Econometric-Process Models for Integrated Assessment of Agricultural Production Systems

By J. Antle, S. Capalbo. 2001

216 citations recorded by the source corpus.

This paper develops the conceptual and empirical basis for a class of empirical economic production models that can be linked to site-specific bio-physical models for use in integrated assessment research. Site-specific data are used to estimate econometric production models, and these data and models are then incorporated into a simulation model that represents the decision making process of the farmer as a sequence of discrete or continuous land use and input use decisions. This discrete/continuous structure of the econometric process model is able to simulate decision making both within and outside the range of observed data in a way that is consistent with economic theory and with site-specific bio-physical constraints and processes. An econometric-process model of the dryland grain production system of the Northern Plains demonstrates the capabilities of this type of model.

Subfields: Environmental Chemistry, General Agricultural and Biological Sciences, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/bfec8970a3925b6589d7519af99ab54694c9c8e4

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In Environmental Chemistry

In General Agricultural and Biological Sciences

In Global and Planetary Change

Citations in the corpus

Brief history of agricultural systems modeling (2017, unknown): “They also can be coupled with process-based models to predict out-of-sample responses (Antle and Capalbo, 2001).”
Evaluating agricultural trade-offs in the age of sustainable development (2016, background): “Modeling approaches for estimating indicator values fall into the following categories: empirical, and process-based biophysical and economic models (Crissman et al., 1998; Antle and Capalbo, 2001; Tittonell, 2013).”
Modelling the Supply of Ecosystem Services from Agriculture: A Minimum-Data Approach (2006, unknown): “Alternatively, in cases where either normal or non-normal σ σ σ σa b a b ab− = + − 2 2 2 2 Source: Montana field data and simulation models reported in Antle and Capalbo (2001); Peru field data and simulation models described in Valdivia (2002).”
Incomplete Credit Markets and Commodity Marketing Behaviour (2011, background): “Yt (Antle and Capalbo, 2001).”
Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science (2017, background): “5), and can be linked to economic models to create “hybrid” models for policy analysis and impact assessment (Antle and Capalbo, 2001; Antle and Stockle, 2015).”
Spatial heterogeneity, contract design, and the efficiency of carbon sequestration policies for agriculture (2003, methodology): “For details, see Antle and Capalbo [2].”
Assessing farm innovations and responses to policies: A review of bio-economic farm models (2007, background): “Mechanistic models are suitable both for extrapolations and long-term predictions, as these models can simulate system ‘‘behaviour outside the range of observed data in ways consistent with established scientific understanding’’ (Antle and Capalbo, 2001).”
Adaptation, Spatial Heterogeneity, and the Vulnerability of Agricultural Systems to Climate Change and CO2 Fertilization: An Integrated Assessment Approach (2004, methodology): “, 1993), and the right-hand side represents the components of the analysis based on the econometric-process simulation model (Antle and Capalbo, 2001).”