Overall, this reduced-form cross-country evidence is at most suggestive of the existence of poverty traps, but it is hardly conclusive. Moreover, this type of evidence tells us little about the specific mechanisms generating the poverty trap or the policy interventions required to escape from that poverty trap. More useful in this respect is a line of microeconometric evidence that focuses on finding direct evidence of the mechanisms underlying specific models of poverty traps. For example, McKenzie and Woodruff (2004) use data from microenterprises in Mexico to search for evidence of poverty traps based on non-convexities in the production function. They take seriously the argument that poverty traps might exist if there are large fixed costs to starting a business. If capital markets are imperfect and potential entrepreneurs are credit-constrained by their lack of collateral, then a poverty trap can exist since individuals who start out with low wealth are unable to finance potentially profitable investments in new businesses. They find that the fixed costs involved in starting up a small enterprise in Mexico are typically very low, in some sectors less than half the monthly wage of a low-wage Mexican worker. They also find that the returns to capital are very high even at very low levels of the capital stock, and cannot reject the hypothesis that returns are decreasing over the entire range of observed capital stocks. They conclude that their evidence is not consistent with this particular mechanism of poverty traps.

In contrast, a number of papers have found microeconometric evidence of spillovers or other externalities that could form the basis of poverty traps. For example, Jalan and Ravallion (2004) argue for the existence of spatial or geographic poverty traps. In a panel of households from China, they find that consumption growth at the household level increases with the local availability of “geographical capital” understood as the availability of roads, the local level of literacy, etc. Their evidence suggests that these aggregate factors (at the local level) increase the returns to capital faced by households. However, the main focus of the paper is to determine the impact of locally aggregate variables on household growth. They do not spell out a feedback mechanism from household growth to the evolution of the geographical capital that could generate a poverty trap. A direct interpretation of their evidence is that it shows that the factors captured in the geographical capital are a constraint to household growth. If we assume that household growth feeds back into these variables, it might be possible to generate a poverty trap, but the degree of feedback necessary to induce such a trap is not specified. A different type of microeconometric evidence can be found in Lokshin and Ravallion (2004), who empirically estimate non-linear dynamics in household income in two transition economies. While they find that adjustment to income shocks is nonlinear, they find no evidence of non-convexities that would cause temporary adverse shocks to permanently lower household income, as would be the case in a variety of models of poverty traps.

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