_θ_ to be negative. Again, by testing the significance of _β, γ_ and _δ,_ we can explore the extent to which reform or good governance had an impact on their own or in combination with each other.

From an econometric point of view, use of elections as a right hand side variable in (1) or (2) raises concerns as unobserved village characteristics that determine the propensity to hold village elections may also affect land use and reallocation decisions. To deal with concerns about endogeneity, we adopt an instrumental variables (IV) approach. A number of studies have used the length of leaders’ tenure as an instrument as this variable is highly correlated with village elections having been held but has little independent impact on economic outcomes (Zhang _et al._ 2003, Shen and Yang 2006). We follow these studies but note that the current leadership may still be correlated with economic outcomes. To avoid this concern, we use the length of tenure of the village leader before the last election cycle. Following Wooldridge (2001), we include the square of this variable and its interaction with the reform dummy to help identify interactions between election and reform variables.

# **4.2 Determinants of compensation received**

Results from tobit regressions of the level of compensation received by households are reported in table 5. Column 1 displays the base equation without the endogenous election variable while columns 2 and 3 report OLS and IV results that include instrumented variables for elections and their interaction with the legal reform dummy. Instrumental variables used to identify the latter comfortably pass the Wald test of exogeneity, the test statistic for which is indicated in the bottom of column 3.

One notes a strong link between land characteristics and the value of compensation received, suggesting that both past and future potential affect the level of compensation. The value of production obtained from the land before it was subject to taking is highly significant and of considerable magnitude, with an elasticity ranging from 0.61 to 0.71 depending on the specifications or estimation approaches. Similarly, location of land next to a major road also contributes to a significant increase in the amount of monetary compensation, more than doubling the latter according to the IV estimates. As compensation can come in kind or cash, it is not surprising to find that the share of compensation received in kind, i.e. the size of land received relative to what was lost, is highly negative. We also note that the use to which land was put had a significant impact on the amount of compensation; even after all the other factors are accounted for, the amount of compensation paid for land to be used for public purposes is estimated to have been significantly lower than land to be used by private investors. This supports the notion that, in cases where private entrepreneurs are involved, farmers losing land were significantly better off, thereby allaying fears that government intervention would be required to ensure a “fair” deal. It suggests that direct negotiation between entrepreneurs and farmers would not make the latter worse off. Also, villages with higher income levels are more likely to pass on compensation payments to the concerned land users.

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