36 research outputs found

    Specification of a Regional-National Recursive Model for IIASA/FAP's Iowa Task 2 Case Study

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    The major objectives of the Food and Agriculture Program (FAP) of the International Institute for Applied Systems Analysis are to evaluate the nature and dimensions of the world food situation, to identify factors affecting it, and to suggest policy alternatives at the national, regional, and global levels to alleviate current food problems and to prevent future ones. The present shortrun problems of policy are explored in FAP's Task 1, "Strategies: National Policy Models for Food and Agriculture" by means of a set of descriptive, general-equilibrium, price-endogenous national models of various countries linked in a consistent international framework. From a longer term perspective the food problem acquires added dimensions; and questions of availability of resources to produce adequate food, efficiency of techniques, and environmental consequences become important. These questions are addressed by FAP's Task 2 "Technological Transformations in Agriculture: Resource Limitations and Environmental Consequences". Quantitative knowledge of the interactions between agriculture and the environment requires a great deal of detailed information on the site-specific nature of resource inputs and on alternative land use practices. A general-equilibrium approach to such types of investigation is not empirically feasible. The research methodology of Task 2 is to formulate a series of region-specific case studies within a general recursive programming framework. The regional-national recursive model specified in this paper represents the intermediate stage of development of the Iowa Case Study. The Iowa model has been specified by a team of researchers including Dr. Earl 0. Heady, James Langley, Andrew Morton, and Burton English of the Center for Agricultural and Rural Development, Iowa State University, and Wen-yuan Huang and Klaus Alt of the Natural Resources Economics Division, U.S. Department of Agriculture. Work is continuing on the specification of various components of the Iowa model along with preliminary applications in accordance with the framework of FAP's Task 2

    Dynamic input demand functions and resource adjustment for US agriculture: state evidence

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    The paper presents an econometric model of dynamic agricultural input demand functions that include research based technical change and autoregressive disturbances and fits the model to annual data for a set of state aggregates pooled over 1950–1982. The methodological approach is one of developing a theoretical foundation for a dynamic input demand system and accepting state aggreage behavior as approximated by nonlinear adjustment costs and long-term profit maximization. Although other studies have largely ignored autocorrelation in dynamic input demand systems, the results show shorter adjustment lags with autocorrelation than without. Dynamic input demand own-price elasticities for the six input groups are inelastic, and the demand functions possess significant cross-price and research effects

    Crop Input Response Functions with Stochastic Plateaus

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    Agronomic research on crop response to nitrogen fertilizer suggests that a plateau function may be appropriate, but the plateau varies across fields and years. Available models that treat the plateau as a stochastic variable are not readily extendable to handle field or year random effects as seems to be appropriate based on the agronomic data. This article develops a method of estimating a response function with a stochastic plateau that can capture random effects. The method is then used to determine economically optimal levels of nitrogen fertilizer for wheat (Triticum aestivum). Copyright 2008, Oxford University Press.
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