The primary focus of this Element is to understand the rise of smart 'social' infrastructures in BoP emerging markets like India. It has been observed that new focus areas and frontiers of global economy are taking shape where social and environmental outcomes along with economic performance are considered to be collective parameters for success or failure of the businesses. This has led to the emergence of new models of entrepreneurship, namely for-profit social businesses. These new models are driven by problem-solving social innovators who are driven by the social and environmental mission besides economic gains. Sustainability and overall success of social businesses is driven by smart social infrastructure, comprising availability of incubation ecosystem for social start-ups, access to patient capital, availability of digital ecosystem, adoption of circular business models, and focus on collaborations, partnerships and networking with diverse stakeholders.

This book substantiates the transformation processes in the system of modern entrepreneurship in the conditions of formation of Industry 4.0. The authors develop a scientific concept of business 4.0, determine the specific features of business 4.0 and current problems and perspectives of its development in developed and developing markets, study the infrastructural provision of business 4.0 in view of its sectorial specifics, outline the perspectives and recommendations in the sphere of development of business 4.0, and offer the scientific and practical recommendations for state and corporate management.

This Element goes far beyond economic theory. It will also be of interest to representatives of the environmental sciences due to its focus on the “green” economy and sustainable development. It will also be interesting to the representatives of the social sciences, as it takes into account the peculiarities of emerging market economies. Learning from the COVID-19 pandemic makes this Element interesting from a health economics perspective.

The empirical literature on the contributions of human capital investments to economic growth shows mixed results. While evidence from OECD countries demonstrates that human capital accumulation is associated with growth accelerations, the substantial efforts of developing countries to improve access to and quality of education, as a means for skill accumulation, did not translate into higher income per capita. In this Element, we propose a framework, building on the principles of 'growth diagnostics', to enable practitioners to determine whether human capital investments are a priority for a country's growth strategy. We then discuss and exemplify different tests to diagnose human capital in a place, drawing on the Harvard Growth Lab's experience in different development context, and discuss various policy options to address skill shortages.

This Element provides a detailed overview of the structural changes in the Asia-Pacific region from the early 2000s onwards. It reviews the most relevant literature on this important topic. The following two research areas are explored: first, by deploying visual network analysis (VNA), we analyse cross-border interbank claims and liabilities of the individual countries located in the Asia-Pacific region. Such an analysis evaluates interbank exposures to systematically important banks within the specific market. The important advantage of VNA is that it allows us to examine the 'hierarchical' cross-country interbank contagion risk that seems to have been neglected in similar studies. Secondly, we evaluate the contagion risk to the individual countries spreading from the financial centres in Hong Kong, Singapore, Tokyo, New York and London. The analysis unveils links and statistical factors that could be used as a key tool for detecting the potential triggers of systemic risk.

Since Meese and Rogoff (1983) results showed that no model could outperform a random walk in predicting exchange rates. Many papers have tried to find a forecasting methodology that could beat the random walk, at least for certain forecasting periods. This Element compares the Purchasing Power Parity, the Uncovered Interest Rate, the Sticky Price, the Bayesian Model Averaging, and the Bayesian Vector Autoregression models to the random walk benchmark in forecasting exchange rates between most South American currencies and the US Dollar, and between the Paraguayan Guarani and the Brazilian Real and the Argentinian Peso. Forecasts are evaluated under the criteria of Root Mean Square Error, Direction of Change, and the Diebold-Mariano statistic. The results indicate that the two Bayesian models have greater forecasting power and that there is little evidence in favor of using the other three fundamentals models, except Purchasing Power Parity at longer forecasting horizons.

This Element focuses on Latin American fossil fuel producer countries and how they are dealing with the transition towards a greener energy matrix. The challenges involved are multiple and ethical in substance. In particular, a worldwide expansion in clean energies would reduce climate change, physical risks. A rapid transition, however, induces the irruption of a new (financial) risk. The energy transition, in addition, could be thought of as a new arena for political disputes. Finally, it evaluates the relevance of monetary policy and financial regulation to tackle the issue from a macro perspective. Energy transition, however, have also long-term but uncertain consequences on the national economy. Henceforth, and in order to minimize risks, a long-term, strategic vision of the challenge confronted by the region becomes mandatory. To tackle all these problems, this Element profits from contributions of different disciplines.