Nominations Sought for the Julius Shiskin Award
The Washington Statistical Society, National Association for Business Economics, and Business and Economics Statistics Section of the American Statistical Association are seeking nominations for the 2017 Julius Shiskin Memorial Award for Economic Statistics.
This annual award is given in recognition of unusually original and important contributions to the development of economic statistics or the use of statistics in interpreting the economy. Contributions can be to the development of new statistical measures, statistical research, use of economic statistics to analyze and interpret economic activity, development of statistical tools, management of statistical programs, or application of data production techniques.
For more information about the award, contact Thomas Evans, Julius Shiskin Award committee secretary, at firstname.lastname@example.org or (202) 691-6354.
Individuals in the public or private sector from any country can be nominated. Completed nominations must be received by March 21. The award will be presented with an honorarium of $1,000. A nomination form and list of previous recipients are available on the ASA website.
This award was established in 1979 to honor Julius Shiskin, who at the time of his death in 1978 was commissioner of the Bureau of Labor Statistics (BLS). He earlier served as chief statistician at the Office of Management and Budget (OMB) and assistant director at the U.S. Census Bureau. At the Census Bureau, he was instrumental in developing an electronic computer method for seasonal adjustment. At OMB, he developed the policies that still govern the release of key economic indicators, and, at BLS, he directed the comprehensive revision of the Consumer Price Index (CPI), which included a new CPI for all urban consumers.
The 2016 award recipient was John Abowd, Edmund Ezra Day Professor at Cornell University and associate director for research and methodology and chief scientist at the Census Bureau, for designing and implementing disclosure avoidance techniques that enable federal statistical agencies to greatly expand the availability of their data while preserving respondents’ confidentiality and for his leadership at Cornell providing access to these data over the internet.