Jan Philipp Dietrich
dietrixyzch@pik-xyzpotsdam.de
Source: Mimi and Eunice | CC-BY-SA Nina Paley
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*' @equations
q13_cost_tc(i2) ..
v13_cost_tc(i2) =e= sum(ct, i13_land(i2) * i13_tc_factor(ct,i2)
* vm_tau(i2)**i13_tc_exponent(ct,i2)
* (1+pm_interest(i2))**15);
*' Relative technological change costs `v13_cost_tc` are calculated as a
*' heuristically derived power function of the land use intensity `vm_tau`
*' for the investment-yield-ratio (see figure below) multiplied by the
*' initial, regional crop areas in 1995 `pm_land_start` and shifted 15
*' years into the future using the region specific interest rate
*' `pm_interest`.
*'
*' ![Investment-yield ratio in relation to $\tau$-factor
*' [@dietrich_forecasting_2014]](tcc_regression.png){ width=60% }
*'
*' The shifting is performed because investments into technological change
*' require on average 15 years of research before a yield increase is
*' achieved, but the model has to see costs and benefits concurrently in
*' order to take the right investment decisions (see also
*' @dietrich_forecasting_2014). Investment costs scale with crop area as a
*' wider areal coverage means typically also higher variety in biophysical
*' conditions and therefore more research required for the same overall
*' intensity boost.
q13_tech_cost_annuity(i2) ..
v13_tech_cost_annuity(i2) =e= (vm_tau(i2)/pc13_tau(i2)-1) * v13_cost_tc(i2)
* pm_interest(i2)/(1+pm_interest(i2));
*' In order to get the full investments required for the desired
*' intensification the relative technological change costs are multiplied
*' with the given intensification rate. These full costs are then
*' distributed over an infinite time horizon by multiplication with the
*' interest rate `pm_interest(i)` (annuity with infinite time horizon).
q13_tech_cost(i2) ..
vm_tech_cost(i2) =e= v13_tech_cost_annuity(i2) + pc13_tech_cost_past(i2);
*' Additionally, the technological change costs coming from past investment
*' decisions are added to the technological change costs of the current
*' period.
> citation("madrat")
Dietrich J, Baumstark L and Giannousakis A (2018). _madrat: May All Data
be Reproducible and Transparent (MADRaT)_. doi: 10.5281/zenodo.1115490
(URL: http://doi.org/10.5281/zenodo.1115490), R package version 1.44.0,
<URL: https://github.com/pik-piam/madrat>.
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Source: Mimi and Eunice | CC-BY-SA Nina Paley
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retrieveData: bundle data as required by the model
readSource: read source data and (dis-)aggregate to ISO country level
calcOutput: calculate data sets as required by the model
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copyleft: AGPL | non-copyleft: BSD2
model: yes | tools: no
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This presentation - slides.com/jandietrich/fable-open-access
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pik-potsdam.de/members/dietrich/GuidelinesOpenSource
pik-potsdam.de/members/dietrich/GuidelinesOpenData
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