The Politics of Information
Problem Definition and the Course of Public Policy in America
Frank R. Baumgartner and Bryan D. Jones
264 pages | 48 figures, 8 tables | 6 x 9 | © 2015
How does the government decide what’s a problem and what isn’t? And what are the consequences of that process? Like individuals, Congress is subject to the “paradox of search.” If policy makers don’t look for problems, they won’t find those that need to be addressed. But if they carry out a thorough search, they will almost certainly find new problems—and with the definition of each new problem comes the possibility of creating a government program to address it.
With The Politics of Attention, leading policy scholars Frank R. Baumgartner and Bryan D. Jones demonstrated the central role attention plays in how governments prioritize problems. Now, with The Politics of Information, they turn the focus to the problem-detection process itself, showing how the growth or contraction of government is closely related to how it searches for information and how, as an organization, it analyzes its findings. Better search processes that incorporate more diverse viewpoints lead to more intensive policymaking activity. Similarly, limiting search processes leads to declines in policy making. At the same time, the authors find little evidence that the factors usually thought to be responsible for government expansion—partisan control, changes in presidential leadership, and shifts in public opinion—can be systematically related to the patterns they observe.
Drawing on data tracing the course of American public policy since World War II, Baumgartner and Jones once again deepen our understanding of the dynamics of American policy making.
Blog mentions and media discussions:
Link to the Policy Agendas Project, which houses the data on which our analysis is based.
Link to the Comparative Agendas Project, providing similar data for many countries.
Click here for a spreadsheet containing the data from all the figures in our book. The name of each sheet in the file (e.g., Fig1-1 or Fig1-2) indicates the figure to which the data are associated. See the book for a complete list of figures and explanation of the measures. The attached spreadsheet allows a reader to replicate exactly any of the analyses presented in the figures.
Click here for the R code written by former UNC-CH PhD student Will Winecoff (now assistant professor at Indiana University) to create all the numeric figures in the book. These commands can be used in conjuction with the data in the spreadsheet above to re-create all the figures, and can be used as a template for other graphing projects in R. Thanks to Will for a very professional job in putting this together.
updated: July 4, 2019