Preference Uncertainty in Non-Market Valuation: A Fuzzy Approach

In this article, we consider uncertain preferences for non-market goods, but we move away from a probabilistic representation of uncertainty and propose the use of fuzzy contingent valuation. We assume that a decision maker never fully knows her own utility function and we treat utility as a fuzzy number. The methodology is illustrated using data on forest valuation in Sweden. Fuzzy contingent valuation provides estimates of resource value in the form of a fuzzy number and includes estimates obtained using a standard probabilistic approach.     

Bottom-up sales forecasting through scenario analysis

A simple but effective bottom-up sales forecasting system, developed for a large New Zealand printing and packaging company, is described and analyzed. A central feature of the method is a procedure called “scenario analysis,” enabling the forecaster to incorporate in a systematic manner a large number of uncertainties in his or her assessment of the future.     

Persistence characteristics of the Chinese stock markets

Using advanced signal processing, this paper identifies the lack of ergodicity, stationarity, independence and the degree of persistence of the Shanghai (SHI) stock market and Shenzhen A shares (SZI) and B shares (SZBI), before and after the various deregulations and reregulations. Their lack of stationarity and ergodicity are ascribed to (1) the initial interventions in these stock markets by the Chinese government by imposing various daily price change limits, and (2) the changing trading styles, after the Chinese government left these equity markets to develop by themselves. The SHI, SZI, and SZBI are moderately persistent with Hurst exponents slightly greater than the Fickian 0.5 of the Geometric Brownian Motion. These stock markets were considerably more persistent before the deregulations, but they now behave more like Geometric Brownian Motions, i.e., efficiently. Thus, the Chinese stock markets are gradually and properly being integrated into one Chinese stock market. Our results are consistent with similar empirical findings from Latin American, European, and other Asian emerging financial markets.     

Marginal Valuation of Charismatic Species: Implications for Conservation

Most contingent valuation studies focus on total willingness to pay (WTP) as a measure of welfare change. For policy involving species preservation, however, it is important to distinguish between the benefits of preventing a species from going extinct and the benefits of preserving numbers above the minimum viable population (MVP) level. Once MVP is exceeded, marginal WTP becomes relevant. These propositions are illustrated for the case of one charismatic species whose management is much debated, minke whales in the Northeast Atlantic Ocean. It is shown that, for a given estimate of total preservation value, strict conservation and extinction can both be optimal. This finding highlights the importance of collecting marginal values in contingent valuation surveys.     

Achieving Attraction Accountability Through an Attraction Response Matrix

Whereas investments in new attractions continue to rise within the theme park industry, knowledge regarding the effects of new attractions on theme park performance and attendance remains scarce. In order to predict the impact of new attractions on the performance of European theme parks, this article presents an Attraction Response Matrix (ARM). The Attraction Response Matrix offers an integrated framework in which research into the effects of new attractions can take place in a systematic manner. The ARM attempts to transform post priori knowledge into a priori knowledge by better understanding the impact of a new attraction and its' mediating causes. The main premise of the ARM is: “in situation A, attraction B will most likely have effect C on target audience D.” By performing research into the relevant effects within certain cells of the ARM and consecutively investigating the relationship between the various cells, a better insight will be gained in the working of new attractions. ARM is based on an extensive ZMET study conducted in The Netherlands.     

Calibration of agricultural risk programming models using positive mathematical programming

Mathematical programming models of farmers’ cropping decisions must first be calibrated before they can be used to examine agricultural producer responses to policy changes. In this paper, we compare three calibration approaches for disentangling the risk parameter from the parameters of the cost function: one assumes a logarithmic utility function, while the others employ an exponential utility function. Historical crop insurance data for southern Alberta, Canada, are used to assess the calibration performance of the three approaches, and sensitivity analysis is implemented to test whether the changes in the optimal land allocation caused by the changes in the values of the parameters are practically reasonable. Only one of the three models is of practical use for policy analysis because it can recover the true values of the parameters and the results of sensitivity analysis are reasonable.     

Boreal Forest Carbon Sequestration Strategies: A Case Study of the Little Red River Cree First Nation Land Tenures*

In this paper, creation of carbon offset and emission reduction credits are examined from the perspective of the Little Red River Cree Nation (LRRCN), a forest tenure holder in northern Alberta. Carbon credits are produced under three scenarios: (1) carbon uptake in forest ecosystems, with postharvest waste left on site; (2) carbon uptake in forests and products; and (3) carbon uptake in forests with harvested fiber used for energy production. A mathematical programming model is used to solve for the minimum prices that cause the LRRCN to include production of carbon credits in its forest management and post‐harvest processing strategies. If LRRCN is paid according to its costs of creating carbon credits, it will opt to use fiber for forest products as this provides the greatest earning potential. If LRRCN faces a fixed price for carbon credits, it will produce fiber for generating electricity in lieu of coal as this strategy has the lowest average cost. However, when costs of feedstock transportation and construction of a power plant are taken into account, carbon uptake in biomass and forest products turn out to be more competitive.     

Long memory options: LM evidence and simulations

This paper demonstrates the impact of the observed financial market persistence or long term memory on European option valuation by simple simulation. Many empirical researchers have observed the non-Fickian degrees of persistence in the financial markets different from the Fickian neutral independence (i.i.d.) of the returns innovations assumption of Black–Scholes’ geometric Brownian motion assumption. Moreover, Elliott and van der Hoek [Elliott, R.J., van der Hoek, J., 2003. A general fractional white noise theory and applications to finance. Math. Finance 13, 301–330] provide a theoretical framework for incorporating these findings into the Black–Scholes risk-neutral valuation framework. This paper provides the first graphical demonstration why and how such long term memory phenomena change European option values and provides thereby a basis for informed long term memory arbitrage. By using a simple mono-fractal fractional Brownian motion, it is easy to incorporate the various degrees of persistence into the Black–Scholes pricing formula. Long memory options are of considerable importance in corporate remuneration packages, since stock options are written on a company’s own shares for long expiration periods. It makes a significant difference in the valuation when an option is “blue” or when it is “red.” For a proper valuation of such stock options, the degrees of persistence of the companies’ share markets must be precisely measured and properly incorporated in the warrant valuation, otherwise substantial pricing errors may result.