We study the question of whether women, on average, pay a price premium — a so-called“pink tax”—for the products they buy. A particular concern facing policy makers is whether such differences are a form of gender based price discrimination. Using scanner data, we find that averaged across the entire retail grocery consumption basket, women pay 4% more per unit for goods in the same product-by-location market as do men. This price differential is generated by a 15% higher average per unit price paid by women on explicitly gendered products, like personal care items, as well as a 3.8% higher average per unit price paid by women on ungendered products, like packaged food items. Higher prices paid by women could be the result of differences in demand elasticity, competitive structure, or sorting into goods with differing marginal costs. To disentangle these mechanisms, we estimate demand differences between men and women and structurally decompose price differences into markups and marginal costs. We find that women are, on average, more price elastic consumers than men, suggesting that as a consumer base women are not likely to be charged higher markups under price discrimination. Overall, we find that the pink tax is not sustained by higher markups charged to women, but by women sorting into goods with higher marginal costs and lower markups. Medical provider price transparency is often touted as a key policy for efficiently lowering health care spending, which is nearly 20% of GDP. Despite its many proponents, the impact of price transparency is theoretically ambiguous: it could lower health care spending via increased consumer price shopping or improved insurer bargaining position but could instead raise health care prices via improved provider bargaining or either tacit or explicit provider collusion. We conduct a randomized-controlled trial to examine the impact of a state-wide medical charge transparency tool in outpatient provider markets in the state of New York. In the experiment, individual providers’ billed charges (list prices) were released randomly at the procedure X geozip level. We use a comprehensive commercial claims database to assess the impact of this intervention and find that the intervention causes a small increase in overall billed charges (+1%) but a relatively lower increase in the charges for procedures with many out-of-network claims (-2%). We find no evidence for quantity effects. We find larger charge increases for specific categories that are almost always insured and less elective in nature, e.g. MRI (+6%) and radiology (+3%) and charge decreases for categories that are less often insured and more elective in nature, e.g. psychology (-2%) and chiropractor (-3%) services. Taken together, these results are consistent with our intervention having a minimal effect on consumer price shopping but a meaningful effect driving increases in providers’ charges, especially for less elective services that are almost always covered by insurance, potentially reflecting perverse price effects resulting from tacit collusion or reduced information asymmetries.