You have a product or service for which the world has been waiting. You've scraped together enough cash to get your idea off the ground. You are confident that your business will succeed. And yet, it is often the case that a short time later you are out of business. Numbers from the U.S. Bureau of Labor Statistics indicate that about half of new businesses fail within the first five years. And with those business failures go the life savings and the dreams of the person who started the business. This article describes five finance and accounting pitfalls that should be avoided in order to increase the likelihood that a small business will succeed. Of course, the most common reason for a small business to fail is that customers don't want the product or service. But small businesses are also often killed because of predictable and preventable finance and accounting mistakes: insufficient capital, poor cash management, poor record keeping and controls, improper product pricing, and uncontrolled growth.

The development of digital economy is becoming an important path to promote the kinetic energy of China's tax revenue development. Based on the panel data from 2011 to 2018, this paper uses Gini coefficient to analyze the regional differences of China's digital economy, and uses fixed effect model, spatial Durbin model, multi-period double difference model and other empirical methods to examine the tax effects of digital economy development. The results show that the regional disparity is the main reason for the regional disparity of digital economy development in China. The development of digital economy directly increases the tax amount of local digital industry, and at the same time it also radiates and drives the increase of local total tax revenue; The tax effect of digital economy has a negative spatial spillover, showing a "siphon effect" to neighboring areas; Mechanism analysis shows that the development of digital economy mainly promotes the increase of local tax revenue through growth effect.

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.

The digital economy industry plays a transformative role in reshaping the global production networks, the local division of production, and the integration and innovation of business forms. However, to what extent the industry enables the high-quality development and upgrading of urban economies is unclear. Based on the census data of digital economy enterprises in Hangzhou in 2008, 2013 and 2018, this paper verifies the characteristics of the digital economy industry and its enabling mechanism for high-quality urban economic development. It is found that: firstly, the digital economy industry has three main forms for the economy, namely, the sharing, scale and scope economy. Secondly, the industry has four major mechanisms to improve the quality of urban economies. That is, it can restructure the global industrial division of labor and value chains, promote the transformation of scale economy from the supply side to the demand side, enable the softening and servitization of industrial structure, and generate the scale of economies. This paper thus contributes to understanding the evolution of enterprise organizational structure and industrial competitiveness and the endogenous technological change under the digital economy.

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.

Green credit policy (GCP) relies on financial means to promote environmental governance. Whether it can achieve the goals of economic development and environmental protection, especially in the context of different institutional supplies, remains to be scientifically tested. Based on the implementation of China’s Green Credit Guidelines in 2012, this study uses panel data of Chinese companies from 2009 to 2019 to explore the influence of GCP on green technology innovation and the role of institutional supply in it. The results show that GCP is instrumental in promoting green innovation in heavily polluting enterprises, and the promotion effect is heterogeneous based on green patent types, firms’ ownership, and regional financial development levels. Further analysis finds that the supply of environmental protection systems by local governments can strengthen the green innovation effect of GCP. However, the institutional supply of innovation has not yet released a promotional effect. This paper finds that green credit can be used as an environmental governance tool and provides inspiration for local governments to issue environmental protection policies scientifically.

Deposit dollarization in Turkey has been on the rise, reaching record levels in 2022. This was caused by the worsening macroeconomic fundamentals along with the transition to the presidential system in 2018 and the associated deviation from the monetary policy stance afterward. The unique case of Turkey presents an excellent natural experiment to explore the dynamics of deposit dollarization and how it is affected by the changes in the institutional structure as well as various social, economic, and financial shocks in a relatively short time. This study examines the time varying reactions of deposit dollarization for the period between 2013 and 2022 based on rolling window maximum entropy bootstrap estimates. Our findings reveal that all the model variables had significant and sometimes asymmetric effects on deposit dollarization during the different stages of this turbulent period. In particular, we observe diminishing effects of real exchange rate, policy credibility and consumer confidence over time. The findings provide ample new evidence regarding the dynamics of deposit dollarization in general, and how it is affected by loss of monetary policy credibility.

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.

Under the background of digital economy, global tax governance has become one of the important topics in today's world development and change. In recent years, new challenges, such as tax base erosion and profit transfer, and the imbalance of cross-border tax source division, have become prominent, forcing the reform of international tax rules and the reshaping of international tax order. Based on this, the article first deeply digs into the scale and cross-border characteristics of the spatial-temporal aggregation of the digital economy, and comprehensively evaluates its impact on the global tax governance pattern. After that, the article combs out the realistic picture and challenges of the current digital tax reform from the aspects of theoretical basis, basic principles and governance mechanism. Finally, based on China's basic national conditions, the article puts forward some institutional ideas and policy suggestions, with a view to improving China's participation, voice and influence in global tax governance, and also enabling governments, enterprises and residents of various countries to enjoy the fruits of world economic development fairly and promote the construction of Community of Shared Future for Mankind.

Green innovation, as a sustainable development approach, can synergistically promote high-quality economic and social development. We select China's A-share-listed manufacturing corporations from 2011 to 2021 as the research sample to empirically study the impact of executive academic experience on green innovation in manufacturing corporations. Further, we test the relationship between executive academic experience and green innovation in manufacturing corporations under the mediating role of corporate social responsibility and the moderating role of heterogeneous environmental regulations. The study shows that (1) executive academic experience helps to promote green innovation in manufacturing corporations; (2) executive academic experience is conducive to promoting the fulfillment of social responsibility by manufacturing corporations; (3) corporate social responsibility plays a mediating role between executive academic experience and green innovation in manufacturing corporations; (4) environmental regulation positively moderates the relationship between executive academic experience and green innovation in manufacturing corporations, and both formal environmental regulation and informal environmental regulation positively moderated the promotion of green innovation in manufacturing corporations by executive academic experience.

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.

In the UK, a concern of prejudice, as well as a lack of gender identity and sexual orientation documentation, implies that LGBT persons mostly hidden to health-care providers. One of a review was carried out to examine primary literature on the psychological support requirements of LGBT cancer patients when receive treatment and after. Important findings: Key topics that have been mentioned include the negative impact on mental health, health care professional education and the absence of inclusive support groups, the pervasiveness of discriminatory practices within healthcare services. The research demonstrates how LGBT cancer patients are being failed by healthcare professionals in terms of psychological support, resulting in unmet requirements. There are some suggestions use to guarantee an LGBT inclusive atmosphere in cancer care, as well as the development of support programmes for LGBT people with cancer. Practical connotation: LGBT wellness and awareness education should be offered for HCP personnel. The registration and tracking of gender identity and sexual orientation is critical to ensuring that LGBT persons are not 'invisible' in cancer, radiation, and continued studies. LGBT cancer groups and services should be established, since information from the study indicated that LGBT individuals are actively seeking these services.

Competitive balance indicates the degree of control participating teams have over a sports competition. Supporters look for excuses to justify their team’s defeat and the triumph of their rivals. If the competition has required a preliminary qualifying group stage, they will argue that the winning team was in an "easy group" from the start, and their team was unlucky to be in a "difficult group". It is therefore of interest to determine what is an "easy group" and what is a "difficult group". This is directly related to the concept of competitive balance. We have a wide range of indices to measure competitive balance. We will use the Distance to Competitive Balance, a standardized index that complies cardinality property. The perfectly unbalanced distribution is the truncated cascade, which allows the maximum value of concentration to be obtained. We focus our attention on the UEFA Champions League, before and after competition, and we measure the competitive balance of the qualifying stage groups between the 1999/2000 and 2022/2023 seasons. The composition of the UEFA Champions League groups seems to be balanced and has no influence on which team will be the champion. A highly competitive group will be more "difficult" in terms of qualifying than a highly concentrated one. Supporters say that their team was unlucky to be in a “difficult” group, but the data does not prove them right.

Electricity price volatility in developing economies, particularly Nigeria, presents a significant challenge to sustainable development. In this paper, we examine the macroeconomic drivers of electricity prices (ELP) in Nigeria based on annual data spanning 1980-2022 and the autoregressive distributed lag (ARDL) procedure. Our model estimates the long-run and short-run impacts of population growth (PG), economic growth (GDP), crude oil price (COPR), and electricity consumption (ELC) on electricity prices (ELP). The empirical findings reveal a positive and long-run effect of PG on ELP, indicating that rising demand from a growing population increases electricity prices. In the short-run, ELC surprisingly co-moved with ELP, which may be attributable to price-sensitive demand within specific consumer segments or periods. Furthermore, GDP and COPR exert positive effects on ELP, indicating that economic growth drives energy consumption and prices, and the cost-driven impact of fossil fuel dependence in electricity generation. These findings shed light on the complex interplay of demographic, economic, and energy market-related forces driving electricity prices in Nigeria. Therefore, the paper proposes some policy suggestions based on the empirical findings.

This paper examines the information content of selected US industries focusing on the dynamic linkages among these industries, the stock market and a number of fundamental variables. The period of investigation spans from January 1960 to December 2021. The empirical strategy includes several methodologies such as regressions, vector autoregressions and volatility models. The idea is to investigate the dynamic linkages among these series at both the mean and the volatility levels. The results point to significant industry returns’ explanatory power for many predictors of economic activity including the stock market. Further, time-varying analysis of the linkages among the industries and the stock market’s returns reveal that certain industries such as Oil and Financials provide consistent information leadership over other industries and across decades. Further, upon assessing the industry–market return volatility spillovers, it was found that a market risk–return profile may not always be economically significant and timely for investors. Finally, crises, financial or otherwise, affect industries but to differing degrees.

The Hospital Price Transparency Final Rule aims at reducing the cost of healthcare in the United States by making information about the prices of medical services more readily available to market participants. The economic rationale is that higher price transparency should reduce the level and the dispersion of prices by disincentivizing hospitals from charging higher prices than possible. Using data on 3789 prices for three diagnostic imaging procedures and on the compliance with the rule for 86 acute care hospitals in the Greater Los Angeles area, we test the hypothesis that price levels and price dispersion are lower among hospitals that are more compliant. We do not reject this hypothesis, although we do not observe strictly decreasing relationships in all analyses. Prices are lower at hospitals with high or medium compliance than at hospitals with low compliance, but there is not a clear difference between hospitals with high and hospitals with medium compliance. Prices are less dispersed among hospitals with high compliance than among hospitals with low compliance, but the evidence for hospitals with medium compliance is less clear. We conclude that high compliance with the Hospital Price Transparency Final Rule implies lower prices and less price dispersion among hospitals.

In his "The World’s smallest macroeconomic model” (Krugman (1999)), Paul Krugman argued that under the assumption of price rigidity, a shortage of money supply leads to underemployment or recession, so increasing money supply can eliminate underemployment and restore full employment. But, how do we increase the money supply? I will show that we need a government deficit to increase the money supply in order to restore full employment from recession. Also, I will show that in a growing economy, if people hold money, a government deficit is necessary to maintain full employment under constant price or inflation. A government deficit is not only effective in pulling the economy out of recession, it is even necessary for continued growth without inviting either recession or inflation. The government deficit in this paper represents the difference between government expenditures and government revenues. When the difference is positive, we say that the government has a deficit. This paper seeks to explore theoretically and normatively the role of government deficits in achieving and maintaining full employment in a growing economy without causing inflation, using a very simple model by Krugman.

Machine learning is playing an increasingly important role in the healthcare industry by transforming the way cancer is diagnosed and treated. By analyzing patient data, genomic data, and imaging data, machine learning algorithms can identify molecular signatures that distinguish cancer patients from healthy patients. Biomarkers that can accurately detect and diagnose cancer can be identified through analysis of these data sources. Additionally, personalized cancer therapies can be developed by identifying the most effective treatments based on individual patient characteristics and cancer type. Some of the machine learning techniques used for cancer biomarker discovery include deep learning and support vector machines, which can respectively identify complex patterns in data and classify data to identify relevant biomarkers. The benefits of using machine learning for cancer biomarker discovery are significant, including more precise and personalized treatments, improved patient outcomes, and the potential to transform cancer diagnosis and treatment. However, there are also challenges associated with using machine learning for cancer biomarker discovery, such as data collection and privacy issues, as well as the need for more powerful computational resources. This article explores the potential of machine learning in cancer biomarker discovery and argues that ongoing research in this field has the potential to revolutionize cancer diagnosis and treatment. Future research directions should focus on further developing machine learning algorithms and effective data collection and privacy protocols.

Based on the panel data of western central-cities from 2002 to 2021, this paper uses the intermediary effect model to analyze the relationship between urban internationalization, innovation ability and urban competitiveness. It is found that: (1) The internationalization of western central-cities has a positive and direct impact on the promotion of urban competitiveness, which has a significant impact on economic strength and infrastructure, and a weak impact on government efficiency and market efficiency The marginal growth effect of internationalization on urban scale will gradually decrease with the improvement of urban development level. (2) The continuous promotion of city internationalization can promote the innovation ability to enhance the competitiveness of the city. Compared with the internationalization of cities, the influence of innovation ability on the competitiveness of cities is small, and the innovation ability of western central-cities and each city is weak. The scale effect has become the main motivation to promote the competitiveness of cities. (3) In the process of internationalization of western central-cities, innovation ability has a part of intermediary effect on the improvement of urban competitiveness, and the effect on urban “hard environment” is significantly greater than that on urban “Soft-environment”. The results of direct and indirect impact tests show that the impact of the process of internationalization of western central-cities on urban competitiveness is exogenous.

Hundreds of articles have been written that include empirical estimates of the dis-employment effects of minimum wages; however, many of these articles find statistically insignificant effects, some find significant negative effects, and a few find significant positive effects. Most of these studies use multivariate analyses which can be criticized for omitting key variables. The omitted variables problem ruins all statistics and estimates. This paper uses reiterative truncated projected least squares (RTPLS), a solution to the omitted variables problem, to estimate the percentage increase in unemployment due to a one percent increase in the real minimum wage using monthly data for the 50 states of the USA from 1987 to 2021. RTPLS produces a separate elasticity for every observation where differences in these estimates are due to omitted variables. We argue that RTPLS solves most of the econometric problems that David Neumark identified in his keynote address at a minimum wage conference in Berlin in 2018. We find that the percentage change in the unemployment rate due to a one percent change in the minimum wage ranges between 1.156 and 3.389, that the elasticities for different states tend to move together over time, and that all these elasticities are statistically significant at a 95 percent confidence level.