Simulating agricultural land rental markets by combining C ombining agent-based models with models and traditional neoclassical economics concepts: The case of the Argentine Pampas to simulate agricultural land rental markets in the Argentine Pampas Federico Bert 1 , Michael North 2 , Santiago Rovere 3 , Eric Tatara 2 , Charles Macal 2 , Guillermo Podestá 4 1 Univ. de Buenos Aires, Facultad de Agronomía and Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina; 2 Argonne National Laboratory, Decision and Information Science Division, USA; 3 Universidad de Buenos Aires, Facultad de Ingeniería, Buenos Aires, Argentina; 4 University of Miami, Rosenstiel School of Marine & Atmospheric Science, Miami, USA; Abstract: Land exchange through rental transactions is a central process in agricultural systems. The land tenure regimes emerge from land transactions and structural and land use changes are tied to the dynamics of the land market. We introduce LARMA, a LAnd Rental MArket model embedded within The Pampas Model (PM), is an agent-based model of Argentinean agricultural systems. designed to explore structural and land use changes in Argentine agriculture. We integrated the LAnd Rental MArket model (LARMA) into the PM due to the important effects land markets have on structural and land use changes for agriculture. LARMA produces endogenous formation of land rental prices (LRP) . LARMA relies on traditional economic concepts neoclassical economics for LRP formation but addresses some drawbacks of this approach by being integrated into an agent-based model modelling framework that considers heterogeneous agents interacting with one another . This paper introduces LARMA and shows results from a set of PM - LARMA simulations. PM-LARMA successfully reproduced the agricultural land tenure patterns regimes and land rental prices observed in the Pampas. Including adaptive, heterogeneous and , interacting agents was critical to this success. We conclude that agent-based model l ing and neoclassical economics traditional economic models can be successfully combined to capture complex emergent land tenure and market price patterns while simplifying the overall model design. 1 1 Abbreviations: AACREA: Asociación Argentina de Consorcios Regionales de Experimentación Agrícola; ABM: Agent-Based Modelling; ACE: Agent-based Computational Economics; AL: Aspiration Level; AM: Activity-Management; CAU: Cropped Area Update; CE: Certainty Equivalent; DPR: Desired Profitability Rate; DSSAT: Decision Support System for Agrotechnology Transfer; EU: Expected Utility; GM: Gross Margin; LARMA: LAnd Rental MArket model; LRP: Land Rental Price; MCP: Market Clearing Price; MP: © 2015. This manuscript version is made available under the Elsevier user license http://www.elsevier.com/open-access/userlicense/1.0/