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This article focuses on regional-level cooperation in higher education by examining the functional, organizational and political approaches (FOPA) framework for higher education regionalization and using supra-national regional universities as established and successful examples of regional-level higher education cooperation among countries.

A conceptual framework is used to provide the structure for analyzing the key approaches to higher education regionalization, followed by an analysis of supra-national regional universities to demonstrate the application of the model.

The FOPA framework for higher education regionalization includes three approaches. The first is the functional approach, which includes both collaborative academic and research activities among higher education institutions as well strategies and policies to help align systems across a region. The second is the organizational approach, which focuses on networks, organizations, institutions and programs, which facilitate partnerships. The third is the political approach, which includes regional-level agreements, declarations and strategic plans to promote higher education collaboration. Key higher education activities for each approach are discussed in generic terms, with examples provided from major regions of the world.

The research was based on desk research only. No interviews were conducted.

A conceptual analysis and a model were provided for the concept of regionalization of higher education and for regional universities, which can help readers locate their interests and research in the regionalization of higher education. Examples of three different types of regional universities were provided to give concrete illustrations of a regional university.

One of the rationales driving regional universities is to address and increase a sense of regional identify and to meet the social, economic and educational needs of the specified region.

Regional universities, such as the University of West Indies, Arab Open University and the Pan-Africa University, are an understudied phenomenon. Using them as innovative and sustainable examples of higher education regional cooperation and the FOPA model, this study illustrates how single-campus, multiple-campus and virtual regional universities are functioning to meet the diversified needs and priorities across a region through cooperation among countries.

The paper presents the facts on the policy challenges and opportunities in the way forward of trade and economic co-operation in South Asia amid the coronavirus disease 2019, which comes to be the least economically integrated region worldwide. Due to tense geopolitics in South Asia, trade is heavily biased toward extra-regional markets despite of existing regional trade agreements (TAs) in the region.

Having tested the stationarity of data with structural break, the paper uses intra-regional trade in addition to other domestic economic variables as exogenous regressors in autoregressive distributed lag multivariate framework, hence raising the quality of statistical inference.

This paper highlights that intra-regional trade significantly affects the economic welfare as measured by Gross Domestic Product per capita of the people from the region, hence raising the need for higher regional trade openness. If trade barriers are overcome, all the South Asian countries will gain through effective implementation of regional TAs.

The study relies on the multivariate technique with regional trade share as the main exogenous variable. In addition, the regulatory and economic conditions of all countries are different which also tends to affect the mutual degree of trade relations.

Over the economic reasons, the manmade barriers owing to political differences are the root cause for the low intra-regional trade. Amid the pandemic, South Asian courtiers have the high time to leverage the bilateral trade for mutual benefits. India being the largest economy can play a decisive role in pushing forward the regional trade bloc – South Asian Association for Regional Cooperation (SAARC) – for achieving its objective through multilateral engagements in a wider perspective.

The present study makes pioneer efforts to examine the dynamic linkages between regional trade and economic growth. The results provide new insight into the dynamics of benefits driven by trade interdependency.

The main goal of this paper is to examine the evolution of Latin American productive integration in terms of the regional value added incorporated in intra-regional exports of Argentina, Brazil, Chile, Colombia, Mexico and Peru. In addition, the study traces the trade and productive integration trajectories for each of these countries from 1995 to 2015.

Based on the use of OECD’s global ICIO input-output tables, this paper applies the methodological framework by Wang et al. (2018) for the analysis of trade flows at the bilateral level, which allows breaking down the value of gross exports of each sector-country, depending on the origin of the value added contained in exports, as well as their use.

The estimates show very low shares of value added from regional partners in the intra-regional exports of the countries studied. Conversely, the weight of the value added incorporated in these exports by countries outside the region has increased in tandem with China’s expanding involvement in Latin America. This development, along with the downward trend in domestic value added incorporated in exports, indicates a lack of a regional integration process of any depth.

This article addresses an economic problem of conventional importance from a global value chain perspective using a novel methodology based on the use of global input–output tables.

The paper investigates the dynamic relationship among the stock markets of South Asian Association of Regional Cooperation (SAARC) countries during the COVID-19 pandemic.

Daily time-series data of four SAARC countries: India, Bangladesh, Pakistan, and Sri Lanka, from February 13th, 2013 to March 31st, 2021 are used. The study considers stock prices prior to the blowout of COVID-19 and during the onset of the pandemic. The novel estimation procedure of the autoregressive distributed lag model is used while the results are also confirmed by post-estimation techniques.

The study confirms that the COVID-19 contagion has adversely influenced the stock returns of SAARC countries. The findings signify that the pattern of cointegration has significantly different regularities in the pattern of causality in the long run and short run during the COVID-19 crisis. Overall, the study revealed that the COVID-19 pandemic has weakened the dynamic connection among the stock markets of SAARC countries.

To dampen uncertainties generated by the COVID-19 pandemic, the authorities and central banks should be equipped with efficient strategies and guidelines to cope with the crisis created by the pandemic. Further, governments should focus on assuaging the panic faced by investors and enhancing the confidence of domestic as well as foreign investors. Further, the weakened integration of financial markets during the crisis offers opportunities for speculative and arbitrage gains for investors.

The research work is an innovative effort to analyze the impression led by COVID-19 on the SAARC stock markets integration.

The study investigates the impact of competition and concentration on bank risk-taking behavior and stability in the South Asian Association for Regional Cooperation (SAARC) region.

Data from 100 banks from 2013 to 2021 was analyzed using dynamic and static measures by using dynamic system GMM.

Results showed that higher competition reduces stability, while concentration in the banking sector produces stability and reduces risk-taking behavior. The findings suggest that regulatory agencies should take different actions based on the degree of banking market concentration to enhance banking sector stability in the SAARC area.

The research helps regulators and decision-makers establish capital requirements at levels that would prevent banks from increasing their risk-taking in order to boost profits and, therefore, reduces hazardous practices that might increase the risk.

The research helps establish capital requirements to prevent banks from increasing risk-taking to boost profits and avoid hazardous practices that could increase nonperforming loans and bank failure risks.

The current study aims to examine the impact of two black swan events on the performance of six stock markets in Gulf Cooperation Council (GCC) economies (Abu Dhabi, Bahrain, Dubai, Oman, Qatar and Saudi Arabia). The two selected black swan events are the US Mortgage and credit crisis (Global Financial Crisis of 2008) and the COVID-19 pandemic.

The performance of all the six stock markets are represented by their return and price volatility behavior, which has been measured by applying ARCH/GARCH model. The comparative analysis is done by employing mean difference models. The data is collected from Bloomberg on a daily frequency.

The response of two black swan events on the GCC stock markets has been heterogenous in nature. During the financial crisis, the impact was heavily felt on most of the stock markets in the GCC countries. It is revealed that the financial crisis had a negative significant impact on four of the six countries. Whereas during the COVID-19 crisis, it is revealed that there is no significant impact on four of the six selected stock markets. The positive significant impact is felt on two stock markets, namely, the Abu Dhabi stock market and the Saudi stock market.

The present investigation attempts to fill the gap in the literature on the intended topic because it is evident from the literature on the chosen subject that no study has been undertaken to evaluate and contrast the impact of the GFC crisis and COVID-19 on the GCC stock markets.

This study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.

A two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.

On average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.

This study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

This study aims to explore the determinants of public debt in selected South Asian Association for Regional Cooperation (SAARC) countries for 19 years, from 2001 to 2019.

Using ordinary fixed and random effect models, the authors examine the role of internal and external factors in determining the composition of public debt. Furthermore, for robustness, they compare the results with two-stage least square (2SLS) regression estimates after considering the problem of endogeneity, overidentification, under-identification and weak instruments.

The findings show that among the selected macroeconomic variables, inflation, exchange rate and broad money have significant negative effects on the debt-GDP ratio. In contrast, military spending, corruption and interest rates appear to positively influence the same as per 2SLS results. From the policymaking perspective, SAARC countries should focus more on reducing military spending and make a concerted effort to augment investments in productive projects. Further, with strong fiscal consolidation and institutional quality, it is important to mitigate the frequent occurrence of corruption conundrums in emerging economies for the development of a transparent economic system.

The study is distinct from previous studies in two ways. First, to the best of the authors’ knowledge, there are no studies focusing on SAARC countries in the context of public debt. Second, the study expands the existing literature on public debt by taking into account both external and internal debts to decipher the within-country and cross-country determinants of debt accumulation. More specifically, this model considers accountability and transparency in the public sector, cross-border security challenges and benefits of globalization by including explanatory variables such as corruption, military expenditure spending and capital inflows.

Due to the close connection between urban cluster and carbon emissions (CEs) but a lack of study on it of the construction industry, this paper aims to explore the relationship between the polycentric spatial structure (PSS) of the urban clusters and CEs of the construction industry (CECI).

This research uses panel data of 10 Chinese urban clusters from 2006–2021, calculates their PSSs in the aspects of economy and employment and adopts a panel regression model to explore the effect of the spatiotemporal characteristics of the PSSs on the CECI.

First, the CECI in 10 Chinese urban clusters showed a rising trend in general, and the CECI in the Yangtze River Delta (YRD) was much higher than those in the rest of urban clusters. Second, both Shandong Peninsula (SP) and Guangdong-Fujian-Zhejiang (GFZ) exhibited high degrees of polycentric characteristics, while Beijing-Tianjin-Hebei (BTH) showed weaker degrees. Third, the results demonstrated that the polycentric development of urban clusters did not help reduce the CECI but rather promote the CE. The polycentric index, considering the linear distance from the main center to sub center, had a more significant impact on the CECI.

Previous studies have investigated the impact of urban spatial structure (USS) on CEs; however, few of them have studied in the field of construction industry. Moreover, most research of CEs have concentrated at the national and provincial levels, with fewer studies on urban clusters. This paper contributes to this knowledge by investigating how the PSS of urban cluster influence the CECI.

This study reveals the economic impact of the Indo-Pacific Strategy on the Regional Comprehensive Economic Partnership (RCEP).

This paper uses the GTAP model to analyze the economic effects of RCEP under the effect of the “Indo-Pacific Strategy” under different scenarios.

The results show that (1) with the improvement of the implementation effect of the US “Indo-Pacific Strategy,” the welfare level of China has gradually had a significant negative impact, while the welfare level of US Allies and partners has been further improved. (2) The implementation of the Indo-Pacific Strategy will further expand the import scale of Japan, South Korea and other Allies that are both RCEP members and the USA and slightly reduce the import scale of the European Union (EU) and other countries. (3) After the USA implemented the “Indo-Pacific Strategy,” its export scale has significantly improved, and it has been able to completely offset the adverse effects of the signing of RCEP on its exports. China's export scale has also gradually declined, and Japan has benefited the most.

There are three main possible contributions to this article: first, the authors combined geopolitical factors to simulate and evaluate the economic effects of RCEP under different Indo-Pacific Strategy implementation scenarios, which is more relevant than analyzing the economic effects of RCEP in a “vacuum.” Second, the standard static GTAP model can only measure the change of equilibrium state before and after the trade policy. At the same time, the dynamic GTAP model (GTAP-Dyn) introduces mechanisms such as capital flow and capital accumulation and treats time as a continuous variable affected by exogenous variables so that each variable has a time dimension so as better to simulate the medium- and long-term economic effects. This paper refers to the dynamic recursion method of Walmsley (2006) and Yang (2011) to update the base year of the GTAP version 10.0 database to 2020, that is the time when RCEP officially reached 2020. The simulation results of shock variables introduced into the baseline scenario are more reliable. Third, the authors analyze the welfare effect of RCEP and the impact on the import and export of relevant countries from the macrolevel and examine the impact on different products in different countries from the microlevel.