Table 2: Estimates of the exposure effect on microfinance uptake for different adjustment strategies. Exposure 1 refers to a village having a high fraction of village leaders, and Exposure 2 refers to a village having a high fraction of savings self-help group participants. β$_{0}$ is the estimated uptake of microfinance in unexposed villages and β$_{A}$ is the average mean difference in uptake comparing exposed to unexposed villages. These results show a sizable effect of adjusting for baseline covariates, including network features by fitting the OM and PS models. Details of these model fits are provided in the supplementary material; in general, degree as well as number and size of components were selected in the OM for both exposures, as was age for models in which demographic variables were included. For the PS models, only degree assortativity was selected for Exposure 2, but degree and component features were also included for Exposure 1. For Exposure 1, using the doubly-robust approach leads to a doubling of the point estimate compared to that of the unadjusted GEE and suggests that a greater number of leaders is negatively associated with microfinance uptake. The DR analyses detect the presence of an exposure effect not detected by the unadjusted analysis. For Exposure 2, the DR approach leads to a 50% increase in the point estimates of its effect, although the latter is associated with a p -value of 0 . 14 . These differences suggest the presence of confounding. In addition, adjusting for both network and sociodemographic covariates reduces estimated standard error for Exposure 1 (by about 50%) but not for Exposure 2. None of the estimates of the Exposure 2 effects reach statistical significance at the 0 . 05 level. Taken together, these results imply that the presence of a high proportion of leaders reduces microfinance uptake—perhaps reflecting the greater influence of leaders when there are fewer of them—but do not demonstrate an effect of participation in savings self-help groups. 7 Est. Adjustment Estimate S.E. Wald-score p -value Exp. 1 β$_{0}$ Crude Estimate 0.209 0.019 11.207 < 0.001 Unadjusted GEE Estimate 0.249 0.043 5.761 < 0.001 Network Covariates Only 0.214 0.019 11.12 < 0.001 Network & Sociodemographic 0.215 0.019 11.11 < 0.001 β$_{A}$ Crude Estimate -0.002 0.039 -0.055 0.478 Unadjusted GEE Estimate -0.069 0.058 -1.191 0.120 Network Covariates Only -0.138 0.031 -4.49 0.001 Network & Sociodemographic -0.137 0.031 -4.45 < 0.001 Exp. 2 β$_{0}$ Crude Estimate 0.203 0.018 11.15 < 0.001 Unadjusted GEE Estimate 0.201 0.018 11.05 < 0.001 Network Covariates Only 0.208 0.018 11.37 < 0.001 Network & Sociodemographic 0.208 0.018 11.38 < 0.001 β$_{A}$ Crude Estimate 0.018 0.04 0.44 0.332 Unadjusted GEE Estimate 0.03 0.038 0.79 0.216 Network Covariates Only 0.045 0.041 1.08 0.143 Network & Sociodemographic 0.045 0.041 1.08 0.143