Private financing of large‐scale infrastructure projects through public private partnerships (PPPs) has grown in recent decades. Together with changes in conventional construction procedures, there have been changes in the project financing model. The use of PPPs raises questions as to the role of the private sector in infrastructure provision and the conditions governing the long‐term contractual relationships between the private and public sectors. In some early examples of PPPs, the government guaranteed a minimum profitability over the cash flows using a set of contractual terms which transferred some of the risk of the project from the private provider back to the government. Using a large toll road project, the Melbourne CityLink Project, as a case study we show how the imposed conditions can be treated as real options, how these options affect the incentive to invest and how the public sector may be transferring considerable value to the private sector through government guarantees.

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Most single-factor and multifactor asset pricing models constitute special cases of the consumption-based asset pricing theory, in which investors’ marginal utility is the key determinant of asset prices. However, in recent years, production-based asset pricing models have been extraordinarily successful in correctly pricing a wide range of anomaly portfolios that are typically mispriced in previous research. In parallel, research on conditioning information has contributed to significantly improve the performance of classic consumption-based asset pricing models. On this basis, in this paper we conduct an in-depth research on the performance of consumption and production-based asset pricing models on the Tokyo Stock Exchange, for the period from 1992 to 2018, in order to test to what extent consumer confidence helps consumption models to correctly capture shifts in the investment opportunity set of investors. To overcome the constraints imposed by the periodicity of macroeconomic data, we use a factor-mimicking portfolio approach that allows us to test the performance of the models into consideration at different frequencies. Our results suggest that the consumer confidence index for Japan helps consumption-based asset pricing models outperform production-based models for different anomaly portfolios. Conversely, in those cases where consumption models perform worse, the production models also perform poorly. These results help to partially reconcile the results provided by the consumption and production models, and constitute a step forward for the purpose of identifying the fundamental risk factors that drive asset prices.

The relatively recent green bond market is increasingly attracting interest at the technical, regulatory, and academic research levels. Although a considerable body of research on green bonds focuses on the investor’s perspective, this study takes the perspective of a project finance sponsor to analyze whether there is a direct financial incentive for issuing green bonds in contrast to other types of financing. In order to measure the impact of green bond financing on the profitability and solvency of environmentally friendly investments, we study the sensitivity of the financial performance of a well-established project finance investment—the Sagunto regasification plant—to shifts in its financial structure. In particular, we develop a base case that allows us to study the impact of green financing compared to other financial structures typically used in project finance, under different scenarios. Our results show that in all cases, the internal rate of return (IRR) for shareholders is higher when green bonds instead of bank loans are issued to finance investments. Additionally, in the vast majority of the scenarios, green bond financing results in higher average debt service coverage ratios. Consequently, our results suggest that green bond financing constitutes a strong financial incentive for sponsors, which can help align their objectives with those of public authorities.

Recent literature shows that market anomalies have significantly diminished, while research on market factors has largely improved the performance of asset pricing models. In this paper we study the extent to which data envelopment analysis (DEA) techniques can help improve the performance of multifactor models. Specifically, we test the explanatory power of the Fama and French three-factor model, combined with an additional factor based on DEA, on a sample of 2101 European equity funds, for the period from 2001 to 2016. Accordingly, we first form the fund portfolios that constitute our test assets and create the efficiency factor. Secondly, we estimate the prices of risk tied to the four factors using ordinary least squares (OLS) on a two-stage cross-sectional regression. Finally, we use the R-squared statistic estimated by generalized least squares (GLS), as well as the Gibbons Ross and Shanken test and the J-test for overidentifying restrictions in order to study the performance of the model, including and omitting the efficiency factor. The results show that the efficiency factor improves the performance of the model and reduces the pricing errors of the assets under consideration, which allows us to conclude that the efficiency index may be used as a factor in asset pricing models.