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Graduation Term
Summer 2026
Degree Name
Master of Science (MS)
Department
Department of Technology
Committee Chair
Klaus Schmidt
Committee Member
Jaby Mohammed
Committee Member
Kim DeVico
Abstract
This study examines why the current top ten U.S. manufacturing states outperform others in productivity and innovation and how follower states can improve their performance. Focusing on the period from 2013 to 2022, it analyzes how operational factors (such as manufacturing scale, capital investment, and exports), innovation inputs and outputs (including research and development spending, patents, and high-skill employment), and workforce and policy conditions jointly shape state-level manufacturing outcomes. The research employs a state-level panel design with two fixed-effects regression equations: a productivity equation using manufacturing gross domestic product per worker as the dependent variable and an innovation equation based on a composite innovation index. Descriptive scatterplots, time-series trends, correlation analysis, analysis of variance, and fixed-effects panel regressions are used to identify statistically significant associations between these determinants and manufacturing performance over time. Results show that manufacturing scale is the strongest predictor of productivity, with capital investment having a positive but smaller effect and export intensity losing significance once scale and other controls are included. For innovation, patent activity is the most robust driver of the innovation index, while manufacturing research and development and the share of high-skill manufacturing workers exhibit positive but statistically weaker effects after controlling for patents and state and year fixed effects. Significant fixed effects indicate that structural characteristics, coordinated industrial strategies, and common shocks, such as the coronavirus disease 2019 (COVID-19) period, materially influence outcomes. The study concludes that lower-performing states should shift from broad, generic incentives to targeted, sector-specific policy bundles that deepen manufacturing scale in existing strengths, support modernization and digitalization, strengthen patenting and commercialization ecosystems, align workforce programs with priority sectors, and incorporate systematic evaluation and sunset provisions for major incentive tools
Access Type
Thesis-ISU Access Only
Recommended Citation
Omitoyin, Grace, "Productivity and Innovation Dynamics in the US Top Manufacturing States" (2026). Theses and Dissertations. 2384.
https://ir.library.illinoisstate.edu/etd/2384