PurposeThis paper presents three models of funding health care in 130 developing countries, based upon a public system, a private system and personal remittances.Design/methodology/approachThe authors trace the funding of health from foreign aid to health funding and health outcomes in the public system, foreign direct investment to health funding in the private system, and personal remittances to health outcomes. This is followed by panel data, fixed effects models subjected to 2-, 3- and 4-stage least squares regressions.FindingsFindings from the first model were that aid in the form of Technical Cooperation Grants funded Infrastructure. Infrastructure Spending due to aid funds Government Health Plans, which reduced the Incidence of Tuberculosis, which in turn reduced Undernourishment and increases Life Expectancy. Other positive health outcomes included reduced Birth Rate and reduced Maternal Mortality. In the second model, Foreign Direct Investment increased Female Employment and GDP per Person, funding Private Health Plans, which increase Life Expectancy, reduced Undernourishment, increased Skilled Care at Birth, increased the Number of Hospital Beds, reduced Maternal Mortality and increased the Birth Rate. In the third model, Remittances influenced both Out-of-Pocket Medical Expenses and Private Plans.Social implicationsPublicly funded programs may be directed to nutrition, increasing life expectancy. Private funding may be directed to improving maternal conditions, with remittances removing the liquidity constraints.Originality/valueThis paper is the first attempt to trace health funding from its sources of foreign aid, foreign direct investment and personal remittances using three separate paths.

The rapid growth of electric vehicles, solar roofs, and wind power suggests that the potential growth in green equity investments is an emerging trend. Accordingly, this study measured the predictors of excess equity returns in a portfolio of global green energy producers, from 2010 to 2019. Fixed-effects panel data regressions of daily returns, followed by quantile regressions, were performed. There was some support for the explanation of green equity returns by market returns and market risk (beta), as indicated by the single-factor Capital Asset Pricing Model (CAPM), and the multifactor Fama–French Three-Factor and Fama–French Five-Factor Models. The most significant predictors of green equity returns were Value-at-Risk at a 95% confidence level, and Value-at-Risk at a 99% confidence level. Expected Shortfall was another extreme risk value measure. The importance of extreme value measures suggests the presence of fat-tailed leptokurtic distributions, whereby excess returns were explained by the risk of loss given adverse conditions, primarily at 95% confidence. We conclude that the proliferation of small firms and new entrants in the renewable energy sector has led to the explanation of returns by extreme values of risk.

Cryptocurrencies are virtual currencies employed in blockchain transactions. They are particularly worthy of theoretical examination, given the limited academic literature on the subject. This paper constructs valuation models of bitcoin and altcoins, both as single investments and components of mutliple-asset portfolios. As single investments, cryptocurrencies are valued at the confluence of Legendre utility functions, with Esscher transformed Geometric Levy pricing processes. As part of portfolios, cryptocurrencies are contained in traditional Markowitz portfolios which are varied by increasing the proportion of the riskless asset, shorting the risky asset, or adding currency options. Theoretical formulations show that Markowitz models combined with bitcoin, located on the Capital Market Line (which we term CML portfolios), have low returns, mainly due to the presence of the riskless asset. Such portfolios are appropriately suited to the investment goals of risk-averse traders, while overlooking the preferences of risk-takers. To satisfy less riskaverse investors, we propose a high-return portfolio with 9 asset choices, consisting of risky assets, cryptocurrencies, US dollars, soybean futures, Treasury bond futures, oil futures, currency options on the US dollar, currency options on the Mexican peso, and technology, or biotechnology stocks. Laplace transforms are employed to suppress volatility, skewness, or kurtosis of returns, which empirical studies have found to contribute to tail risk contained in outliers in fat-tailed distributions.

This paper evaluates the ability of exchange rate regimes to influence economic growth. Exchange rate regimes for 186 countries were classified into four categories. For the full sample, exchange rate regimes increased economic growth although inflation reversed the increase in economic growth, both for the full sample, and for developed countries. For developing countries, during the historical time period, all of the classifications increased economic growth with increasing flexibility of the exchange rate regime. For the modern period, developed countries displayed similar significant relationships, as did high, middle, and low income countries, small island states, and inland states.