Technological advancements in the last few decades have created energy and cost-efficient power plants, but it is not a prominent feature in the electricity supply-chain. While many long-term and short-term energy alternatives are available, Pakistan still has a significant number of people who do not have access to electricity; as there are many areas that are neither connected to the national grid nor the provincial grids. This paper aims to find the reasons behind the energy crisis in Pakistan, keeping Islamabad as the focus of study, and to find the effect of use of renewable resources on the reduction of shortage of electricity. We will be focusing on the facts that how energy crisis has been affecting the economic growth of the country.  Our data collection will be based on primary sources and secondary sources along with which we will be conducting pilot study to check the feasibility of using the solar energy as an alternative form of electricity.

This paper examines the efficiency, in its weak form, of the clean energy stock indices, Clean Coal Technologies, Clean Energy Fuels, and Wilderhill, as well as the cryptocurrencies classified as "dirty", due to their excessive energy consumption, such as Bitcoin (BTC), Ethereum (ETH), Ethereum Classic (ETH Classic), and Litecoin (LTC), from January 2020 to May 30, 2023. In order to meet the research objectives, the aim is to answer the following research question, namely whether: i) the events of 2020 and 2022 accentuated the persistence in the clean energy and dirty energy indices? The results show that clean energy indices such as digital currencies classified as "dirty" show autocorrelation in their returns; the prices are not independent and identically distributed (i.i.d). In conclusion, arbitrage strategies can be used to obtain abnormal returns, but caution is needed as prices can rise above their real market value and reduce trading profitability. This study contributes to the knowledge base on sustainable finance by teaching investors how to use forecasting strategies on the future values of their investments.

Green innovation, driven by China's new development concept, plays a crucial role in high-quality economic development. In line with the green development trend, businesses increasingly prioritize whether their corporate environmental responsibilities (CER) can effectively enhance corporate green innovation (CGI) levels. This paper examines the influence and mechanism of CER on CGI using a dynamic perspective, drawing from 1,640 manually-collected panel data of Shanghai and Shenzhen A-share listed companies between 2010 and 2017. The primary findings indicate that the impact of CER on CGI possesses phase-specific characteristics and a dual effect of "crowding in" and "crowding out." The current phase of CER negatively affects green innovation, while the lag phase has a positive effect. CER's impact on various CGI types is heterogeneous: specifically, it follows an "inverted-N" trajectory (inhibition-promotion-inhibition) for "strategic green innovation" and has a promotional effect on "substantive green innovation," which is stronger and has a longer time lag. The mechanism analysis reveals that financing constraints play a critical mediating role. A heterogeneity analysis based on multiple dimensions (ownership, industry, and location) suggests that CER has a more significant driving force for CGI among state-owned firms, high-polluting industries, and enterprises in inland areas. Finally, the paper presents corresponding suggestions for government and corporate entities.

Alternative bio actively chemicals may be found in natural goods and traditional herb medications, but only a few plant-information formulations have been rigorously studied and verified for their potential as medicinal therapies. The study of plant-derived elements' immunomodulation capabilities and their ability as provoke the immune system as combat various elemental disorders like cancer is, nonetheless, a promising area in current therapeutics information on plant-derived chemicals. This research showed how network pharmacology may be applied as define and validate natural individual elements or more complicated preparations as prospective cancer therapies information on their various aim capabilities in this research. We give a summary of the present state of understanding on network pharmacology, with a particular emphasis on various technical methods and their implications for cancer treatment.

The paper addresses the alternative policy options available to address the question of lives versus livelihood in an SIRD model augmented with a macroeconomic structure. An important contribution of the paper lies in designing the policy of lockdown dependent on the extent of the constraint on the health facilities. The paper supplements the literature with a less stringent version of the lockdown policy, viz. soft lockdown policy which is shown to be more attractive from a public policy standpoint and has actually been practised in many countries across the globe during the recent pandemic. Finally, the optimal policy derived on the basis of the level of lockdown and adjustment of the binding constraint on health facilities depends on the objective of policy makers contingent on the relative weights of lives versus livelihood.

Non-compliance with tax obligations, particularly by wealthy taxpayers and large corporations, continues to represent a source of social injustice that fuels social instability, especially in developing countries. Understanding the strategies of tax evasion and avoidance is of critical importance. This article highlights five main strategies used by large corporations and wealthy taxpayers to avoid taxes, including tax havens, the underground economy, aggressive tax optimization, alternative financial markets, and crypto currencies. We also propose several actions to tackle global tax non-compliance, including prevention, peer reporting, active monitoring of compliance indicators and inter- national cooperation. These actions can be combined to achieve optimal results in reducing tax evasion and avoidance.

Entrepreneurs are important actors in economic activities and creators of social wealth. Excellent entrepreneurs contribute their wisdom to the accumulation of social wealth and the promotion of high-quality economic and social development. The business environment is the main manifestation of the soft power of cities and regional economic development, and a better business environment can effectively attract enterprises and promote their sustainable growth. Using data from Chinese A-share listed companies from 2009-2019 as a research sample, the following research conclusions were drawn: (1) A better business environment helps enhance entrepreneurship. (2) A better business environment promotes entrepreneurship by reducing rent-seeking expenses and corporate credit costs. (3) Compared to traditional enterprises, high-tech enterprises are better able to enjoy the benefits brought by business environment optimization and further enhance entrepreneurship. When competition is low, entrepreneurs face lower rent-seeking expenses, which is conducive to stimulating entrepreneurship. The businessenvironment can promote fairness and bring more equal financing opportunities for enterprises, which has a higher impact on entrepreneurship for the group facing higher financing constraints. This study meticulously analyzes the impact ofthebusiness environment on entrepreneurship, providing references for the next steps of optimizing the business environment and enhancing entrepreneurship.

Access to electricity, a fundamental element of contemporary life, is essential for economic success. Its impact extends to the fundamental foundations of industrial development and has the power to improve a wide range of industries, including healthcare, transportation, utilities, and education. This article aims to analyse the effect of electricity access on primary education in Central Africa over the period 1997-2019. To this effect, we employ data mainly from the World Development indicator on 9 countries of Central Africa. Using the pooled ordinary least squares estimation technique, the results indicate that access to electricity contributes positively and significantly to primary educational attainment in Central Africa during the study period. The results are Robust to the use of alternative estimation strategy and eventual endogeneity problems in the results are account through the two stage least square estimation techniques which confirm our baseline results as well as the nature of the relationship between access to electricity and primary education in Central Africa. These results have important implications for policies in overcoming barriers to electricity access.

We empirically address the effects of monetary policy on the housing market in China using a novel Time-Varying Parameter VARX model. We show that an expansionary monetary has positive effects on the housing market, while during COVID-19, the effects are approaching to zero or even negative. In addition, the effects of the LPR policy are strong and even larger than that of COVID-19. Relative impulse response functions in the shorter and longer time horizons are dynamic and especially during COVID. This paper also contributes to the housing literature to show that COVID-19 can block the transmission of monetary policy.

This research paper examines changes in patient care management in acute care hospitals between 2001 and 2011. During this time, there were two opposing factors at play: the competition effect of the reform and the policymaker’s decision to reduce public hospitals across France. By studying the trends, it is evident that there has been a significant overall shift in patient care management during this period. This change could be attributed to the global competition effect and the concentration of in-patients in specific public facilities. Through the difference-in-difference method, the study analyzed time variations in the intensity of local competition. It was found that local competition had a negligible impact on patient care management. Additionally, the study revealed that there was a significant positive competition effect on high-technical procedures for the private sector, which is in line with the market segment where private sector hospitals have a leadership position and the pro-competitive reform intensified this position. The study also uncovered a negative competition effect on the length of stay for public hospitals. Prior to the implementation of the DRG-based payment reform, public sector hospitals were paid a global budget. However, after the reform was implemented, they had to shorten the length of stay to increase the number of stays. For-profit hospitals have always been paid based on the number of stays. The results are robust and consistent when alternative measures of local competition are used.

The Human Development Index (HDI) aims to present a more robust picture of a country’s development status than that suggested by national income per capita. The HDI aggregates dimension indices based on transformed measures for the core values of health, education, and income per capita. Assumptions are made regarding the upper and lower bounds used to re-scale each core value into its dimension index, as well as the functional form used to create the HDI. The treatment of income in the HDI’s construction suggests incompatibilities with its underlying capability theory, which stresses the importance of individuals’ abilities to make their own consumption and life choices. We examine the currently formulated HDI, as well as two influential proposed alternatives which generalize the aggregation functions of the pre-2010 HDI formulation and the current HDI, in light of recent empirical research into the relationship between well-being and income. We use underlying data for 2016, a representative year, to examine distributional changes as well as specific country rankings. We find that the income bounds used to calculate the income dimension index in the HDI should be changed. We also suggest that the three aggregation formulations, along with prominent descriptions of the assumptions and consequent implications of each approach, should be disseminated for policymakers and the public to consider.

The rise of privately issued digital currencies, which primarily serve as alternative investment assets poses a challenge to the traditional financial instruments traded in the financial market. This study examines the dynamic relationship between the major privately issued digital currency (Bitcoin) and two financial market securities in Nigeria. The paper employed Vector Autoregressive (VAR) model and presents three relevant findings. First, the impulse response function indicates the absence of a significant response of the Nigerian financial market to shocks emanating from the Bitcoin market, implying lower connectedness between the two markets. Secondly, the outcome of the variance decomposition reveals a lower contribution of Bitcoin to changes in stock prices and treasury bills, however, stock prices and treasury bills contributed higher impact to each other compared to the contribution of Bitcoin. Thirdly, a weak bi-directional causality between the Bitcoin and treasury bills was observed and a uni-directional causality running from treasury bills and stocks, implying the existence of portfolio rebalancing from the fixed income to the equities market. Despite the weak connection between digital currency and the financial market, the paper recommends that the Central Bank of Nigeria and the Securities and Exchange Commission should maintain monitoring the development of crypto exchanges and continue reviewing the existing policy restricting cryptocurrency transactions through banks to avoid its unsavoury effects.

Adenosine alterations to RNA, which are largely determined by RNA modification writers (RMWs), are critical for cancer growth and progression. These RMWs can catalyze different types of adenosine modifications, such as N6-methyladenosine (m6A), N1-methyladenosine (m1A), alternative polyadenylation (APA), and adenosine-to-inosine (A-to-I) RNA editing. These modifications have profound effects on gene expression and function, such as immune response, cell development. Despite this, the clinical effects of RMW interactive genes on these cancers remain largely unclear. A comprehensive analysis of the clinical impact of these epigenetic regulators in pan-cancer requires further comprehensive exploration. Here, we systematically profiled the molecular and clinical characteristics of 26 RMWs across 33 cancer types using multi-omics datasets and validated the expression level of some RMWs in various cancer lines. Our findings indicated that a majority of RMWs exhibited high expression in diverse cancer types, and this expression was found to be significantly associated with poor patient outcomes. In the genetic alterations, the amplification and mutation of RMWs were the dominant alteration events. Consequently, the RNA Modification Writer Score (RMW score) was established as a means to assess the risk of RMWs in pan-cancer. We found that 27 of 33 cancers had significantly higher scores compared with normal tissues, and it was significantly correlated with prognosis. We also evaluated their impact on the tumor microenvironment and the response to immunotherapy and targeted therapy. These findings verified the important role of RMWs in different aspects of cancer biology, and provided biomarkers and personalized therapeutic targets for cancer.

In light of the events of 2020 and 2022, this study aims to examine the co-movements between the capital markets of the Netherlands (AEX), France (CAC 40), Germany (DAX 30), the United Kingdom (FTSE 100), Italy (FTSE MIB), Spain (IBEX 35), Russia (IMOEX), and spot prices of crude oil (WTI), silver (XAG), gold (XAU), and platinum (XPT) from January 1, 2018 to December 31, 2022. The purpose of this analysis is to answer the following research question: (i) Did the events of 2020 and 2022 increase the shocks between stock markets and WTI, XAG, XAU, and XPT prices? The findings indicate that time series do not follow a normal distribution and are stationary. In response to the question of investigation, we found that during the Tranquil period, it was possible to verify the existence of 28 causal relationships (out of 110 possibilities). During the stress period, there was a very significant increase in the number of causal relationships between the market pairs under analysis (62 causal relationships out of 110 possibilities), including a relative increase in the influence of commodities on capital markets and capital markets on commodities. These findings show that during the events of 2020 and 2022, capital markets and commodities significantly accentuated their co-movements among themselves, indicating that alternative markets such as WTI, XAG, XAU, and XPT do not provide safe-haven properties. These results have implications for portfolio diversification during times of global economic uncertainty.

This paper provides an overview of the existing literature on the use of artificial intelligence (AI) in various fields, including economics, finance, mining, manufacturing, and innovation. The paper identifies the drivers and effects of AI deployment in the context of innovation and highlights the challenges and opportunities that arise from the use of AI. The studies reviewed in this paper cover various topics related to forecasting, including the impact of AI on professional skills, hybrid forecasting techniques for predicting commodity prices, and novel deep reinforcement learning algorithms for crude oil price forecasting. The paper’s contribution lies in its systematic and comprehensive approach to reviewing the literature, which allows for a better understanding of the impact of AI on various fields and the identification of strategies to address the challenges that arise from its deployment.

Gold has been traditionally well recognized as a safe heaven for financial markets. Lately, Bitcoin has been gradually considered as a popular alternative. Since the outbreak of COVID-19 in early 2020, it has become even more necessary and critical to examine the diversification capability of them to hedge financial risks associated with an unexpected crisis comparable to the pandemic. This paper hence employs the wavelet analysis, complemented by the multivariate DCC-GARCH approach, to measure the coherence of the gold and Bitcoin prices with six representative stock market indices, three for developed economies and three for emerging economies, all of which are heavily affected by the pandemic. To have a more balanced and comprehensive analysis, two-year data are used, spanning from 12th April 2019 to 15th April 2021, which covers approximately one year before and one year after the announcement of the COVID-19 pandemic. The results suggest that the returns of both gold and Bitcoin are generally not strongly correlated with the market returns of all six indices, particularly for short-term investment horizons. That is, investors in all six indices can benefit through gold, as well as Bitcoin, in terms of hedging. Meanwhile, compared with Bitcoin, gold shows to be less correlated with the indices, particularly for long-term investment horizons. The findings hence suggest that gold and Bitcoin offer diversification benefits to investors in the market indices during a crisis such as the COVID-19 pandemic, especially for short-term investment horizons. The study also reminds policymakers thinking beyond the pandemic about the future of the earth, including air pollution and health, for sustainable development of the whole world.

Carbon emissions trading is essential for reducing carbon emissions, and its role in regional carbon unlocking needs further clarification. This study uses the difference-in-differences (DID) model and synthetic control model (SCM) to evaluate the carbon unlocking effect of China’s six pilot carbon trading provinces. This study found that (1) carbon lock-in effects in China are mainly influenced by technology lock-in and fixed input lock-in; (2) each province’s overall carbon lock-in level presents a decreasing trend yearly, and the regional distribution presents characteristics of “low in the east and high in the west”; (3) carbon emissions trading pilot policies effectively promote the carbon unlocking effect in pilot regions overall, with Guangdong having the most significant unlocking effect. Conversely, Beijing, Hubei, Chongqing, and Shanghai also had different degrees of carbon unlocking. Finally, (4) an assessment of impact mechanisms indicates that technology and institutions have a significant mediating role in effectively promoting carbon unlocking under the carbon trading policy. Conversely, social behavior has an inverse effect, and fixed assets are not affected by the policy. This study demonstrates the carbon unlocking effect of carbon emissions trading and provides a quantitative reference for implementing carbon emissions trading policies and determining carbon unlocking paths.

The construction and optimization of a portfolio is a complex process that has been a historically active research area in finance. For portfolios with highly correlated assets, the performance of traditional risk-based asset allocations methods such as the mean-variance (MV) model is limited when numerous assets are correlated. A novel clustering-based asset allocation method, called Hierarchical Risk Parity (HRP), provides an opportunity to mitigate these limitations in portfolio construction. HRP utilizes the hierarchical relationships between the covariance of assets in a portfolio to determine weight distributions, eliminating the need for the inversion of the covariance matrix that is required by most traditional risk-based asset allocation methods. This research examines the viability of Hierarchical Risk Parity (HRP) method in portfolio construction of a US equity portfolio and compares the performances of HRP to traditional asset allocation methods exemplified by the mean-variance (MV) method. The results of this research show that the performance of the HRP method is comparable to the performance of the MV method. Given these findings, HRP provides an advantageous approach for portfolio construction in practical scenarios where correlated assets are present in the portfolios.

The low-carbon city pilot is an important policy for promoting sustainable development and addressing climate change. The level of green technological innovation is a significant driving force for China's transition to high-quality development and the realization of carbon peaking and carbon neutrality goals. This essay takes the panel data of 30 provinces in China from 2008 to 2020 as the research sample, regards the number of urban green invention patent applications as a quantifiable indicator of the level of urban green technological innovation, and takes the policy of low-carbon city pilot as a quasi-natural experiment, and uses the difference-in-differences model to test the impact of low-carbon city pilot on the level of urban green technological innovation, and to investigate the mechanism of action within. The main conclusions are as follows: (1) The policy of low-carbon city pilot has an outstanding promotion effect on the level of urban technological innovation. (2) Using the mediating effect to analyze, it is found that the low-carbon city pilot policy can improve the level of urban green technological innovation through the development of green finance.

Bank capital requirements would entail large social costs if they made resource allocation suboptimal and banking services costly by unduly limiting the banks’ ability to lend. This paper considers three main factors that may make capital requirements relevant, namely, deposit insurance subsidies, stock valuation errors, and tax shields derived from debt financing. The theoretical model analyzes the combined effects of the three factors on the banks’ incentives to make fairly priced loans, which should also be socially optimal loans. A key finding is that the long-term cost of capital requirements is likely to be very small when deposit insurance is underpriced. Increased funding costs resulting from higher capital requirements are absorbed by shareholders of banks, rather than passed on to borrowers. Under some reasonable assumptions, higher capital requirements improve resource allocation by countervailing distortionary effects of deposit insurance subsidies. Short-term adjustment costs can still be large, but it should be relatively easy to mitigate the short-term effects.