Conventional wisdom informs us that innovation leads to society’s well-being by fostering things like economic growth and higher living standards. It’s pretty much accepted that technology advancements in industrialization, computers, medical technology, and business practices are the big drivers. Economists also claim that innovation drives a specific aspect of economic strength, called productivity.

Or at least it should. An article this week in Technology Review points out that at least one innovation measure is on the decline. Researchers have noticed that since the 1973, US productivity growth has started to flatten.

Tyler Cowen, Professor of Economics, at George Mason calls it the “The Great Stagnation,” which conveniently is the same title as the book he authored. Cowen and others use a measurement called total factor productivity (TFP), which according to Wikipedia ”accounts for effects in total output not caused by inputs.” Basically it’s a metric for how efficiently the economic inputs are utilized for production. The idea is that this reflects the rate of technological advancement, aka innovation.

The chart below tells the sad tale:

The graphic is from a recent report (PDF) compiled by The Hamilton Project that tries to make some sense of what’s happening to innovation in the US. I have several problems with the report, but most of it is centered on the linkage between this TFP metric and innovation.

Anecdotally, having lived through both the pre-70s and post-70s, I can say with a fair amount of confidence that innovation in the latter era has been a lot more impressive than in the former. And not just innovation, but the rate of innovation.

From post-WWII to the 70s, the biggest advancements were the establishment of personal transportation in the modern automobile and the spread of television as the dominant media. It allowed people and goods to be transported freely across the country — at least where the roads go — and enabled near universal access to entertainment and news from homes. Not bad.

But since the 70s we’ve seen the rise of personal and mobile computing, the internet, genetic sequencing (and molecular-based medicine, in general), as well as my favorite and yours, high performance computing. So today, nearly any type of information accumulated by society can be accessed and manipulated from anywhere. To me, that’s more impressive than a 56 Chevy and a 19-inch black and white.

It also should be pointed out that even useful innovation is often ignored. Obviously in that case, it can’t get reflected in productivity. This may be especially true when the rate of innovation is so high that it’s hard for people or businesses to know when to hop aboard.

Some sectors tend to adopt technology quicker than others. For example, manufacturing and biotech have not embraced HPC with nearly the enthusiasm of say, academia and government research. And on the more personal level, technologies like VoIP, (which, as a Skype user, I can attest is a tremendous productivity booster), has yet to be picked up en masse. The reasons for resisting new technologies can be financial, educational or cultural, but they certainly play a big part in adoption.

Then there’s just the more general question whether innovation can exist independently of an economy’s productivity. Some observers have noticed that the flattening of the TFP slope after 1973 coincides with the US government’s abandonment of Keynesian economic policy (run deficits when the private sector cut back, otherwise run surpluses). The implication here is that productivity is more likely to correlate to government spending habits.

On that note, it might be worthwhile to look at what the government is spending its money on. Certainly we’ve seen funding for defense and entitlements — two areas unlikely to contribute to much to either innovation or productivity — increase substantially in the past four decades. Meanwhile US investments in R&D as a percent of GDP dropped from 2.2 percent in 1964 to about 1 percent today. But that in itself is no guarantee, given that R&D spending was below 1 percent in the 1950s, when TFP was doing just dandy.

Then there’s the observant economist who noticed that the TFP for durable goods actually increased during the past four decades, compared to the pre-70s pace. At the same time, the TFP for non-durable goods, which includes the service sector, actually flattened out (it was never very steep to begin with). Since the service sector has grown disproportionally to the durable goods sector, the overall slope of the TFP has flattened.

That’s not to say we shouldn’t do better in the innovation arena. But I do see the problem more as one of adoption than any perceived decline in innovation itself. Again, HPC users could be viewed as a microcosm of the problem. The technology has a good track record for improving productivity, with enough case studies to choke a modest-sized library. Innovation here comes in many forms — accelerators (GPUs and FPGAs), architectures (clusters, SMP machines, and exotics), and software (MPI, OpenMP, CUDA, OpenCL, and so on). The array of choices is overwhelming to the HPC newbie. Here, as elsewhere, understanding the technology is going to be the key to productivity.

In any case, be wary of reports that claim innovation is in trouble. Economists have a propensity to forecast doom scenarios, which is why economics is often referred to as the dismal science. They also love to uncover correlations like this, since that is the lifeblood of their field. But understanding the interplay between technology, economics and society is a daunting task, filled with variables that, frankly, no one fully understands.