players ( _ai_ ). Thus _ei = ei(a1+a2); ei’ < 0; i = 1, 2._ Each land user will therefore convert land until the point where the agricultural rent equals the marginal loss of forest benefits: Next, we define the response function, i.e., the optimal amount of forest cleared for one land user as a function of the amount cleared by the other, based on the above equation (first order condition): _ai = si (aj); si’<0; i,j = 1, 2; i_ ≠ _j._ Assume now that player 1 moves first (referred to as a Stackelberg game in the game literature). The optimal forest clearing for the land user, taking into account the impact his decision will have on player 2, would be: Player 1 will now clear more forest. The element ( _s2’ e1’_ ) gives the additional benefit of his forest conversion: it squeezes player 2’s forest clearing by an amount _s2’_ , and the marginal benefit of this squeeze is _e1’_ . Angelsen (2001) suggests that such squeezing effects tend to be stronger the more scarce forest has become, but land still being allocated on a first-come-first-served basis.

# **_Summing up_**

When land rights are being established by forest clearing, forest is converted beyond the point to which it would be converted in the basic von Thünen model. This clearing is also socially suboptimal. Better tenure security will in this case boost deforestation. In a study of property rights and deforestation in Nicaragua, Liscow (2005) concludes that: “This study offers strong evidence that, contrary to many theoretical predictions, tenancy insecurity protects forests. ... This result reveals the costs of creating better markets for land titling without creating any markets for the positive externalities provided by forests.” We investigated three reasons beyond the standard environmental argument of negative externalities why a substantial share of tropical deforestation may be excessive: land race, land speculation, and strategic squeezing. In the first two cases some forest with a negative agricultural rent will be cleared. As for the third case, although some costs due to forest loss (e.g., environmental benefits) are included, this solution is not socially optimal: the cost imposed on the others is ignored, thus there is a negative externality not factored into the decision making.

In empirical work it may be difficult to distinguish clearly between these, but based on earlier reviews of deforestation studies (e.g., Kaimowitz and Angelsen, 1998) one may suggest that the “land race” phenomenon is the most common strategic argument. Rudel (1993) gives a good illustration of this in his study from Ecuador. Forest land was converted to pasture so quickly to secure rights that farmers could not stock them with cattle. Some of these lands therefore reverted to secondary forest.

# **2.5 Community forest management**

## **_2.5.1 Introduction_**

Community forest management (CFM) or just community forestry refers to an institutional arrangement where a set of rights and obligations concerning forest use and management rests with the local communities.<sup>29</sup> It is useful to distinguish between CFM that has originated locally and

> 29 A number of different labels exist are used for similar or closely related arrangements: joint forest management, forest-co-management, local forest management, community-based forest management, village

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