81,449 research outputs found

    A Forward Looking Version of the MIT Emissions Prediction and Policy Analysis (EPPA) Model

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    Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).This paper documents a forward looking multi-regional general equilibrium model developed from the latest version of the recursive-dynamic MIT Emissions Prediction and Policy Analysis (EPPA) model. The model represents full inter-temporal optimization (perfect foresight), which makes it possible 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. It was designed with the flexibility to represent different aggregations of countries and regions, different horizon lengths, as well as the ability to accommodate different assumptions about the economy, in terms of economic growth, foreign trade closure, labor leisure choice, taxes on primary factors, vintaging of capital and data calibration. The forward-looking dynamic model provides a complementary tool for policy analyses, to assess the robustness of results from the recursive EPPA model, and to illustrate important differences in results that are driven by the perfect foresight behavior. We present some applications of the model that include the reference case and its comparison with the recursive EPPA version, as well as some greenhouse gas mitigation cases where we explore economic impacts with and without inter-temporal trade of permits.This research was supported by the U.S Department of Energy, U.S. Environmental Protection Agency, U.S. National Science Foundation, U.S. National Aeronautics and Space Administration, U.S. National Oceanographic and Atmospheric Administration; and the Industry and Foundation Sponsors of the MIT Joint Program on the Science and Policy of Global Change: Alstom Power (USA), American Electric Power (USA), A.P. MÞller-Maersk (Denmark), Cargill (USA), Chevron Corporation (USA), CONCAWE & EUROPIA (EU), DaimlerChrysler AG (USA), Duke Energy (USA), Electric Power Research Institute (USA), Electricité de France, Enel (Italy), Eni (Italy), Exelon Power (USA), ExxonMobil Corporation (USA), Ford Motor Company (USA), General Motors (USA), Iberdrola Generacion (Spain), J-Power (Japan), Merril Lynch (USA), Murphy Oil Corporation (USA), Norway Ministry of Petroleum and Energy, Oglethorpe Power Corporation (USA), RWE Power (Germany), Schlumberger (USA),Shell Petroleum (Netherlands/UK), Southern Company (USA), StatoilHydro (Norway), Tennessee Valley Authority (USA), Tokyo Electric Power Company (Japan), Total (France), G. Unger Vetlesen Foundation (USA)

    TRACING THE EFFECTS OF AGRICULTURAL COMMODITY PRICES ON FOOD PROCESSING COSTS

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    Although food processing sector production is inherently linked to the availability and prices of agricultural materials (MA), this link appears to be weakening due to adaptations in input costs, technology, and food consumption patterns. This study assesses the roles of these changes on food processors costs and output prices, with a focus on the demand for primary agricultural commodities. Our analysis of the 4-digit U.S. food processing industries for 1972-1992 is based on a cost-function framework, augmented by a profit maximization specification of output pricing, and a virtual price representation for agricultural materials and capital. We find that falling virtual prices of MA and input substitution have provided a stimulus for MA demand. However, scale effects have been MA-saving relative to intermediate food products, and disembodied technical change has strongly contributed to declining primary agricultural materials demand relative to most other inputs.Demand and Price Analysis, Industrial Organization,

    Optimal forest rotation age under efficient climate change mitigation

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    This paper considers the optimal rotation of forests when the carbon flows of forest growth and harvest are priced with an increasing price. Such an evolution of carbon price is generally associated with economically efficient climate change mitigation, and would provide incentives for the land-owner for enhanced carbon sequestration. With an infinitely long sequence of even-aged forest rotations, the optimal harvest age changes with subsequent rotations due to the changing carbon price. The first-order optimality conditions therefore also involve an infinite chain of lengths for consecutive forest rotations, and allow the approximation of the infinite-time problem with a truncated series of forest rotations. Illustrative numerical calculations show that when starting from bare land, the initial carbon price and its growth rate both primarily increase the length of the first rotation. With some combinations of the carbon pricing parameters, the optimal harvest age can be several hundred years if the forest carbon is released to the atmosphere upon harvest. This effect is not, however, entirely monotonous. Consequently, the currently optimal harvest ages are generally lower with higher rates of carbon price increase. This creates an interesting temporal aspect, suggesting that the supply of wood and carbon sequestration by forests can change considerably during subsequent rotations under an increasing price on carbon.Comment: in Forest Policy and Economics, 201

    Seasonality in the Irish dairy processing industry

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    The dairy landscape in the Republic of Ireland is characterized by pastoral spring-calving systems and a bell-shaped milk production curve. This seasonality at producer level initiates various implications at processor level, such as poor utilization of plant capacity off-peak season, a requirement for seasonal labour management and limited product options in autumn and winter months due to the properties of late-lactation milk. An optimization model was developed to analyze the impact of production seasonality and quota removal on the Irish dairy processing industry in terms of maximum processor gross surplus, the optimum product mix and the marginal values of the milk solids fat, protein and lactose. Processor gross surplus was specified as a function of product sales revenue, less variable costs of collecting and processing raw milk and general overhead (fixed) costs. 5 scenarios with differing milk intake curves were examined whereby a flatter intake curve incurred less monthly variation in the marginal producer milk price, capacity utilization and product mix as well as a higher surplus as compared to more seasonal patterns. However, an isolated consideration of financial indicators at processor level disregards key characteristics of Irish grass-based seasonal milk production and producer-processor interdependencies. It was therefore concluded that a broader modelling approach integrating both the producer and the processor perspectives is desirable for more holistic analysis of sector-wide implications.Dairy processing, seasonality, milk quota abolition, processor profit, product mix, Farm Management, Livestock Production/Industries,

    Study on the feasibility of a tool to measure the macroeconomic impact of structural reforms

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    The main aim of this study is to assess the feasibility of empirical tools to study the impact of structural reforms on the macroeconomic performance in the member countries of the European Union (EU). This report presents the results of the project "Study on the feasibility of a tool to measure the macroeconomic impact of structural reforms" (ECFIN-E/2005/001) and amalgamates the findings of the two previous interim reports and the main conclusions of the workshop held in Brussels on May 11th. The main goal of the project is to determine the most reliable and robust methods to investigate the impacts of economy-wide structural reforms as well as reforms in individual markets or sectors, and to make suggestions as to how they best to implement them and possible improvements of the institutional dataset. In addition, a roadmap has been created which includes the main steps in the model-developing process, and solutions feasible even in the short term are discussed.The most relevant conclusion to be drawn from the study is that the most appropriate tool that can be developed in the short term is the integration of a DSGE model (preferably QUEST due to its in-house availability) with different satellite models, to be developed.structural reforms, product markets, labour markets, financial markets, Dreger, Artïżœs, Moreno, Ramos, Suriïżœach

    Biomass Supply from Alternative Cellulosic Crops and Crop Residues: A Preliminary Spatial Bioeconomic Modeling Approach

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    This paper introduces a spatial bioeconomic model for study of potential cellulosic biomass supply at regional scale. By modeling the profitability of alternative crop production practices, it captures the opportunity cost of replacing current crops by cellulosic biomass crops. The model draws upon biophysical crop input-output coefficients, price and cost data, and spatial transportation costs in the context of profit maximization theory. Yields are simulated using temperature, precipitation and soil quality data with various commercial crops and potential new cellulosic biomass crops. Three types of alternative crop management scenarios are simulated by varying crop rotation, fertilization and tillage. The cost of transporting biomass to a specific demand location is obtained using road distances and bulk shipping costs from geographic information systems. The spatial mathematical programming model predicts the supply of biomass and implied environmental consequences for a landscape managed by representative, profit maximizing farmers. The model was applied and validated for simulation of cellulosic biomass supply in a 9-county region of southern Michigan. Results for 74 cropping systems simulated across 39 sub-watersheds show that crop residues are the first types of biomass to be supplied. Corn stover and wheat straw supply start at 21/Mgand21/Mg and 27/Mg delivered prices. Perennial bioenergy crops become profitable to produce when the delivered biomass price reaches 46/Mgforswitchgrass,46/Mg for switchgrass, 118/Mg for grass mixes and $154/Mg for Miscanthus giganteus. The predicted effect of the USDA Biomass Conversion Assistance Program is to sharply reduce the minimum biomass price at which miscanthus would become profitable to supply. Compared to conventional crop production practices in the area, the EPIC-simulated environmental outcomes with crop residue removal include increased greenhouse gas emissions and reduced water quality through increased nutrient loss. By contrast, perennial cellulosic biomass crops reduced greenhouse gas emissions and improved water quality compared to current commercial cropping systems.biomass production, bioenergy supply, biofuel policy, bioenergy, cellulosic ethanol, agro-ecosystem economics, ecosystem services economics, agro-environmental trade-off analysis, mathematical programming, EPIC, Agricultural and Food Policy, Crop Production/Industries, Environmental Economics and Policy, Land Economics/Use, Production Economics, Resource /Energy Economics and Policy, Q16, Q15, Q57, Q18,

    Estimating Euler equations

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    In this paper we consider conditions under which the estimation of a log-linearized Euler equation for consumption yields consistent estimates of preference parameters. When utility is isoelastic and a sample covering a long time period is available, consistent estimates are obtained from the loglinearized Euler equation when the innovations to the conditional variance of consumption growth are uncorrelated with the instruments typically used in estimation. We perform a Montecarlo experiment, consisting in solving and simulating a simple life cycle model under uncertainty, and show that in most situations, the estimates obtained from the log-linearized equation are not systematically biased. This is true even when we introduce heteroscedasticity in the process generating income. The only exception is when discount rates are very high (e.g. 47% per year). This problem arises because consumers are nearly always close to the maximum borrowing limit: the estimation bias is unrelated to the linearization and estimates using nonlinear GMM are as bad. Across all our situations, estimation using a log-linearized Euler equation does better than nonlinear GMM despite the absence of measurement error. Finally, we plot life cycle profiles for the variance of consumption growth, which, except when the discount factor is very high, is remarkably flat. This implies that claims that demographic variables in log-linearized Euler equations capture changes in the variance of consumption growth are unwarranted
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