As the 2012 American election ended, many media outlets began to attribute the surprise margin of victory for Barack Obama to a number of characteristics such as the strong urban and visible minority support for Obama. We here at the Martin Prosperity Institute decided to take a closer look at the interactions between geography and the voting patterns, in relation to other attributes. This analysis culminated in a whitepaper that was released today. The whitepaper examines the voting patterns across all U.S. metros and their relationship to population, GDP, patents awarded and Creative Class occupations. By examining these relationships, it allows for a greater understanding of the characteristics of regions that voted for a particular candidate. This Insight is the first of two and will focus on 2012 voting patterns and patents. Previous Insights have looked at which regions are the most innovative, and this Insight indicates how these regions voted.
The metrics used in this Insight are the same as in the whitepaper. We applied the voting shares for the candidates within each metro to the population, GDP, patents and Creative Class data. We then used these results to determine if/how each metro’s individual voting results contribute to the population, GDP, patents, and Creative Class totals for each respective candidate. After this, we calculated the cumulative results for each of the candidates across the four variables.
Technological innovation and the competitiveness that often ensues are central to economic development, and this is partially why MPI chose to examine innovation (patents) in relation to geographic voting patterns. Exhibit 1 displays a top ten list of the metros that contribute the highest share to the total number of patents awarded within the U.S. The first column displays the top ten metros with the highest individual patent share of total patents produced, while the second and third columns show the top ten metros that contribute the most to the respective candidate’s total patent share (as weighted by voting share). At first glance, one can see that for both Obama and Romney, the combination of all non-metro areas contributes the largest and approximately the same amount to each candidate’s total patent share than any single metro. While for both candidates San Jose is the largest single metro contributor, a trend develops in which leading tech metros contribute a much larger share to Obama’s patent total than Romney’s. Other large tech centers such as San Francisco, Boston, Seattle and New York are all examples of metros that contribute a larger amount to Obama’s total patent share. In the case of San Francisco, the share attributed to Obama is more than triple that to Romney. Houston, Dallas and Phoenix are metros that contributed to a larger share of Romney’s patent total than Obama’s. Atlanta, surprisingly contributed an almost even share to both candidate’s total.
Exhibit 1: Top 10 contributors to patent share
When looking at smaller rising tech hubs such as Rochester, NY; Albany, NY; and Rochester, MN, Obama generally captured a greater amount of the vote. Huntsville, AL; Wichita, KS; Boise/Nampa, ID and Lexington, KY though are some of the thriving tech hubs that contributed a greater share to Romney’s patent total than Obama’s. This is not surprising as each of the aforementioned metros is within strong Republican voting states. What we found quite interesting within the analysis is that other than in the previously mentioned metros, not only did Obama generally fare better within Democratic metros that are very innovative, Obama generally did well in innovative metros despite their location. Tucson, AZ; Durham, NC; Raleigh, NC; and Austin, TX are all metros with high numbers of patents awarded (total and per capita) in strong Republican voting states, that contributed a larger amount to Obama’s total patent share than Romney’s. What this might suggest is that Obama’s appeal and subsequent strong voting share within some of the most technologically advanced regions in the world is partially a reason for his success in the past election.
Using our data, we also looked at the cumulative patent share that each metro contributes to the respective candidate’s total, as displayed in Exhibit 2. Displayed on the Y-axis is the cumulative patent share, and on the X-axis is each metro by total population from largest to smallest. The pink line shows the U.S. results, while the blue line is for Obama and the red for Romney. The faster a line rises the more quickly a smaller number of regions contribute to the overall total. Obama’s success in the election within tech hubs can be seen within Exhibit 2 as the gap between him and Romney, is quite substantial. The large gap is created within the highly populated metros, as Obama’s voting share within the top 25 most populated metros attributes to almost 25% of the total patents produced (about 13% for Romney) in the U.S. The gap between the two candidates continues to grow throughout the medium to small size cities, as the largest gap is found at the end of the graph. The disparity between the two candidate’s increases the greatest due to spikes in the graph found at #10 Boston, #11 San Francisco, #31 San Jose, and other large tech hubs.
Exhibit 2: Cumulative patent share
Regional prosperity is directly linked to innovation and a growing number of advanced tech hubs are starting to emerge throughout the U.S. as local businesses and policy makers try to adapt to the knowledge economy. These tech centers are becoming the economic drivers within regions, due to their innovative and productive capacities, which is why analyzing the geographic voting patterns within these areas is crucial. As displayed within this Insight, part of Obama’s success within the 2012 election can be attributed to his success within these growing tech centers throughout the U.S.
For more information regarding this Insight, please read the corresponding white paper found here. The Atlantic Cities have also looked at the interactions between the election results across a number of metrics such as education, working class share, population density, and others. That report can be found here.
The Martin Prosperity Institute at the University of Toronto‘s Rotman School of Management is the world’s leading think-tank on the role of sub-national factors — location, place and city-regions — in global economic prosperity. We take an integrated view of prosperity, looking beyond economic measures to include the importance of quality of place and the development of people’s creative potential.