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Network theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the actual risk by individual investors. We investigate the bipartite network of US mutual fund portfolios and their assets. We follow its evolution during the Global Financial Crisis and study the diversification, as understood in modern portfolio theory, and the similarity of the investments of different funds. We show that, on average, portfolios have become more diversified and less similar during the crisis. However, we also find that large overlap is far more likely than expected from benchmark models of random allocation of investments. This indicates the existence of strong correlations between fund investment strategies. We exploit a deliberately simplified model of shock propagation to identify a systemic risk component stemming from the similarity of portfolios. The network is still partially vulnerable after the crisis because of this effect, despite the increase in the diversification of multi asset portfolios. Diversification and similarity should be taken into account jointly to properly assess systemic risk.

We construct two examples of shareholder networks in which shareholders are connected if they have shares in the same company. We do this for the shareholders in Turkish companies and we compare this against the network formed from the shareholdings in Dutch companies. We analyse the properties of these two networks in terms of the different types of shareholder. We create a suitable randomised version of these networks to enable us to find significant features in our networks. For that we find the roles played by different types of shareholder in these networks, and also show how these roles differ in the two countries we study.

Zimbabwe faces an uncertain future for condom funding and potential condom insecurity as international donors prioritize creating more self-sustaining markets and the government identifies how to best ensure access and uptake. We tested the impact of an intensive intervention on demand and supply after a price increase to the social marketed condom, Protector Plus. The study occurred during a deteriorating economy and pressure to reach sustainability quickly. We highlight where strategic donor investments can impact condom programming and markets. We randomized ten purposively selected districts in Zimbabwe and assigned them to two study groups to test the impact of an intensive social marketing intervention. To the best of our knowledge, this is the first experimental study conducted within a larger market strengthening context. We tracked sales of Protector Plus and distribution of the public sector condom monthly. We conducted baseline and follow-up surveys among consumers and traders, and used the difference-in-difference method to test the intervention's impact on condom preferences and brand equity. Protector Plus sales rebounded to previous levels after the price increase. We detected no significant difference in sales between the experimental and control districts. Among traders, there were no significant differences in brand preference for Protector Plus attributed to the intervention. Among consumers, there was a significant increase in emotional attachment and beliefs about condom efficacy in the experimental districts. Study findings demonstrate where international donor and government investments can impact condom programming and condom markets. Broader findings from the intervention highlight where investments can improve condom coverage, cost recovery, and collaboration between the public, social marketing, and commercial sectors. Strategic investments for strengthening condom markets include: consumer research to segment markets, willingness to pay studies to set price points, distribution system improvements to increase efficiency, intensive demand generation to increase demand and use, market facilitation across sectors, and market intelligence to inform decision making. When a disciplined social marketing approach is used, the market benefits: subsidies can be better targeted, branded products can appeal to the right audiences, and room can be made for the commercial sector to enter the market.

This study is conducted to examine the concerns of the foreign direct investment (FDI) causing environment degradation and also to test the validity of the traditional Environmental Kuznets Curve (EKC) in the context of emerging markets in the Asian region. Data of these countries from 1980–2016 are utilised. This study employs panel cointegration Fully Modified Ordinary Least Squares (FMOLS), which treats the endogeneity problem, and its estimators are adjusted for serial correlation. Moreover, this study also uses panel Dynamic Ordinary Least Squares (DOLS), which includes contemporaneous value, leads and, lags of the first difference of the regressors to correct endogeneity problems and serial correlations. Findings from this study indicate that the pollution heaven hypothesis and the EKC curve are generally valid in the region. In addition, FDI has a strong impact on the environment.

Recently, China is named among the most carbon dioxide (CO )-emitting countries in the world after the United State of America (USA). A major part of Chinese carbon dioxide emissions is as a result of offshore industrial activities which come into the economy as foreign direct investment (FDI). Following this, the present study seeks to investigate the nexus between CO emissions, FDI, energy use, and tourism arrivals, and possibly to advise on who will bear the responsibility of offshore CO emissions. Utilizing ARDL-bound testing and Granger causality approaches for both short- and long-run effects the author found that economic growth (GDP) has a positive relationship with both tourism arrivals, energy use, FDI, and CO .This contributes to heavy CO emissions which the author classified as the outsourced/offshore CO emissions in China's FDI. Tourism arrivals have a bi-directional (feedback) causal relationship with energy use and a uni-directional causal relationship with CO (transmitting from tourism to CO ). Both FDI and energy use have a bi-directional (feedback) causal relationship; CO , energy use, and tourism arrivals have a unidirectional relationship with GDP which established the triangular nexus causality among the variables and the impact on GDP. Hence, the policy implication should be geared towards implementing the policies and regulations that will checkmate and reduce the excesses of foreign firms to the environment quality of China and promote environmentally friendly economic activities.

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that \"fat\" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

Environmental pollution, rapid economic growth, and other social factors have adverse effects on public health, which have consequently increased the burden of health expenditures during the last two decades. This paper provides a comprehensive analysis of carbon dioxide (CO2) emissions and the environment index, as well as economic and non-economic factors such as Gross Domestic Product (GDP) growth, foreign direct investment, population aging, and secondary education impacts on per capita government and private health expenditures in 13 emerging economies for the time period of 1994–2017. We employ robust econometric techniques in this endeavor of panel data analysis to account for the issues of heterogeneity and cross-sectional dependence. This study applies the Lagrange Multiplier (LM) bootstrap approach to investigate the presence of panel cointegration and empirical results underscore the existence of cointegration among variables. For the execution of long-run analysis, we incorporate the two latest estimators, i.e., continuously updated-fully modified (CUP-FM) and continuously updated- bias corrected (CUP-BC). Findings of long-run elasticities have documented that the air-pollution indicators, i.e., CO2 emissions and the environment index, have a positive and significant influence on government health expenditures, while in contrast, both factors negatively influence private health expenditures in emerging economies. We find that economic factors such as GDP growth consistently show a positive impact on both government and private health expenditures, whereas, foreign direct investment exhibits a significant negative and positive impact on government and private health expenditures respectively. Findings of non-economic factors can be used to argue that population aging increases health expenditures while secondary education lowers private health spending in emerging markets. Furthermore, empirical analysis of heterogeneous causality indicates that CO2 emissions, the environment index, GDP growth, foreign direct investment, and secondary education have a unidirectional causal relationship with government and private health expenditures. Population aging has a strong relationship of bidirectional causality with government health expenditures and unidirectional causal relationship with private health expenditures. Findings of this paper put forward key suggestions for policy makers which can be used as valuable instruments for better understanding and aiming to maximize public healthcare and environmental quality gains which are highly connected with sustainable GDP growth and developments in emerging economies.

Background Making the case for investing in public health by illustrating the social, economic and environmental value of public health interventions is imperative. Economic methodologies to help capture the social value of public health interventions such as Social Return on Investment (SROI) and Social Cost-Benefit Analysis (SCBA) have been developed over past decades. The life course approach in public health reinforces the importance of investment to ensure a good start in life to safeguarding a safe, healthy and active older age. This novel review maps an overview of the application of SROI and SCBA in the existing literature to identify the social value of public health interventions at individual stages of the life course. Methods A systematic scoping review was conducted on peer-reviewed and grey literature to identify SROI and SCBA studies of public health interventions published between January 1996 and June 2019. All primary research articles published in the English language from high-income countries that presented SROI and SCBA outputs were included. Studies were mapped into stages of the life course, and data on the characteristics of the studies were extracted to help understand the application of social value methodology to assess the value of public health interventions. Results Overall 40 SROI studies were included in the final data extraction, of which 37 were published in the grey literature. No SCBA studies were identified in the search. Evidence was detected at each stage of the life course which included; the birth, neonatal period, postnatal period and infancy ( n  = 2); childhood and adolescence ( n  = 17); adulthood (main employment and reproductive years) ( n  = 8); and older adulthood ( n  = 6). In addition, 7 studies were identified as cross-cutting across the life course in their aims. Conclusion This review contributes to the growing evidence base that demonstrates the use of social value methodologies within the field of public health. By mapping evidence across stages of the life course, this study can be used as a starting point by public health professionals and institutions to take forward current thinking about moving away from traditional economic measures, to capturing social value when investing in interventions across the life course.

The purpose of our study is to figure out the transitions of the cryptocurrency market due to the outbreak of COVID-19 through network analysis, and we studied the complexity of the market from different perspectives. To construct a cryptocurrency network, we first apply a mutual information method to the daily log return values of 102 digital currencies from January 1, 2019, to December 31, 2020, and also apply a correlation coefficient method for comparison. Based on these two methods, we construct networks by applying the minimum spanning tree and the planar maximally filtered graph. Furthermore, we study the statistical and topological properties of these networks. Numerical results demonstrate that the degree distribution follows the power-law and the graphs after the COVID-19 outbreak have noticeable differences in network measurements compared to before. Moreover, the results of graphs constructed by each method are different in topological and statistical properties and the network’s behavior. In particular, during the post-COVID-19 period, it can be seen that Ethereum and Qtum are the most influential cryptocurrencies in both methods. Our results provide insight and expectations for investors in terms of sharing information about cryptocurrencies amid the uncertainty posed by the COVID-19 pandemic.