The study analyses the long growth rate period contribution to human development in West African Economic and Monetary Union (WAEMU) from 1996 to 2019 introducing time and institutional indicators effects analyses. Time and institutional effects both greatly improve model's diagnostics statistics. Time effects reduce growth variable coefficient and its significance, but not institutional effects. Combined effects inhibit growth contribution to human development. It appears essential to increase the resiliency of growth and the efficiency of government institutions.

This paper deals with the gender gap in accessing and using financial services provided by mobile money and financial institutions. Using data from ECOWAS member countries, we applied the Fairlie decomposition method to estimate and decompose the gender gap. The results show that mobile money contributes to improving of the use of services compared to financial institutions. However, it also increases the gender gap in women's disadvantages in accessing and using these services. The difference in the level of education and income between males and females is the main factor explaining the gender gap.

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.

Calculating the amount of regulatory capital to cover unexpected losses due to operational events in the upcoming year has caused problems because of difficulties in fitting probability distributions to data. It is consequently difficult to judge an appropriate level of capital that reflects the risk profile of a financial institution. We provide theoretical and empirical analyses to link the calculated capital to the sum of losses using appropriate statistical approximations. We conclude that, in order to reasonably reflect the associated risk, the capital should be approximately half the sum of losses, with a wide bound for the ratio of capital to sum.

This paper provides a thorough review of the shifting landscape of economic analysis, spotlighting recent trends and predicting future paths. While traditional economic models remain key for interpreting economic activity, they are being supplemented by fresh methods and cross-disciplinary viewpoints. The increased attention to inequality studies, using advanced statistical techniques and unique data sources, underscores the growing emphasis on fairness and distribution within economic analysis. The incorporation of behavioral elements into economic models also expands our comprehension of economic decision-making and market results. Notably, the emergence of computational economics-integrating artificial intelligence (AI), big data, and machine learning into economic scrutiny-represents a major development. Often referred to as ’smart economics,’ this field employs technology to formulate, address complex economic dilemmas, and perceive economic activity in unconventional ways. Yet, the application of AI and machine learning in economics introduces new hurdles around data privacy, algorithmic bias, and the transparency of model outcomes. The impact of the digital revolution on economic analysis is significant, as the advent of computational economics and the surge of big data are transforming research techniques and policy implications. Concurrently, the advent of the circular economy indicates a radical shift in our perspective on economic sustainability, carrying considerable implications for environmental policy and business tactics.  In the future, it’s anticipated that these trends will further modify the realm of economic analysis, with AI and machine learning integration, emphasis on sustainability and fairness, and the influence of big data becoming more pronounced. As these changes take place, it’s imperative for researchers, policymakers, and practitioners to remain adaptable and flexible, prepared to capitalize on the opportunities and tackle the challenges these trends present.

This paper examines whether sell-side analyst-affiliated investors trade stocks before their analysts release material information. Using class action lawsuits, I explore the pre-lawsuit periods and investigate how potentially informed analysts trade their covered firms. The event study finds that analyst-affiliated investors reduce their stockholdings of firms prior to their own analyst downgrades. The findings are more pronounced among investors employed by investment banks. The post-trading performance of analyst-affiliated investors suggests that they have superior information and front-run to maximize benefits.

How does democracy relate to the initial economic policy responses to Covid-19? Using a cross country analysis, we find that countries with a higher degree of democracy have stronger economic policy responses than their peers. However, when we separate monetary and financial policies from fiscal policy, democracy is not associated with the latter when we control for the income level of a country. Finally, for countries with lower levels of labor participation, high levels of income inequality are associated with weaker policy responses.

I present a theoretical model and an empirical approach for jointly estimating the effectiveness of fiscal policy and the stochastic process of sovereign interest rate shocks. The theoretical model has features relevant to small open and emerging economies. Interest rate shocks affect the ability of firms to finance payroll expenses. This theoretical feature creates a propagation mechanism for interest rate shocks and affects government spending multipliers. This paper proposes a strategy for jointly estimating government spending multipliers and the interest rate shock process parameters.

This study investigates the impact of inventor CEOs on firm performance using a manually collected database of firms' inventors. Our findings reveal that, on average, firms with inventor CEOs experience a one- and two-percentage-point increase in ROA and ROE, respectively, compared to firms with noninventor CEOs. To address potential endogeneity issues, we employ turnover analysis, an instrumental variable approach, and propensity score matching. The estimation results suggest that inventor CEOs significantly enhance firm performance by fostering innovation and total factor productivity. This research contributes novel evidence on the relationship between inventor CEOs and firm performance.

Following the seminal paper on Optimum Currency Areas (OCA) by Mundell (1961) a wealth of literature has been published on the business cycles synchronisation and its main determinants. This work provides a systematic review of this research field both at country-level synchronization and regional level. The paper aims to evaluate the contribution of the related literature’s methodologies to the measurement of the business cycle and the estimation of the level of synchronization. The discussion of the collected papers is expected to substantially assist researchers, practitioners, and policy makers keen to employ themselves in the area of business cycles synchronisation.

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.

We develop a four-party model involving banks, merchants, consumers, and platform firms to explain why large shopping malls can offer interest-free installment services to consumers. Using a collaboration between an online shopping platform firm and multiple banks to issue co-branded credit cards as a natural experiment, we find that consumers’ spending on the platform fulfills the requirements for merchants and banks to choose a four-way model. This study highlights the pivotal role of platform firms in the credit card market.

We generalize the 3-player game introduced by Mêgnigbêto (2018) to analyze the synergies existing between universities, the industry and the government in the Triple Helix, a model of research and innovation introduced by Leydesdorff and Etzkowitz (1995). We consider situations involving any number of actors and we allow for a differentiation of their contributions. The resulting game has nonnegative Harsanyi dividends, implying its convexity. The relative size of the core measures the extent of the synergies and the Shapley value measures the contribution of each actor to these synergies. Incidentally, the resulting game lends itself to a wide range of applications.

This study underscores the chronic issue of gender pay disparity that prevails across different STEM fields and educational qualification levels in Australia. Despite instances where women's incomes may align or even surpass men's, the broader pattern of inequality remains undeniable. The study advocates for targeted strategies to address gender pay gaps, particularly in fields like Engineering and Science, and emphasises the significance of cultivating inclusive work environments that recognise and reward contributions regardless of gender. This study serves as a critical call to action to rectify these inequities and promote a more balanced and equitable STEM landscape.

This paper investigates the effect of economic policy uncertainty (EPU) on the systemic risk of the fintech industry. To achieve this goal, we first estimate the evolution of system-wide systemic risk using the CatFin method. We further examine whether EPU significantly affects systemic risk. Our findings demonstrate that the systemic risk of the fintech industry is time-variant and sensitive to major crisis events. Systemic risk tends to increase after major crises, especially the outbreak of the COVID-19 pandemic. EPU has a considerable impact on systemic risk, notably during periods of turmoil.

Since 2011, the conflict in Syria left the country with a devastating energy sector and fragile economy. The residents struggle daily to live with only two hours a day of electricity. The crisis encouraged some Syrians to assemble photovoltaic (PV) panels to generate energy. Unfortunately, the geopolitical risks, the inflation, and displacement are making the situation worse. The geopolitical risks are complex and multifaceted due to the ongoing war and the involvement of various regional and international actors. In this letter, we focus on the situation in war-torn Syria, its economy, and the opportunities for renewable energy development in the country. We also give some recommendations for academics and policy makers.

This paper aims to investigate the impact of political promotion on the productivity of manufacturing firms using the database of Chinese industrial enterprises from 1998 to 2007. We found that the political promotion of officials had a negative impact on manufacturing firm productivity, and this impact varied according to the characteristics of officials and enterprises. In addition, there was an age "ceiling effect" among Chinese municipal officials. Further research showed that the regional level of rule of law mitigated the negative effect of political promotion on the productivity of manufacturing firms. Finally, this paper makes policy recommendations for improving the promotion mechanism of officials, enhancing regional legalization, and transforming government functions.

The aim of this article is to model a negotiation between shareholders in high-technology-risk industries and local residents on the safety investments to be implemented. The methodology used is a Nash bargaining model, with a DE curve representing shareholders' dividend demands and an NS curve representing the safety demands of local residents' associations. The model is used to determine the level of safety investment required. One of the main results is that the estimation of a higher accident risk is accompanied by both a higher safety investment and a higher dividend payout. The most obvious implication of this result is that it is undoubtedly necessary to give greater weight to local residents in investment decision-making, in order to improve the well-being of all stakeholders.

This paper presents an analytical framework to assess the probability of achieving nationally determined contributions (NDC). The prediction model based on the Kaya identity is used to simulate the pathway of carbon emission until the target year. Applying the modified STIRPAT framework (named CO-STIRPAT) to data observed in South Korea shows that the probability that the predicted pathway with existing climate technology will stay above the NDC target pathway is significantly high. The result suggests that it is necessary to design a climate policy to improve energy intensity and carbon intensity by accelerating the advance in climate technology.

We extend the Shariah-compliant digital assets and Islamic Fintech literature through exploring the time-frequency associations between the volatility index (VIX) and cryptocurrencies (both Islamic and traditional). Employing wavelet-based technique, we find that Islamic cryptocurrencies demonstrate low or no coherency with stock market volatility compared to traditional cryptocurrencies (except Tether) during the whole time and frequency bands, highlighting the hedging capabilities of Islamic cryptocurrencies. Tether also serves the same against VIX, as there is a low or favorable link between these variables. Finally, our findings would be prolific to digital currency traders and investors in designing the portfolio strategies.