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

Luca Di Corato and Sebastian Hess

No 150190, 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. from Agricultural and Applied Economics Association

Abstract: 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.

Keywords: International Development; Land Economics/Use; Research Methods/Statistical Methods (search for similar items in EconPapers)
Pages: 32
Date: 2013-06-01
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Persistent link: https://EconPapers.repec.org/RePEc:ags:aaea13:150190

DOI: 10.22004/ag.econ.150190

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