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It is widely argued that money laundering (ML) is not a new phenomenon and the pervasiveness of ML is associated with some severe economic, social and political costs. Due to the lack of studies on the ML’s issue in the UAE, this study aims to examine the determinants of ML in the country between 1975 and 2020.

The autoregressive distributed lag bounds testing results demonstrate the presence of long-run relationship between ML and the selected macroeconomics variables. The analysis is validated by the dynamic ordinary least squares, the fully modified ordinary least squares and the canonical co-integration regression estimators.

The estimation result reveals that while the real estate market, outflow of money, arms procurement and size of the underground economy influences the size of ML positively, gold trade, the level of financial development and the size of economic activities are negatively associated with ML, both in the short- and long-run.

Up to date from a country-level analysis, no study has been devoted to the ML in UAE, except for Aljassmi et al. (2023). To the best of the authors’ knowledge, this study is the first to investigate the determinants of laundered money in the UAE economy. Based on these outcomes, strategies and measures which will deter the laundering of illicit funds through the real estate and gold market, remittance system, financial system and arms procurement contracts in the UAE are recommended.

This study presents time-series data estimations on the association between the indicators of institutional environment and inward foreign direct investment (FDI) in India utilizing a comprehensive data set from 1996 to 2021.

The study employs the nonlinear autoregressive distributive lag (NARDL) model. The asymmetric ARDL framework evaluates the existence of cointegration among the factors under study and highlights the underlying nonlinear effects that may exist in the long and short run.

The significance of coefficients of negative shock to “control of corruption” and positive shock to “rule of law” is greater when compared to “government effectiveness, regulatory quality, political stability/absence of violence.” The empirical outcomes suggest the positive influence of rule of law, political stability and government effectiveness on FDI inflows. A high “regulatory quality” is observed to deter foreign investment. The “voice and accountability” index and negative shocks to the “rule of law” are exhibited to have no substantial impact on the amount of FDI that the country receives.

This study empirically examines the institutional determinants of FDI in India for a comprehensive period of 1996–2021. The study's findings imply that quality of the institutional environment has a significant bearing on India's inward FDI.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0375

The article aims to establish whether the degree of aversion to inflation and the responsiveness to deviations from potential output have changed over time.

This paper assesses time variation in monetary policy rules by applying a time-varying parameter generalised methods of moments (TVP-GMM) framework.

Using monthly data until December 2022 for five inflation targeting countries (the UK, Canada, Australia, New Zealand, Sweden) and five countries with alternative monetary regimes (the US, Japan, Denmark, the Euro Area, Switzerland), we find that monetary policy has become more averse to inflation and more responsive to the output gap in both sets of countries over time. In particular, there has been a clear shift in inflation targeting countries towards a more hawkish stance on inflation since the adoption of this regime and a greater response to both inflation and the output gap in most countries after the global financial crisis, which indicates a stronger reliance on monetary rules to stabilise the economy in recent years. It also appears that inflation targeting countries pay greater attention to the exchange rate pass-through channel when setting interest rates. Finally, monetary surprises do not seem to be an important determinant of the evolution over time of the Taylor rule parameters, which suggests a high degree of monetary policy transparency in the countries under examination.

It provides new evidence on changes over time in monetary policy rules.

This paper examines the effect of restrictions on executive pay and high CEOs’ compensation on bank performance following the “2008 UK bank rescue policy”.

Using the difference-in-difference estimation technique we assess the relationship between executive compensation and financial performance of rescued banks relative to non-rescued banks over the period 1999–2019.

Our main finding indicates that the relationship between executive compensation and financial performance declines in rescued banks relative to non-rescued banks. Further, we document that performance continues to deteriorate in rescued banks relative to non-rescued banks. Our results are robust to different estimation techniques.

This study contributes to the literature that examines the efficacy of government bailouts during the 2008 crisis. To the best of the author’s knowledge, this study is among the first to examine the long-term implications of bank rescue and pay restrictions on executive compensation and performance post–rescue.

The purpose of this study is to investigate the interplay between fiscal dominance and monetary policy in South Africa from 1960 to 2023.

The study employs a structural vector autoregression (SVAR) medel to analyze the relationship between fiscal dominance and monetary policy. Short-term and long-term shocks of government borrowing and deficits are examined to understand their impact on inflation dynamics.

Fiscal dominance has a significant effect both in the short and long run. There is evidence that government debt and deficits increase inflation, overriding the effects of monetary policy aimed at maintaining price stability. On the other hand, the study reveals that money supply shocks have a greater effect in reducing fiscal dominance compared to interest rate shocks. The variance movement on inflation is significantly explained by government debt and deficits. This emphasizes the persistence of inflationary pressures associated with fiscal dominance, highlighting the importance of effective policy interventions to mitigate inflationary risks.

This study contributes to the existing literature by providing insights into the dynamics of fiscal dominance in South Africa. Moreover, this study extends the theoretical framework of the fiscal theory of the price level (FTPL) and the government budget constraint. This study contributes valuable insights into the dynamics of fiscal dominance in South Africa and offers guidance for policymakers in formulating strategies to safeguard economic stability.

This article employs a panel vector autoregression (PVAR) model to examine the relationship between digital financial inclusion (DFI), economic growth (EG), and gender equality (GE) across different levels of financial development.

Based on the current financial development dynamics, this study applies the PVAR method to two groups of countries: the first group represents the high financial development group, and the second group represents the low financial development group, during the period from 2015 to 2021.

The findings from impulse response functions reveal that digital financial inclusion fosters economic growth in nations with advanced financial systems, while simultaneously mitigating gender inequality. Conversely, in countries with less developed financial infrastructures, digital financial inclusion stimulates economic growth but exacerbates gender disparities. Moreover, the variance decomposition analysis indicates that the linkage between economic growth, digital financial inclusion, and gender inequality is more intertwined in countries with limited financial development than in those with well-established financial systems.

Effective deployment of new technologies relies heavily on technological infrastructure. This policy focuses on constructing and developing information technology infrastructure to create favorable conditions for the implementation of new DFI technologies. This study also emphasizes promoting equitable education and training by ensuring that both women and men have equal opportunities to access quality education and training. This may involve investing in early childhood education, providing access to primary education, and offering scholarships to women in technology, science, and engineering fields.

This study combines perceived knowledge, perceived psychologic risk with Theory of Planned Behaviour (TPB) to examine the influence on tourists' intention to choose a safe destination and willingness to pay (WTP) more for safety measures. An online survey was conducted in 2021 to approach tourists globally. After 10 weeks, we received 365 valid responses. SmartPLS software version 3.3 was applied to run structural equation modelling to test the proposed hypotheses. Research results reveal that intention to choose a safe destination mediates the relationship between perceived knowledge of COVID-19, perceived psychological risk and the WTP more for safety measures while moderating role of educational level is also addressed. In turn, perceived psychological risk mediates the relationship between perceived knowledge of COVID-19 and intention to choose a safe destination. As a result, this study implies that destination managers should take actions to promote their WTP more for safety measures.

The Indian stock market can be tricky when there's trouble in the world, like wars or big conflicts. It's like trying to read a secret message. We want to figure out what makes investors nervous or happy, because their feelings often affect how they buy and sell stocks. We're building a tool to make prediction that uses both numbers and people's opinions.

Hybrid approach leverages Twitter sentiment, market data, volatility index (VIX) and momentum indicators like moving average convergence divergence (MACD) and relative strength index (RSI) to deliver accurate market insights for informed investment decisions during uncertainty.

Our study reveals that geopolitical tensions' impact on stock markets is fleeting and confined to the short term. Capitalizing on this insight, we built a ground-breaking predictive model with an impressive 98.47% accuracy in forecasting stock market values during such events.

To the best of the authors' knowledge, this model's originality lies in its focus on short-term impact, novel data fusion and high accuracy. Focus on short-term impact: Our model uniquely identifies and quantifies the fleeting effects of geopolitical tensions on market behavior, a previously under-researched area. Novel data fusion: Combining sentiment analysis with established market indicators like VIX and momentum offers a comprehensive and dynamic approach to predicting market movements during volatile periods. Advanced predictive accuracy: Achieving the prediction accuracy (98.47%) sets this model apart from existing solutions, making it a valuable tool for informed decision-making.

The study aims to investigate the risk transmission from COVID-19 to global agriculture, energy, natural resources/mining and environmentally/socially responsible investments. Additionally, it explores the connectedness of global energy indices with global agriculture, natural resources/mining and environmentally/socially responsible investments. The study develops a new COVID-19-based Global Fear Index (GFI) to achieve the objectives, thus contributing to the prevailing literature.

The data of Global indices are selected from January 2020 to December 2021. The study uses multivariate BEKK-GARCH and TVP-VAR models to explore COVID-19 risk transmission and connectedness between global indices.

Significant shock and volatility transmissions from COVID-19 to all global indices are observed. Results show that global agriculture, natural resource/mining markets and environmentally and socially responsible investments are safe havens during COVID-19. Furthermore, these global investment choices are barely connected with global energy indices.

Portfolio managers and investors should invest in global indices to gauge the risk-adjusted return during the pandemic and upcoming health-related risks. Investors in energy sectors are advised to diversify the risk by adding safe-haven assets to their portfolios.

The findings shed light on the importance of environmentally and socially responsible investments as a separate asset class where ecologically friendly and socially sentimental investors could invest in diversifying the risk of their portfolios.

The paper offers valuable insights to policymakers and investors regarding asset pricing, risk management and financial market stability during pandemic-type emergencies.

The primary purpose of this research is to identify and compare the multifractal behavior of different sectors during these crises and analyze their implications on market efficiency.

We used multifractal detrended fluctuation analysis (MF-DFA) to analyze stock returns from various sectors of the Moscow Stock Exchange (MOEX) in between two significant periods. The COVID-19 pandemic (January 1, 2020, to December 31, 2021) and the Russia–Ukraine conflict (RUC) (January 1, 2022, to June 30, 2023). This method witnesses multifractality in financial time series data and tests the persistency and efficiency levels of each sector to provide meaningful insights.

Results showcased persistent multifractal behavior across all sectors in between the COVID-19 pandemic and the RUC, spotting heightened arbitrage opportunities in the MOEX. The pandemic reported a greater speculative behavior, with the telecommunication and oil and gas sectors exhibiting reduced efficiency, recommending abnormal return potential. In contrast, financials and metals and mining sectors displayed increased efficiency, witnessing strong economic performance. Findings may enhance understanding of market dynamics during crises and provide strategic insights for the MOEX’s investors.

Understanding the multifractal properties and efficiency of different sectors during crisis periods is of paramount importance for investors and policymakers. The identified arbitrage opportunities and efficiency variations can aid investors in optimizing their investment strategies during such critical market conditions. Policymakers can also leverage these insights to implement measures that bolster economic stability and development during crisis periods.

This research contributes to the existing body of knowledge by providing a comprehensive analysis of multifractal properties and efficiency in the context of the MOEX during two major crises. The application of MF-DFA to sectoral stock returns during these events adds originality to the study. The findings offer valuable implications for practitioners, researchers and policymakers seeking to navigate financial markets during turbulent times and enhance overall market resilience.