The referendum incentive compatibility hypothesis: Some new results using information messages

We report results from a laboratory experiment that allows us to test the incentive compatibility hypothesis of hypothetical referenda used in CV studies through the public or private provision of information messages. One of the main methodological issues about hypothetical markets regards whether people behave differently when bidding for a public good through casting a ballot vote than when they are privately purchasing an equivalent good. This study tried to address the core of this issue by using a good that can be traded both as private and public: information messages. This allows the elimination of confounding effects associated with the specific good employed. In our case information dispels some of the uncertainty about a potential gain from a gamble. So, the approximate value of the message can be inferred once the individual measure of risk aversion is known. Decision tasks are then framed in a systematic manner according to the hypothetical vs real nature of the decision and the public vs private nature of the message. A sample of 536 university students across three countries (I, UK and NZ) participated into this lab experiment. The chosen countries reflect diversity in exposure to the practice of advisory (NZ) and abrogative (Italy) referenda, with the UK not having any exposure to it. Under private provision the results show that the fraction of participants unwilling to buy information is slightly higher in the real treatment than in the hypothetical one. Under public provision, instead, there is no statistical difference between real and hypothetical settings, confirming in part the finding of previous researchers. A verbal protocol analysis of the thought processes during choice highlights that public provision of information systematically triggers concerns and motivations different from those arising under the private provision setting. These findings suggest that the incentive compatibility of public referenda is likely to rely more on affective and psychological factors than on the strategic behaviour assumptions theorised by economists

Improving Parametric Mortgage Prepayment Models with Non-parametric Kernel Regression

Developing a good prepayment model is a central task in the valuation of mortgages and mortgage-backed securities but conventional parametric models often have bad out-of-sample predictive ability. A likely explanation is the highly non-linear nature of the prepayment function. Non-parametric techniques are much better at detecting non-linearity and multivariate interaction. This article discusses how non-parametric kernel regression may be applied to loan level event histories to produce a better parametric model. By utilizing a parsimonious specification, a model can be produced that practitioners can use in valuation routines based on Monte Carlo interest rate simulation.

Random Time Forward Starting Options

We introduce a natural generalization of the forward-starting options, first discussed by M. Rubinstein. The main feature of the contract presented here is that the strike-determination time is not fixed ex-ante, but allowed to be random, usually related to the occurrence of some event, either of financial nature or not. We will call these options {\bf Random Time Forward Starting (RTFS)}. We show that, under an appropriate "martingale preserving" hypothesis, we can exhibit arbitrage free prices, which can be explicitly computed in many classical market models, at least under independence between the random time and the assets' prices. Practical implementations of the pricing methodologies are also provided. Finally a credit value adjustment formula for these OTC options is computed for the unilateral counterparty credit risk.Comment: 19 pages, 1 figur

Does Stock Return Predictability Affect ESO Fair Value?

Executive Stock Options (ESOs) are modified American options that cannot be valued using standard methods. With a few exceptions, the literature has discussed the ESO fair value by assuming unpredictable stock returns which are not supported by the available empirical evidence. In this paper we obtain the fair value of American ESOs when stock returns are predictable and, specifically, driven by the trending Ornstein-Uhlenbeck process of Lo and Wang (1995). We solve the executive’s portfolio allocation problem for a simple buy-and-hold strategy when his wealth can be distributed between a risk-free asset and a market portfolio. This problem is jointly solved with the executive’s optimal exercise policy. We find that executives tend to wait longer the higher the predictability, independently of the composition of executive’s asset menu. We have also analyzed the implications under the FAS123R proposals for the ESO fair value and found that, even for low autocorrelations, there is a meaningful mispricing when unpredictable returns are erroneously assumed.Executive Stock Options; Risk Aversion; Undiversification; Predictability; FAS123R

‘Yes-in-my-backyard’: Spatial differences in the valuation of forest services and local co-benefits for carbon markets in México

Forests provide many and large benefits, including cost-efficient climate change mitigation. However international carbon markets have not stimulated the demand for forestry offsets. Domestic market-mechanisms are emerging inmany countries and forests could be highly valued through these policies asmost of the benefits produced by forests are enjoyed locally. Here, a choice experiment explores drivers of valuation and willingness to pay for forest carbon services in voluntary markets in Mexico by comparing the valuation of citizens from four regions to test geographical preference for projects (n = 645). Findings from multinomial-logit models show valuation of forest carbon services is transferable and citizens would pay more for offsets from projects closer to their homes. Proximate forests provide a range of co-benefits to local users, including environmental services and opportunities for recreation. Factors related to valuation include sense of responsibility, previous knowledge of carbon emissions, previous visits to the sites, regional identification and the valuation of local environmental services (e.g. improvements in local air quality). Knowledge of spatial heterogeneity in valuation of the use of forest services can help to design market-based instruments by identifying highly valued areas for environmental services programs and carbon markets