A structural model for green bonds is developed to explain the formation and dynamics of green bond prices and to address the issue of the so-called ‘greenium’, that is, the difference between the yields on a conventional bond and a green bond with the same characteristics. We provide answers to the following questions: What are the determinants of the green bond value? Do green bonds enhance the credit quality of the issuer? Are green bonds a relatively cheap tool to fund sustainable investments? We also study the effect of investors' environmental concern on portfolio allocation. Our results have direct policy implications and suggest that an improvement in credit quality could ultimately lead to a lower cost of capital for green bond issuers and that governmental tax-based incentives and an increase in investors' green awareness play a significant role in scaling up the green bonds market.

The purpose of the paper is to analyse the impact of the tax system on the ®rm's incentives to invest and disinvest in an uncertain environment. This paper follows the real options approach, which allows us to investigate the value to a ®rm of waiting to invest and/or disinvest, when payoffs are stochastic and investments partially reversible. The implications for the magnitude and directions of the effects of tax policy are studied; also the case of tax policy uncertainty is examined. I. I n t ro d u c t i o nIn this paper we analyse the impact of the tax system on the ®rm's incentives to invest and disinvest in an uncertain environment. The paper follows the real options approach, which allows us to investigate the value to a ®rm of waiting to invest and/or disinvest, when payoffs are stochastic and investments are irreversible to some degree.Making an investment involves relinquishing an option to invest in future. An opportunity to make a real investment is a call option on a stock that consists of the capital in place, and making the investment is like exercising the option, where the cost of the investment is the strike price of the option. However, exercising the option at the instant its intrinsic value becomes positive is not optimal, because the option has a value in waiting: if uncertainty is low, the value in waiting will be little, while, if uncertainty is high, setting a high trigger may be more convenient. As a result, the optimal time to kill the option is well after the point at which expected discounted future cash¯ow equals the cost of investment.Abandoning the investment involves giving up an option to disinvest in future. In this case, disinvesting is like exercising a put option, where the resale price of capital is the strike price of the option. The optimal time to give up such an option is well before the point at which expected discounted future cash¯ow equals the cost of investment.A substantial number of papers have been developed within the real options approach. Brennan and Schwartz (1985) apply options analysis to a natural resource extraction problem. McDonald and Siegel (1986) and Dixit (1989) price option values associated with à The paper has been presented at the 1999 European Economic Association Meeting: I wish to thank the participants for their helpful comments. Many thanks especially to two anonymous referees for their insightful comments.

This paper addresses the following unresolved questions from the perspective of ambiguity theory: Why do some firms issue equity instead of debt? Why did most firms retain their cash holdings instead of distributing them as dividends in recent times? How do firms change their financing policies during a period of severe financial constraints and ambiguity, or when facing the threat of an unpredictable financial crisis? We analyze how the values of the firm's equity and debt are affected by ambiguity. We also show that cash holdings are retained longer if the investors' ambiguity aversion bias is sufficiently large, while cash holdings become less attractive when the combined impact of ambiguity and ambiguity aversion is relatively low.

An optimal weighting scheme is proposed to construct economic, political and financial risk indices in emerging markets using an approach that relies on consistent tests for stochastic dominance efficiency. These tests are considered for a given risk index with respect to all possible indices constructed from a set of individual risk factors. The test statistics and the estimators are computed using mixed integer programming methods. We derive an economic, political and financial risk ranking of emerging countries. Finally, an overall risk index is constructed. One main result is that the financial risk is the leading contributor to sovereign risk in emerging markets followed by the economic and political risk.JEL Classifications: C12; C13; C14; C15; G01