How long might the younger-old live: A predictive model

Life expectancy amongst older people in industrialised countries has been improving over an extended period and still continues to do so. This has ramifications for providers of services to this population, thus necessitating a level of forward planning. Predictive models of remaining life expectancy for older age groups can assist long-term planning processes. This paper presents an extrapolative approach to forecasting remaining life expectancy. Based on logistic modelling of historic mortality and survivorship for the “younger-old” male population of England and Wales over the period 1970-2005, a parsimonious two-parameter model is derived. This model provides a close correspondence to published period life table data. Trends in these parameters are then fitted and extrapolated to enable projections of life expectancy up to 40 years into the future. Alternative assumptions are used to determine a range of future life expectancy trajectories for a 65-year-old male. Occupational pension scheme provision is identified as an area of particular concern in the context of increasing longevity. As an illustration, the life expectancy trajectories are combined with differing discount rate assumptions to generate a number of alternative pension liability scenarios for the extrapolation period.     

Will tighter futures price limits decrease hedge effectiveness?

The events triggered by the Global Financial Crisis (GFC) have led to calls for the regulation of financial markets. Given that regulation may involve opportunity costs, this paper examines whether tighter futures price limits can reduce the effectiveness of a futures hedge. We propose a new model that uncovers the underlying spot-futures dynamics when futures prices are subject to limits. We use the model to determine the maximum number of limit days that can occur before minimum variance hedging outcomes are adversely affected. Application of this model to the US soybean and corn markets reveals that existing limits do not reduce hedge effectiveness. If the frequency of limit days increases from current levels of 1% to approximately 3–4%, conventional hedging approaches will experience economically and statistically significant increases in portfolio variance. These results are important for hedgers, clearing houses and regulators in light of the recent calls for derivatives regulation.     

Consuming in one's mind: An exploration

Consumer research generally focuses on the consumption of tangible objects and experiences, which are concrete. However, consumers often consume in their minds by fantasizing, dreaming, or imagining that they possess some desired object or that they are living some experience. In this article, the term consumption dreams is used to refer to mental representations of consumption objects that consumers desire and experiences that they want to realize. These are distinguished from uncontrolled mental activities that occur when asleep. The results of two exploratory studies that examined consumption dreams are presented. In the first study, five adult consumers were asked about their most important consumption dream, as well as the factors that influenced this dream and the behaviors that ensued. The second study consisted of a survey of 195 adult consumers where the determinants and consequences of consumption dreaming were probed. It was found that indulging in consumption dreaming is a common activity among most consumers and that consumption dreams and their characteristics depend on general as well as dream‐based variables. In addition, those dreams were found to impact on several consumer behaviors. A causal model involving a subset of the variables examined in this exploratory research was put forward and tested with the survey data. The results showed the value of a proposed conceptual framework to generate theoretical propositions about consumption dreaming. © 2005 Wiley Periodicals, Inc.     

An integrated tax-subsidy policy for carbon emission reduction

A carbon tax is often cited by economists as an effective instrument to mitigate greenhouse gas emissions, but there is little political interest in the United States. In light of this political unpopularity, we develop and examine a net-revenue constrained carbon tax and subsidy program. The optimal revenue constrained tax and subsidy schedule based on our utility maximization model taxes energy sources with high emissions to energy price ratio, and subsidizes sources with low emissions to energy price ratios. This approach may be more palatable than a traditional carbon tax because it can change the relative price of low and high emissions energy sources while providing a mechanism to limit net tax increases and energy price increases. We find that a constrained tax/subsidy program provides welfare gains relative to a no-tax scenario. Welfare gains are estimated to be 1% and 36% of the welfare gains from a Pigouvian tax for the motor fuels industry and electric power industry, respectively. In contrast, subsidies for low-emitting energy sources funded from general tax funds rather than from high-emission energy tax revenues lead to welfare decreases substantially below our proposed tax/subsidy policy approach.     

Exchange traded contracts for difference: Design,pricing, and effects

Contracts for Difference (CFDs) are a significant financial innovation in the design of futures contracts. Over‐the‐counter trading in the UK is significant and has created controversy, but there is no published academic research into the design, pricing, and effects of CFDs. This study analyzes CFD contract design and pricing. It uses a unique database of trades and quotes on exchange traded equity CFDs introduced by the Australian Securities Exchange to test theoretical pricing relationships, and draws out implications for successful design and trading arrangements for the introduction of new derivative contracts. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark     

REVERSE REGRESSIONS AND LONG‐HORIZON FORECASTING

Long‐horizon predictive regressions in finance pose formidable econometric problems when estimated using available sample sizes. Hodrick in 1992 proposed a remedy that is based on running a reverse regression of short‐horizon returns on the long‐run mean of the predictor. Unfortunately, this only allows the null of no predictability to be tested, and assumes stationary regressors. In this paper, we revisit long‐horizon forecasting from reverse regressions, and argue that reverse regression methods avoid serious size distortions in long‐horizon predictive regressions, even when there is some predictability and/or near unit roots. Meanwhile, the reverse regression methodology has the practical advantage of being easily applicable when there are many predictors. We apply these methods to forecasting excess bond returns using the term structure of forward rates, and find that there is indeed some return forecastability. However, confidence intervals for the coefficients of the predictive regressions are about twice as wide as those obtained with the conventional approach to inference. We also include an application to forecasting excess stock returns. Copyright © 2011 John Wiley & Sons, Ltd.