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Presented by Indraneel Kumar, AICP Eda Unal Purdue Center for Regional Development

Exploring Patents & Citations Using GIS 2008 Indiana GIS Conference Indiana Geographic Information Council. Presented by Indraneel Kumar, AICP Eda Unal Purdue Center for Regional Development Purdue University. Why Study Patents & Citations?.

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Presented by Indraneel Kumar, AICP Eda Unal Purdue Center for Regional Development

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  1. Exploring Patents & Citations Using GIS2008Indiana GIS ConferenceIndiana Geographic Information Council Presented by Indraneel Kumar, AICP Eda Unal Purdue Center for Regional Development Purdue University

  2. WhyStudy Patents & Citations? • Patents are considered “output indicators” of innovation • Inventors are part of human capital • Citations are used to study “knowledge flows”; spillovers; feedback effects • Knowledge-based assets • Innovation & inventors are essential for the knowledge economy

  3. Outline • National trends • Indiana trends • Citations database • Next steps • Acknowledgements

  4. Top Ten Patents From U.S.

  5. Patents 1991-1994

  6. Patents 1995-1998

  7. Patents 1999-2002

  8. Exploratory Spatial Data Analysis Patents, 2002 Percentile Distribution Patents, 2000 Percentile Distribution • Percentile distribution of number of patents by states does not change significantly year-by-year • From 2000-2002, Illinois lost, Michigan gained • From 1996-2000, distribution remained almost identical

  9. Exploratory Spatial Data Analysis Patents per 100,000 population, 2000 Patents per 100,000 population, 2002 • Percentile distribution of number of patents per 100,000 population by states shows a different pattern • Idaho is leading followed by Minnesota, Vermont, & Massachusetts during 2000-2002

  10. Exploratory Spatial Data Analysis Patents per 100,000 Employment, 2000 Patents per 100,000 Employment, 2002 • Percentile distribution of number of patents per 100,000 employment similar to population • Idaho, Minnesota, Vermont, Massachusetts, & California

  11. Exploratory Spatial Data Analysis • Scatter plots between patents, total employment, professional and technical services, and health care and social assistance employment • BEA, data suppression issues

  12. Exploratory Spatial Data Analysis • Does a state with high/low patent counts affect its neighbors? • Spatial clustering exists or not? • Do other economic variables affect patents or not? • Spatial autocorrelation improves after removing • the outliers

  13. Exploratory Spatial Data Analysis • Patents vs. Spatial Lag variables of Total Employment and Professional and Technical Employment in 2002 • Excluding a few outliers, the direction of slope does change

  14. Patents From Indiana • From Year 1963-2002; 43,485 Utility Patents were granted • First Inventor’s home address is Indiana • At a state level, home and work place address usually is the same • Exception is the counties at the “Edge” neighboring major metropolitan areas (Northeast Indiana & Chicago; Dearborn County & Cincinnati) • At a metropolitan level, home and work place address might match

  15. Patents From Indiana • At a county level, home and work place address might not match • Inter-county commuting is prevalent in Indiana, particularly within metropolitan areas • Selection of spatial scale is important !!! • Exploratory Spatial Data Analysis (ESDA) reveals that a sub-state geography might be a useful scale for study

  16. Top Ten Patents From Indiana by Class

  17. Determining Patent Citations: Class 514 • Class 514 Indiana Patents in 2002 • 102 Patents Cited 917 Patents • 25 Different States including Indiana • 30% Cited Patents are from other countries Citing-Cited Database (22 million records) Patents Database (3.4 million records)

  18. Determining Patent Citations: Class 514

  19. Determining Patent Citations: Class 514

  20. Determining Inventors in progress….

  21. Determining Inventors in progress….

  22. Next Steps • Tests of significance • County level mapping by different patent classes • County level distribution of inventors • Relationships to regional growth, if any!

  23. Acknowledgement • In this presentation, the data was taken from “The NBER Patent Citations Data File: Lessons, Insights and Methodological Tools” by Brownyn H. Hall, Adam B. Jaffe, and Manuel Trajtenberg; University of California at Berkeley • Florida International University • Spatial Analysis Laboratory, GeoDa, UIUC • ET GeoWizards; Hawths Tools • ESRI ArcGIS Spatial Statistics Toolbox

  24. Thank You!! Indraneel Kumar- ikumar@purdue.edu Eda Unal- unale@purdue.edu

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