Monte Carlo Valuation of natural gas investments

This paper deals with the valuation of energy assets related to natural gas. In particular, we evaluate a baseload Natural Gas Combined Cycle (NGCC) power plant and an ancillary instalation, namely a Liquefied Natural Gas (LNG) facility, in a realistic setting; specifically, these investments enjoy a long useful life but require some non-negligible time to build. Then we focus on the valuation of several investment options again in a realistic setting. These include the option to invest in the power plant when there is uncertainty concerning the initial outlay, or the option's time to maturity, or the cost of CO2 emission permits, or when there is a chance to double the plant size in the future. Our model comprises three sources of risk. We consider uncertain gas prices with regard to both the current level and the long-run equilibrium level; the current electricity price is also uncertain. They all are assumed to show mean reversion. The two-factor model for natural gas price is calibrated using data from NYMEX NG futures contracts. Also, we calibrate the one-factor model for electricity price using data from the Spanish wholesale electricity market, respectively. Then we use the estimated parameter values alongside actual physical parameters from a case study to value natural gas plants. Finally, the calibrated parameters are also used in a Monte Carlo simulation framework to evaluate several American-type options to invest in these energy assets. We accomplish this by following the least squares MC approach.

Landscape valuation through discrete choice experiments: Current practice and future research reflections

This work has been presented in: V Conference AERNA, Faro (Portugal), 30 May 2012-1 June 2012 and IV Workshop on Valuation Methods in Agro-food and Environmental Economics, Castelldefels (Barcelona, Spain), 12 July 2012-13 July 2012.

Economic Valuation of Ecosystem Services: Conflicts in Classification

4 p.

Classifying Ecosystem Services for Economic Valuation: The case of forest water services

30 p.

Valuation of wind energy projects: A real options approach

27 p.

Global and local challenges for best practices in assessment. The 9th Conference on the International Test Commission. Book of abstracts

The 9th International Test Commission Conference (ITC) took place at the Miramar Palace in San Sebastian, Spain, between the 2nd and 5th of July, 2014. The Conference was titled, “Global and Local Challenges for Best Practices in Assessment.” The International Test Commission, ITC (www.intestcom.org), is an association of national psychological associations, test commissions, publishers, and other organizations, as well as individuals who are committed to the promotion of effective testing and assessment policies and to the proper development, evaluation, and uses of educational and psychological instruments. The ITC facilitates the exchange of information among members and stimulates their cooperation on problems related to the construction, distribution, and uses of psychological and educational tests and other psychodiagnostic tools. This volume contains the abstracts of the contributions presented at the 9th International Test Commission Conference. The four themes of the Conference were closely linked to the goals of the ITC: - Challenges and Opportunities in International Assessment. - Application of New Technoloogies and New Psychometric Models in Testing. - Standards and Guidelines for Best Testing Practices. - Testing in Multilingual and Multicultural Contexts.

Valuation of Wind Energy Projects: A Real Options Approach

We address the valuation of an operating wind farm and the finite-lived option to invest in it under different reward/support schemes: a constant feed-in tariff, a premium on top of the electricity market price (either a fixed premium or a variable subsidy such as a renewable obligation certificate or ROC), and a transitory subsidy, among others. Futures contracts on electricity with ever longer maturities enable market-based valuations to be undertaken. The model considers up to three sources of uncertainty: the electricity price, the level of wind generation, and the certificate (ROC) price where appropriate. When analytical solutions are lacking, we resort to a trinomial lattice combined with Monte Carlo simulation; we also use a two-dimensional binomial lattice when uncertainty in the ROC price is considered. Our data set refers to the UK. The numerical results show the impact of several factors involved in the decision to invest: the subsidy per MWh generated, the initial lump-sum subsidy, the maturity of the investment option, and electricity price volatility. Different combinations of variables can help bring forward investments in wind generation. One-off policies, e.g., a transitory initial subsidy, seem to have a stronger effect than a fixed premium per MWh produced.