What Can Social Policies Do to Innovation?

Like it or not, government socioeconomic policies influence innovation.

Some of them, e.g., R&D tax credits and innovation grants, do that in a positive way. Others, such as the notorious Prohibition of 1920-1933, deeply damaged U.S. innovation.

Traditionally the bulk of attention is focused on economic policies while the importance of the social aspect is usually overlooked.

This should change: the growing body of data suggests that social policies implemented at both federal and state levels can have a profound effect on the innovation process.

The Liberalization Premium

Solid support to the above statement comes from the 2018 study by Keyvan Vakili and Laurina Zhang. Vakili and Zhang analyzed the impact of two social liberalization policies — the legalization of same-sex marriages and medical marijuana — on patenting rates across U.S. states.

During the period covered in the study, 1990-2007, six states and the District of Columbia legalized same-sex marriages (unions or domestic partnerships before 2004), and 11 states legalized medical marijuana.

Vakili and Zhang found that starting 2-3 years post-implementation, both policies led to increased state-level patenting. The increase was by 5% for same-sex marriages and 6% for medical marijuana.

The authors presented data suggesting that the introduction of liberal policies in the affected states influenced innovation through shifting public opinions to a more open and inclusive status. Consequently, that led to the formation of new collaborations composed of individuals with more diverse backgrounds.

Vakili and Zhang also found that many patents filed after the implementation of both policies were drawn upon novel technological cross-pollination, which resulted in these patents being more original and impactful.

Vakiri and Zhang’s results shouldn’t come as a total surprise. There is enough anecdotal evidence pointing to a correlation between liberal social policies and the innovation potential of a given U.S. state. For example, one of the most innovative states, Massachusetts, was the first in the country to legalize same-sex marriages in 2004.

The Anti-Liberalization Penalty

Vakili and Zhang also analyzed the effect of one anti-liberalization policy: abortion restrictions. In 1990-2007, 34 states have passed at least one new abortion restriction, ranging from extended waiting periods, mandatory counseling, and limitations in insurance coverage to near-total abortion bans.

The passing of one additional abortion restriction reduced patenting by 1%, which roughly translates to about 21 fewer patents per year at the state level.

Such a modest reduction may not sound like a big deal. And yet, it shouldn’t be taken lightly given the changing abortion law landscape in the United States. It’s quite possible that 22 states may soon not just restrict the access to abortions further but essentially ban all or nearly all of them.

The results of these actions on innovation output in affected states are difficult to calculate.

The Regional Growth Center Angle

The above results strongly suggest that social policies influence innovation at the state level and can create a regional advantage — or disadvantage.

This is especially relevant given the idea to create eight to 10 regional growth centers in the Midwest metro areas of the United States. Central to the idea is the infusion of about $100 billion of federal money over the next 10 years in the form of direct R&D funding, tax and regulatory benefits, and infrastructure support.

Interestingly, many of these prospective growth centers are located in the states that are planning to implement the most restrictive abortion laws.

Policymakers would be wise to take this aspect into account when calculating the potential innovation outcome of this massive investment of federal money.

Image credit: Tim Marshall on Unsplash

About Eugene Ivanov

Eugene Ivanov is the Founder of (WoC)2, an innovation consultancy that helps organizations extract maximum value from the wisdom of crowds by coordinated use of internal and external crowdsourcing.
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