Alessandra Dalla Valle

Oil and gas depletion: Diffusion models and forecasting under strategic intervention

Abstract.Crude oil and natural gas depletion may be modelled by a diffusion process based upon a constrained life-cycle. Here we consider the Generalized Bass Model. The choice is motivated by the realistic assumption that there is a self-evident link between oil and gas extraction and the spreading of the modern technologies in wide areas such as transport, heating, cooling, chemistry and hydrocarbon fuels consumption. Such a model may include deterministic or semi-deterministic regulatory interventions. Statistical analysis is based upon nonlinear methodologies and more flexible autoregressive structure of residuals. The technical aim of this paper is to outline the meaningful hierarchy existing among the components of such diffusion models. Statistical effort in residual component analysis may be read as a significant confirmation of a well-founded diffusion process under rare but strong deterministic shocks. Applications of such ideas are proposed with reference to world oil and gas production data and to particular regions such as mainland U.S.A., U.K., Norway and Alaska. The main results give new evidence in time-peaks location and in residual

A test for the hypothesis of skew-normality in a population

90\%

Pre-launch forecasting of a pharmaceutical drug

times to depletion.

Diffusion of nuclear energy in some developing countries

One of the extensions of the normal distribution is the skew-normal distribution, which through the variations of a shape parameter regulates the skewness of the distribution, allowing for a continuous variation from normality to non-normality. This article introduces a test for the hypothesis of skew-normality in a population, and it is based on the Anderson–Darling goodness-of-fit test.One of the extensions of the normal distribution is the skew-normal distribution, which through the variations of a shape parameter regulates the skewness of the distribution, allowing for a continuous variation from normality to non-normality. This article introduces a test for the hypothesis of skew-normality in a population, and it is based on the Anderson–Darling goodness-of-fit test.

The Skew-Normal Distribution

Purpose The emergence of a pharmaceutical drug as a late entrant in a homogeneous category is a relevant issue for strategy implementation in the pharmaceutical industry. This paper aims to suggest a methodology for making pre-launch forecasts with a complete lack of information for a late entrant. Design/methodology/approach The diffusion process of the emerging entrant is estimated using the diffusion dynamics of pre-existing drugs, after an appropriate assessment of the drug’s entrance point. The authors’ methodology is applied to study the late introduction of a pharmaceutical drug in Italy within the category of ranitidine. Historical data of seven already active drugs in the category are used to assess and estimate ex ante the dynamics of a late entrant (Ulkobrin). Findings The results of applying the procedure to the ranitidine market reveal a high degree of accuracy between the ex post observed values of the late entrant and its ex ante mean predicted trajectory. Moreover, the assessed launch date corresponds to the actual date. Research limitations/implications The category has to be homogeneous to ensure a high degree of similarity among the existing drugs and the late entrant. For this reason, radical innovations cannot be forecast with this methodology. Originality/value The proposed approach contributes to the still challenging research field of pre-launch forecasting by estimating the dynamic features of a homogeneous category and exploiting them for forecasting purposes.