A Dynamic Stochastic Programming Framework for Modeling Large Scale Land Deals in Developing Countries
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The attractiveness of agricultural land available in developing countries has markedly
increased in the last few years. Driven by rising and highly volatile prices for agricul-
tural commodities, large land acquisitions have been undertaken by foreign investors.
We formalize the discussion surrounding such large scale land deals through a dynamic
stochastic programming model. Within this framework, we first determine the value of
a land development project under uncertainty about prices for agricultural commodi-
ties, political risk and irreversible capital investment. Second, given an exogenously
set corporate tax rate, we determine, in both a cooperative and a non-cooperative set-
ting, the optimal land rental payment. We show that 1) the optimal policy scheme is
equivalent to a risk-sharing contract, 2) trading o¤ rental payment with tax revenue
is detrimental for both total project value and domestic benefits and 3) taxation has
a neutral impact on long-run the land development pace. We complete our study by
illustrating our results through an empirical application based on observed individual
land deals from Ethiopia and simulations for a specific crop in a selected region that
has recently been targeted by foreign investments.