Full metadata
Title
State R&D Tax Credits: Social and Economic Outcomes
Description
Research and Development (R&D) tax credits are one of the most widely adopted policies state governments use to incentivize R&D spending by firms operating in a state. R&D spending is associated with increases in firm productivity, innovation, and higher wages. However, most studies into these tax credits examine only the effect the credit has on firm-based R&D spending and assume the increases in R&D spending mean states are receiving the social and economic benefits endogenous growth theory predicts. This dissertation connects R&D tax credits with the expected outcomes of R&D spending increases to evaluate the efficacy of the tax credits. Specifically, the dissertation connects R&D tax credits to the movement of researchers between states, innovative activity, and state fiscal health. The study uses a panel of U.S. PhD graduates and a fixed-effects linear probability model to show R&D tax credits have a small but statistically significant impact on PhDs moving to states that have the tax credit. Using a structural equation model and a latent innovation variable, the dissertation shows R&D tax credits have a small but significant impact on innovative activity mediated by R&D spending. Finally, the dissertation examines the effect of R&D tax credits on a state’s short- and long-run fiscal health by using a distributed lag model to illustrate R&D tax credits are associated with decreases with fiscal health.
Date Created
2020
Contributors
- Selby, John David (Author)
- Bretschneider, Stuart (Thesis advisor)
- Bozeman, Barry (Committee member)
- Siegel, Don (Committee member)
- Swindell, David (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
107 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.62714
Level of coding
minimal
Note
Doctoral Dissertation Public Administration and Policy 2020
System Created
- 2020-12-08 11:58:31
System Modified
- 2021-08-26 09:47:01
- 3 years 2 months ago
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