This paper analyzes the consequences of parallel trade on health care systems in a two-country model with a vertical distributor relationship. In particular, two cost-sharing systems - coinsurance and indemnity insurance - are compared with respect to changes in copayments and public health...

This paper studies interaction of pharmaceutical regulation and parallel trade in a North-South framework. An innovative Örm located in the North can sell its drug only in the North or in both countries. Governments may limit reimbursement for the drug. Reimbursement limits reduce the Örmís...

Although personalized medicine is becoming the new paradigm to manage some diseases, the economics of personalized medicine have only focused on assessing the efficiency of specific treatments, lacking a theoretical framework analyzing the interactions between pharmaceutical firms and healthcare...

We investigate the welfare impact of parallel imports using a large panel data set containing monthly information on sales, ex-factory prices, and further product characteristics for all 700 antidiabetic drugs sold in Germany between 2004 and 2010. We estimate a two-stage nested logit model of...

We investigate the welfare impact of parallel imports using a large panel data set containing monthly information on sales, ex-factory prices, and further product characteristics for all 700 anti-diabetic drugs sold in Germany between 2004 and 2010. We estimate a two-stage nested logit model of...

We investigate the welfare impact of parallel imports using a large panel data set containing monthly information on sales, ex-factory prices, and further product characteristics for all 700 anti-diabetic drugs sold in Germany between 2004 and 2010. We estimate a two-stage nested logit model of...

Human decision-making differs due to variation in both incentives and available information. This generates substantial challenges for the evaluation of whether and how machine learning predictions can improve decision outcomes. We propose a framework that incorporates machine learning on...

Human decision-making differs due to variation in both incentives and available information. This generates substantial challenges for the evaluation of whether and how machine learning predictions can improve decision outcomes. We propose a framework that incorporates machine learning on...