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The aim of this paper is to evaluate empirically the impact of oil price fluctuations on the relationship between banking sector development and economic growth in oil-importing MENA countries.

The study used the newly developed panel autoregressive distributed lagged (ARDL) approach in order to address any potential endogeneity between research variables.

The empirical results show a unidirectional causality in the long run from oil price to both economic growth and banking sector development for oil-importing countries. Also, banking sector development not only leads directly to economic growth but also can play a moderator role in the oil price—economic growth nexus.

The study has two principal limitations. On the one hand, this study was conducted in a relatively limited sample of countries. On the other hand, the study did not consider others indicators for banking sector development and others macroeconomic variables.

The results found have imperative implications for banks' managers, regulators and researchers. Bank managers should be more concerned with the negative repercussions of oil price fluctuations on the development of their banks. The regulatory authorities must emphasize policies and strategies to further strengthen their banking sector in order to alleviate the negative influence of oil price shocks on economic growth. Researchers focused on finance-growth nexus must take into account the potential influence of oil price shocks.

The developed conceptual model allows examining to what extent the oil price fluctuations might affect the relationship between economic growth and banking sector development. This effect is neither evaluated nor clarified in the relevant literature.

This research empirically investigates the evidence of the financial development and economic growth nexus in sub-Saharan Africa from 1995 to 2022.

A series of preliminary tests are conducted before using the two-stage estimated generalized least squares and robust least squares methods for the analysis. Two indices are constructed to measure financial development: one for the banking sector indicators and another for the market-based indicators (Ustarz and Fanta, 2021).

The results indicate that the banking sector index significantly impacts the gross domestic product (GDP) per capita positively. The market sector index has a negatively significant effect on the GDP per capita. Government expenditure has a positive impact on the GDP per capita.

Policymakers in sub-Saharan Africa should improve and implement finance–growth inclusive strategies that promote financial reforms and development to efficiently impact all population sectors. Policymakers should take stringent measures to ensure that the banking sector's development is sustainable to lead economic growth. The governments should strategize and promote capital market development using favorable listing rules for companies in the stock markets. Global stock market integration should be encouraged to diversify risks, increase public awareness, raise investors' confidence level and reduce stock market impediments like high taxes and regulatory barriers.

Previous study findings on the financial development and economic growth nexus are inconclusive and debatable. This study employs the financial development index approach.

This paper seeks to examine the interrelationship between inclusive business, private sector credit and economic welfare in Africa.

The study uses the seemingly unrelated regression, system generalized method of moments and bootstrap quantile regression in a panel of 54 economies in Africa, over the period 2006–2020.

The authors show that countries that provide more credit to the private sector have better incentives to enhance the ease of doing business. The authors find that ease of doing business and domestic credit to the private sector have a positive and significant effect on economic welfare at higher quantile levels. The authors find that ease of doing business substitutes private sector credit to boost economic welfare, while business account complements private sector credit to boost economic welfare. The authors show that the marginal effect of inclusive business on economic welfare is greater in countries that provide more credit to the private sector.

The implication is that countries that focus on developing their private sector (through credit expansion) should be able to encourage or facilitate the inclusion of businesses to achieve a sustainable economic welfare.

The implication is that policymakers should be able to develop their business environment through inclusive financing so as to build business confidence in the society.

The paper examines the interrelationship between inclusive business, private sector credit and economic welfare in Africa.

This paper aims to analyse economic growth in Africa focussing on the role of digitalization and financial sector development.

The authors employ country-level data from 36 African countries over the period 2000–2020 and used fixed effect, random effect and the Hausman–Taylor estimation techniques.

The study, first finds that, digitalization propels financial sector development in Africa. Building on this, the study further finds that, digitalization conditioned on financial sector development at best does not promote economic growth in Africa. However, results of the net effects suggest that digitalization, overall, improve economic growth in Africa.

In the current environment of a sluggish global economy, digitalization can play an important role in assisting policymakers to spur economic growth. This has attracted the attention of many researchers in the developed world. However, little is done about the subject matter in Africa.

The findings of this paper are novel in the African sub-region with important policy implications.

The conflict in Russian Ukraine is a problem for the world economy because it hinders growth and drives up inflation when it is already high. The trade route between India and Russia is also impacted by the Russia-Ukraine crisis. This study aims to compile the most recent data on how the present global economic crisis is affecting it, with particular emphasis on the Indian economy.

This research develops a mathematical forecasting model to evaluate how the Russia-Ukraine crisis would affect the Indian economy when perturbations are applied to the major transport sectors. Input-output modeling (I-O model) and interval programing (IP) are the two precise methods used in the model. The inoperability I-O model developed by Wassily Leontief examines how disruption in one sector of the economy spreads to the other. To capture data uncertainties, IP has been added to IIM.

This study uses the forecasted inoperability value to analyze how the sectors are interconnected. Economic loss is used to determine the lowest and highest priority sectors due to the Russia-Ukraine crisis on the Indian economy. Furthermore, this study provides a decision-support conclusion for studying the sectors under various scenarios.

In future studies, other sectors could be added to study the Russian-Ukrainian crises’ effects on the Indian economy. Perturbation is only applied to transport sectors and could be applied to other sectors for studying the effects of the crisis. The availability of incomplete data is a significant concern in this study.

Russia-Ukraine conflict is a significant blow to the global economy and affects the global transportation network. This study discusses the application of the IIM-IP model to the Russia-Ukraine conflict. It also forecasts the values to examine how the crisis affected the Indian economy. This study uses a variety of scenarios to create a decision-support conclusion table that aids decision-makers in analyzing the Indian economy’s lowest and most affected sectors as a result of the crisis.

This article aims to evaluate the entry and exit of companies from local productive structures, with a specific focus on the sectoral complexity of these activities and the complexity of these portfolios. The study focuses on empirically demonstrating the thesis that related economic diversification exacerbates the development gap between more and less complex regions.

The article uses indicators formulated by the economic complexity approach. They allow a relevant descriptive analysis of the economic diversification process in Brazilian micro-regions and provide the foundation for the econometric tests conducted. Through three distinct estimation strategies (OLS, logit, probit), the influence of complexity and relatedness on the entry and exit events of firms from local portfolios is tested.

In all estimated models, the stronger relationship between an activity and a portfolio significantly increases its probability of entering the productive structure and, at the same time, acts as a significant factor in preventing its exit. Furthermore, the results reveal that the complexity of a sector reduces the probability of its specialization in less complex regions while increasing it in more complex regions. On the other hand, sectoral complexity significantly increases the probability of a sector leaving less complex local structures but has no significant effect in highly complex regions.

Due to the data used, the indicators are calculated considering only formal job numbers. Additionally, the tests do not detect the influence of spatial issues. These limitations should be addressed by future research.

The article characterizes a prevailing process of uneven development among Brazilian regions and brings relevant implications, primarily for policymakers. Specifically, for less complex regions, policies should focus on creating opportunities to improve their diversification capabilities in complex sectors that are not too distant from their portfolios.

The article makes an original contribution by proposing an evaluation of regional diversification in Brazil with a focus on complexity, introducing a more detailed differentiation of regions based on their complexity levels and examining the impact of sectoral complexity on diversification patterns within each group.

The purpose of this study is to use the structural model to determine the influence of mobile telecommunication on Egypt’s economic growth from 2000 to 2009. By focusing on mobile unique subscribers and mobile broadband-capable device penetration as indicators of telecommunications adoption, the authors seek to understand their overarching effects on the nation’s economic landscape.

The paper uses quarterly time-series data set over the period 2000–2019 and uses a structural econometric model based on an aggregate production function, a demand function, a supply function and an infrastructure function to detect causality and examine long-run relationships between variables.

The findings of the structural model reveal that both mobile unique subscribers and mobile broadband-capable device penetration significantly contributed to Egypt’s gross domestic product (GDP) growth from 2000 to 2019. Specifically, a 1% increase in mobile unique subscriber penetration and mobile broadband-capable device adoption is estimated to result in an average annual contribution to GDP growth of 0.172% and 0.016%, respectively.

The scarcity of panel data is the main research limitation for comparative study with other Middle East and North African Region (MENA) countries. Research extensions would include testing the significance of complementarities such as improving governance measures and building human capacity for both households and firms, which are necessary to boost the impact of telecommunication on economic growth in the MENA region.

Based on these findings, the study puts forth policy recommendations aimed at maximizing investment in network utilization, including mobile and internet services, as well as fixed broadband subscriptions. It highlights the crucial role of these investments in promoting social and economic development, not only in Egypt but also across the MENA region as a whole.

The findings of this research emphasize the importance of strategic investments in network utilization, encompassing mobile, internet services and fixed broadband subscriptions. Such investments are pivotal for fostering social and financial inclusion. The study underscores the potential of these investments to drive social and economic progress, not just within Egypt but throughout the entire MENA region.

Overall, existing literature generally supports the notion that the telecommunications sector has a positive economic impact. However, there is a gap in the literature when it comes to understanding the specific effects of the Egyptian telecommunications sector on the country’s economy, particularly in relation to the Egypt Vision 2030. The study aims to fill this gap by focusing specifically on Egypt and providing additional insights into the direct and indirect effects of the Egyptian telecommunications sector on the economy. By conducting a thorough analysis of the sector’s role, the authors aim to contribute to the existing literature by providing context-specific findings and recommendations.

The COVID-19 pandemic severely impacted tourism, and the hotel and restaurant industry was the most affected sector, which faced issues related to business uncertainty and unemployment during the crisis. The analysis of recovery time and the influence factors is significant to support policymakers in developing an effective response and mitigating the risks associated with the tourism crisis. This study aims to investigate numerous factors affecting the recovery time of the hotel and restaurant sector after the COVID-19 crisis by using survival analysis.

This study uses the quarterly value added with the observation time from quarter 1 in 2020 to quarter 1 in 2023 to measure the recovery status. The recovery time refers to the number of quarters needed for the hotel and restaurant sector to get value added equal to or exceed the value added before the crisis. This study applies survival models, including lognormal regression, Weibull regression, and Cox regression, to investigate the effect of numerous factors on the hazard ratio of recovery time of hotels and restaurants after the COVID-19 crisis. This model accommodates all cases, including “recovered” and “not recovered yet” areas.

The empirical findings represented that the Cox regression model stratified by the area type fit the data well. The priority tourism areas had a longer recovery time than the non-priority areas, but they had a higher probability of recovery from a crisis of the same magnitude. The size of the regional gross domestic product, decentralization funds, multiplier effect, recovery time of transportation, and recovery time of the service sector had a significant impact on the probability of recovery.

This study contributes to the literature by examining the recovery time of the hotel and restaurant sector across Indonesian provinces after the COVID-19 crisis. Employing survival analysis, this study identifies the pivotal factors affecting the probability of recovery. Moreover, this study stands as a pioneer in investigating the multiplier effect of the regional tourism and its impact on the speed of recovery.

The tourism multiplier effect (TME) is the total economic impact of tourism demand, representing the linkages between tourism and other businesses in an area. However, study about it is limited in Indonesia, especially at the provincial level and after the COVID-19 crisis. This study aims to estimate the TME in all provinces of Indonesia, test its differences in priority and non-priority areas before and after the COVID-19 crisis, analyze its spatial distribution and examine the determinant factor of TME

This study applies an input-output model to measure the TME of all provinces in Indonesia, an independent sample t-test to examine the similarity of TME in priority and nonpriority areas, a paired sample t-test to examine the similarity of it before and after the COVID-19 crisis, and spatial analysis to check its spatial relationship.

The result shows that regional TME ranges from 1.25 to 2.05 in 2019, which changed slightly over time. The empirical result shows the TME difference before and after the COVID-19 crisis, and there is a spatial correlation in terms of TME with the hot spots are clustered in the eastern region of Indonesia, However, there was a slight change in the position of hot spots during the COVID-19 crisis. Moreover, the spatial model shows that value-added and employment in agriculture, manufacturing, trade and transportation affect the size of TME.

This study contributes to the academic literature by providing the first estimate of the TME at the provincial level in Indonesia, comparing the it in priority and non-priority areas before and after the COVID-19 crisis, and mapping its spatial distribution.

This study attempts to examine the relationship between the banking sector and stock market development in India.

To analyze the relationship between banks and stock market development, the ratio of stock market capitalization to GDP is proxied by stock market development. The determinants of the stock market development are used for analysis namely domestic credit to the private sector as a ratio of GDP is used as a proxy for the development of banks, saving rate, per capita real GDP, and inflation. The autoregressive distributed lag (ARDL)-Bounds testing approach is used for the analysis. The paper also used the unrestricted error correction model and CUSUM and CUSUM square test to check the stability of the model.

The ARDL bounds test found that there is a long-run relationship between stock market development and bank-centered financial development. The results also revealed that the stock market is positively influenced by the development of banks, savings, and per capita real GDP in the short-run as well as long-run.

This paper suggests that improvement of banking sector plays an important role to increase liquidity of the capital market development in India. This paper also suggests that the economic growth and savings rate have positive impact to induce the capital market growth in both short run and long run.

The study has investigated the empirical relationship between the banking sector and the stock market development in a different methodological approach by using an ARDL model which is appropriate for a small sample size. There are few studies related to bank-centered financial development and stock market development in the context of India.