International price differentiation in pharmaceuticals based on Ramsey prices has been widely discussed in the literature while empirical studies have assessed its validity indirectly by estimating the relationship between prices and income. The present study evaluates the Ramsey pricing of pharmaceuticals by directly analyzing whether pharmaceutical prices vary inversely with the price elasticities of demand and derives a pricing rule in case of interdependent demand and price distortions via insurance coverage. In this regard, it first develops a theory to analyze the Ramsey pricing of pharmaceuticals by considering important confounding factors such as insurance, income, and cross-prices. Then it identifies and estimates the price elasticities of demand for 33 molecules in 34 countries for the period 2008-2020 by using recently developed double/debiased machine learning methods. The results overall support the inverse elasticity rule with nuances. Within national markets, the evidence of Ramsey pricing is moderate with strong cross-elasticity effects. On the other hand, Ramsey prices for generics are prevalent across countries.
The inverse elasticity rule in pharmaceuticals: a theoretical and empirical analysis / Nutarelli, Federico; Buyukyazici, Duygu; Riccaboni, Massimo. - (2025).
The inverse elasticity rule in pharmaceuticals: a theoretical and empirical analysis
Nutarelli Federico;Buyukyazici Duygu;Riccaboni Massimo
2025
Abstract
International price differentiation in pharmaceuticals based on Ramsey prices has been widely discussed in the literature while empirical studies have assessed its validity indirectly by estimating the relationship between prices and income. The present study evaluates the Ramsey pricing of pharmaceuticals by directly analyzing whether pharmaceutical prices vary inversely with the price elasticities of demand and derives a pricing rule in case of interdependent demand and price distortions via insurance coverage. In this regard, it first develops a theory to analyze the Ramsey pricing of pharmaceuticals by considering important confounding factors such as insurance, income, and cross-prices. Then it identifies and estimates the price elasticities of demand for 33 molecules in 34 countries for the period 2008-2020 by using recently developed double/debiased machine learning methods. The results overall support the inverse elasticity rule with nuances. Within national markets, the evidence of Ramsey pricing is moderate with strong cross-elasticity effects. On the other hand, Ramsey prices for generics are prevalent across countries.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

