Presented by Adam Komarek (IFPRI), Belhouchette H. (CIHEAM-IAMM), Blanco M. (UPM-ETSIA), Chenoune R. (CIHEAM-IAMM), El Ansari L. (CIHEAM-IAMM) and Flichman G. (CIHEAM-IAMM) at the Africa RISING Monitoring and Evaluation Meeting, Arusha, Tanzania, 13-14 November 2014

1. 1/11
DAHBSIM:
Dynamic Agricultural Household Bio-Economic
Simulation Model
Adam Komarek (IFPRI), Belhouchette H. (CIHEAM-IAMM), Blanco M. (UPM-ETSIA),
Chenoune R. (CIHEAM-IAMM), El Ansari L. (CIHEAM-IAMM)
and Flichman G. (CIHEAM-IAMM)
Africa RISING Monitoring and Evaluation Meeting, Arusha, Tanzania,
13-14 November 2014

2. 2/11
Background to DAHBSIM
• Dynamic Agricultural Household Bio-Economic Simulation Model
• The DAHBSIM team participated in the development of several
bio-economic models.
• The most relevant are:
• Cebalat Model: A recursive stochastic supply model (1)
• FSSIM-MP: static, generic, positive, supply model (2)
• FSSIM-DEV: static, generic, positive household model (3)
• DAHBSIM has combined characteristics of these previous models
-----------------------------------------------------------
(1) Blanco M., Belhouchette H., Flichman G., (2012)
(2) Louhichi K., Belhouchette H., Blanco M., Flichman G., et al ( 2010)
(3) Louhichi K., Belhouchette H., Blanco M., Flichman G., et al (2013)

3. 3/11
What is DAHBSIM?
• Dynamic: For analyzing sustainability of agricultural systems
• Agricultural: it is applied to agricultural systems
• Household: Production and consumption decisions cannot be
considered separately in most cases of sub-Saharan Africa
• Bio-Economic: It represents the impacts of production and
consumption decisions on the environment and vice-versa
• SIMulation Model: It simulates different scenarios, such as policy
changes, climate change, technological change

4. 4/11
What is DAHBSIM?
• It is a tool for analyzing the relations between
intensification with land, energy, water and the
environment, issues related with Sustainable
Intensification in BioSight Project
• The production side is activity based
• Consumption function is based on exogenous elasticities
• Presently, DAHBSIM is a farm-household model being
developed for application to a set of households in
Dedza, Malawi.

5. • DAHBSIM applies a dynamic-recursive optimization
approach:
• An inter-temporal optimization is performed over a T
year moving time horizon
• First year’s results are retained (from survey) and
recursive equations are introduced before the second
optimization, for taking into account the effect on
resources of the previous year choices.
• This procedure is repeated for all periods.
5/11
Model structure

6. 6/11
Simplified model structure
External database: farm-level resources, climate, and soil data
Cropping module
• land and labour
constraints
• Endogenous rotations
Objective function
• Maximize utility from
consumption
• Mean-standard-deviation
• T year rolling time horizon
Modules can be turned
on or off, GAMS solver
Farm module
• Link crop and livestock
module, land and labour
• product supply and
demand
• Farm Income
Biophysical module
• Nitrogen and water
response functions
• Choices in t-1 impacts
soil fertility in t
Livestock module
• Nutrient requirements
• Livestock dynamics
Household module
• Product consumption
balance
• Time allocation balance
• Household income
Outputs: land use, input and output levels, time allocation, household
consumption, income, environmental externalities

7. 7/11
Simplified biophysical crop module structure
Weather
PM-ET0
Crop potential
evapotranspiration
Potential crop
evapotranspiration-dependent
yield
Crop Coefficient (Kc)
potential to actual
evapotranspiration
Evapotranspiration
limited yield
Water limited crop
evapotranspiration
Soil water
Rainfall Irrigation
Drainage
Nitrogen limited
yield
N Leaching
Actual yield (minimum of
the two calculations)
This calculation is performed after each
iteration on the different soil types. Soil water
and nitrogen content is a result of the previous
crop in t-1 & fertilization and water in t
Soil nitrogen balance
factors:
N Residues, N fertilization,
organic fertilization, Soil N
balance

8. 8/11
Rainfall and modelled maize yield

9. 9/11
Malawi case-study data
• Using a complete database*
• Organization of data for DAHBSIM
• Data structure used by DAHBSIM has two entries:
• Information belonging to each household
• Information related with production processes
(activities)
____________________________________________
* Provided by the Africa RISING M&E Team, IFPRI. C. Azzari, C. Roberts and H. Beliyou.

10. 10/11
Next steps
• Model validation: observed vs predicted data
• Model application: sustainable agricultural
intensification scenarios across diverse farms.
• Changes in soil water and nitrogen, sowing dates and
seed densities
• Forage crop integration for livestock nutrients, changes
in herd dynamics through changes in feeding regimes
• Assess trade-offs across different contexts

11. Africa Research in Sustainable Intensification for the Next Generation
africa-rising.net
The presentation has a Creative Commons licence. You are free to re-use or distribute this work, provided credit is given to ILRI.
11/11
Thank You