its level) puts more emphasis to increases for poorer households, as the proportional effects (i.e. logs) are given more weight in these cases. To explore this further, we divided households into quintiles based on the levels of expenditure per capita, and then applied propensity score matching (with a single nearest neighbor) to each category. The striking result, shown in Table 5, is that the impact of VRF borrowing is only strong for the poorest quintile, a finding that holds both for 2002 and 2004. It would thus be appropriate to categorize the VRF policy as “pro-poor.” It is instructive to breakdown the impacts further, for each major category of income; the results are shown in rows 8-14 in Table 7. More VRF borrowing is associated with more farm income (up 49%, albeit from a modest base of just 522 baht per capita per month) and more income from non-farm enterprises (up 26%). On the other hand, VRF borrowing is not associated with higher wage or transfer income.

One may also break down the impacts by consumer expenditure category (see rows 15-26 in Table 7). There are substantial increases in spending on grain and meat, and also on vehicle operation, although this last effect is not quite statistically significant. None of the other measured impacts are statistically significant. These results differ somewhat from those reported by Kaboski and Townsend (2009, Table 5), who found, for a sample of villages in central Thailand, that VFR credit raised spending on alcohol, and on repairs to homes and vehicles.

The VRF appears to have the biggest impact in rural areas. If the analysis is repeated for rural households only, the effect is a statistically significant 6.9% boost to expenditure and 4.3% increase in income in 2004 (upper panel of Table 4), although the comparable effects in 2002 were much smaller.

There are minimal gender effects. For households that reported having a male head, VRF borrowing was associated with a 5.2% rise in expenditure and 4.8% increase in income. These figures are only marginally higher than those for female-headed households, where expenditure rose 5.0% and income by a (nonsignificant) 2.8%, as shown in rows 31 and 32 of Table 7.

In addition to the effect on income or expenditure, it might also be expected that VRF borrowing would have an effect on the accumulation of household assets. It is not possible to measure household gross or net assets using the Socioeconomic Survey data, but there is a listing of the major physical assets, of which some of the most important are given in Table 6. There we see, for instance, that 64% of all households surveyed had a phone in 2004; the rate was 59% for VRF borrowers and 67% for non-borrowers. We then used our propensity-score matching and found that, for instance, phone ownership among VRF borrowers was 5.4 percentage points higher than among comparable non-borrowers. Similar effects were found for VCRs, fridges, washing machines, and motorized transport. This, coupled with the smaller impact on income than on expenditure, suggests that VRF borrowing was used to some extent in order to get improved access to consumer and producer durables, despite the fact that fewer than 2% of households reported that this was the ostensible purpose of their VRF borrowing (see Table 2).

_Village Fund, draft of June 29, 2009_ _Page 12 of 34_