Valuing Flexibility: The case of an Integrated Gasification Combined Cycle Power Plant

In this paper we analyze the valuation of options stemming from the flexibility in an Integrated Gasification Combined Cycle (IGCC) Power Plant. First we use as a base case the opportunity to invest in a Natural Gas Combined Cycle (NGCC) Power Plant, deriving the optimal investment rule as a function of fuel price and the remaining life of the right to invest. Additionally, the analytical solution for a perpetual option is obtained. Second, the valuation of an operating IGCC Power Plant is studied, with switching costs between states and a choice of the best operation mode. The valuation of this plant serves as a base to obtain the value of the option to delay an investment of this type. Finally, we derive the value of an opportunity to invest either in a NGCC or IGCC Power Plant, that is, to choose between an inflexible and a flexible technology, respectively. Numerical computations involve the use of one- and two-dimensional binomial lattices that support a mean-reverting process for the fuel prices. Basic parameter values refer to an actual IGCC power plant currently in operation.

Unions, Monetary Shocks and the Labour Market Cycle

Published as an article in: Economic Modelling, 2011, vol. 28, issue 3, pages 1140-1149.

Employment comovements at the sectoral level over the business cycle

This paper extends the technique suggested by den Haan (2000) to investigate contemporaneous as well as lead and lag correlations among economic data for a range of forecast horizons. The technique provides a richer picture of the economic dynamics generating the data and allows one to investigate which variables lead or lag others and whether the lead or lag pattern is short term or long term in nature. The technique is applied to monthly sectoral level employment data for the U.S. and shows that among the ten industrial sectors followed by the U.S. Bureau of Labor Statistics, six tend to lead the other four. These six have high correlations indicating that the structural shocks generating the data movements are mostly in common. Among the four lagging industries, some lag by longer intervals than others and some have low correlations with the leading industries indicating that these industries are partially influenced by structural shocks beyond those generating the six leading industries.

Cyclical Features of Uzawa-Lucas Endogenous Growth Model

This paper analyzes the cyclical properties of a generalized version of Uzawa-Lucas endogenous growth model. We study the dynamic features of different cyclical components of this model characterized by a variety of decomposition methods. The decomposition methods considered can be classified in two groups. On the one hand, we consider three statistical filters: the Hodrick-Prescott filter, the Baxter-King filter and Gonzalo-Granger decomposition. On the other hand, we use four model-based decomposition methods. The latter decomposition procedures share the property that the cyclical components obtained by these methods preserve the log-linear approximation of the Euler-equation restrictions imposed by the agent’s intertemporal optimization problem. The paper shows that both model dynamics and model performance substantially vary across decomposition methods. A parallel exercise is carried out with a standard real business cycle model. The results should help researchers to better understand the performance of Uzawa-Lucas model in relation to standard business cycle models under alternative definitions of the business cycle.

Activation of violaxanthin cycle in darkness is a common response to different abiotic stresses : a case study in Pelvetia canaliculata

Background: In the violaxanthin (V) cycle, V is de-epoxidized to zeaxanthin (Z) when strong light or light combined with other stressors lead to an overexcitation of photosystems. However, plants can also suffer stress in darkness and recent reports have shown that dehydration triggers V-de-epoxidation in the absence of light. In this study, we used the highly stress-tolerant brown alga Pelvetia canaliculata as a model organism, due to its lack of lutein and its non-photochemical quenching independent of the transthylakoidal-ΔpH, to study the triggering of the V-cycle in darkness induced by abiotic stressors. Results: We have shown that besides desiccation, other factors such as immersion, anoxia and high temperature also induced V-de-epoxidation in darkness. This process was reversible once the treatments had ceased (with the exception of heat, which caused lethal damage). Irrespective of the stressor applied, the resulting de-epoxidised xanthophylls correlated with a decrease in Fv/Fm, suggesting a common function in the down-regulation of photosynthetical efficiency. The implication of the redox-state of the plastoquinone-pool and of the differential activity of V-cycle enzymes on V-de-epoxidation in darkness was also examined. Current results suggest that both violaxanthin de-epoxidase (VDE) and zeaxanthin-epoxidase (ZE) have a basal constitutive activity even in darkness, being ZE inhibited under stress. This inhibition leads to Z accumulation. Conclusion: This study demonstrates that V-cycle activity is triggered by several abiotic stressors even when they occur in an absolute absence of light, leading to a decrease in Fv/Fm. This finding provides new insights into an understanding of the regulation mechanism of the V-cycle and of its ecophysiological roles.

Scenario Cluster Lagrangian Decomposition in two stage stochastic mixed 0-1 optimization

In this paper we introduce four scenario Cluster based Lagrangian Decomposition (CLD) procedures for obtaining strong lower bounds to the (optimal) solution value of two-stage stochastic mixed 0-1 problems. At each iteration of the Lagrangian based procedures, the traditional aim consists of obtaining the solution value of the corresponding Lagrangian dual via solving scenario submodels once the nonanticipativity constraints have been dualized. Instead of considering a splitting variable representation over the set of scenarios, we propose to decompose the model into a set of scenario clusters. We compare the computational performance of the four Lagrange multiplier updating procedures, namely the Subgradient Method, the Volume Algorithm, the Progressive Hedging Algorithm and the Dynamic Constrained Cutting Plane scheme for different numbers of scenario clusters and different dimensions of the original problem. Our computational experience shows that the CLD bound and its computational effort depend on the number of scenario clusters to consider. In any case, our results show that the CLD procedures outperform the traditional LD scheme for single scenarios both in the quality of the bounds and computational effort. All the procedures have been implemented in a C++ experimental code. A broad computational experience is reported on a test of randomly generated instances by using the MIP solvers COIN-OR and CPLEX for the auxiliary mixed 0-1 cluster submodels, this last solver within the open source engine COIN-OR. We also give computational evidence of the model tightening effect that the preprocessing techniques, cut generation and appending and parallel computing tools have in stochastic integer optimization. Finally, we have observed that the plain use of both solvers does not provide the optimal solution of the instances included in the testbed with which we have experimented but for two toy instances in affordable elapsed time. On the other hand the proposed procedures provide strong lower bounds (or the same solution value) in a considerably shorter elapsed time for the quasi-optimal solution obtained by other means for the original stochastic problem.

Data Revisions in the Estimation of DSGE Models

Revisions of US macroeconomic data are not white-noise. They are persistent, correlated with real-time data, and with high variability (around 80% of volatility observed in US real-time data). Their business cycle effects are examined in an estimated DSGE model extended with both real-time and final data. After implementing a Bayesian estimation approach, the role of both habit formation and price indexation fall significantly in the extended model. The results show how revision shocks of both output and inflation are expansionary because they occur when real-time published data are too low and the Fed reacts by cutting interest rates. Consumption revisions, by contrast, are countercyclical as consumption habits mirror the observed reduction in real-time consumption. In turn, revisions of the three variables explain 9.3% of changes of output in its long-run variance decomposition.

Biotic vs. Abiotic Control of Decomposition: A Comparison of the Effects of Simulated Extinctions and Changes in Temperature

The loss of species is known to have significant effects on ecosystem functioning, but only recently has it been recognized that species loss might rival the effects of other forms of environmental change on ecosystem processes. There is a need for experimental studies that explicitly manipulate species richness and environmental factors concurrently to determine their relative impacts on key ecosystem processes such as plant litter decomposition. It is crucial to understand what factors affect the rate of plant litter decomposition and the relative magnitude of such effects because the rate at which plant litter is lost and transformed to other forms of organic and inorganic carbon determines the capacity for carbon storage in ecosystems and the rate at which greenhouse gasses such as carbon dioxide are outgassed. Here we compared how an increase in water temperature of 5 degrees C and loss of detritivorous invertebrate and plant litter species affect decomposition rates in a laboratory experiment simulating stream conditions. Like some prior studies, we found that species identity, rather than species richness per se, is a key driver of decomposition, but additionally we showed that the loss of particular species can equal or exceed temperature change in its impact on decomposition. Our results indicate that the loss of particular species can be as important a driver of decomposition as substantial temperature change, but also that predicting the relative consequences of species loss and other forms of environmental change on decomposition requires knowledge of assemblages and their constituent species' ecology and ecophysiology.

Biotic vs. Abiotic Control of Decomposition: A Comparison of the Effects of Simulated Extinctions and Changes in Temperature

The loss of species is known to have significant effects on ecosystem functioning, but only recently has it been recognized that species loss might rival the effects of other forms of environmental change on ecosystem processes. There is a need for experimental studies that explicitly manipulate species richness and environmental factors concurrently to determine their relative impacts on key ecosystem processes such as plant litter decomposition. It is crucial to understand what factors affect the rate of plant litter decomposition and the relative magnitude of such effects because the rate at which plant litter is lost and transformed to other forms of organic and inorganic carbon determines the capacity for carbon storage in ecosystems and the rate at which greenhouse gasses such as carbon dioxide are outgassed. Here we compared how an increase in water temperature of 5 degrees C and loss of detritivorous invertebrate and plant litter species affect decomposition rates in a laboratory experiment simulating stream conditions. Like some prior studies, we found that species identity, rather than species richness per se, is a key driver of decomposition, but additionally we showed that the loss of particular species can equal or exceed temperature change in its impact on decomposition. Our results indicate that the loss of particular species can be as important a driver of decomposition as substantial temperature change, but also that predicting the relative consequences of species loss and other forms of environmental change on decomposition requires knowledge of assemblages and their constituent species' ecology and ecophysiology

Occupational exposure to nano-TiO2 in the life cycle steps of new depollutant mortars used in construction

The present work is focused on the measurement of workers exposure to nano-TiO2 in the life cycle steps of depollutant mortars. It has been done in the framework of the SCAFFOLD project, which aims at the management of potential risks arising from the use of manufactured nanomaterials in construction. Main findings can be summarized as follows: (1) The occupational exposure to nano-TiO2 is below 0.3 mg/m(3) for all measured scenarios. The highest concentrations were measured during the cleaning task (in the nano-TiO2 manufacturing process) and during the application (spraying) of depollutant coatings on a wall. (2) It was found a high release of particles above the background in several tasks as expected due to the nature of the activities performed. The maximum concentration was measured during drilling and during adding powder materials (mean total particle concentration up to 5.591E+04 particles/cm(3) and 5.69E+04 particles/cm(3)). However, considering data on total particle concentration released, no striking differences have been observed when tasks have been performed using conventional materials in the sector (control) and when using materials doped with nano-objects.