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This paper, based on the 2022 Master Class delivered at the 50th National Economic Meeting organized by ANPEC, discusses how post-Keynesian macroeconomics and New Developmentalism complement each other to understand middle-income economies' development in financial globalization. It summarizes my academic reflection about the advance in post-Keynesian thinking to develop macroeconomics for peripheral middle-income economies.

As part of this reflection, I first bring up the idea of a developmental convention and, next, how peripheral financialization impacts the elaboration of this convention. Given the asymmetric configuration of the international financial system and the context of hierarchical currencies, I discuss the challenge of overcoming underdevelopment in peripheral economies. The post-Keynesian macroeconomics and advances in the structuralist debate provide the analytical tools to understand how peripheral economies develop virtuous or vicious growth cycles. At the end of the paper, I present some comments on the stagnation of the Brazilian economy.

The growth strategy with foreign savings does not provide the conditions for middle-income economies to operate with sufficient economic policy autonomy to promote productive transformation. To this end, a developmental convention should replace the neoliberal convention that has dominated since the 1970s.

The dynamics of peripheral, middle-income economies, often influenced by international liquidity flows, are a crucial area of study. This research underscores the importance of understanding these dynamics, as it forms the basis for economic policy recommendations. The paper also highlights the inadequacy of the growth strategy with foreign savings in the current configuration of the international financial system, emphasizing the need for middle-income economies to operate with greater economic policy autonomy to foster productive transformation.

This paper examines the extent to which exchange rate volatility (ERV) is crucial for small island economies. These economies by their very nature and size tend to be net importers and highly dependent on trade for their economic survival. The island of Mauritius is used as a case study.

A GARCH model has been utilized using yearly data for the period 1993–2022. The ARDL bounds cointegration approach has been used to determine the long run relationship between exchange rate volatility and the performance of exports. The ECM-ARDL model has been used to estimate the short-run relationships, that is the speed of adjustments between the variables under consideration.

The findings reveal that exchange rate volatility has a positive and significant effect on exports in the short run as well as in the long run. The study also finds out that export has a long-term relationship with world GDP per capita. Both the presence and degree of exchange rate volatility are important aspects for consideration in policy making.

The literature gap that this study attempts to close is one related to global impacts within the recent time horizon. Recently, numerous important events shaped the financial and economic landscape globally, including but not limited to the financial crisis of 2008 and the COVID-19 pandemic in 2019. Both these events stressed the global volume of trade and the exchange rate markets, and these events affects small islands comparatively more given their heavy dependence on international trade for economic development, albeit economic survival.

The purpose of this study is to investigate the impact of pervasive immigrant inflows on GDP productivity growth in selected OECD countries, including Australia, Canada, Germany, Italy, New Zealand and the USA. The study aims to consider patent filing residence and non-residence as well as R&D expenditure to see if large immigrant destination countries can accept many immigrants to generate knowledge and creativity and stimulate economic development.

The study uses OECD and WDI data sets from 2000 to 2019 and employs a fundamental correlation matrix and static panel model to analyze the data. The study examines the impact of residential and non-residential patent applications and R&D expenditure on GDP productivity growth in the selected OECD countries.

The study found an adverse effect for residential patent applications, while non-residential patent application and R&D expenditure variables were strongly linked to GDP productivity. This indicates that to reap the benefits of skilled immigration inflows, the selected OECD countries must devote more resources to research and development and build a knowledge-based economy. This will improve economic efficiency and overall growth.

This paper assists policymakers in comprehending how to effectively utilize immigration inflows in developed and emerging economies in order to construct a future knowledge-based economic system.

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.

This viewpoint engages with Jem Bendell’s deep adaptation framework which was developed as a response to the threat of collapse. Proponents of deep adaptation argue that societal collapse is either likely, inevitable or already underway. The deep adaptation framework is employed as a tool to contemplate the necessary adaptation of tourism development and planning in a context of polycrisis leading to collapse.

This is a conceptual viewpoint article that is built on deductive analysis of recent events, reports and scientific findings. It employs the deep adaptation framework to analyse possible alternative tourism futures in the face of the threat of collapse.

Bendell’s framework included four aspects of response to the recognition of the threat of collapse: resilience, relinquishment, restoration and reconciliation. In this work, the deep adaptation framework is employed to analyse what a deep adaptation approach to tourism might offer for efforts in securing optimal social and ecological outcomes. Findings highlight damaging activities that we should relinquish, more resilient approaches that communities could encourage and restorative practices such as rewilding and pluriversal economies as protective measures. This work recommends a precautionary approach to transform tourism education, research and practice in order to secure better tourism futures.

This work is novel in engaging with the threat of future collapse and in using the deep adaptation framework to consider alternative tourism futures.

This study aims to test the dynamic impact of public debt and economic growth on newly democratized African countries (South Africa and Namibia) and compare the findings with those of newly democratized European countries (Germany and Ukraine) during the period 1990–2022.

The methodology involves three stages: identifying the appropriate transition variable, assessing the linearity between public debt and economic growth and selecting the order m of the transition function. The linearity test helps identify the nature of relationships between public debt and economic growth. The wild cluster bootstrap-Lagrange Multiplier test is used to evaluate the model’s appropriateness. All these tests would be executed using the Lagrange Multiplier type of test.

The results signify the policy switch, as the authors find that the relationship between public debt and economic growth is characterized by two transitions that symbolize that the current stage of the relationship is beyond the U-shape; however, an S-shape. The results show that for newly democratized African countries, the threshold during the first waves was 50% of GDP, represented by a U-shape, which then transits to an inverted U-shape with a threshold of 65% of GDP. Then, for the European case, it was 60% of GDP, which is now 72% of GDP.

The findings suggest that an escalating level of public debt has a negative impact on economic growth; therefore, it is important to implement fiscal discipline, prioritize government spending and reduce reliance on debt financing. This can be achieved by focusing on revenue generation, implementing effective taxation policies, reducing wasteful expenditures and promoting investment and productivity-enhancing measures.

The primary objective of this research is to chronicle how the Environmental Protection Agency (EPA) and other United States Federal Government Agencies (USFGA) agencies have played a role in shaping the trajectory of financial reporting for sustainability, with a particular emphasis on triple bottom line (TBL). This exploration extends to other indexes reporting sustainability data encompassed within financial, social and environmental reporting.

This study adopts an illustrative methodology, utilizing data sourced from governmental, business and international organizational documents.

Sustainability accounting predominantly finds its place within the framework of TBL. However, it is crucial to note that sustainability reporting remains voluntary rather than mandatory. Nevertheless, accounting firms and professional accounting societies have embraced it as a supplementary facet of financial accounting reporting.

The research highlights the historical evolution of sustainability within the USFGA and corporate entities. Corporations’ interest in accounting for sustainability performances has significantly contributed to the emergence of voluntary sustainability accounting rules, as embodied by the TBL.

This paper aims to examine and compare the export performance and competitiveness of Indian and Chinese textile and clothing industry in post-multifibre arrangement (MFA) era.

Balassa’s revealed comparative advantage Index is used to assess the competitiveness of Indian and Chinese textile and clothing exports.

The results indicate that China’s textiles and garments sector holds a greater proportion of the global market compared with India. India has a robust comparative advantage in silk, carpets and cotton post-MFA. Vegetable textile fibers, paper yarn and woven fabrics of paper yarn are also competitive. China had a strong comparative advantage in silk and fabrics; special woven fabrics, tafted textile fabrics, lace, tapestries, trimmings and embroidery in 2005. China also recorded comparative advantage in silk, man-made filaments: strip and the like of man-made textile materials, fabrics; special woven fabrics, tafted textile fabrics, lace, tapestries, trimmings and embroidery and fabrics; knitted or crocheted in 2021.

This study’s results and recommendations could assist the Indian and Chinese Governments develop policies to upgrade their garment industries.

Though vast literature reviews are available for textile and apparel export performance in India and China separately, there are few studies on comparisons. This study is a significant attempt to evaluate India and China’s competitiveness in the global market.

In this paper we investigate why the process of structural change in Brazil was growth accelerating before 1980 and why it was growth reducing after this year.

We investigate the causes of this change in behavior using the shift-share decomposition method.

The results indicate that in the first period there were high productivity gains as result of improvement in economic fundamentals such as the quality of capital and of labor and innovations. In this way, reallocation of workers between sectors, that is part of the process of structural change, was an inducer of economic growth. However, after 1980, mainly between 1991 and 2011, sectors that achieved productivity gains did so by reducing labor, which was absorbed by sectors with poor performance in terms of productivity growth. Furthermore, factors such as the deindustrialization that developed countries have been undergoing, the international situation, the stage of Brazilian economic development and its possible premature deindustrialization contributed to a growth reducing structural change.

Our differential to the matter is applying the shift-share methodology without combining any of the ten sectors analyzed, adopting a slightly different time frame than similar studies and presenting the shift-share results in a graphically manner in addition to the traditional numbers. By representing graphically how much each of the ten sectors is contributing to the structural change in the economy we are emphasizing the specificities of each of these sectors instead of just considering the aggregated view like manufacturing industry versus other industries or modern services versus traditional services.

The purpose of this study is to shed light on the twin transition in China in the organization of innovation processes in artificial intelligence (AI) and green technology (GT) development and to understand the role of foreign multinationals in Chinese innovation systems.

A qualitative research approach is used by interviewing executives from German multinationals with expertise in AI and GT development and organization of innovation processes in China. In total, 11 semi-structured interviews were conducted with companies, and the data were analysed with a thematic qualitative text analysis.

The findings show that AI applications for GT are primarily developed in cross-company projects that are led by local and regional authorities through the organization of industrial districts and clusters. German multinationals are either being integrated, remaining autonomous or being excluded from these twin transition innovation processes.

This paper aims to fill the gap in the literature by providing one of the first qualitative approach towards twin transition innovation processes in China and exploring the integration of multinational enterprises in cluster organizations. To the best of the author’s knowledge, this is one of the first twin transition studies from this perspective in emerging economies.