systemic differences were discovered during the analysis. We carry out a more nuanced comparison between the type of information each data source provides, as well as the magnitude of these differences and their causes in Appendix II. Due to the granularity of SDI, which includes information on source and quality of electricity, as well as differences in definitions and on expected accuracy from direct observations versus small-area estimations, this paper favors the use of SDI data on access to electricity. Nonetheless, we note that the GEP data might still provide useful information for other studies when no first-hand data is available, particularly when using electrification as a control that might also capture other socioeconomic variables.

# 4. Results

This section presents and discusses the main results for each quality indicator. All specifications include controls at the facility level and county fixed effects.

## 4.1. Provider's Knowledge

Diagnostic errors are a source of avoidable illness and death, now more than ever since many previously incurable conditions now have a treatment (Khullar, Jha, & Jena, 2015). We explore here two indicators for diagnostic accuracy, one related to children and adults' illnesses and another one focusing on children and pregnant women-related ailments. As shown in Table 2, access to a stable electricity connection is positively related to diagnostic accuracy at the facility level, while longer distance to the nearest at least fair quality road is negatively related with this measure of provider's knowledge.

Column 1 in Table 2 displays the results for general cases (diarrhea with dehydration, pneumonia, diabetes, and tuberculosis). Here, access to electricity service is related to an increase of 4.20 percentage points in the diagnostic accuracy compared to facilities without access to electricity. Even though unstable access to electricity is also positively related to diagnostic accuracy, the relationship is not significant. Column 2 shows diagnostic accuracy for childhood and pregnant women cases (diarrhea with dehydration, pneumonia, postpartum hemorrhage, and neonatal asphyxia); the results follow the same logic, with a positive and significant relationship between access to a stable electricity connection and diagnostic accuracy of 5.03 percentage points.

The specification includes controls for a comprehensive set of facility-level covariates, including access to improved sources of water or sanitation and small area poverty and population density estimations to control for possible sorting. Given the broad set of controls used, the results suggest that facilities with better infrastructure might attract and/or retain better-skilled providers, which is in line with evidence from Lenz, L. et al., 2016, where mainly for rural areas, access to grid electricity facilitates recruiting trained staff in Rwanda.

On the other hand, increasing distance to at least a fair quality primary or secondary road is negatively related to provider's diagnostic accuracy at facility level. Using the quantile distribution of this geospatial variable by distance, it is seen that the further the facility is from fair or good quality roads, the worse the results of provider knowledge. While there seems not to be any significant differences between quintiles one and two, facilities in the third quintile of the distance variable have 3.7 and 2.5 percentage points lower diagnostic accuracy than at the facilities which are in the first quantile - the closest to the fair or good quality roads. This 12