visited the project clinic, as opposed to only 41 percent in the control group. The di¤erence-in-di¤erences estimate, 8 percentage points or a 19% increase, is highly signi...cant.

– In regression 2, table 3, we look at an alternative measure of sta¤ performance the waiting time –de...ned as the di¤erence between the time the user left the facility and the time the user arrived at the facility, subtracting the examination time. On average, the waiting time was 133 minutes in the control facilities and 119 in the treatment facilities. The di¤erence is highly signi...cant.<sup>21</sup> Table 4, column 1, reports the results on absenteeism.<sup>22</sup> The point estimates suggest a substantial treatment e¤ect. On average, the absence rate, de...ned as the ratio of workers not physically present at the time of the post-intervention survey to the number of workers employed, is 19 percent (10 percentage points) lower in the treatment facilities. Column 2 presents the result when only using the nominator as the dependent variable. In the treatment facilities, 3.1 workers were present on average as compared to 2.3 in the control clinic. Thus, in response to more extensive community monitoring, health workers are more likely to be at work.

Enumerators also visually checked the condition of the health center, i.e. whether ‡oors and walls were clean, the condition of the furniture and the smell of the facility. Each condition was ranked on a score from 1 (dirty) to 3 (clean). Through principal components analysis, we transform these four variables into a summary score (the ...rst component): “condition of the clinic”. There is a large and signi...cant improvement in the treatment clinic. The point estimate implies that treatment clinics, on average, score 0.56 standard deviations (in the sample of control facilities) higher than the control facilities. Thus, treatment clinics appear to have put more e¤ort into keeping the clinic in decent condition in response to the intervention.<sup>23</sup> The ...ndings on immunization of children under ...ve are reported in tables 5a5d.<sup>24</sup> We have information on how many times (doses) in total each child has been

> 21The point estimates for the treatment e¤ect in table 3 are similar, but somewhat less precisely estimated, when only using data from the post-intervention survey, i.e. when estimating (2) instead of (4).

> 22The post-intervention survey was not announced in advance. At the start of the survey, enumerators physically veri...ed the provider’s presence. A worker was counted as absent if, at the time of the visit (during facility hours), he or she was not in the clinic. Sta¤ reported to be on outreach were omitted from the absence calculation. In the full sample, 47 percent of the health workers were absent. Chaudhury et al. (2006), based on a larger sample of both rural and urban health centers in Uganda, report that 37 percent of the workers, on average, are absent.

> 23Improvements in treatment practices are also substantiated by the qualitative data assembled. As reported in the appendix, table A.8., for all three subjective measures (overall change in the quality of services provided over the last year, change in sta¤ politeness, change in availability of medical sta¤), there are positive and signi...cant di¤erences between the treatment and control communities’ responses.

> 24We report results of estimating (2) rather than the di¤erence-in-di¤erences equation (4), since the pre-treatment vaccination outcomes were strongly in‡uenced by a mass immunization campaign implemented prior to the survey period. Due to reported irregularities in the top management of the unit in charge of the immunization campaigns, we have not been able to assemble accurate information on the actual timing of the campaign prior to the intervention.

18