determined by levels of (or changes in) vulnerability. That is, reducing vulnerability would be one of the drivers of rural infrastructure spending decisions. On the other hand, vulnerability may or may not guide research and extension investments. Profitability, for example, may play a more prominent role in the allocation of such investments. Cumulative aspects may also be affecting such decisions. For example, only where previous investments in research and extension exist should further investments be expected—unless a critical threshold can be achieved, no investments will be initiated. In order to explore these issues, we proceed in sequential steps exploring two other estimation approaches.

# _<u>Lagged estimation</u>_

We estimate the probability of pertaining to high or very high vulnerability categories in 2007 against spending in two past time periods: (i) levels of 2006 agricultural spending (Table 4); and (ii) levels of 2003 agricultural spending (Table 5), allowing for potentially longer-term intertemporal effects. This is captured in specification (2‘‘).

We find that 2006 agricultural spending effect on 2007 VAM is statistically significant and positive, as it was the case for the contemporaneous 2007 results, although the size of the association is larger (Table 4, Column 1). Results also confirm a larger association of restricted vis-à-vis extended spending, similar to 2007. Although investment spending continues to have a positive and significant effect on VAM, the association of current spending appears to also be important and much larger. It is, however, unclear how current spending—mostly wages and salaries—may be related to vulnerability. Increasing current spending may be associated with a larger presence of civil servants as investment spending increases in most needed areas (pointing to a complementary rather substitutive nature between both types of spending). Other explanation might imply accepting a negative income effect on vulnerability associated with salaries of civil servants.<sup>11</sup> The one-year lag does not reveal important differences in the magnitude of the effects of the different functional classifications of agricultural spending vis-àvis contemporaneous specifications. Infrastructure maintains its statistical significance and association with increased vulnerability, and there is a positive impact from spending in research and extension, which is the largest among all specifications and functional classifications. Department-specific effects remain unchanged with respect to 2007 contemporaneous effects.

> vulnerability and spending. The effect on VAM 2003 is found to be a statistically significant and positive factor of future agricultural spending. In other words, past vulnerability seems to affect agricultural spending allocations. Further work is needed to properly account for this potentially endogenous relationship. The preferred option, an instrumental variable approach, faces a number of difficulties, however. Finding good instruments is challenging, more so in this case, where many variables— including weather and geographic variables—– are already used to update the independent variable, VAM. Furthermore, political outcomes and managerial capacity of a municipality are arguably not exogenous to either spending decisions or vulnerability to food insecurity issues. Interestingly, Faguet (2004) analysis of determinants of agricultural spending finds that neither municipal capacity nor institutional features (in particular, the supervisory extent of civil society) are significant factors.

> 11 We control for civil servant ―density‖ as well as other variables capturing institutional public capacity in the robustness check section. We cannot, however, control for income effects associated with salaries and other current spending.

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