Accommodating energy price volatility in life cycle cost analysis of asphalt pavements

Energy price is related to more than half of the total life cycle cost of asphalt pavements. Furthermore, the fluctuation related to price of energy has been much higher than the general inflation and interest rate. This makes the energy price inflation an important variable that should be addressed when performing life cycle cost (LCC) studies re- garding asphalt pavements. The present value of future costs is highly sensitive to the selected discount rate. Therefore, the choice of the discount rate is the most critical element in LCC analysis during the life time of a project. The objective of the paper is to present a discount rate for asphalt pavement projects as a function of interest rate, general inflation and energy price inflation. The discount rate is defined based on the portion of the energy related costs during the life time of the pavement. Consequently, it can reflect the financial risks related to the energy price in asphalt pavement projects. It is suggested that a discount rate sensitivity analysis for asphalt pavements in Sweden should range between –20 and 30%.

An Analysis of Colombian Power Market Price Behavior from an Industrial Organization Perspective

We analyze the behavior of spot prices in the Colombian wholesale power market, using a series of models derived from industrial organization theory -- We first create a Cournot-based model that simulates the strategic behavior of the market-leader power generators, which we use to estimate two industrial organization variables, the Index of Residual Demand and the Herfindahl-Hirschman Index (HHI) -- We use these variables to create VAR models that estimate spot prices and power market impulse-response relationships -- The results from these models show that hydroelectric generators can use their water storage capability strategically to affect off-peak prices primarily, while the thermal generators can manage their capacity strategically to affect on-peak prices -- In addition, shocks to the Index of Residual Capacity and to the HHI cause spot price fluctuations, which can be interpreted as the generators´ strategic response to these shocks

A demand-driven analysis of tourist accommodation price: A quantile regression of room bookings

Tourist accommodation expenditure is a widely investigated topic as it represents a major contribution to the total tourist expenditure. The identification of the determinant factors is commonly based on supply-driven applications while little research has been made on important travel characteristics. This paper proposes a demand-driven analysis of tourist accommodation price by focusing on data generated from room bookings. The investigation focuses on modeling the relationship between key travel characteristics and the price paid to book the accommodation. To accommodate the distributional characteristics of the expenditure variable, the analysis is based on the estimation of a quantile regression model. The findings support the econometric approach used and enable the elaboration of relevant managerial implications.

A hybrid commodity price-forecasting model applied to the sugar-alcohol sector

Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

Phenolic composition of South American red wines classified according to their antioxidant activity, retail price and sensory quality

In this study, 73 South American red wines (Vitis vinifera) from 5 varietals were classified based on sensory quality, retail price and antioxidant activity and characterised in relation to their phenolic composition. ORAC and DPPH assays were assessed to determine the antioxidant activity, and sensory analysis was conducted by seven professional tasters using the Wine Spirits Education Trust`s structured scales. The use of multivariate statistical techniques allowed the identification of wines with the best combination of sensory characteristics, price and antioxidant activity. The most favourable varieties were Malbec, Cabernet Sauvignon, and Syrah produced in Chile and Argentina. Conversely, Pinot Noir wines displayed the lowest sensory characteristics and antioxidant activity. These results suggest that the volatile compounds may be the main substances responsible for differentiating red wines on the basis of sensory evaluation. (C) 2011 Elsevier Ltd. All rights reserved.

A simple analysis of the US emission permits auctions

We examine a stylized version of EPA auctions when agents know the list of values of sellers and buyers. There are inefficient equilibria where no goods are traded and efficient equilibria where all exchange occurs at a uniform price. We also provide examples under incomplete information when the uniform price equilibrium holds and when it does not hold. (C) 1999 Elsevier Science S.A. All rights reserved. JEL classification: D44; Q29.

Qualitative assessment of stock prices listed on the Sao Paulo stock exchange: An approach from the perspective of homogeneity analysis

The stock market suffers uncertain relations throughout the entire negotiation process, with different variables exerting direct and indirect influence on stock prices. This study focuses on the analysis of certain aspects that may influence these values offered by the capital market, based on the Brazil Index of the Sao Paulo Stock Exchange (Bovespa), which selects 100 stocks among the most traded on Bovespa in terms of number of trades and financial volume. The selected variables are characterized by the companies` activity area and the business volume in the month of data collection, i.e. April/2007. This article proposes an analysis that joins the accounting view of the stock price variables that can be influenced with the use of multivariate qualitative data analysis. Data were explored through Correspondence Analysis (Anacor) and Homogeneity Analysis (Homals). According to the research, the selected variables are associated with the values presented by the stocks, which become an internal control instrument and a decision-making tool when it comes to choosing investments.

Tests for the hysteresis hypothesis in Brazilian industrialized exports: A threshold cointegration analysis

This paper examines the hysteresis hypothesis in the Brazilian industrialized exports using a time series analysis. This hypothesis finds an empirical representation into the nonlinear adjustments of the exported quantity to relative price changes. Thus, the threshold cointegration analysis proposed by Balke and Fomby [Balke, N.S. and Fomby, T.B. Threshold Cointegration. International Economic Review, 1997; 38; 627-645.] was used for estimating models with asymmetric adjustment of the error correction term. Amongst sixteen industrial sectors selected, there was evidence of nonlinearities in the residuals of long-run relationships of supply or demand for exports in nine of them. These nonlinearities represent asymmetric and/or discontinuous responses of exports to different representative measures of real exchange rates, in addition to other components of long-run demand or supply equations. (C) 2007 Elsevier B.V. All rights reserved.

Forward-looking versus recursive-dynamic modeling in climate policy analysis: A comparison

This paper develops a multi-regional general equilibrium model for climate policy analysis based on the latest version of the MIT Emissions Prediction and Policy Analysis (EPPA) model. We develop two versions so that we can solve the model either as a fully inter-temporal optimization problem (forward-looking, perfect foresight) or recursively. The standard EPPA model on which these models are based is solved recursively, and it is necessary to simplify some aspects of it to make inter-temporal solution possible. The forward-looking capability allows one to better address economic and policy issues such as borrowing and banking of GHG allowances, efficiency implications of environmental tax recycling, endogenous depletion of fossil resources, international capital flows, and optimal emissions abatement paths among others. To evaluate the solution approaches, we benchmark each version to the same macroeconomic path, and then compare the behavior of the two versions under a climate policy that restricts greenhouse gas emissions. We find that the energy sector and CO(2) price behavior are similar in both versions (in the recursive version of the model we force the inter-temporal theoretical efficiency result that abatement through time should be allocated such that the CO(2) price rises at the interest rate.) The main difference that arises is that the macroeconomic costs are substantially lower in the forward-looking version of the model, since it allows consumption shifting as an additional avenue of adjustment to the policy. On the other hand, the simplifications required for solving the model as an optimization problem, such as dropping the full vintaging of the capital stock and fewer explicit technological options, likely have effects on the results. Moreover, inter-temporal optimization with perfect foresight poorly represents the real economy where agents face high levels of uncertainty that likely lead to higher costs than if they knew the future with certainty. We conclude that while the forward-looking model has value for some problems, the recursive model produces similar behavior in the energy sector and provides greater flexibility in the details of the system that can be represented. (C) 2009 Elsevier B.V. All rights reserved.

Cost-effectiveness analysis of routine rotavirus vaccination in Brazil

Objective. The objective of this study was to conduct a cost-effectiveness analysis of a universal rotavirus vaccination program among children : 5 years of age in Brazil. Methods. Considering a hypothetical annual cohort of approximately 3 300 000 newborns followed over 5 years, a decision-tree model was constructed to examine the possible clinical and economic effects of rotavirus infection with and without routine vaccination of children. Probabilities and unit costs were derived from published research and national administrative data. The impact of different estimates for key parameters was studied using sensitivity analysis. The analysis was conducted from both healthcare system and societal perspectives. Results. The vaccination program was estimated to prevent approximately 1735 351 (54%) of the 3 210 361 cases of rotavirus gastroenteritis and 703 (75%) of 933 rotavirus-associated deaths during the 5-year period. At a vaccine price of 18.6 Brazilian reais (R$) per dose, this program would cost R$121 673 966 and would save R$38 536 514 in direct costs to the public healthcare system and R$71 778 377 in direct and indirect costs to society. The program was estimated to cost R$1 028 and R$1 713 per life-years saved (LYS)from the societal and healthcare system perspectives, respectively. Conclusions. Universal rotavirus vaccination was a cost-effective strategy for both perspectives. However, these findings are highly sensitive to diarrhea incidence rate, proportion of severe cases, vaccine coverage, and vaccine price.

Cost-effectiveness analysis of universal childhood vaccination against varicella in Brazil

This study conducts a cost-effectiveness analysis of a childhood universal varicella vaccination program in Brazil. An age and time-dependent dynamic model was developed to estimate the incidence of varicella for 30 years. Assuming a single-dose schedule; vaccine efficacy of 85% and coverage of 80%, the program could prevent 74,422,058 cases and 2905 deaths. It would cost R$ 3,178,396,110 and save R$ 660,076,410 to the society and R$ 365,602,305 to the healthcare system. The program is cost-effective (R$ 14,749 and R$ 16,582 per life-year saved under the societal and the healthcare system`s perspective, respectively). The program`s cost-effectiveness is highly sensitive to the vaccine price and number of doses. (C) 2008 Elsevier Ltd. All rights reserved.

Investigating technical and scale efficiencies of Australian universities through data envelopment analysis

Performance indicators in the public sector have often been criticised for being inadequate and not conducive to analysing efficiency. The main objective of this study is to use data envelopment analysis (DEA) to examine the relative efficiency of Australian universities. Three performance models are developed, namely, overall performance, performance on delivery of educational services, and performance on fee-paying enrolments. The findings based on 1995 data show that the university sector was performing well on technical and scale efficiency but there was room for improving performance on fee-paying enrolments. There were also small slacks in input utilisation. More universities were operating at decreasing returns to scale, indicating a potential to downsize. DEA helps in identifying the reference sets for inefficient institutions and objectively determines productivity improvements. As such, it can be a valuable benchmarking tool for educational administrators and assist in more efficient allocation of scarce resources. In the absence of market mechanisms to price educational outputs, which renders traditional production or cost functions inappropriate, universities are particularly obliged to seek alternative efficiency analysis methods such as DEA.