A Dynamic Stochastic Programming Framework for Modeling Large Scale Land Deals in Developing Countries

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 agricultural 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 commodities, 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.