Catalog of Holdings

Study Report

Study Number: CA-050-001-1-1-United States-ICPSR-1987

Subject Area: Economic Attitudes and Behavior

Bibliographic Citation: Estimating the elasticities of demand for cocaine and heroin with data from 21 cities from the Drug Use Forecasting (DUF) program, 1987-1991.  [machine-readable data file] / Caulkins, Jonathan P.  [principal investigator(s)] / Ann Arbor, MI: Inter-university Consortium for Political and Social Research  [distributor].

Originating Archive Number: 6567

Date Accessioned: 7/9/1997

Number of Files Received: 1

Comments: This study is received on ICPSR periodic release CD-ROM, PCD97001. All its files are stored under subdirectory, S6567. The data files, the codebook file, the SAS statements files and the SPSS statements files are stored in self-extracting compressed format.

Access Status: Restricted to UW-Madison only

Date Ordered: 6/1/1997

Documentation: Machine-readable codebook file, SAS statements files and SPSS statements files.

Abstract: The objective of this research was to estimate the elasticity of the demand for cocaine and heroin with respect to the price. Price elasticity is the percentage of change in the dependent quantity corresponding to a one-percent change in price. The project involved the development of an econometric model to determine price elasticity, given that national- and city-level data on the consumption of cocaine and heroin are insufficient or nonexistent. The researchers circumvented this lack of data by partitioning the desired elasticity into the product of two elasticities, involving a measurable intermediate quantity whose relationship to the quantity of consumption could be modeled and estimated by measurable techniques. The intermediate quantity used for this project was the fraction of arrestees testing positive for cocaine or heroin as measured by the Drug Use Forecasting (DUF) System. From the Drug Enforcement Administration's (DEA's) System to Retrieve Information from Drug Evidence (STRIDE) data, expected purity was computed by regressing on log quantity and dummy variables for location and quarter. Price series were produced by finding the median standardized price per expected pure gram for each location and quarter. Variables for Part 1, National Data, include year, quarter, standardized prices for a gram of cocaine and a gram of heroin, and expected purity of cocaine and heroin. The Cities Data, Part 2, cover city, year, quarter, number of observations used to compute the median price of cocaine and heroin, standardized prices, and expected purity

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