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This study aims to test a public–private partnership (PPP) success model by examining the direct effects of two input factors (facilitative leadership and communication quality) on an outcome factor, namely, PPP success (PPP project success and PPP relational success), as well as the mediating effect of trust as a process factor on these relationships.

The present research uses the sociotechnical systems theory as the guiding framework. This is a quantitative study that uses a questionnaire survey and purposive sampling. The respondents comprise 266 public and private sector employees who have been involved in various PPP projects. The data gathered from the survey are analysed using SPSS and structural equation modelling (AMOS version 23.0).

The findings of this study indicate that facilitative leadership, communication quality and trust are positively correlated with PPP success, that is, PPP relational and PPP project success. Trust is found to mediate the relationship between facilitative leadership and communication quality with PPP success.

This paper upholds the importance of facilitative leadership, communication quality and trust in a PPP setting.

This study enriches the knowledge of PPP projects regarding facilitative leadership, communication quality and trust. It also discusses the vital role of these variables in ensuring PPP success.

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 paper is to evaluate the efficiency of Algerian banks and examine the effects of explanatory factors on their performance.

In this paper, a methodology of two-stage network data envelopment analysis (DEA) is used to explore the efficiency of a sample of 13 Algerian banks during the 2013–2017 period. In the first stage, the network DEA is used to assess the overall and stages efficiencies. In the second stage, the partial least squares (PLS) regression is conducted to determine the potential effects of explanatory factors on stages efficiency.

The main empirical results indicate that Algerian banks need an efficiency improvement in both stages. The overall efficiency of the Algerian banking system improves over the study period. The deposit producing efficiency is positively affected by bank size and bank age. The revenue earning efficiency is negatively associated with bank size and bank age. The domestic banks are more efficient than foreign banks in the deposit producing stage and the foreign banks are more efficient than domestic banks in the revenue earning stage.

The results might be used as guidelines for both managers and policymakers in order to improve banks and banking system performance.

To the best of our knowledge, this study is the first that uses the DEA in investigating the efficiency of Algerian banks by dividing the overall efficiency into deposit producing and revenue earning efficiencies. Unlike most studies that have usually used OLS regression, Tobit regression and bootstrapped truncated regression, this study is the first in the bank efficiency literature that uses PLS regression to investigate the potential effect of explanatory variables on deposit producing and revenue earning efficiencies.

Audit rotation (AR) is a key policy initiative implemented in global jurisdictions to deal with concerns about audit quality. Auditing financial reports involves communicating attested value-relevant company information to investors, and hence audit quality plays a role in the quality of financial reporting information. This paper aims to investigate whether AR affects the degree of information asymmetry (IS) between investors. It further aims to examine whether voluntary AR results in less asymmetric information compared to mandatory AR. Additionally, it examines whether political connections moderate the association between AR and IS.

The authors use data from publicly traded banks across the Gulf Cooperation Council (GCC) for the period 2010–2018. The authors include several variables to control for corporate governance and other firm-specific characteristics by using country-year fixed-effects regression model.

The authors find higher IS for banks that periodically rotate auditor, while banks voluntarily choose to rotate auditors obtain high-quality audits, which results in higher trading volume and lower stock return volatility, hence lower IS. The results suggest that when banks voluntarily choose to rotate auditors, investors perceive these banks as more committed to obtaining high-quality audits relative to mandatory AR. Providing higher quality audits enhances the credibility of reported information and thus reduce the level of IS. Moreover, IS following AR is higher for politically connected banks than for similar but politically unconnected banks. Finally, investors perceive voluntary AR as a disciplining tool, which mitigates IS. This mitigating role is not affected by bank political connectedness.

This study has limitations as the definition of AR could be interpreted as binary or too narrow, and hence it may not be appropriate to generalize findings to different contexts. Nonetheless, this study casts light on a new perspective to reconcile the existing mixed evidence on the influence of AR on IS and the moderating role of political connections. A further limitation is that because of data unavailability, the authors were unable to use other proxies (e.g. bid-ask spreads and analyst forecast dispersion) of IS.

The present findings provide insight to regulators, policymakers and standard setters on the potential adverse effect of political connections on the role of AR in mitigating IS. The results underscore the importance of voluntary AR, and suggest that regulators, policymakers and standard setters encourage firms to rotate their auditors periodically.

This study provides evidence in a setting that is unique at the economic, social and regulatory levels. Prior literature is lacking and has been centered on developed countries or focusing on single-country specifications. The data set of this study is unique and allows us to examine the interplay between political influence that arises through ownership and management roles of influential members of state.

This paper aims to provide new perspectives on the integration of East Asian stock markets and the dynamic volatility transmission to the Bitcoin market utilising daily data from 2014 to 2020.

The authors undertake comprehensive analyses of the dependency dynamics, systemic risk and volatility spillover between major East Asian stock and Bitcoin markets. The authors employ a vine-copula-CoVaR framework and a VAR-BEKK-GARCH method with a Wald test.

(a) With exception of KS11 and N225; HSI and SSE; HSI and KS11, which have moderate dependence, dependencies among other markets are low. In terms of tail risk, the upper tail risk is more significant in capturing strong common variation. (b) Two-way and asymmetric risk spillover effects exist in all markets. The Hong Kong and Japanese stock markets have significant risk spillovers to other markets, and quite notably, the Chinese stock market is the largest recipient of systemic risk. However, the authors observe a more significant risk spillover from the Chinese stock market to the Bitcoin market. (c) The VAR-BEKK-GARCH results confirm that the Korean market is a significant emitter of volatility spillovers. The Bitcoin market does provide diversification benefits. Interestingly, the Chinese stock market has an intriguing relationship with Bitcoin. (d) An increase in spillovers in East Asia boosts spillovers to Bitcoin, but there is no intuitive effect of Bitcoin spillovers on East Asian spillovers.

For the first time, the authors examine the dynamic linkage between Bitcoin and the major East Asian stock markets.

This paper aims to examine the extent to which sell-side analysts efficiently incorporate firms’ corporate social responsibility (CSR) activities into their earnings forecasts. In addition, this paper also investigate the CSR information efficiency of analysts vis-à-vis that of investors.

This paper measures CSR activities by using CSR strength and CSR concern scores from the Morgan Stanley Capital International Environmental, Social and Governance database. This paper uses analysts’ earnings forecast errors and dispersion as proxies for their information efficiency. To compare the CSR information efficiency of analysts to that of investors, this paper uses the Vt/Pt ratio, which is the equity value estimates inferred from analysts’ earnings forecasts (a proxy for analysts’ CSR information efficiency) to the stock price of the focal company (a proxy for investors’ CSR information efficiency).

The regression analysis indicates that analysts’ earnings forecasts are optimistically biased and more dispersed for firms with positive CSR activities. The paper also finds that analysts’ forecasts are more optimistically biased than investors in interpreting CSR activities.

The lack of standardized protocols in CSR reporting and activities has raised the risk of mispricing by analysts, threatening the stability of sustainable investments. This paper suggests that regulators and standard-setters should establish a uniform framework governing firms’ CSR activities, along with their reporting and measurement, to ensure more consistent and reliable evaluations of CSR practices.

Analysts’ mispricing of CSR activities may distort sustainable investing, as it can overly focus on the positive impacts of stakeholder theory, overlooking agency theory’s warnings about managerial self-interest. Investors need to assess CSR efforts with a dual perspective, acknowledging their societal value but also examining their alignment with shareholder interests.

To the best of the authors’ knowledge, this research is the first to assess the efficiency of analysts versus investors in processing CSR information amidst growing sustainable investment interests. Furthermore, building on Dhaliwal et al. (2012), which found that voluntary CSR disclosures correlate with more accurate analyst forecasts, this research provides fresh perspectives on the evolving nature of how analysts assimilate CSR information over time.

This paper aims to model the relationship between oil price and stock returns for selected sectors in Nigeria using monthly data from January 2007 to December 2016.

The authors use both the linear (symmetric) autoregressive distributed lag (ARDL) by Pesaran et al. (2001) and non-linear (asymmetric) ARDL by Shin et al. (2014), and they also account for structural breaks using the Bai and Perron (2003) test that allows for multiple structural changes in regression models.

The results indicate that the strength of this relationship varies across sectors, albeit asymmetric and breaks. The authors identify two structural breaks that occur in 2008 and 2010/2011, which coincidentally correspond to the global financial crisis and the Arab spring (Libyan shutdowns), respectively. Moreover, the authors observe strong support for asymmetry and structural breaks for some sectors in the reaction of sector returns to movement in oil prices. These findings are robust and insensitive when considering different oil proxies. While further extensions can be pursued, the consideration of asymmetric effects as well as structural breaks should not be jettisoned when modelling this nexus.

This study is one of the very few studies that have investigated the sectoral behaviour of stocks to oil price shocks, particularly in Nigeria. This paper contributes to the oil stock literature using the recent technique of asymmetry and also considering the role structural breaks play in the relationship between oil price and stock returns.

It has been two decades since the first academic paper shone a spotlight on non-GAAP earnings. The past 20 years of research investigates concerns over the misuse of these disclosures and resulted in some significant changes to accounting and reporting standards across the globe. This paper aims to document the history of non-GAAP reporting and outline the emerging themes of the now matured practice of non-GAAP reporting.

This systematic literature review searches two popular databases to identify the academic publications relating to non-GAAP reporting between 2002 and 2022. The paper uses bibliographic mapping to present the key statistics of the non-GAAP reporting field of research.

The non-GAAP reporting environment started out as the “wild West’ but, through regulation and public awareness, emerged as an important supplement to the traditional outputs of financial reporting. Current consensus is recent non-GAAP earnings are informative to users but there is lack of research into qualitative non-GAAP disclosures and the vast body of archival research needs triangulating with more experimental studies.

This paper contributes to the literature by documenting the past 20 years of non-GAAP reporting and identifying the important existing and emerging research areas concerning non-GAAP earnings disclosures.

Known as the major capital providers in Belt and Road countries and the largest carbon emitter in the world, what role China's outward direct investment (ODI) plays in carbon neutralization has become a matter of concern. This study aims to measure the impact of China's ODI on the carbon emissions of Belt and Road countries.

Based on an econometric model and an inter-regional input–output model, a new model measuring the carbon emission effects of ODI is developed.

The empirical results show that (1) in general, China's ODI generates an emission-reduction effect in Belt and Road countries; (2) The relationship between the emission-reduction effect and income level of host countries shows an approximate inverted U-shaped trend; and (3) China's ODI generates stronger emission-reduction effects on capital-intensive industries.

This study quantitatively measures the scale of carbon emission-increase and reduction effect, which is relatively lacking in previous studies. This study explores the heterogeneity from the perspectives of regions, countries and industries. The authors have compiled an inter-regional input–output table for the Belt and Road countries for 2014 to provide a broad basis for the study of related issues.

The purpose of this paper is to test the overshooting effects of monetary expansion on prices of agricultural products at farm production, processing and circulation stages in China, and to investigate the heterogeneity of the overshooting mechanisms in these three links.

Empirical results are obtained through the vector error correction model and the overshooting framework proposed by Saghaian et al. (2002b). Specifically, we first apply the Dickey–Fuller generalized least squares (DF-GLS) method to test the stationarity of the key variables, and then use the Johansen’s (1991) method to conduct the cointegration test. Finally, the vector error correction model is employed to examine the overshooting hypotheses in the three stages of China’s agricultural sector.

Empirical results indicate that overshooting of prices relative to monetary expansion in China’s agricultural sector is a common phenomenon, but with significant heterogeneity. Firstly, at the stage of agricultural production, the overshooting degree and restoration rate of material price are greater than those of agricultural products price. Secondly, at the processing stage of agricultural products, both the purchase price of agricultural products and industrial producer price have an overshooting effect, but the overshooting effect of the former is more significant than the latter. Thirdly, at the circulation stage of agricultural products, the overshooting coefficient of the wholesale price index of agricultural products is the most significant, while that of the retail and purchase price of agricultural products is not significant.

The paper contributes to proposing a comprehensive framework on testing the overshooting effects for three main stages of agricultural sector in China and empirically investigating the heterogeneity of the overshooting mechanisms in different stages with time series methods.