This paper estimates panel vector autoregressions to analyze the endogenous connection between COVID-19 and non-communicable diseases (NCDs). Using weekly, US state-level data, the study finds evidence of a significant positive effect of NCD-related mortality on deaths due to COVID-19. I find this effect to be higher for males than females. Results are robust to several sensitivity checks, so large deviations are unexpected.

In his 1922 review for Cambridge Magazine of Keynes's A Treatise on Probability, and again in his 1926 review "Truth and Probability" (published in 1931 and republished in Kyburg and Smokler's 1980 edition), Ramsey provided examples critiquing Keynes's logical theory of probability. However, these examples do not disprove Keynes's theory as all of them are flawed. The flaws arise because all the pairs of propositions that Ramsey used to substantiate his criticisms are irrelevant to each other. Such irrelevant propositions are explicitly excluded from Keynes's theory in pages 4-6 of his A Treatise on Probability. This paper highlights that Ramsey's examples, which involve irrelevant propositions, do not disprove Keynes's Boolean, relational logic. The only other defense of Keynes's theory, put forth by Watt in 1989, was found to be deficient by Brady in 2022.

This paper investigates the degree of inflation persistence across regions in Portugal by analyzing the Consumer Price Index (CPI) growth rates for NUTS II regions. The study employs the Augmented Dickey-Fuller (ADF) test to determine whether the CPI data for Portugal is stationary or non-stationary. The results of the ADF test reveal that the IPC data for Portugal is non-stationary, indicating that inflation exhibits persistence in the long run. The study further assesses the persistence of inflation by estimating an autoregressive integrated moving average (ARIMA) model for each region. The Ljung-Box test is used to test for autocorrelation in the time series data, and the Hurst exponent is calculated to evaluate the presence of long-term memory in the time series data. The study finds that there is significant autocorrelation in the time series data for all regions, supporting the presence of persistence in inflation at the regional level in Portugal. The Hurst exponent also shows that the time series data for each region exhibits a high degree of persistence in inflation. Finally, the study applies the ARIMA model to each CPI division's data and uses the Ljung-Box test to test for autocorrelation in the time series data. The results show that some CPI divisions exhibited higher levels of persistence compared to others. For example, the "Housing, water, electricity, gas and other fuels" division exhibited high persistence, while the "Communication" division exhibited low persistence. This study contributes to the existing literature by exploring regional inflation persistence in Portugal and its implications for policymaking. The results provide insights into the inflation persistence patterns across regional levels in Portugal, by emphasizing the need to consider regional differences in inflation dynamics when formulating effective policy interventions. Understanding the persistence of inflation is crucial for policymakers to ensure price stability and sustainable economic growth.

Part of the present inflation is caused by the breakdown of globalization, in particular supply chains, part is caused by the Corona Pandemic, in particular lockdowns, part is caused by the Ukrainian War, part is caused by European sanctions, and part – and not the smallest one – is caused by the European Central Bank’s printing money by hook or by crook in the past and in the presence. This paper attributes inflation decisively to the overwhelming money creation by the European Central Bank.

When human civilization is thriving to the rapid economic and social development, the deteriorating ecological environment has also pressured the society to put environmental protection issues on the agenda future development. Therefore, green innovation is not merely a requirement for a corporate’s long-term development but the basics of sustainable development of human society. As an objective indicator to measure a company's commitment to social responsibility, corporate environmental responsibility has an extremely important impact on a corporate's business philosophy and innovation strategy. However, the existing literature rarely studies between these two variables. This paper collects the data of listed companies from 2010 to 2019 and empirically tests the impact of corporate environmental responsibility on corporate green innovation. The study finds that corporate environmental responsibility can promote green innovation by reducing financing constraints, improving corporate governance and increasing government subsidies and R&D investment, and the result is still significant under a series of robustness checks. The placebo test suggests that the Jiangsu enterprise responsibility construction pilot has facilitated the development of enterprises' green innovation to a great extent. The conclusions enrich existing literature on corporate environmental responsibility and corporate green innovation, providing implications for government policy orientation, social atmosphere guidance and corporate strategic decision-making process.

The use of All-Terrain Vehicles (ATVs) has gained considerable attention within the recreation industry. The incorporation of ATVs into tourism and recreational activities has demonstrated substantial economic potential for local economies. However, there is a lack of comprehensive knowledge regarding the economic impact of ATV recreation. This paper conducts an extensive review of existing literature from 2004 to 2022, evaluating the economic impact of ATVs on local economies in the United States. The review aims to identify commonalities and disparities among existing economic impact studies and assess whether these studies have included costs associated with ATV-induced environmental, societal, and public health damages in their economic assessments. To this end, there is a scarcity of scientific peer reviewed journal articles that exclusively focus on the economic impact of ATVs. As such, we reviewed a total of seven publications comprising reports. The results of our analysis shed light on similarities and differences in aspects of resident and non-resident ATV spending, type of ATV expenditures, and the approaches used to evaluate economic impact assessment. The findings indicate that existing studies have assessed the economic impact of ATVs solely based on gross expenditures, lacking comprehensive inclusion of the costs associated with ATV damages to the environment, society, and human health. This study advocates for the need for a more comprehensive consideration of both benefits and costs in the economic impact of ATVs to assist ATV business managers, policymakers, and researchers in making informed decisions and planning future programs.

Bank deposit is closely related to systemic risks. In addition, considering that resident deposits in China have significant seasonal characteristics, this paper focuses on which component of deposits drives the systemic risk volatility, that is, it can supplement the existing forecast information. We use X-13ARIMA-SEATS to decompose deposit into three subsequences. The research findings show that the forecast effect of subsequence models is better than that of benchmark series. Most importantly, the model with trend component has the best forecast performance.

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.

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.

The aim of this study is to solve the problem of labor allocation in cases where the company has fewer employees than the number of existing jobs based on the evaluation of work quality according to multiple objectives. Optimizing labor allocation not only benefits the company by maximizing the use of human resources, but also saves employees' energy. In addition, employees are assigned to tasks that match their skills and qualifications, maximizing their productivity. The research results show that the multi-objective decision-making algorithm based on the Hungarian algorithm is a suitable method to help leaders of companies solve the aforementioned problem text.

We assess the impact of the Strategic Economic Plan on Singapore’s long-term GDP per capita. To our knowledge, we are the first to evaluate the effect of the 1991 plan on Singapore’s successful growth trajectory using methodologies aimed at causal identification. In other words, this article applies the Synthetic Control method and World Bank data from 1970 to 2018. We estimate an average increase of 6,641.71 US$ in Singapore’s GDP per capita. Results remain robust to placebo and leave-one-out tests and the Synthetic Difference-in-Differences method.

This research delves into the temporal dynamics of a nation's pursuit of a targeted GDP per capita level, employing five different survival machine learning models, remarkably Deep Learning algorithm (DeepSurv) and Survival Random Forest. This nuanced perspective moves beyond static evaluations, providing a comprehensive understanding of the developmental processes shaping economic trajectories over time. The economic implications underscore the intricate balance required between calculated risk-taking and strategic vulnerability mitigation. These findings guide policymakers in formulating resilient economic strategies for sustained development and growth amid the complexities inherent in contemporary economic landscapes.

Banks are at the core of economic functioning in various countries and are the cause of their development in various fields. In a changing environment, they must deal with certain risks and maintain financial stability as the ultimate objective. The primary objective of this study is to examine the correlation between credit risk and bank stability within the Tunisian banking sector, with a specific focus on understanding the moderating impact of the COVID-19 pandemic. To achieve this, we employ several econometric techniques, including panel unit root and cointegration tests, panel Vector Error Correction Model (VECM), Fully Modified Ordinary Least Squares (FMOLS), and Dynamic Ordinary Least Squares (DOLS). Our empirical analysis relies on a panel dataset that encompasses a comprehensive sample of 8 Tunisian banks over 2000-2020. The results of our analysis unveil a significant negative relationship between credit risk and bank stability, indicating that higher levels of credit risk exert a detrimental effect on the overall stability of Tunisian banks. Furthermore, our study highlights that this adverse impact is further exacerbated during the COVID-19 pandemic, suggesting that the pandemic acts as a moderator. The findings of this study hold substantial implications for policymakers, regulators, and bank managers in Tunisia. They emphasize the critical importance of implementing robust risk management practices to mitigate credit risk and bolster bank stability. Additionally, the research underscores the need to consider the unique challenges introduced by external shocks, such as the COVID-19 pandemic, when assessing the overall stability of the banking system.

We offer an extensive analysis of the significance of information within the realm of Gaussian quadratic economies. We build upon the seminal papers of Morris and Shin (2002, 2007) and consider a signal game of incomplete information. Particularly, we question the suitability of partial transparency portrayed by fragmented information in addition to the private signal in terms of welfare effects. We can summarize our findings in two main points. First, fragmented information, in conjunction with a private signal, can reduce the reliance on public signals. Second, a conflicting effect arises between increasing full disclosure and increasing the precision of fragmented (semi-public) information when examining different complex scenarios, involving for example endogenous private information or imperfect correlated signals. For a critical threshold, an optimal communication strategy designed by fragmented information should be implemented whenever that kind of information is acquired at a high precision.

Overall development of a country largely depends on the economic policy instruments particularly fiscal and monetary policy to streamline the development and continue the developmental progress. These two policies have significant effects on long-term growth. It is noticed that policy adoption and reforms in both fiscal and monetary policies undertaken by Southeast Asian nations during the 1960s through 1990s have contributed to their advancement. This paper discusses the strategies for flourishing as emerging economies. Examples from Singapore, Thailand and Vietnam are highlighted in this study. It is found that prudent fiscal and monetary policy, effective discounting and interest rate; modernized tax system and most importantly policy regime are the contributing factors of these emerging economies. However, in spite of high-income growth and development because of supportive these policy initiatives, administrative and politico-economic constraints challenged the path of economies. Long-term development strategies are suggested to sustain the growth and continue the development pace.

This paper evaluates the treatment effect of high-speed rail (HSR) operation on city consumption using the dataset of Chinese cities from 2003 to 2019. Firstly, the applicability of observations is discussed; secondly, observations with no appropriate contrast samples are dropped for more precise empirical results. Then, propensity score matching (PSM) is implied to have the database much more balanced and suitable for the difference-in-difference (DID) framework, that is, the PSM-DID approach. The main results find a novel phenomenon of Simpson's paradox regarding the HSR-consumption nexus, which indicates that even though we can observe the positive effect on the whole, the results argue negative relationships between HSR and consumption within subclass cities. In addition, a dose-response assessment (DR) and some other checks have been proposed to demonstrate robust estimation results.

This paper aims to study and quantify the impact of agricultural exports on economic growth along with other variables in Tunisia. For that purpose, we estimate the relationship between GDP, agricultural exports, other exports, and imports by applying the ARDL approach under the period 1990-2020. The results show a negative and insignificant impact of agricultural exports on economic growth in the long and short run. Other exports negatively and significantly impact economic growth, while imports are found to have a positive impact on long-term economic growth. The findings have economic implications for sectors and activities that should be promoted to accelerate economic 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.

The recent interest rate policy decisions of the South African Reserve Bank have been criticized significantly by left-leaning political parties and civic society organisations for being anti-poor, anti-labour, and pro-capital because of their implications for household debt. Existing literature has established that interest rates and house prices are insignificant determinants of household debt dynamics in South Africa. Taking advantage of additional data for the period 2013-2022, and contrary to the previous studies, the paper maintains that house prices and the central bank policy rate play a crucial role in household debt dynamics. Applying a Markov Switching regression to quarterly data for the period 1981Q1 to 2022Q1, the paper finds that house prices and the policy rate have a significant influence on household debt dynamics. It establishes the existence of a ‘house price boom, low policy rate burden’ regime and a ‘high policy rate burden, low house price’ regime. The coexistence of the ‘house price boom’ and the ‘low policy rate’ explains the debt euphoria characterised by significant household leveraging.

Educational equity is the foundation of social equity, and education equalization is one of the serious issues to be solved by the government. This work considers one education equalization reform conducted by Suzhou Industrial Park of China, namely, the comprehensive "five to nine" (CFTN) housing purchase admission qualification adjustment policy, as an example and uses the resold housing transaction data to identify the effect of the equalization policy by the difference-in-differences (DID) method. Based on this natural experiment, the quantitative assessment results show that (1) the CFTN policy has a significantly positive effect on housing prices in nine-year consistent (NYC) school districts that belong to high-quality school districts; (2) the CFTN policy has no significant effect on housing prices in non-NYC consistent school districts that belong to ordinary school districts. These results uncover that the one-size-fits-all CFTN policy can only obtain significant housing price equilibrium effects in school districts above a certain level of education quality. For regions with backward education levels, the policy is ineffective. For these regions, continuously increasing high-quality educational resources and increasing educational service levels are essential solutions to reduce educational inequality.