This study investigates the effects of innovation reform on wealth inequality by analyzing China’s Comprehensive Innovation Reform Pilot Zones (CIRPZs). Employing a difference-in-differences methodology, we assess the impact of CIRPZs on urban wealth distribution among China’s prefecture-level cities. Our findings reveal a paradox: although CIRPZs are designed to stimulate economic growth and technological advancement, they inadvertently exacerbate wealth inequality. This outcome is confirmed through a series of rigorous robustness checks. We identify two key mechanisms driving this phenomenon: the virtual wealth effect, whereby technological progress disproportionately benefits tech-savvy individuals and firms, and wage stratification, leading to increased income disparities within innovative sectors. Additionally, we find that the impacts of CIRPZs vary across regions, with significant widening of wealth inequality observed in Beijing-Tianjin-Hebei, the middle reaches of the Yangtze River, and Chengdu-Chongqing, while a moderating effect is noted in the Central Plains. These insights emphasize the nuanced effectiveness of innovation reform policies and their implications for policymakers in developing economies. We advocate for policy frameworks that balance technological advancement with equitable economic outcomes, a crucial step for fostering sustainable and inclusive development.

This study examines the impact of the Russia-Ukraine conflict, which began on February 24, 2022, on natural gas prices and supply security in major global markets. Six months after the conflict's onset, natural gas prices surged by an average of 78.65% across international markets. Notably, prices in the European Union, Russia, the United Kingdom, Japan, and South Korea saw substantial increases, while price hikes in China, the United States, and Australia were comparatively smaller. Despite these price fluctuations, the security of natural gas supply in key international markets remained largely unaffected. Using the Differences-in-Differences (DID) method, the study analyzed the conflict's impact on supply security, employing a mediation effects model to examine the roles of supply, demand, and price. The findings reveal that the conflict significantly reduced natural gas supply security, with negative effects on both supply and demand, although price changes did not mediate this reduction in supply security. Furthermore, the regional impact on supply security was minimal, likely due to the high integration of the global natural gas market. Overall, the Russia-Ukraine conflict notably influenced natural gas supply security by affecting supply and demand factors.

Recent research has demonstrated that many mean-variance and shortfall-based optimal portfolio selection fail to out-perform the Naive (1/n) Portfolio in out-of-sample testing. This paper revisits this line of inquiry by applying the Naive and Sharpe Portfolios to 1100 sector-specific S&P 500 re-sampled data sets from the 2007-2021 time frame. Using April 2020 as the baseline train-test split break point, the Naive Portfolio delivers statistically significantly superior Sharpe Ratios in the test data in ten of the eleven sectors. However, the Sharpe Portfolio delivers statistically significantly superior shortfall values in all eleven sectors in the test data. Using March 2020 and May 2020 as alternative breakpoints gave similar results to the baseline analysis. Interestingly, when the data set was truncated at February 2020 (i.e., before the Covid correction) the Sharpe Portfolio returned statistically significantly better Sharpe Ratios than the Naïve Portfolio in the test data in all but the Energy sector; as in the baseline analysis, the Sharpe Portfolio returned statistically significantly superior shortfall values for all eleven sectors. Thus, the Sharpe Portfolio can deliver acceptable out-of-sample performance, but the conditions for success appear to vary by sector and test data erraticism.

In recent years, as global climate change intensifies and ESG investment concepts gain prominence, climate risk has become a crucial factor for investors and financial markets. Investigating how climate risk is priced in the Chinese capital market is both theoretically and practically important for promoting the sustainable development of China's capital markets and advancing green finance. This study employs natural language processing (NLP) to quantify the proportion of climate risk-related content in the annual reports of listed companies, creating an indicator to assess their climate risk level. The study uses climate risk of listed companies as the explanatory variable and annual stock returns as the dependent variable, applying a fixed-effects model to empirically examine the impact of climate risk on investment returns. The study finds that: first, the climate risk of listed companies shows a clear trend of change over time; second, there is a significant positive correlation between the climate risk of listed companies and investment returns.

The gender characteristics of initial wage levels in the labour market were investigated using data from the China Family Panel Studies (CFPS), and gender differences in the individual retirement accounts wealth of urban employees were studied on this basis. The results indicate that for female employees, the individual retirement accounts wealth they obtained through longer life expectancy is largely offset by their low level of income and short contribution period, and the net pension wealth of female employees who retire at statutory retirement age is even lower than that of male employees. Due to the inheritability of account balances, extending the retirement age will increase the individual retirement account net pension wealth of all employees, and each year of extension will bring more net pension wealth increase to male employees.

Forty-five UK universities were approached, drawn from 21 universities whose client technology/knowledge-transfer firms perform consistently well (category 1 universities), and 24 universities whose client technology/knowledge-transfer firms perform consistently poorly (category 2). Contact was established with staff in the Technology Transfer Office (TTO) or similar department, resulting in 72 persons identified as either “leading” TTO staff or “operational” TTO staff. These individuals were subject to semi-structured interviews around a 10-point questionnaire to arrive at consensus opinions. Results indicate that independently of whether the university is regarded as “entrepreneurial” or not, the TTOs of category 1 universities are more ambidextrous than those of category 2 universities.

This is the first study to examine how Nigerian output is affected by the news-based Economic Policy Uncertainty Index by Tumala et al. (2023) and Climate Uncertainty Index by Salisu et al. (2023). Using ARDL and Granger causality on quarterly data from 2016Q2 to 2024Q1, the findings show that increased economic and climate uncertainties result in decreased output. Additionally, the study reveals that climate uncertainty has a more significant effect on output compared to economic policy uncertainty. The Granger causality indicates one-way causality from climate uncertainty to output, thereby reinforcing the substantial influence of climate uncertainty on output in Nigeria.

The determinants of production-based carbon emission (PCE) have been extensively examined in the literature. However, PCE only accounts for emissions generated within the territory of a country and does not capture emissions embedded in imported goods. The rapid growth in Consumption-based Carbon Emissions (CCE) in Sub-Saharan Africa (SSA), driven by increasing imports and economic activities, highlights the need for a comprehensive understanding of these emissions. This motivates us to examine the impact of Renewable Energy Consumption (REC) on CCE in SSA. We employed a two-step system Generalized Method of Moments (GMM) methodology, utilizing data from 1995 to 2020. The results show a negative effect of REC on CCE, suggesting that increases in renewable energy consumption tend to reduce CCE. In contrast, the positive impact of real GDP and population indicates that economic growth and population expansion tend to bolster carbon emissions. These findings underscore the importance of implementing policies harmonizing economic growth with sustainable energy strategies. They provide valuable insights for informed environmental and economic planning decisions.

This study seeks to investigate how climate change affects actual output in African countries, using greenhouse gas emission as a case study. This paper uses the actual output of Nigeria, Ghana, Liberia, The Gambia, Cabo Verde, and Sierra Leone for the analysis. Climate change is proxied by greenhouse gas emission, which are extracted from the International Monetary Fund (IMF) database, for the period, 1980 to 2022. Descriptive statistics, unit root, and panel System Generalized Method of Moments 1(SGMM1) are estimated, and the result shows that agricultural greenhouse gas emission reduces the output of the selected African Countries, while other greenhouse gases such as building and other sector’s greenhouse gas emission, energy industries greenhouse gas emissions, mineral industry greenhouse gas emission and road transport greenhouse gas emission increase output. For actual output to increase, the paper suggests policy remedies such as sustainable farming practices and adoption of climate-smart technologies.

The COVID-19 crisis has led to an unprecedented surge in teleworking. Teleworking during the COVID-19 pandemic has brought both benefits and costs. Yet, its impact on business resilience remains underexplored. This study examines the impacts of teleworking on business resilience from two perspectives: business continuity and employee furlough. Furthermore, we highlight the role of female leadership in shaping these impacts. Using a matched dataset of more than 3,000 global firms, we tested four hypotheses and found empirical support. We found that female leadership enhances the positive effects of teleworking on business continuity while mitigating its negative effects on employment.

This study investigates the efficacy of diverse machine learning survival models, including Cox, Kernel SVM, DeepSurv, Survival Random Forest, and MTLR models, employing the concordance index to assess their predictive abilities. The primary objective of this research is to identify the most accurate model for forecasting the time it takes for a country to witness a 10% surge in unemployment within a 120-month timeframe (2013-2022), utilizing variables from the MVI dataset of 28 American countries. Through the comparative evaluation of complex survival models, we discovered that DeepSurv, a sophisticated machine learning algorithm, excels in capturing intricate nonlinear relationships, while conventional models exhibit comparable performance under specific circumstances. The weight matrix, a pivotal element of our analysis, meticulously assesses the economic repercussions of various risk factors, vulnerabilities, and capabilities.

The goal of this paper is to provide an overall presentation of corruption as occupational fraud building on the findings of an empirical study conducted in Greece. As uncertainty leads to increased levels of corruption, Greece was chosen due to the prolonged period of uncertainty the country faces, caused by the 2010 financial crisis and followed by the Covid pandemic crisis. 400 questionnaires reviewing corruption perception were gathered and analyzed by gender, age, marital status, education level, position, occupation, and monthly income, as well as urban vs rural area of residence. The findings of the study were compared with and critically evaluated against those of the previous studies for Greece. Respondents in age group 36-49 believe that if appropriate measures are taken it is possible to tackle corruption in the public sector, in contrast to people aged 18-35 who disagree completely. Residents of rural areas do not consider corruption to be a serious problem and are more willing to whistleblowing (in contrast to residents of urban areas). The study findings have important practical implications in the context of designing effective corruption reduction policies.

This research investigates the determinants of women's empowerment within households in a developing country. The investigation specifically focuses on the impact of employment and fertility, considering constraints imposed by family rules that play a pivotal role in shaping women's empowerment. The theoretical framework outlined in this study posits a simplistic model demonstrating that, within the prevailing family structure and household composition, earned income and fertility may bear significant relevance. Utilizing data extracted from the Pakistan Social and Living Standards Measurement Survey, we engage in estimating the level of female empowerment, operationalized as the extent of female authority over household expenditures. Notably, our empirical approach accounts for the endogeneity of employment and fertility through a two-stage estimation process. This involves leveraging information on family rules—representative of a family's cultural norms—pertaining to work and childbearing. Our empirical findings affirm the viability of family-specific rules as instruments to estimate and subsequently predict employment and fertility. Importantly, the evidence gleaned underscores the critical role of selecting valid threat options in theoretical analyses of women's empowerment.

The diplomatic relations between Azerbaijan and Pakistan have undergone significant development since the late 1990s. Despite some studies focusing on diplomatic and political relations, the economic dimension of this partnership has not been systematically covered. In this paper, a robust least squares (RLS) approach is used to model bilateral trade between the two countries and identify statistically significant determinants, including economic, institutional, and cultural factors, after analyzing the main economic and subsectoral trade dynamics of both countries. The results reveal that Azerbaijan's imports from Pakistan are significantly associated with the country's higher income and market size, while Pakistan's elevated exchange rate and trade costs hinder bilateral trade. In addition, Pakistan's rising manufacturing output increases exports to Azerbaijan but decreases imports from Azerbaijan. Among institutional determinants, government effectiveness, the trade freedom index (TFI), and political stability play significant roles in bilateral trade. Lastly, it was found that cultural proximity increases Pakistani exports to Azerbaijan but not imports from Azerbaijan. The analysis also indicates that domestic savings stimulate Pakistani exports. These findings underscore the complex nature of bilateral trade between Azerbaijan and Pakistan and highlight the need for institutional arrangements to harmonize trade flows and boost welfare gains from trade. The results may be of great importance to intergovernmental working groups, domestic policymakers, and businesses.

Objective: The paper, specifically examines whether the recently formed Regional Comprehensive Economic Partnership (RCEP) can potentially facilitate minimising the constraints to renewable energy goods exports at the regional level in Asia. Data, Methodology and Findings: Using the panel data from 11 RCEP members from 2006 to 2014, this study has applied the ‘meta frontier stochastic gravity frontier’ methodology and confirms that the establishment of RCEP has the potential to improve trade in renewable energy commodities within the RCEP region. Policy Implications: The policy implication is that when countries work together, it will lead to enormous benefits for national, regional, and worldwide prospects of a more sustainable energy future. Practical Policy Implications: In terms of practical policy implications, the developed RCEP member countries should actively engage in promoting R&D activities and protecting intellectual property rights concerning renewable energy production, which are essential for countries to integrate with the world market and to lift the export frontiers of both the developed and developing RCEP member countries to reach the unrestricted export of renewable energy technology.

The COVID-19 pandemic has changed the everyday ways of life across the world. The objective of this study is to understand the impacts of nationwide lockdown restrictions on female workforce of New Zealand. To conduct this study three subsets were selected: working mothers, essential workers and women in high-risk industries. New Zealand has a gender segregated workforce, and more women on the frontline as essential workers who faced risks from COVID-19. A quantitative approach based on secondary data published by the Government of New Zealand was employed in this study. The analysis was carried out under three themes: family wellbeing, essential workers and women in high-risk industries. All the themes point to the fact that the working women of New Zealand indeed have been critically impacted compared with working men.

This paper presents an operational framework for assessing the trajectories of production, energy, emissions, and capital accumulation to ensure the implementation of Nationally Determined Contributions (NDCs). The framework combines widely used methodologies (STIRPAT, system dynamics, and optimization) to simulate the pathways of variables until a target year. The CO-STIRPAT dynamic system allows us to identify the spillover pathways from carbon policy to economic growth based on output optimization principles; to conduct a more systematic analysis of the interconnections between the main drivers that determine carbon emissions; to develop a cost-effective climate policy mix that is a backbone for the right combination of carbon pricing, energy efficiency, and carbon intensity; and to assess NDC targets with respect to ambition gaps, implementation gaps, and feasibility.

This paper attempts to introduce an overlapping generations structure into Paul Krugman's "The world's smallest macroeconomic model" (Krugman (1999)) to examine the implications of fiscal policy, particularly fiscal deficits, in a framework suitable for policy analysis. In that paper, Krugman argued that under the price rigidity assumption, a shortage in the money supply leads to underemployment and recession, so increasing the money supply would eliminate underemployment and restore full employment. But how can the money supply be increased? I show that in order to restore full employment out of a recession, a fiscal deficit is needed to increase the money supply. I also show that in a growing economy, fiscal deficits are necessary to maintain full employment at constant prices or inflation. Fiscal deficits are not only effective in pulling the economy out of recession, they are even necessary for growth to continue without recession or inflation. The fiscal deficit in this paper represents the difference between government spending and government revenues. If this difference is positive, we say that the government is in deficit. Krugman's original model is a one-period static model. I intend to extend this model to a dynamic overlapping generations model.

In this paper I will show that budget deficit (or fiscal deficit) is necessary to achieve full employment under constant prices or inflation, using a model of endogenous growth in which consumers hold money for the reason of liquidity and live forever. Budget deficit need not be offset by future budget surpluses. I consider the continuous time case by taking the limit of the discrete time case when the time interval approaches zero. A continuous time dynamic model seems to be more general than a discrete time model. When the actual budget deficit is greater (smaller) than the value which is necessary and sufficient for full employment under constant prices, an inflation (a recession) occurs. The main argument of this paper is that a growing economy requires the continuation of budget deficit, and that we should not think of paying off the resulting government debt with taxes.

This study examines the role of news sentiments in the GCC equity markets’ connectedness. We collected news titles for the period from 22nd June 2006 until 31st December 2020 from Gulf News, which is the most widely read English newspaper in the Arab World. We filter these news titles using a carefully designed list of keywords that capture public sentiment on matters related to financial markets. Next, we classify the news titles to compute the geographically distinguished sentiment indexes that allow for a detailed analysis of the source of news sentiment spillovers to compare the impact of domestic versus regional sentiments on the equity markets of GCC countries. Our quantile regression results reveal that equity markets in the GCC are most sensitive to news sentiments when underperforming. Moreover, our results from the connectedness approach suggest that the UAE equity markets are most influenced by domestic sentiments, whilst the KSA equity market is most influenced by regional sentiments from the other GCC countries. Mixed results are found for other countries. The time-varying component of this study also shows that the influence of news spillovers intensified during the major crises events, including the COVID-19 outbreak.