State Job Data Against Patents

What does the trend for utility patents look like compared to state job growth/loss figures?
 

The data in the below chart via a downloadable Excel file

One of the more powerful data partitions for utility patent counts is by year, whether it's regional, class or organizational data. Using these yearly data points, we can search for trends within a data set, as well as correlations across trends of joined data. We've explored the implications of economic data with respect to organizational patents with our visualization on Apple Inc.'s recent history (https://developer.uspto.gov/visualization-detail/apple). This visualization uses yearly state job data from the Bureau of Labor Statistics, presented against yearly state patent count data. The BLS data source offers four different data buckets for jobs, which we aggregate into job losses and job gains total, and job net change. We can select between a given Job Measure using the Job Measure Selector parameter control on the right. We can compare this data against either Utility Patent Count (the raw value) and Utility Patents per 1000 People (which accounts for population variance). We then use a polynomial trend line on these two measures to sketch out the tendency of the data set.

Job Net Change turns out to generally be too chaotic to draw a meaningful trend line (having an extremely low R-squared value). The other data points and aggregations, however, are generally smooth enough to have a meaningful trend line. What we find is that there's a rather strong correlation between the other job data sets and aggregations (where the Job Loss sets and aggregations are inversely correlated). This correlation is odd, however, in that the trend for Utility Patents per 1000 People is contracted compared to, say, the Job Gain Total, for all states ('(All)' in the State dropdown). The patent count trendline swings upward slightly after the job measure trendline, falls into its valley well before the job measure does, and climbs back upwards well before.

This points to possible limitations in this analysis. Since the lag isn't consistent, the correlation is suspicious, and may not hold for the next ten or twenty years of data. Naively extrapolating from the current correlation trend would have the patent measures predicting the job trend from an increasingly large period of time, which is clearly absurd. Additionally, this job data has a narrow scope, representing only the last 20 years, and is significantly impacted by the economic downturn in the last decade.

On a final note, it's intriguing that the data for some states is actually very different from the trends in the aggregation data for all states. The Job Gain Total and Utility Patents per 1000 People trendlines for the state of Maine, for example, is very loosely correlated. These divergences may point toward a better understanding of how the economic and patenting outlook for these states differs from the nation at large. Why is Maine's correlation so loose? What about Mississippi?

Sources:
PTMT - Extended Year Set - Patent Counts by Country, State, and Year - Utility Patents (December 2014)
http://www.uspto.gov/web/offices/ac/ido/oeip/taf/cst_utlh.htm

BLS - Annual BED data by state - Table 1 (multiple)
http://www.bls.gov/bdm/bdmann.htm#state

Census Population Estimates
http://www.census.gov/popest/data/state/asrh/1980s/tables/st6070ts.txt
http://www.census.gov/popest/data/state/asrh/1980s/tables/st7080ts.txt
http://www.census.gov/popest/data/state/asrh/1980s/tables/st8090ts.txt
http://www.census.gov/popest/data/state/totals/1990s/tables/ST-99-03.txt
http://www.census.gov/popest/data/intercensal/state/tables/ST-EST00INT-01.csv
https://www.census.gov/popest/data/state/totals/2014/tables/NST-EST2014-01.csv

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