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This paper aims to investigate the relationship between the Kingdom of Saudi Arabia (KSA)’s expenses in the health and social fields and the achievement of sustainable development goals (SDGs) 1 (elimination of poverty) and 3 (good health and well-being). This paper also examines the effects of the COVID-19 pandemic on these expenses and goals.

This paper observes the public expenses and the targets of the SDGs of KSA during 1981–2022. This paper tests the stationarity of the variables and then uses the ordinary least square model or the autoregressive distributed lag model, depending on the unit root test results. This paper also observes the change in target goals between the two years of the pandemic and the two preceding years.

The results show the influence of social expenditure on the progress of SDG-1, whereas the impact of health expenditure on SDG-3 is not significant. This paper also proves the impact of the pandemic on public expenses and social SDGs.

This paper attracts the attention of policymakers to the importance of assessing their SDG initiatives and the consequent outcomes. Additionally, this paper documents the initiatives for sustainable development in KSA, an important emerging country. Given the universal nature of the SDGs and the importance of KSA as an economic power with a large youth human capital potential, the findings offer insights applicable beyond KSA and provide valuable lessons for governments worldwide regarding the optimization of public spending for SDG achievement. Moreover, monitoring SDG advancement in this important country helps assess the progress of the the United Nations (UN)’s 2030 Agenda for Sustainable Development. Therefore, This paper helps boost the completion of this agenda and contributes to the bottom-up approach of the UN 2030 Vision, implicating all categories of stakeholders, including the academic community.

This paper furthers the literature on SDG achievement by analyzing the relationship between public expenses and SDGs. This paper contributes to the debate concerning the best methodology suitable for SDG valuation and adds to the few studies using autoregressive tests. Moreover, this paper enriches the scarce studies dealing with emerging countries and reviews the assessment of SDGs in KSA. Additionally, this paper investigates the effect of the COVID-19 pandemic on the assigned resources for SDGs and, consequently, on the related indicator scores.

The aim of this study is to analyze which socioeconomic factors (economic, demographic, and political) most commonly affect the social expenditure of the European Union (EU) and Organization for Economic Co-operation and Development (OECD) countries.

A panel data fixed-effects model is employed for 34 OECD and 23 EU countries between 2000 and 2020.

Results indicate that, in all country groups, economic factors have the most significant influence on social expenditures, with income being the primary determinant, particularly in EU countries. The negative impacts of unemployment and inflation underscore the importance of counter-cyclical measures adopted by countries to maintain stability in their social expenditures. The most influential demographic factor is found as the old-age-dependency ratio. While the rule of law affects social expenditure positively, government effectiveness and female labor force participation affect it negatively. The positive effect of Konjunkturforschungsstelle (KOF) indexes shows the globalization effect, which can be attributable to the compensation hypothesis.

Governments enforce inclusive and sustainable policies to boost economic activities and GDP, thus combating inflation and unemployment and regulating the labor market and socioeconomic problems about aging populations and women’s economic participation to control social expenditures. The rule of law and institutional quality will also boost economic growth.

This study focuses on the effects of social expenditures in a broader view within the framework of the three main factors (economic, demographic, political) and attempts to determine the key factors that account for the differences in social expenditure between the OECD and EU countries.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0384

Asian countries have had persistent unemployment levels. The purpose of this paper is to investigate the impact of government spending on unemployment. Furthermore, this paper investigates the moderating role of institutional quality on the government spending–unemployment nexus.

Using data from 35 Asian countries from 2000 to 2022, the dynamic ordinary least squares and fully modified ordinary least squares technique is used to tackle with aforementioned issue. In addition, pooled mean group estimation is applied to verify the robustness of the findings.

The results show that an increase in government expenditure and better institutions reduce the unemployment rate. Interestingly, the negative impact of government expenditure on unemployment will enhance and intensify with better institutional quality. Furthermore, trade openness and foreign direct investment decrease unemployment in Asian countries. The results are robust to various specifications.

Findings from this study provide important implications for governments. Governments should use public expenditure efficiently and enhance and improve institutional quality to reduce unemployment.

To the best of the author’s knowledge, this study pioneers the investigation of the moderating role of institutional quality in the relationship between government expenditure and unemployment in Asian countries.

The purpose of this study is to explore the relationship between government spending, public debt and the informal economy. In addition, this paper investigates the moderating role of public debt in government spending and the informal economy nexus.

By utilizing a data set spanning from 2000 to 2017 of 32 Asian economies, the study has employed the dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS). The study is also extended to consider the marginal effects of government spending on the informal economy at different degrees of public debt.

The results indicate that an increase in government spending and public debt leads to an expansion of the informal economy in the region. Interestingly, the positive effect of government spending on the informal economy will increase with a rise in public debt.

This study stresses the role of government spending and public debt on the informal economy in Asian nations. To the best of the authors' knowledge, this study pioneers to explore the moderating effect of public debt in the public spending-informal economy nexus.

The objective of this study is to reevaluate the correlation among pharmaceutical consumption, per capita income, and life expectancy across different age groups (at birth, middle age, and advanced age) within the OECD countries between 1998 and 2018.

We employ a two-step methodology, utilizing two independent approaches. Firstly, we con-duct the Dumitrescu-Hurlin pairwise panel causality test, followed by Machine Learning (ML) experiments employing the Causal Direction from Dependency (D2C) Prediction algorithm and a DeepNet process, thought to deliver robust inferences with respect to the nature, sign, direction, and significance of the causal relationships revealed in the econometric procedure.

Our findings reveal a two-way positive bidirectional causal relationship between GDP and total pharmaceutical sales per capita. This contradicts the conventional notion that health expenditures decrease with economic development due to general health improvements. Furthermore, we observe that GDP per capita positively correlates with life expectancy at birth, 40, and 60, consistently generating positive and statistically significant predictive values. Nonetheless, the value generated by the input life expectancy at 60 on the target income per capita is negative (−61.89%), shedding light on the asymmetric and nonlinear nature of this nexus. Finally, pharmaceutical sales per capita improve life expectancy at birth, 40, and 60, with higher magnitudes compared to those generated by the income input.

These results offer valuable insights into the intricate dynamics between economic development, pharmaceutical consumption, and life expectancy, providing important implications for health policy formulation.

Very few studies shed light on the nature and the direction of the causal relationships that operate among these indicators. Exiting from the standard procedures of cross-country regressions and panel estimations, the present manuscript strives to promote the relevance of using causality tests and Machine Learning (ML) methods on this topic. Therefore, this paper seeks to contribute to the literature in three important ways. First, this is the first study analyzing the long-run interactions among pharmaceutical consumption, per capita income, and life expectancy for the Organization for Economic Co-operation and Development (OECD) area. Second, this research contrasts with previous ones as it employs a complete causality testing framework able to depict causality flows among multiple variables (Dumitrescu-Hurlin causality tests). Third, this study displays a last competitive edge as the panel data procedures are complemented with an advanced data testing method derived from AI. Indeed, using an ML experiment (i.e. Causal Direction from Dependency, D2C and algorithm) it is believed to deliver robust inferences regarding the nature and the direction of the causality. All in all, the present paper is believed to represent a fruitful methodological research orientation. Coupled with accurate data, this seeks to complement the literature with novel evidence and inclusive knowledge on this topic. Finally, to bring accurate results, data cover the most recent and available period for 22 OECD countries: from 1998 to 2018.

Real estate projects are capital-intensive and deeply intertwined with economic factors, making them subject to various influences besides local housing needs. This paper aims to comprehensively understand the dynamics of the Egyptian real estate market, examining real estate cycles, driving factors and their correlation and scale of impact.

The study conducts a literature review to explore real estate cycles and their driving factors, along with the relationship between real estate and macroeconomic cycles. It then delves into the dynamics of the Egyptian real estate market, followed by a time series analysis that incorporates five key indicators: economic indicator, demand indicator, supply indicator, capital flow indicator and cost indicator over a 12-year interval (2012–2023), to examine short-term cycle factors, followed by correlation and multi-linear regression analysis to elucidate interrelations among these factors.

Through measuring and comparing the prementioned indicators with different economic and social events, the study paints a comprehensive picture of the macroeconomic environment and the real estate cycle in Egypt. Where demand has been found to be more sensitive and directly affected by macroeconomic factors than the supply. With the economic factor as the factor with the highest impact, especially in times of economic fluctuations, the impact has been immediate and short-term. These findings support the idea that the demand in Egypt is speculative, laying a threat of longer recession periods in the long term and having greater and more direct impact.

This paper contributes to the understanding of the Egyptian real estate market by integrating insights from real estate cycles, macroeconomics and specific market dynamics. The application of time series, correlation and multi-linear regression analysis provides a nuanced understanding of the interplay between several factors shaping the real estate cycle. Ultimately, the findings offer valuable insights for decision-makers involved in urban development planning, facilitating more informed and precise decision-making processes.

The purpose of this study is to quantify and evaluate the efficiency of knowledge services public libraries (PLKS) in China and to analyze the factors affecting the efficiency of PLKS. The focus of this study is to explore the characteristics and changing trends of PLKS and how to improve the efficiency of PLKS. The conclusions drawn in this paper are expected to provide important references for academic research and practical exploration in related fields.

This study constructs a three-stage process of PLKS. On this basis, the efficiency is analyzed by using the Super-NSBM model, and the influencing factors of PLKS are analyzed by using OLS. Finally, through the comprehensive interpretation of the measured data and the existing social development conditions, the authors put forward relevant recommendations.

In the first stage, the PLKS in China meets the basic requirements, but there is an obvious waste of resources in the second stage. In addition, China’s public libraries show obvious regional differences in knowledge service efficiency. Finally, it was found that economic and technological factors can increase the efficiency of PLKS, but the increase in the number of university students will reduce the efficiency of PLKS.

In this study, the authors provide an exhaustive deconstruction and explanation of PLKS, which leads to the proposal of a three-stage PLKS efficiency conversion process. Furthermore, the authors identify a diverse set of quantifiable metrics that are readily accessible for open collection. Notably, the authors correlated the efficiency of PLKS with the influencing factors, exploring PLKS from a new perspective and enriching the research related to PLKS.

It was to investigate whether gender diversity – gender balance – within political municipal government teams affected the municipal indebtedness. Government ideology, the gender of the mayor and the wealth of the municipal environment were considered as moderators.

We used GMM estimators on two dynamic models and a sample of 144 Spanish municipalities with more than 50,000 inhabitants for the period 2013–2022.

Gender diversity within government teams reduces the municipal debt. Furthermore, the government right-wing ideology and the female gender of the mayor are robust moderators of the effects of the gender diversity within government teams on institutional indebtedness.

The differences in financial autonomy and powers to apply public policies by municipalities in the different countries, as well as some differential aspects within the right-wing ideological spectrum, may condition our findings. Within relational demography, gender diversity impacts municipal performance, opening the way to explore other relations in future research.

The tendency to implement legislation to try to achieve high gender balances within political decision-making bodies generates higher gender diversity, and our research shows that it leads to a better financial performance, a matter of transcendental importance for EU, credit rating agencies, and lenders.

This study provides new knowledge about the effect of gender within political decision-making bodies on municipal budgetary management. It is the first research analysing the impact of gender balance in the strict sense within decision-making bodies on municipal indebtedness.

In light of the repercussions of the COVID-19 pandemic, electronic auditing otherwise known as computer-assisted audit tools and techniques (CAATTs) has become inevitable to automate the auditing process worldwide. Accordingly, the purpose of this study is to examine the influence of technological, organizational and environmental (TOE) factors on public sector adoption of CAATTs in developing countries such as Jordan under the COVID-19 pandemic conditions.

This study used 136 usable responses from the managers of internal audit (IA) of the Jordanian public sector entities. The data collected were analyzed using partial least squares-structural equation modeling. The TOE framework has been used in this study to consider a wide set of TOE factors. Then, this study suggests a CAATTs adoption model that incorporates the related technology factors of the diffusion of innovation theory to environmental and organizational factors. Further, this study contributes to the TOE framework by addressing government regulations, audit bodies’ support and audit task complexity as environmental factors affecting CAATTs adoption in the context of the public sector.

The results revealed that for technological factors, only the compatibility affects CAATTs adoption by the IA departments. For organizational factors, organizational readiness, top management support, auditors’ information technology competency and entity size were found to be significant factors. From the environmental factors, both government regulation and audit task complexity influence the CAATTs adoption. Besides, entity size moderates the influence of top management support on the CAATTs adoption in the public sector.

The findings could highlight the significance of the CAATTs adoption in the public sector institutions (by internal auditors) post-COVID-19, taking into consideration the TOE framework’s factors. Also, the findings are significant for the decision-makers and regulators in declaring new legislation for the electronic IA profession in the Jordanian public sector.

It turns out that the CAATTs adoption in the public sector can definitely enhance their ability to achieve the role of IA in preserving public funds and restricting corrupt practices within the public sector.

To the best of the authors’ knowledge, this study is one of the first studies that address the professional audit agency support and audit task complexity as environmental factors, as well as the entity size as an organizational factor, that affect CAATTs adoption in the IA department of the public sector.

This study aims to investigate the determinants of GST_efficiency of the Indian states to assist the policymakers, government and GST council to devise their policies and strategies to boost the GST_efficiency of the Indian states.

The analysis has used the panel data set of 27 Indian states and 3 UTs with a time span of 2017–18 to 2022–23. The study has used the Generalized Method of Moment regression for exploring the determinants of GST_efficiency of the state governments in India.

The findings depict that sectoral composition, inflation rate, financial development, state’s self-reliance, per capita income and gross fiscal deficit have a significant effect on GST_efficiency of the state governments. The findings support the Tanzi effect 1977 and claim that the rise in the inflation level erodes GST_efficiency of the state governments. The rise in the self-reliance of the state government will make the Indian states self-dependent and will reduce their reliance on central transfers.

The government should make efforts to make the Indian states self-reliant by increasing the share of OTR (Own Tax Revenue) instead of increasing their revenue efficiency in short-run through devolution and central transfers. Moreover, the Indian government should devise their macro-economic policies to curb the inflation level and gross fiscal deficit of the state governments in the country.

To the best of the authors’ knowledge, this may be the first study to explore the determinants of GST_efficiency of the state governments in India.