850 resultados para Fixed costs
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We analyze technology adoption decisions of manufacturing plants in response to government-sponsored energy audits. Overall, plants adopt about half of the recommended energy-efficiency projects. Using fixed effects logit estimation, we find that adoption rates are higher for projects with shorter paybacks, lower costs, greater annual savings, higher energy prices, and greater energy conservation. Plants are 40% more responsive to initial costs than annual savings, suggesting that subsidies may be more effective at promoting energy-efficient technologies than energy price increases. Adoption decisions imply hurdle rates of 50-100%, which is consistent with the investment criteria small and medium-size firms state they use. © 2003 Elsevier B.V. All rights reserved.
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The research and development costs of 68 randomly selected new drugs were obtained from a survey of 10 pharmaceutical firms. These data were used to estimate the average pre-tax cost of new drug development. The costs of compounds abandoned during testing were linked to the costs of compounds that obtained marketing approval. The estimated average out-of-pocket cost per new drug is 403 million US dollars (2000 dollars). Capitalizing out-of-pocket costs to the point of marketing approval at a real discount rate of 11% yields a total pre-approval cost estimate of 802 million US dollars (2000 dollars). When compared to the results of an earlier study with a similar methodology, total capitalized costs were shown to have increased at an annual rate of 7.4% above general price inflation.
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Seminal work by Weitzman (1974) revealed prices are preferred to quantities when marginal benefits are relatively flat compared to marginal costs. We extend this comparison to indexed policies, where quantities are proportional to an index, such as output. We find that policy preferences hinge on additional parameters describing the first and second moments of the index and the ex post optimal quantity level. When the ratio of these variables' coefficients of variation divided by their correlation is less than approximately two, indexed quantities are preferred to fixed quantities. A slightly more complex condition determines when indexed quantities are preferred to prices. Applied to climate change policy, we find that the range of variation and correlation in country-level carbon dioxide emissions and GDP suggests the ranking of an emissions intensity cap (indexed to GDP) compared to a fixed emission cap is not uniform across countries; neither policy clearly dominates the other.
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© 2012 by Oxford University Press. All rights reserved.This article reviews the extensive literature on R&D costs and returns. The first section focuses on R&D costs and the various factors that have affected the trends in real R&D costs over time. The second section considers economic studies on the distribution of returns in pharmaceuticals for different cohorts of new drug introductions. It also reviews the use of these studies to analyze the impact of policy actions on R&D costs and returns. The final section concludes and discusses open questions for further research.
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We estimate a carbon mitigation cost curve for the U.S. commercial sector based on econometric estimation of the responsiveness of fuel demand and equipment choices to energy price changes. The model econometrically estimates fuel demand conditional on fuel choice, which is characterized by a multinomial logit model. Separate estimation of end uses (e.g., heating, cooking) using the U.S. Commercial Buildings Energy Consumption Survey allows for exceptionally detailed estimation of price responsiveness disaggregated by end use and fuel type. We then construct aggregate long-run elasticities, by fuel type, through a series of simulations; own-price elasticities range from -0.9 for district heat services to -2.9 for fuel oil. The simulations form the basis of a marginal cost curve for carbon mitigation, which suggests that a price of $20 per ton of carbon would result in an 8% reduction in commercial carbon emissions, and a price of $100 per ton would result in a 28% reduction. © 2008 Elsevier B.V. All rights reserved.
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We conduct the first empirical investigation of common-pool resource users' dynamic and strategic behavior at the micro level using real-world data. Fishermen's strategies in a fully dynamic game account for latent resource dynamics and other players' actions, revealing the profit structure of the fishery. We compare the fishermen's actual and socially optimal exploitation paths under a time-specific vessel allocation policy and find a sizable dynamic externality. Individual fishermen respond to other users by exerting effort above the optimal level early in the season. Congestion is costly instantaneously but is beneficial in the long run because it partially offsets dynamic inefficiencies.
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The effectiveness of vaccinating males against the human papillomavirus (HPV) remains a controversial subject. Many existing studies conclude that increasing female coverage is more effective than diverting resources into male vaccination. Recently, several empirical studies on HPV immunization have been published, providing evidence of the fact that marginal vaccination costs increase with coverage. In this study, we use a stochastic agent-based modeling framework to revisit the male vaccination debate in light of these new findings. Within this framework, we assess the impact of coverage-dependent marginal costs of vaccine distribution on optimal immunization strategies against HPV. Focusing on the two scenarios of ongoing and new vaccination programs, we analyze different resource allocation policies and their effects on overall disease burden. Our results suggest that if the costs associated with vaccinating males are relatively close to those associated with vaccinating females, then coverage-dependent, increasing marginal costs may favor vaccination strategies that entail immunization of both genders. In particular, this study emphasizes the necessity for further empirical research on the nature of coverage-dependent vaccination costs.
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To maintain a strict balance between demand and supply in the US power systems, the Independent System Operators (ISOs) schedule power plants and determine electricity prices using a market clearing model. This model determines for each time period and power plant, the times of startup, shutdown, the amount of power production, and the provisioning of spinning and non-spinning power generation reserves, etc. Such a deterministic optimization model takes as input the characteristics of all the generating units such as their power generation installed capacity, ramp rates, minimum up and down time requirements, and marginal costs for production, as well as the forecast of intermittent energy such as wind and solar, along with the minimum reserve requirement of the whole system. This reserve requirement is determined based on the likelihood of outages on the supply side and on the levels of error forecasts in demand and intermittent generation. With increased installed capacity of intermittent renewable energy, determining the appropriate level of reserve requirements has become harder. Stochastic market clearing models have been proposed as an alternative to deterministic market clearing models. Rather than using a fixed reserve targets as an input, stochastic market clearing models take different scenarios of wind power into consideration and determine reserves schedule as output. Using a scaled version of the power generation system of PJM, a regional transmission organization (RTO) that coordinates the movement of wholesale electricity in all or parts of 13 states and the District of Columbia, and wind scenarios generated from BPA (Bonneville Power Administration) data, this paper explores a comparison of the performance between a stochastic and deterministic model in market clearing. The two models are compared in their ability to contribute to the affordability, reliability and sustainability of the electricity system, measured in terms of total operational costs, load shedding and air emissions. The process of building the models and running for tests indicate that a fair comparison is difficult to obtain due to the multi-dimensional performance metrics considered here, and the difficulty in setting up the parameters of the models in a way that does not advantage or disadvantage one modeling framework. Along these lines, this study explores the effect that model assumptions such as reserve requirements, value of lost load (VOLL) and wind spillage costs have on the comparison of the performance of stochastic vs deterministic market clearing models.
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The possibility of encouraging the growth of forests as a means of sequestering carbon dioxide has received considerable attention, partly because of evidence that this can be a relatively inexpensive means of combating climate change. But how sensitive are such estimates to specific conditions? We examine the sensitivity of carbon sequestration costs to changes in critical factors, including the nature of management and deforestation regimes, silvicultural species, relative prices, and discount rates. (C) 2000 Academic Press.
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Quantity-based regulation with banking allows regulated firms to shift obligations across time in response to periods of unexpectedly high or low marginal costs. Despite its wide prevalence in existing and proposed emission trading programs, banking has received limited attention in past welfare analyses of policy choice under uncertainty. We address this gap with a model of banking behavior that captures two key constraints: uncertainty about the future from the firm's perspective and a limit on negative bank values (e.g. borrowing). We show conditions where banking provisions reduce price volatility and lower expected costs compared to quantity policies without banking. For plausible parameter values related to U.S. climate change policy, we find that bankable quantities produce behavior quite similar to price policies for about two decades and, during this period, improve welfare by about a $1 billion per year over fixed quantities. © 2012 Elsevier B.V.
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BACKGROUND: Fitness costs and slower disease progression are associated with a cytolytic T lymphocyte (CTL) escape mutation T242N in Gag in HIV-1-infected individuals carrying HLA-B*57/5801 alleles. However, the impact of different context in diverse HIV-1 strains on the fitness costs due to the T242N mutation has not been well characterized. To better understand the extent of fitness costs of the T242N mutation and the repair of fitness loss through compensatory amino acids, we investigated its fitness impact in different transmitted/founder (T/F) viruses. RESULTS: The T242N mutation resulted in various levels of fitness loss in four different T/F viruses. However, the fitness costs were significantly compromised by preexisting compensatory amino acids in (Isoleucine at position 247) or outside (glutamine at position 219) the CTL epitope. Moreover, the transmitted T242N escape mutant in subject CH131 was as fit as the revertant N242T mutant and the elimination of the compensatory amino acid I247 in the T/F viral genome resulted in significant fitness cost, suggesting the fitness loss caused by the T242N mutation had been fully repaired in the donor at transmission. Analysis of the global circulating HIV-1 sequences in the Los Alamos HIV Sequence Database showed a high prevalence of compensatory amino acids for the T242N mutation and other T cell escape mutations. CONCLUSIONS: Our results show that the preexisting compensatory amino acids in the majority of circulating HIV-1 strains could significantly compromise the fitness loss due to CTL escape mutations and thus increase challenges for T cell based vaccines.
The tithe: Public research university STEM faculty perspectives on sponsored research indirect costs
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This study sought to understand the phenomenon of faculty involvement in indirect cost under-recovery. The focus of the study was on public research university STEM (science, technology, engineering and mathematics) faculty, and their perspectives on, and behavior towards, a higher education fiscal policy. The explanatory scheme was derived from anthropological theory, and incorporated organizational culture, faculty socialization, and political bargaining models in the conceptual framework. This study drew on two key assumptions. The first assumption was that faculty understanding of, and behavior toward, indirect cost recovery represents values, beliefs, and choices drawn from the distinct professional socialization and distinct culture of faculty. The second assumption was that when faculty and institutional administrators are in conflict over indirect cost recovery, the resultant formal administrative decision comes about through political bargaining over critical resources. The research design was a single site, qualitative case study with a focus on learning the meaning of the phenomenon as understood by the informants. In this study the informants were tenured and tenure track research university faculty in the STEM fields who were highly successful at obtaining Federal sponsored research funds, with individual sponsored research portfolios of at least one million dollars. The data consisted of 11 informant interviews, bolstered by documentary evidence. The findings indicated that faculty socialization and organizational culture were the most dominant themes, while political bargaining emerged as significantly less prominent. Public research university STEM faculty are most concerned about the survival of their research programs and the discovery facilitated by their research programs. They resort to conjecture when confronted by the issue of indirect cost recovery. The findings direct institutional administrators to consider less emphasis on compliance and hierarchy when working with expert professionals such as science faculty. Instead a more effective focus might be on communication and clarity in budget processes and organizational decision-making, and a concentration on critical administrative support that can relieve faculty administrative burdens. For higher education researchers, the findings suggest that we need to create more sophisticated models to help us understand organizations dependent on expert professionals.
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