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Financial market holds superior information that can give insights into the future trajectory of economic growth. Further, identifying sectors that hold the key to future economic growth is important for all economies, but particularly relevant to emerging markets. However, unlike existing studies, the paper provides new insights into the forward-oriented nexus between financial markets and economic growth.

This paper takes a forward-looking approach of using financial market information to predict future economic growth. The authors use ARDL modeling approach to predict economic growth using the information from stock market sectoral returns.

The authors find that sectoral stock returns significantly improve economic growth forecasts. However, the forecasting superiority is not uniform across sectors and horizons. Auto, consumers' spending, materials and realty sectors provide the most forecasting gains. In contrast, banking, capital goods and industrial sectors provide superior forecasts, but only at horizons beyond one year. The authors also find that the forecast superiority of sectors at longer horizons is inversely related to volatility.

Research highlights the need for sector-focused policy actions in driving economic growth. Further, the findings of the paper identify sectors that drive short-, medium- and long-term economic growth.

There is a significant heterogeneity among different sectors and across horizons in predicting economic growth. Results suggest that targeted policy actions in sectors like materials, metals, oil and gas, and realty are key in driving economic growth. Further, policies geared toward the grassroots industries are at least as beneficial as the large-scale industries. Evidence also suggests the need for an active fiscal policy to address infrastructural bottlenecks in primary industries like basic materials and energy. Evidence nevertheless does not undermine the role of monetary policy actions.

Unlike any paper till date, the innovation of the paper is that it takes an ARDL modeling approach to measure stock market sectoral returns' ability to forecast economic growth several months ahead in the future. Though the paper considers the Indian case, the innovation and contribution extents to the entire field of economic studies.

The literature on economic forecasting, is showing an increase in criticism, of the inaccuracy of forecasts, with major implications for economic, and fiscal policymaking. Forecasts are subject to the systemic uncertainty of human systems, considerable event-driven uncertainty, and show biases towards optimistic growth paths. The purpose of this study is to consider approaches to improve economic foresight.

This study describes the practice of economic foresight as evolving in two separate, non-overlapping branches, short-term economic forecasting, and long-term scenario analysis of development, the latter found in studies of climate change and sustainability. The unique case of Ireland is considered, a country that has experienced both steep growth and deep troughs, with uncertainty that has confounded forecasting. The challenges facing forecasts are discussed, with brief review of the drivers of growth, and of long-term economic scenarios in the global literature.

Economic forecasting seeks to manage uncertainty by improving the accuracy of quantitative point forecasts, and related models. Yet, systematic forecast failures remain, and the economy defies prediction, even in the near-term. In contrast, long-term scenario analysis eschews forecasts in favour of a set of plausible or possible alternative scenarios. Using alternative scenarios is a response to the irreducible uncertainty of complex systems, with sophisticated approaches employed to integrate qualitative and quantitative insights.

To support economic and fiscal policymaking, it is necessary support advancement in approaches to economic foresight, to improve handling of uncertainty and related risk.

While European Union Regulation (EC) 1466/97 mandates pursuit of improved accuracy, in short-term economic forecasts, there is now a case for implementing advanced foresight approaches, for improved analysis, and more robust decision-making.

Building economic resilience and adaptability, as part of a sustainable future, requires both long-term strategic planning, and short-term policy. A 21st century policymaking process can be better supported by analysis of alternative scenarios.

To the best of the authors’ knowledge, the article is original in considering the application of scenario foresight approaches, in economic forecasting. The study has value in improving the baseline forecast methods, that are fundamental to contemporary economics, and in bringing the field of economics into the heart of foresight.

The purpose of this study is to empirically investigate how external debt vulnerability has affected the economy of emerging countries over time, with particular reference to Sub-Saharan African countries. It also deals with the policy issues associated with the economic effects.

The techniques of dynamic ordinary least squares and fully modified ordinary least squares are used in this investigation, covering the period 1990–2022. A panel of 43 Sub-Saharan African countries is used in the study.

The estimation results reveal that external debt vulnerability impacted negatively on economic growth, thus validating the concerns raised about the debt problem in Sub-Saharan Africa. Furthermore, the results revealed that domestic credit and openness of economy played a passive role and were therefore unable to cushion the adverse effect of debt vulnerability. Capital stock, however, stands out as the only variable that played a significant positive role in facilitating economic growth. The results are considered to be highly reliable for short-term forecast of economic growth and formulation of relevant policies.

Over the years, economic analysts and stakeholders have expressed concern about the inadequate ratio of foreign reserves to external debt in developing countries. The effect of this external debt vulnerability on the economy of these countries has yet to be given sufficient attention by researchers. In view of this perceived void, this current study is carried out to determine the economic and policy consequences of the problem.

This paper aims to explore and analyse stakeholders’ perceptions of the development priorities and suggests more effective strategies to assist sustainable economic growth in the United Arab Emirates (UAE).

The authors use the World Bank data set, which collects various stakeholders’ opinions on the UAE development. First, the exploratory factor analysis has been applied to detect the main groups of development priorities. Second, the fuzzy cluster analysis has been conducted to detect the groups of stakeholders with different attitudes towards the importance of extracted groups of priorities. Third, clusters have been compared according to demographics, media usage and shared prosperity goals.

The two main groups of development priorities have been extracted by the exploratory factor analysis: economic priorities and sustainability priorities. Four clusters have been detected according to the level of motivation when it comes to the economic and sustainability priorities: Cluster 1 (High economic – High sustainability), Cluster 2 (High economic – Medium sustainability), Cluster 3 (High economic – Low sustainability) and Cluster 4 (Low economic – Low sustainability). Members of the cluster that prefer a high level of economic and sustainability priorities (Cluster 1) also prefer more diversified economic growth providing better employment opportunities and better education and training for young people in the UAE.

Limitations stem from the survey being conducted on a relatively small sample using the data collected by the World Bank; however, this data set allowed a comparison of various stakeholders. Future research should consider a broader sample approach, e.g. exploring and comparing all of the Gulf Cooperation Council (GCC) countries; investigating the opinions of the expatriate managers living in the UAE that are not from GCC countries; and/or including other various groups that are lagging, such as female entrepreneurs.

Several practical implications were identified regarding education and media coverage. Since respondents prioritize the economic development factors over sustainability factors, a media campaign could be developed and executed to increase sustainability awareness. A campaign could target especially male citizens since the analysis indicates that males are more likely to affirm high economic and low sustainability priorities than females. There is no need for further diversification of media campaigns according to age since the analysis did not reveal relevant differences in age groups, implying there is no inter-generational gap between respondents.

This paper contributes to the literature by comparing the perceived importance of various development goals in the UAE, such as development priorities and shared prosperity indicators. The fuzzy cluster analysis has been used as a novel approach to detect the relevant groups of stakeholders in the UAE and their developmental priorities. The issue of media usage and demographic characteristics in this context has also been discussed.

Technology is an important factor contributing to the economic development of countries. In the context of the 4th industrial revolution, a country's success lies in its ability to grasp and absorb the level of technology into production and economic development. This aims of this research are to evaluate the impact of the tourism and technological contribution on economic growth in East Asian countries in the period of 2010–2019.

This research uses the feasible generalised least squares (FGLS) to revise the diagnostic problems and other advanced techniques to check the robustness; the research results confirm that there is no impact between tourism and economic growth.

The main driving force behind economic comes from: technological contribution, financial development and foreign direct investment inflows.

The research confirms that there is a significant and negative relationship between exchange rate and economic growth.

This paper aims to explore the extreme effect of crude oil price fluctuations and its volatility on the economic growth of Middle East and North Africa (MENA) countries. It also investigates the asymmetric and dynamic relationship between oil price and economic growth. Further, a separate analysis for each MENA oil-export and oil-import countries is conducted. Furthermore, it studies to what extent the quality of institutions will change the effect of oil price fluctuations on economic growth.

As the effect of oil price fluctuations is not the same over different business cycles or oil price levels, the paper uses a panel quantile regression approach with other linear models such as fixed effects, random effects and panel generalized method of moments. The panel quantile methodology is an extension of traditional linear models and it has the advantage of exploring the relationship over the different quantiles of the whole distribution.

The paper can summarize results as following: changes in oil price and its volatility have an opposite effect for each oil-export and oil-import countries; for the former, changes in oil prices have a positive impact but the volatility a negative effect. While for the latter, changes in oil prices have a negative effect but volatility a positive effect. Further, the impact of oil price changes and their uncertainty are different across different quantiles. Furthermore, there is evidence about the asymmetric effect of the oil price changes on economic growth. Finally, accounting for institutional quality led to a reduction in the impact of oil price changes on economic growth.

The study concludes more detailed results on the impact of oil prices on gross domestic product growth. Thus, it can be used as a decision-support tool for policymakers.

Human capital is a portfolio of rich skills that the labour possesses. Human capital has attracted significant attention from scholars. Nevertheless, empirical findings on the utility of human capital have often been divided. To address the research gap in the literature, the authors attempt to understand how human capital plays a significant role in financial development and economic growth nexus.

The authors rely on secondary data published by the World Bank. The authors use econometric tools such as the autoregressive distributive lag (ARDL) model and related statistical tests to study the relationship between human capital, India's financial growth and gross domestic product (GDP) growth.

Study findings suggest that human capital and financial development contribute significantly to economic growth. Further, the authors found that human capital has a positive and significant moderating effect on the path of joining financial development and economic growth.

The study contributes to the human capital debate. Despite the rich body of literature, the study based on World Bank data confirms the previous findings that investment in human capital is always useful for the financial and economic growth of the nation.

This paper reveals some unique findings regarding effect of financial development and economic growth nexus which opens the window of new dimension to think about their nexus. It also provides a different pathway to foster the economic growth by using human capital and financial development as together, especially in India.

Over the years, public sector reforms in emerging economies have focused on improving national budget systems and financial management practices to promote sustainable development. In the context of the COVID-19 crisis, this article examines whether the strength or effectiveness of national budget systems and related financial management practices moderates the impact of fiscal policy measures on economic recovery and resilience.

The article uses bivariate correlations and difference-in-difference analyses to examine the relationship between budget system effectiveness, government stimulus measures and forecasts of economic recovery and resilience. The analysis uses data from the Public Expenditure and Financial Accountability (PEFA) program, International Monetary Fund (IMF) and World Bank.

The article finds that estimates of economic recovery and resilience are higher in countries with more reliable budget processes and more transparent public finances. Also, the strength or effectiveness of the budget system before the pandemic appears to moderate the impact of government stimulus measures on economic recovery and resilience over a medium-term forecast horizon.

This is a prospective analysis based on economic forecasts from the IMF, which are subject to change in the coming years. In addition, the analysis uses subjective budget system indicators, which present measurement challenges that often influence this area of research. Better comparative data in the future, for example, large administrative datasets, will enable researchers to explore these issues with less estimation bias.

The findings are relevant for policymakers and budget officials in developing countries in Africa who are engaged in plans to improve national budget systems and enhance resilience to crises, such as the COVID-19-induced economic crisis. The findings also have implications for developing countries beyond Africa with similar economic and fiscal conditions.

The findings have implications for economic and budgetary planning for the social sector as well as the efficient delivery of public services in developing countries. Public managers have a critical role to play in adapting national budget systems and financial management reforms within complex and evolving economic circumstances even after the coronavirus pandemic.

The authors use novel and latest data on country responses to the COVID-19 pandemic as well as medium-term economic forecasts to examine the relationship between national budget systems and post-pandemic economic recovery and resilience in the African context. Previous research has only addressed these issues in the context of industrialized countries, and a limited number of empirical studies examine these relationships. The findings also have significant value for policymakers outside Africa who are facing similar challenges related to the coronavirus pandemic.

This study aimed to know the effect of cross-sectional risk, which comprises business-specific risk and stock market volatility, as a variable for estimating macroeconomic risk in Indonesia. This study observes public companies in Indonesia and Indonesian macroeconomic data from 2004 to 2020. In this study, the author uses term spread as the dependent variable that reflects macroeconomic risk. The cross-sectional risk comprises financial friction (FF), cash flow (CF), debt–service ratio, and stock market volatility as independent variables. By using the Autoregressive Distributed Lag (ARDL) Model method, this study shows that business-specific and stock market risk can estimate macroeconomic risk, so that it becomes an early signal of economic shock, such as recession or high inflation, in the future. The model in this study also examines the cross-sectional risk relationship with other macroeconomic indicators, such as the Consumer Confidence Index (CCI), money supply (M0), and Indonesia’s trade balance (TB).