ABSTRACT
We use the number of finalists and winners recognized by the Innovations in American Government Awards (IAGA) programme to measure state government innovativeness from 1986 to 2013. The measure is moderately related to two existing state policy innovativeness indexes. The fifty states vary remarkably and persistently in government innovativeness, which is more driven by internal antecedents than external ones. We find that between-state effects outperform within-state effects in explaining government innovativeness. We also reveal that government ideology, citizen ideology, and social capital are positively related to government innovativeness. The index developed in this study can be used in pertinent studies, and the findings contribute to the literature on public sector innovation.
Acknowledgement
An early version of this manuscript entitled ‘Measuring and Explaining the U.S. State Government Innovativeness’ has been presented on the Social Innovation Research Conference (SIRC) organized by the School of International Affairs and Public Affairs, Fudan University, Shanghai, China, 21st–22nd May 2015. I owe a debt of thanks to Sandford Borins, whose valuable comments and suggestions are of great help to improve this manuscript. I would like to thank Frederick J. Boehmke, Bin Chen, Steven Kelman, Richard Walker, and Yin Wang for helpful suggestions. I am also grateful to the anonymous reviewers’ informative and constructive comments. Financial support from Lien Foundation at Singapore and Renmin University of China is also appreciated. All errors remain my own.
Disclosure statement
No potential conflict of interest was reported by the author.
Supplementary material
Supplemental data for this article can be accessed at http://dx.doi.org/10.1080/14719037.2016.1177108
Notes
2. We exclude Washington, D.C. from our analysis due to missing data.
4. The data are available at: http://rcfording.wordpress.com/state-ideology-data/
5. We also use the original data and the primary results remain unchanged (see Supplemental Table 3).
6. The data are available at: http://perg.tamu.edu/PERG/Data.html. The data of Alaska and Hawaii are unavailable.
7. State government size is measured by the number of full-time equivalent employees from the US Census Bureau.
8. The original data are from the Annual Survey of State Government Finances, and we use structured data available at: http://slfdqs.taxpolicycenter.org/pages.cfm
11. The data on total personal income are from the US Bureau of Economic Analysis and we derive implicit gross domestic product (GDP) price deflator from the National Income and Product Accounts (NIPA). See: http://www.bea.gov/regional/ and http://www.bea.gov//national/nipaweb/DownSS2.asp
12. The data are from the US Bureau of Economic Analysis.
13. The data are gleaned from Google geodata available at: http://www.distancefromto.net/us-state/Massachusetts
14. Federal government involvement as a binary variable is not log transformed.
15. The above results imply that the between-state effects predominate in the variations of state government innovativeness, and we also aggregate the data into cross-sectional structure to re-estimate the models. The results are reported in Supplemental Table 4, and the key findings remain unchanged.
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Liang Ma
Liang Ma is an associate professor at the School of Public Administration and Policy, Renmin University of China, China and a senior research fellow at the Nanyang Centre for Public Administration, Nanyang Technological University, Singapore. He earned his PhD from School of Management, Xi’an Jiaotong University, China. His research interests are public organizational innovation and public service performance.