How MDMA flows across the USA: evidence from price data

This study uses wholesale prices of MDMA for 59 cities in the USA published by the National Drug Intelligence Center (NDIC) over the period of 2002–2011 to identify trafficking patterns of MDMA. Price differentials and correlations between pairs of cities are used to infer the presence of a link and the direction of flow of MDMA. The presence of inward and outward links is used to categorise each city as a ‘source’, ‘destination’, ‘transit’, or ‘weakly integrated’ city. The analysis identified low prices close to the Canadian and Mexican borders, in a number of cities such as Chicago, Miami, New York City, a trio of cities in the Carolinas, and along the West Coast. A number of these cities are linked to large numbers of other cities, indicating hub- or source-like status. The findings generate insights into the status of major US cities in the MDMA trafficking network.     

Increasing the transparency of stated choice studies for policy analysis: Designing experiments to produce raw response graphs

We believe a lack of transparency undermines both the credibility of, and interest in, stated choice studies among policy makers. Unlike articles reporting the results of contingent valuation studies, papers in the stated choice literature rarely present simple tabulations of raw response data (that is, a table or graph showing the percentage of respondents agreeing to purchase a good or service, or vote for a proposed management plan as a function of price). We describe an approach for adding “policy” tasks to a standard orthogonal‐in‐attribute‐levels research design that allows the researcher to plot raw responses as a function of changes in only one characteristic of the offered good or service. We demonstrate this approach using data from a stated choice study of private demand for cholera and typhoid vaccines in Kolkata, India, carried out in the summer of 2004. © 2006 by the Association for Public Policy Analysis and Management.     

Effect of testing and social distancing measures on COVID-19 deaths in India: Role of pre-existing socio-economic factors

We examine the effect of testing and social distancing measures on the severity of COVID19 across Indian states during the 68th day nationwide lockdown period. We also explore whether pre-existing socio-economic factors such as quality of health care and the ability to practice social distancing influences the effect of these policy measures across states. Using daily level data between April 1 and May 31 for 18 of the major states, we find that both testing and social distancing have a negative effect on COVID-19 fatalities in India. Further, testing is more helpful in reducing CFR for states with lower per capita health expenditure and weaker medical infrastructure. This highlights how ramping up testing can aid states that have a weak health care system through the detection of infection, contact tracing and isolation. In contrast, social distancing measures are more effective in states that are less populous and have lesser people dwelling in single-room houses. Our results confirm the role of pre-existing institutional factors in shaping the effect of policy actions on health outcomes.