comparisons could further enrich policymaking for resilient SMEs amid evolving economic landscapes.

Economic globalization has intensified economic volatility around the world, and the importance of economic resilience has become increasingly prominent in the face of rising uncertainty due to frequent domestic and foreign shocks. Based on provincial panel data in China from 2008-2019, a comprehensive indicator system is constructed to measure regional economic resilience (RER), and the impact of financial driver (FD) on RER is explored from staged, pathway and non-linear perspectives. The main findings are as follows. (1) Both national and regional levels of FD and RER show an upward trend, and the impact of FD on RER has an “inverted-U” shape: as the capacity of FD increases, its impact on regional economic resilience shifts from promoting to inhibiting. The RER has significant spatial agglomeration characteristic. (2) Interestingly, staged analysis shows FD can significantly promote RER only when it is in the “recovery stage”. (3) The pathway analysis of its effect on regional economic resilience shows the following characteristics: financial scale > financial efficiency > financial deepening. (4) From different regions, there are significant differences in the effect of FD on the promotion of regional economic resilience: central region > western region > eastern region. Finally, the corresponding suggestions were provided.

The purpose of this paper is to examine and elucidate the effect of the announcement of winning a US federal contract by pharmaceutical companies, traded on the NASDAQ stock exchange on the share prices. The analysis is based on a sample of 327 event days from 12 pharmaceutical companies listed on the NASDAQ market for a given period (2010 – 2021). The sample is analysed by using the event study methodology and Capital Asset Pricing Model (CAPM) in order to examine the abnormal returns and cumulative abnormal returns during an event window of 10 days before the event and 10 days after the event. While prior researchers have identified significant positive abnormal returns following different types of contract announcements, this study aims to contribute to the existing literature by exploring the specific impact of the public contract in the pharmaceutical market on market shares. By investigating this unique aspect, the research fills a gap in previous studies and enhances our understanding of the relationship between public contract announcements and market performance. The data collection utilises secondary data from the official open data source of US federal spending information and daily stock prices. The collected data is analysed quantitatively using event study methodology, allowing for statistical examination of abnormal returns, such as ANOVA analysis, t-statistic, beta index, time series analysis and linear regression. The research findings indicate a significant impact of public contract-winning announcements on cumulative abnormal returns, suggesting a positive reaction from the market. However, average abnormal returns within the event window were positive but not statistically significant. These results imply that winning a government contract has a limited impact on the stock market. The implications of this research highlight the importance of public contract announcements in the pharmaceutical industry and their influence on share prices. The findings provide valuable insights for investors and stakeholders, aiding decision-making processes related to investment opportunities and market performance.