48 research outputs found
Does oil price uncertainty affect energy use?
Theory predicts that the presence of fixed costs affects the relationship between energy use and energy price changes, as the firm's output and investment decisions respond differently to energy price increases and decreases. The asymmetry in response to energy price changes is exacerbated by uncertainty with respect to future energy prices, but to date the empirical literature does not explicitly take uncertainty into account. The contribution of this paper is twofold. First, we develop a new measure of energy price uncertainty. Second, we apply the measure to explain energy use in 8 OECD countries between 1978 and 1996, trying to identify whether indeed energy price uncertainty effects the asymmetry resulting from changes in energy use.
A NOTE ON HIGH DISCOUNT RATES AND DEPLETION OF PRIMARY FORESTS
Conventional wisdom implies that high discount rates accelerate depletion of tropical forests. As shown in this article, this result does not necessarily hold in a two-state variable model that distinguishes between primary and secondary forest stocks. In the context of a fixed concession period and imperfect government control, logging of primary forests may be both accelerated and depressed as discount rates increase.Resource /Energy Economics and Policy,
Asymmetric adaptations to energy price changes
The effectiveness of policies to reduce the use of energy depend on the elasticity of substitution between the various inputs and on the rate of technological progress. This paper presents a theoretical model emphasising energy investments\' characteristics of uncertainty and irreversibility that result in testable hypotheses concerning the relative values of substitution parameters and rates of technological change in periods of high and increasing energy prices and in periods of low prices. Estimation results for a panel of sectors of the Dutch economy show that the elasticity of substitution between energy and other inputs is low in periods of low energy prices, whereas it is significantly higher in the preceding period of high and increasing energy prices. Furthermore, energy-saving technological progress in periods of high and increasing energy prices is also significantly higher than if energy prices are low and falling. The regression results suggest that, due this asymmetric response of firms to changes in energy prices, taxing energy in the current period of low energy prices will not yield substantial reductions in energy use of Dutch industry.
Land Degradation in Ethiopia: What Do Stoves Have To Do With It?
In Ethiopia deforestation is a major problem and many peasants have switched from fuelwood to dung for cooking and heating purposes, thereby damaging the agricultural productivity of cropland. The Ethiopian government has embarked on a two-pronged policy in an effort to stem deforestation and the degradation of agricultural lands: (i) tree planting or afforestation; (ii) dissemination of more efficient stove technologies. The motivation in here is, therefore, to examine the potential of the strategy of disseminating improved stoves in the rehabilitation of agricultural and forests lands. For empirical analysis we used a dataset on cross-section of 200 farm households from the highlands of Tigrai, northern Ethiopia. We used a two-step procedure reminiscent of hedonic pricing. Results in this paper indicate that farm households in Tigrai/ Ethiopia are willing to adopt new/improved stove innovations if these result in economic savings. Moreover, results suggest a significant positive impact in slowing the degradation of agricultural and forested lands. On a per household basis, we found that adopters will collect 68.3 kg less wood each month, while more dung in the form of manure becomes available as 19.899 kg less dung is collected each month. In terms of wood alone, assuming an average of 79 t of biomass per ha, we found the potential reduction in deforestation amounts to some 1,794 ha per year, not an inconsequential savings.land degradation, technology adoption, fuel-savings efficiency, stoves, Ethiopia, Land Economics/Use, Q12, Q16, Q24,
Threshold Effects of Energy Price Changes
The effectiveness of policies to reduce the use of energy depend on the elasticity of substitution between the various inputs and on the rate of technological progress. This paper presents a theoretical model emphasising energy investmentsâ characteristics of uncertainty and irreversibility that result in hypotheses concerning the relative values of substitution parameters and rates of technological change in periods of high and increasing energy prices and in periods of low prices. The theoretical model suggests that threshold level effects exist. Firms are induced to substitute away from energy only if prices of energy exceed a certain threshold level and they reverse the technology only if prices are low enough. Using panel data for the Dutch economy we do not find threshold effects in the level of energy prices.
Threshold effects of energy price changes
This paper presents a theoretical model emphasising energy investmentsâ characteristics of uncertainty and irreversibility. The theoretical model suggests threshold effects. Firms are induced to substitute away from energy only if prices of energy exceed a certain threshold level and they reverse the technology only if energy prices are low enough. Estimating a simple investment relation using panel data for the Dutch economy, we find evidence for threshold effects.
Subsidizing the adoption of energy-saving technologies; Analyzing the impact of uncertainty, learning and maturation
As part of the Kyoto Protocol, many countries have committed themselves to substantially reduce the emission of greenhouse gases within a politically imposed time constraint. Investment subsidies can be an important instrument to stimulate the adoption of energy-saving technologies to achieve emission reduction targets. This paper addresses the impact of adoption subsidies on the amount of energy savings, taking into account both the endogenous and uncertain nature of technological progress. Neglecting these two characteristics of technological progress tends to result in overestimation of the short-run effectiveness of investment subsidies, whereas the long-run effects are ambiguous
A method for the deliberate and deliberative selection of policy instrument mixes for climate change adaptation
Policy instruments can help put climate adaptation plans into action. Here, we propose a method for the systematic assessment and selection of policy instruments for stimulating adaptation action. The multi-disciplinary set of six assessment criteria is derived from economics, policy, and legal studies. These criteria are specified for the purpose of climate adaptation by taking into account four challenges to the governance of climate adaptation: uncertainty, spatial diversity, controversy, and social complexity. The six criteria and four challenges are integrated into a step-wise method that enables the selection of instruments starting from a generic assessment and ending with a specific assessment of policy instrument mixes for the stimulation of a specific adaptation measure. We then apply the method to three examples of adaptation measures. The methodâs merits lie in enabling deliberate choices through a holistic and comprehensive set of adaptation specific criteria, as well as deliberative choices by offering a stepwise method that structures an informed dialog on instrument selection. Although the method was created and applied by scientific experts, policy-makers can also use the method
A Federated Database for Obesity Research:An IMI-SOPHIA Study
Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.</p
A Federated Database for Obesity Research:An IMI-SOPHIA Study
Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders