using the standardized definitions and methods developed under the Rural Income Generating Activities (RIGA) Project (Davis et al., 2010).<sup>5</sup> This approach facilitated comparison across countries. Production that had been consumed or stored was valued at unit values either derived from reported sales or, when absent, from median unit values at community or district levels (see Davis et al. (2010) for details). Other in-kind income was valued at market prices. A similar approach was followed to value (in-kind) income from on-farm trees.<sup>6</sup> Finally, as a broader, more encapsulating measure of the welfare effects associated with tree adoption and management, we compare average consumption levels among farmers growing trees on their farms with the consumption levels of those who do not grow trees on their farms, controlling for the characteristics of their environment. In particular, to do so real daily consumption per person (in 2011 purchasing power parity $) was regressed on whether the household had trees on farms or not and district fixed effects. The average difference in consumption is thus identified from the within-district difference in real daily consumption per person between tree and non-tree growing households

# 2.3 Correlates of on‐farm tree adoption

At first glance, there appear few incentives for smallholder farmers to incorporate trees into their farming systems (Arnold and Dewees, 1997; Dewees, 1995a; Franzel, 1999; Godoy, 1992). There is a long time lag between planting and harvesting, while poor farmers are often liquidity constrained with a high discount rate. Access to (formal and informal) credit is limited, making it difficult to overcome the liquidity gap and poorer farmers often have smaller landholdings, necessitating attempts to generate revenues annually on all the land available to them. Insecure property rights further discourage collected at the crop level (see table A.2 for description of available data), making it difficult to attribute costs to a particular crop. Importantly, the gross income ratio used here remains unbiased, under the assumption that the share of net over gross income is the same for income from trees on farms as for overall agricultural or total income. Put differently, to the extent that the share of expenditures on tree crop production to income from trees on farms is smaller than the share of expenditures on all agricultural production to income from agricultural production, the gross income from trees to gross agricultural income ratios reported here will be underestimates. A similar reasoning holds for the ratio of gross income from trees to overall gross income.

> 5 Under this method, seven basic categories of household income are considered: _(i)_ crop production; _(ii)_ livestock production; _(iii)_ agricultural wage employment; _(iv)_ non-agricultural wage employment; _(v)_ non-agricultural self-employment; _(vi)_ transfers; and ( _vii_ ) when available, other income sources like rental income, fishing or saving accounts. See Davis et al. (2010) for details.

> 6 In a recent study, Angelsen et al. (2014) show that environmental and forest incomes can also be important in certain communities, especially those with closer access to forests. As in most standard household budget surveys, such income is not appropriately recorded in the LSMS-ISA data and has not been accounted for here either. A forestry module for LSMSISA and other national surveys has recently been developed to address this information gap (Bakkegaard et al., 2016).

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