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Author Nelson, G.C.; van der Mensbrugghe, D.; Ahammad, H.; Blanc, E.; Calvin, K.; Hasegawa, T.; Havlik, P.; Heyhoe, E.; Kyle, P.; Lotze-Campen, H.; von Lampe, M.; Mason, d’C., Daniel; van Meijl, H.; Müller, C.; Reilly, J.; Robertson, R.; Sands, R.D.; Schmitz, C.; Tabeau, A.; Takahashi, K.; Valin, H.; Willenbockel, D.
Title Agriculture and climate change in global scenarios: why don’t the models agree Type Journal Article
Year 2014 Publication Agricultural Economics Abbreviated Journal Agric. Econ.
Volume 45 Issue 1 Pages 85-101
Keywords climate change impacts; economic models of agriculture; scenarios; system model; demand; CMIP5
Abstract Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0169-5150 ISBN Medium Article
Area Expedition Conference
Notes CropM, TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4536
Permanent link to this record
 

 
Author Robinson, S.; van Meijl, H.; Willenbockel, D.; Valin, H.; Fujimori, S.; Masui, T.; Sands, R.; Wise, M.; Calvin, K.; Havlik, P.; Mason d’Croz, D.; Tabeau, A.; Kavallari, A.; Schmitz, C.; Dietrich, J.P.; von Lampe, M.
Title Comparing supply-side specifications in models of global agriculture and the food system Type Journal Article
Year 2014 Publication Agricultural Economics Abbreviated Journal Agric. Econ.
Volume 45 Issue 1 Pages 21-35
Keywords global agricultural models; global food system scenario analysis; general equilibrium; partial equilibrium; growth; trade
Abstract This article compares the theoretical and functional specification of production in partial equilibrium (PE) and computable general equilibrium (CGE) models of the global agricultural and food system included in the AgMIP model comparison study. The two model families differ in their scopepartial versus economy-wideand in how they represent technology and the behavior of supply and demand in markets. The CGE models are deep structural models in that they explicitly solve the maximization problem of consumers and producers, assuming utility maximization and profit maximization with production/cost functions that include all factor inputs. The PE models divide into two groups on the supply side: (1) shallow structural models, which essentially specify area/yield supply functions with no explicit maximization behavior, and (2) deep structural models that provide a detailed activity-analysis specification of technology and explicit optimizing behavior by producers. While the models vary in their specifications of technology, both within and between the PE and CGE families, we consider two stylized theoretical models to compare the behavior of crop yields and supply functions in CGE models with their behavior in shallow structural PE models. We find that the theoretical responsiveness of supply to changes in prices can be similar, depending on parameter choices that define the behavior of implicit supply functions over the domain of applicability defined by the common scenarios used in the AgMIP comparisons. In practice, however, the applied models are more complex and differ in their empirical sensitivity to variations in specificationcomparability of results given parameter choices is an empirical question. To illustrate the issues, sensitivity analysis is done with one global CGE model, MAGNET, to indicate how the results vary with different specification of technical change, and how they compare with the results from PE models.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0169-5150 ISBN Medium Article
Area Expedition Conference
Notes CropM, TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4735
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Author Gutierrez, L.; Piras, F.; Roggero, P.P.
Title A global vector autoregression model for the analysis of wheat export prices Type Journal Article
Year 2015 Publication American Journal of Agricultural Economics Abbreviated Journal American Journal of Agricultural Economics
Volume 97 Issue 5 Pages 1494-1511
Keywords Global dynamic models; price analysis; wheat market; lagged dependent-variables; commodity-markets; error-correction; food-prices; unit-root; regressors; tests; cointegration; dynamics; time
Abstract Food commodity price fluctuations have an important impact on poverty and food insecurity across the world. Conventional models have not provided a complete picture of recent price spikes in agricultural commodity markets, and there is an urgent need for appropriate policy responses. Perhaps new approaches are needed to better understand international spill-overs, the feedback between the real and the financial sectors, as well as the link between food and energy prices. In this article, we present the results from a new worldwide dynamic model that provides the short and long-run impulse responses of the international wheat price to various real and financial shocks.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0002-9092 1467-8276 ISBN Medium Article
Area Expedition Conference
Notes TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4658
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Author Siebert, S.; Ewert, F.
Title Future crop production threatened by extreme heat Type Journal Article
Year 2014 Publication Environmental Research Letters Abbreviated Journal Environ. Res. Lett.
Volume 9 Issue 4 Pages
Keywords climate-change; simulation-models; wheat yields; day length; temperature; growth; impact; co2; phenology; patterns
Abstract Heat is considered to be a major stress limiting crop growth and yields. While important findings on the impact of heat on crop yield have been made based on experiments in controlled environments, little is known about the effects under field conditions at larger scales. The study of Deryng et al (2014 Global crop yield response to extreme heat stress under multiple climate change futures Environ. Res. Lett. 9 034011), analysing the impact of heat stress on maize, spring wheat and soya bean under climate change, represents an important contribution to this emerging research field. Uncertainties in the occurrence of heat stress under field conditions, plant responses to heat and appropriate adaptation measures still need further investigation.
Address 2016-10-31
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1748-9326 ISBN Medium Article
Area Expedition Conference
Notes CropM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4813
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Author Nelson, G.C.; van der Mensbrugghe, D.; Ahammad, H.; Blanc, E.; Calvin, K.; Hasegawa, T.; Havlik, P.; Heyhoe, E.; Kyle, P.; Lotze-Campen, H.; von Lampe, M.; Mason, d’C., Daniel; van Meijl, H.; Müller, C.; Reilly, J.; Robertson, R.; Sands, R.D.; Schmitz, C.; Tabeau, A.; Takahashi, K.; Valin, H.; Willenbockel, D.
Title Agriculture and climate change in global scenarios: why don’t the models agree Type Journal Article
Year 2014 Publication Agricultural Economics Abbreviated Journal Agric. Econ.
Volume 45 Issue 1 Pages 85-85
Keywords climate change impacts; economic models of agriculture; scenarios; system model; demand; cmip5
Abstract Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty.
Address 2016-10-31
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0169-5150 ISBN Medium Article
Area Expedition Conference
Notes CropM, TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4796
Permanent link to this record