One aspect of these markets that we had not anticipated was the significant churn in the private sector. Of the 301 private facilities in the control group operational at randomization, 57 (19%) had exited by August 2018 and 55 (15%) new facilities had entered. These closure rates far exceed the 8.2% reported by McKenzie & Paffhausen (2019) for small firms in LMICs. In our 2015 census itself, we were able to identify 202 (21%) facilities from the government master facility list in February 2015 that were no longer operational, and 379 (40%) facilities that were not part of the 938 facilities listed in the government records.

A second key feature of our data is the close link between the JHIC score, licensing status and market outcomes, which shows up in every aspect of facility performance. In the private sector at baseline, the JHIC score for unlicensed relative to licensed providers was 21% lower.<sup>19</sup> JHIC scores and licensing status were also strongly correlated with facility exits in the control group, with a 1 SD increase in the JHIC score (9.6 percentage points) associated with a 7.7 percentage point decline in exits (Table 2). However, facilities that exit the market by endline tend to be small and represent only 3% of all patients in the data (Table S9 of the Supplemental Material).

Column 1, Table 2 then shows that a 1 SD increase in the JHIC score (12.1 percentage points) was correlated with an increase of USD 1.9 (PPP) in out-of-pocket (OOP) payments per visit, a correlation that remains robust to the inclusion of machine-selected controls. As is well understood, this association between prices and the JHIC score does not identify the structural hedonic parameter in the presence of patient sorting. While we cannot address patient sorting fully, we can assess the sensitivity of our estimates to select features of the patient population in each facility, as shown in Column 2, Table 2. Here, in addition to the machine-selected controls from Column 1, we also include patient wealth, education, self-reported health status and distance traveled to the health facility, all characteristics that are likely correlated with the demand for higher quality care. Although these variables are positively associated with OOP payments, there is virtually no change in the price premium for higher quality as measured by the JHIC score, which retains its strong statistical significance.

Vertical differentiation requires a positive price-quality correlation in the private sector (which we find) but not necessarily a quantity-quality correlation as some facilities could be niche highend facilities. Nevertheless, we do find a positive, but insignificant correlation between market share and the JHIC score in the private sector. We can also ask whether the positive valuation of quality extends to patients visiting public sector clinics. Since prices in the public sector are administratively determined and therefore uncorrelated with the JHIC score, a positive valuation of quality should show up in demand and we indeed find a strong quantity response with a 1 SD increase in the JHIC score associated with a 3.1 percentage points increase in outpatients among public facilities.

These results strongly suggest that (a) consumers placed a premium on safety as measured by

> 19Throughout the paper, unlicensed refers to facilities that do not have a license or have an expired license.

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