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This study aims to analyse the drivers of the shift towards the global adoption of International Financial Reporting Standards (IFRS) in 23 non-European Union countries over the period from 2001 to 2019.

This study used various panel data models, including fixed effects panel Logit and Probit models for IFRS adoption status, and ordered panel data models for examining the extent and timing of IFRS adoption, accommodating the multifaceted nature of the dependent variable.

The results suggest that countries with a high Anglo-Saxon cultural background, human development and strong legal enforcement, particularly in controlling corruption, are more likely to adopt IFRS fully and early. Notably, the extent of business disclosure in these countries impacts IFRS adoption status but does not significantly affect the extent or timing of adoption. Surprisingly, the findings reveal that countries with higher financial openness are less likely to adopt IFRS.

These results are relevant to standard setters and regulators in countries on the verge of adopting IFRS who are interested in financial, institutional and cultural factors and their impacts on IFRS adoption.

This research stands out for its emphasis on the pivotal role of cultural and institutional nuances in shaping the trajectory of IFRS adoption within non-European Union countries, thereby broadening the accounting discourse.

The purpose of this paper is to focus on the impact of trade openness and technology import on the change in demand structure of employment toward skilled workers. Because of the limited number of empirical papers done in the case of Tunisia, this research investigates whether these factors had similar effects on relative labor demand in Tunisia to those observed in the international literature.

For this purpose, the paper uses a manufacturing industries database provided by the Tunisian National Institute, the Quantitative Economic Institute and Comtrade of United Nations for six manufacturing industries. The methodology used here is a panel data technique, and consists of estimating a dynamic relative employment equation.

Empirical results show that trade liberalization and technology change positively affect relative employment of Tunisian manufacturing industries which confirms the existence of skill biased technological change that contributes to increase the relative demand for skilled workers.

The paper adds to existing literature by studying for the first time the case of Tunisian manufacturing industries by using dynamic model. The paper deals also with an econometrics issues related to the use of suitable estimation methodology in the case of dynamic panel data at macroeconomics level.

Energy affects all areas of daily life. Especially with the industrial revolution, the fact that manufacturing has become the engine of economic growth has led to a rise in energy consumption. In this process, the countries of the world have increased their economic growth with traditional energy consumption, and this has increased carbon emissions. However, to fulfill the sustainable development goals, both the continuation of economic growth and the reduction of carbon emissions are required. In this context, the substitution of renewable energy consumption in place of traditional energy sources has started to be discussed. The aim of this study is to research the relationships among CO₂ emissions, manufacturing growth, and renewable energy consumption. For this aim, the relationship among carbon emissions, manufacturing growth, and renewable energy consumption is analyzed for the period 1997–2019 in 38 Organisation for Economic Co-operation and Development (OECD) countries. With respect to the findings of autoregressive distributed lag (ARDL) test results, manufacturing growth enhances CO₂ emissions both in the short and long terms. As the proportion of renewable energy consumption in total energy consumption rises, CO₂ emissions decrease both in the short and long terms. On the other hand, according to the Dumitrescu–Hurlin causality test results, there is a one-way causality relationship from carbon emissions to manufacturing growth and from renewable energy consumption to carbon emissions. When the findings are evaluated together, it is understood that renewable energy consumption is a substantial factor in tackling the deadlock of lessening the carbon emissions without adversely impacting manufacturing growth. Therefore, policymakers need to encourage renewable energy consumption.

This paper aims to test for volatility spillovers among Islamic stock markets with the exogenous impact of geopolitical risk (GPR) to check the risk transmission among Saudi Arabia, Malaysia, Indonesia and Turkey. Researchers test for both the symmetric and asymmetric risk transmission.

For the symmetric response of volatility, the study uses simple generalized autoregressive conditional heteroscedastic (GARCH) and for the asymmetric response of volatility with the exogenous impact of GPR, the exponential GARCH models have been adopted.

The results suggest spillover effects exist from Turkey to Saudi Arabia, Indonesia to Malaysia and Saudi Arabia and Malaysia to Indonesia. The findings of volatility spillover from GPR to sample countries suggest that only Malaysia and Indonesia experience volatility spillovers from GPR.

The present study is limited to the context of four countries and Islamic equities; the study contributes to the literature on volatility spillover, Islamic finance, GPR and asset pricing.

This study contributes to individual, institutional investors’ policymakers’ knowledge in determining security prices, trading plans, investment hedging and policy regulation.

The extant literature disregards the GPR index to examine the volatility spillover effects among Islamic stock markets, which allow researchers to justify the mechanism of risk transmission due to GPR across the Islamic stock market.

To the best of the authors’ knowledge, this is the first research of its type to look at volatility spillover and GPR transmission in Islamic stock markets.

This paper aims to investigate the dynamic linkage between stock prices and exchange rate changes for the Gulf Arab countries (Kuwait, Qatar, Saudi Arabia and United Arab Emirates [UAE]).

The author uses the Markov-switching autoregression to detect regime-shift behavior in the stock returns of the Gulf Arab countries and Markov-switching vector autoregressive (MS-VAR) model to capture the dynamic interrelatedness between exchange and stock returns over the period 2000–2018.

This study’s analysis finds evidence to support the persistence of two distinct regimes for all markets, namely, a low-volatility regime and a high-volatility regime. The low-volatility regime illustrates more persistence than the high-volatility regime. Specifically, exchange rate changes do not have an influence on the stock market returns of the Gulf Arab countries, regardless of the regimes. On the other hand, stock market returns have a substantial impact on exchange markets for all countries, except Saudi Arabia, and it is more noticeable during the regime of high volatility.

The findings shed light on the interconnectedness between two of the most important financial markets in the complex international financial environment. They are thus of particular interest for economic policymakers and portfolio investors.

The author distinguishes this study from previous studies in several ways. First, while previous empirical studies of the dynamic linkage between stock prices and foreign exchange markets are primarily devoted to developed markets or emerging markets, this study’s interest is concentrated on four Gulf Arab financial markets (Kuwait, Qatar, Saudi Arabia and UAE). Second, unlike most investigations in the literature that only estimate this link for the whole period, this study attempts to estimate during the good and bad period by using a two-regime MS-VAR model. To the best of the author’s knowledge, this is the first study of the Gulf Arab countries on the stock and foreign exchange markets to apply this model.

This paper examines the volatility spillover effects from traditional financial assets to cryptocurrency markets and vice versa. It aims to provide insights into the dynamic interconnectedness of these markets.

This paper employs the time-varying parameter vector autoregression technique to examine the volatility spillover among the crypto markets (across leading cryptocurrencies such as Bitcoin (BTC), USD Tether, NEAR Protocol (NEAR), Immutable and Dogecoin) and traditional financial instruments (Treasury Bills (TBILL) and Volatility Index).

The results reveal significant bidirectional volatility spillovers between cryptocurrencies and traditional financial assets. NEAR and BTC act as a major transmitter of volatility, both influencing others significantly (71.63 and 68.17%, respectively) and being influenced by others (54.74 and 62.3%, respectively). TBILL and Grayscale Bitcoin Trust ETF are the largest net receivers of volatility, indicating a higher dependency on other assets’ volatility.

Understanding the volatility spillover dynamics can aid investors in portfolio diversification and risk management. The findings provide actionable insights for constructing portfolios that include both cryptocurrencies and traditional financial assets, allowing for more informed investment decisions under volatile market conditions.

This paper contributes to the literature by analyzing volatility spillovers among traditional financial markets and various major cryptocurrencies. It offers a framework for assessing how shocks in one market or cryptocurrency can propagate to others, thereby enhancing the understanding of interconnectedness between markets. This understanding improves our ability to risk manage modern portfolios, which increasingly include significant alternative assets like cryptocurrencies.

The purpose of this study is to investigate the relationship between renewable energy consumption and economic growth, using the threshold variables of non-renewable energy consumption, urbanization level and per-capita income.

This study used a panel threshold regression model, on combined African countries and divided African countries into five regions (northern, western, central, southern and eastern Africa). The study used panel data from 54 African countries, from 1990 to 2018.

This study established a threshold interval where the significant negative impact of renewable energy consumption on the economic growth of combined African countries is different at each split asymmetric phase, meaning the relationship is negative and non-linear. Further, the study established the threshold effect of divided African countries into regions, revealed a negative effect of renewable energy consumption on economic growth and compared the differences of threshold effect and coefficient in the regions, which further highlight the varying resource and renewable energy development across African countries.

This study recommends strategies and investment priorities on energy transition, through optimizing renewable energy in Africa, hence aggressive investment in the renewable energy sector is highly encouraged especially for the oil-producing state to promote clean and sustainable energy.

The contribution of this study is the establishment of a non-linear panel threshold model to examine the asymmetric effect of renewable energy consumption on economic growth which to the best of the authors’ knowledge is pioneer research in Africa. Additionally, an in-depth analysis of renewable energy consumption’s effect on the economic growth of all the regions in Africa.

The purpose of this study is to investigate the relationship between renewable energy and economic growth of Bulgaria.

This study analyzes the relationship between renewable energy and economic growth of Bulgaria for the period 1990-2016, based on annual data, by using the Toda–Yamamoto analysis and Autogressive Distrubuted Lag (ARDL) bound test. This period is characterized by the democratization of the Balkans and several crisis cycles in Bulgaria. Renewable energy consumption (REC, percentage of total final energy consumption), renewable electricity output (REO, percentage of total electricity output) and economic growth (GDP constant 2010 US$) were used. The levels or differences of the variables that are stationary were investigated using the augmented Dickey–Fuller (ADF), Philips–Perron (PP) and Kwiatkowski-Philips-Schmidt-Shin (KPSS) unit root tests.

Three different results were obtained from this study. One showed that renewable energy consumption and renewable electricity output are the causes of economic growth. Another result of this study is that economic growth and renewable electricity output are the causes of renewable energy consumption. The last result is that economic growth and renewable energy consumption are not causes of renewable electricity output. There was no long-term relationship between variables.

The ARDL and Toda–Yamamoto tests were used because of lack of data sets. Thus, it is estimated that there is no long-term relationship.

This study is an original work for Bulgaria, showing the results of the relationship between renewable energy and economic growth. In line with the results of this study, renewable energy projects related to Bulgaria can be predicted.