Impact of low-input agriculture (low fertiliser/pesticide use) via Micro-Econometric Multi-Crop Cost Allocation models - Discussion paper

Abstract Micro-econometric multi-crop (MEMC) models are commonly used in Europe with farm-level panel data but face several empirical challenges, including lacking cost accounting data (which is the case for FADN data), frequent null crop acreages and unobserved heterogeneity across farm(er)s. To overcome these limitations, we propose a new structural model, the Endogenous Regime Switching Micro-Econometric Multi-Crop Model with Cost Input Allocation (MEMC-CA) and assess its empirical performances based on French farm dataset.This paper presents the MEMC-CA model, which is used to analyze farmers' decisions regarding crop acreages choice, yield levels and variable input uses (pesticides and fertilizers). The model is based on a profit maximization framework at the farm level.Along the lines of Carpentier and Letort (2012, 2014), the basic modelling framework model integrates three interrelated components: (i) a system of crop acreage choice equations based on an acreage management cost function, (ii) a system of crop yield supply equations, and (iii) a system of variable input demand allocation equations. Crop yield supply and variable input demand equations are derived from quadratic yield functions. Acreage choice equations are derived from a quadratic acreage management cost function, as in Positive Mathematical Programming (PMP) models based on the so-called “PMP term”.Two options are available for dealing with the lack of cost accounting data. The first option involves two steps. First, agrochemicals costs are allocated to the crops of the farms using the (CA, for cost allocation) approach proposed by Koutchadé et al (2024). This two-step modelling framework is called the CA+MEMC model for simplicity. Second, the estimated crop-specific agrochemicals are added to the initial dataset for estimating the MEMC model. The second option consists of replacing the agrochemicals demand equation system of the MEMC model by the variable input allocation equations considered in the CA approach of Koutchadé et al (2024). The resulting model, the MEMC-CA model, is estimated in one step, based on an approach similar to the one employed for estimating the MEMC model.The empirical application employs an unbalanced panel comprising 1,083 arable farms in northeastern France, observed from 2007 to 2014. The estimation results indicate that the MEMC model provides a good fit for the observed data and captures key features of farmers’ production behavior. Model validation shows that the CA+MEMC and MEMC-CA specifications perform well in predicting crop choice and production regimes, particularly in reproducing zero acreage outcomes, as well as (expected) yield levels. However, validation results tend to show that these specifications perform poorly regarding allocation of variable input to crops. More precisely, the quality estimated crop-specific allocation is not sufficient for the calibrated simulation models to provide reliable results for policy directly targeting uses of variable inputs, such as pesticide and/or fertilizer taxes. Yet, the calibrated simulation models can provide reliable results for policies targeting acreage choices, such as area-based coupled payments. This working paper provides the details of the section 3.2.3 in the Deliverable D4.2: Final report on the impact of agricultural, climate, environmental and trade policies Keywords: null crop acreages, input cost allocation, heterogeneity, crop production decisions, ERS-MEMC models, random parameter models, SAEM algorithm. Citation KOUTCHADE, O. P., Carpentier, A., & Femenia, F. (2026). Impact of low-input agriculture (low fertiliser/pesticide use) via Micro-Econometric Multi-Crop Cost Allocation models - Discussion paper (Version v01). BrightSpace Horizon Europe project GA Nr. 101060075. https://doi.org/10.5281/zenodo.19743946 ----------------- Funding acknowledgement Funded by the European Union. Grant Agreement No. 101060075. Views and opinions expressed are those of the authors only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the granting authority can be held responsible for them. Legal notice This document was produced under the terms and conditions of Grant Agreement No. 101060075 for the European Commission. It does not necessary reflect the view of the European Union and in no way anticipates the Commission’s future policy in this area. The European Commission is not liable for any consequence stemming from the reuse of this publication. © BrightSpace, 2026 The reuse of this document is authorised under a Creative Commons Attribution 4.0 International (CCBY 4.0) licence (https://creativecommons.org/licenses/by/4.0/). This means that reuse is allowed provided appropriate credit is given and any changes are indicated. For any use or reproduction of elements that are not owned by the BrightSpace consortium, permission may need to be sought directly from the respective right holders. Project information BrightSpace Horizon Europe project Grant Agreement No. 101060075 https://cordis.europa.eu/project/id/101060075 CALL: Innovative governance, environmental observations and digital solutions in support of the Green Deal WORK PROGRAMME Topic ID: HORIZON-CL6-2021-GOVERNANCE-01-12 EU agriculture within a safe and just operating space and planetary boundaries BrightSpace Project coordination: Wageningen Economic Research, The Hague, NL Contact: brightspace.wser@wur.nl | Website: www.brightspace-project.eu Project duration: 1 November 2022 – 31 October 2027.