importance of the market-power channel although alternate interpretations, which we discuss, may also be consistent with the findings.

**Result 1: Facilities improved in ways that went beyond the “letter of the law:”** We first looked for strategic behavior among facilities with respect to the regulation, which would suggest that it was the regulation itself that led to the changes we observed. A facility interested in minimizing the cost of complying with the regulatory requirements would have (a) started with the lowest-cost items and (b) undertaken changes that were just sufficient to meet the compliance threshold. Indeed, a striking consequence of the scoring rubric in the JHIC was that if facilities had complied with all items in the lowest-cost category, their score would have increased by 34 percentage points or 3.2 SD, placing the average facility well above the 60% compliance score that would have staved off future warnings or sanctions. Instead, consistent with our previous results, we find that the impact of the intervention was 3.4, 7.4 and 6.3 percentage points (all p-values _<_ 0.01) on compliance with the lowest, medium and high cost items (Table A10). An alternative classification by items that affected the marginal versus the fixed-cost again yielded similarly sized impacts on both, despite the fact that all the items in the lowest-cost category were fixed-cost items that are therefore independent of the number of patients (Table A10).

We also do not find evidence that facilities focused on “just” meeting the compliance threshold. For instance, 66% of facilities had a JHIC score lower than 40% at baseline, implying they faced the most frequent follow-ups (every three months) and risk of closure if the facility did not move to the next category by the third visit. Facilities closest to this cutoff-point could have strategically moved to the next higher compliance category (41%-60%), with more lenient warnings and sanctions. Figure A7 shows evidence of lack of strategic behavior on this front; using a McCrary-type density test we cannot reject the null hypothesis of continuity of the density of the JHIC score for treatment facilities around 40% of the maximum score (p-value = 0.246).

In contrast to the regulatory-driven incentives, we find some evidence that market-based incentives played a role among private facilities. Table A3 shows that price-quality correlations are statistically significant and higher for infrastructure, equipment and medium-cost supplies, compared to SOPs and these correlations are robust to the inclusion of machine-selected controls. This is consistent with our finding in Table 4 of little improvement in compliance with SOP standards, despite strong regulatory incentives and very low costs of doing so. Further, impacts for private facilities are higher in markets where there were more public facilities, suggesting an important role of public facilities in the market (Table A11).

We emphasize that these results do not imply a zero role for regulatory incentives, but rather that facilities invested in ways that went _beyond_ the regulatory incentives, potentially driven by beliefs over other facility’s beliefs. These models also do not include the public sector, which accounts for 71% of the market share in our setting. The improvement in the public sector can be modeled as “exogenous” with implications for other private facilities, but this does not address the question of why the public sector improved in the first place.

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