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

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

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

Resource information

Date of publication
Mai 2013
Resource Language
ISBN / Resource ID
OSF_preprint:46205-C69-B9B

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.

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Authors and Publishers

Author(s), editor(s), contributor(s)

Sebastian Hess
Luca Di Corato

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Geographical focus