cross-market spillovers, the impact of program duration, and spillovers on other quality measures that were not part of the inspection process. The estimating equations and accompanying tables are detailed in Sections 7 and 9 of the Supplemental Material.

**Cross-Market Externalities** : Cross-market externalities, whereby control health facilities in markets located near treatment facilities are affected by the treatment, may bias our estimates of the impact of the regulation. We identify cross-market externalities using exogenous variation in the local density of facilities induced by the stratified market-level randomization, following a method similar to Miguel & Kremer (2004). We find no significant cross-market externalities in the JHIC score, patient load, OOP payments, exit and entry of new facilities (Table S12 in the Supplemental Material).

**Program Duration** : Next, we exploit variation in the timing of the inspections and the endline to examine the impact of program duration, which captures both the fact that facilities that were in the program longer will have been inspected more often (2.4 times versus 1.6 to 2.0 times for other groups) and that program impacts can fade out over time. Our main identifying assumption, which we verify in Section 7.2 in the Supplemental Material, is that conditional on the controls, the variation in the date of first inspection and the date of the endline are not correlated with the JHIC score.

In markets where the time elapsed from first (last) inspection to endline was 15 (10) months, the JHIC score increased by 7 percentage points (0.65 SD, p-value _<_ 0.01), compared to 4 percentage points for treated markets where the time from first (last) inspection to endline was 11 (7) months. This suggests little “fade-out” and potentially larger effects as the model scales up (Figure S4 and Table S14 in the Supplemental Material).

**Impacts on non-incentivized outcomes** : One concern with regulations on specific inputs is that they can reduce quality along non-incentivized dimensions (Blau, 2003, 2007). We were particularly concerned about this possibility given the results presented by Contreras-Loya et al. (2021), who find that structural improvements are accompanied by declines in the quality of clinical processes in private facilities. We therefore estimated the impact of the regulation on multiple process and structural measures of quality that were not part of the JHIC instrument. These include: (a) compliance with infection prevention and control practices across 19,178 observations of clinical interactions; (b) quality indicators reported by patients in 11,098 exit surveys and; (c) healthcare staff composition and remuneration for 7,663 staff.<sup>27</sup>

Fortunately, we do not find significant negative changes along any of these dimensions, with small typically positive effect sizes and statistically insignificant after correcting for multiple hypotheses. To the extent that we can interpret the individually significant estimates, in public facilities, we find an _increase_ in consultation length, which has shown to be positively correlated with clinical accuracy, as well as an increase in the ratio of healthcare workers to total staff and total

> 27In the 13% of health facilities with more than 15 staff, we chose a random sample stratified by cadre.

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