Macro Roundup

Ben Southwood, “The Rise And Fall Of The Industrial R&D Lab,” Works In Progress, August 28, 2020, https://www.worksinprogress.co/issue/the-rise-and-fall-of-the-american-rd-lab/

“…No one is quite sure why the lab model failed. It’s obvious that a scenario where Xerox is paying scientists to do research that ultimately mostly benefits other firms, potentially even competitors that help to put it out of business, could never survive. Similarly, the tension between managing scientists with their own pure research goals in such a way that they produce something commercially viable, while still leaving them enough latitude to make important leaps, seems huge. But these problems were always there in the model.What is harder to identify is an exogenous shock or set of shocks that changed the situation that existed from the 1930s until somewhere between the 1960s and the 1980s. One possibility is antitrust enforcement. From 1949 authorities pursued a case against AT&T’s Bell Labs, which ultimately resulted in the forced divestiture of their non-telecoms arms, separation from their vertically integrated manufacturing, and compulsory no-fee licensing of all 7,820 of its non-telecoms patents (1.3% of the total stock of patents in force in the USA at the time). There is evidence that this move rippled across the US economy, providing a foundation for many of the great innovations of the next fifty years. But this would be true of almost any mass patent invalidation: the monopoly restrictions of patents once they are granted are the cost we pay for the investment in innovation that came before. As well as spurring innovation outside, as a one off, this move likely had a chilling effect on innovation in big firms’ R&D labs. Later enforcement actions, such as the 1974 suit that eventually led to AT&T’s 1982 breakup, would have pushed in the same direction.These actions reduced the incentive to generate precisely the game-changing general purpose technologies that we want. They did this by creating a risk that if you did go from zero to one and manage to gobble up the whole marketplace, you’d have that taken away. What’s more, they reduced the size, scope, and vertical integration of firms—and all of these mean that innovation spills over more, and is captured less by the firm. If antitrust means that large, extensive businesses like AT&T are more likely to be broken up, there is less value in research that can only be captured by businesses that are or can become large and extensive…..…There is a promising spark of big lab activity. Big Tech firms are investing heavily in machine learning, neural nets, and other artificial intelligence research. Google employs 1,700 AI researchers who write more highly collaborative, better-cited papers than university authors, work with more expensive and advanced equipment, and use bigger datasets. Large firm publications in machine learning are then feeding into the patents of other firms, and thus spilling over to society in general. Google X funds ‘moonshot’ high-risk, high-reward, ideas, including Google’s self-driving car and other projects like Google Glass and balloon internet for rural areas. Prof. Arora and collaborators think this return to R&D is driven by fears of a new wave of anti-tech antitrust enforcement: Google and Facebook invest in research because buying it through acquisitions has become more difficult legally. But the case for the opposite is just as strong: they attract antitrust ire because their internal investment has paid off and they have taken huge shares of various markets on the back of it. In this opposite story, a small recent return to R&D labs would come down to the long term effects of the relatively weaker antitrust enforcement seen since the1980s. Smashing up today’s big businesses in a reenactment of the decisions that brought down the Bell system would be likely to have similar effects now as it did then. Their large scale and scope, and relative confidence that they will be able to benefit from technologies they develop at least somewhere in their firm is a key reason they spend so much time innovating. It looks likely that America will continue to drive the world’s research for a considerable period. American innovation is likely to go along one of two paths - or perhaps a blend of the two. Perhaps antitrust bodies will be restrained, and we will see the return of various large in-house labs. This, combined with the increased scientific contribution of India, China, and other rising powers, could see productivity speeding ahead at the clip of the 1960s once again….”

Note the writer argues that one reason FB and Google invest so much in research is the difficult of buying new IP because of anti-trust issues which is at odds with how I think of how innovation is working today which is more buy versus build (pharma acquiring small promising biotech firms)

Hypothesis that the reason major industrial labs failed was anti-trust action, and the danger more aggressive competition policy could pose to the “new” industrial labs like Google.

Study finds that black led violent protest related to the murder of MLK likely caused a 1.6-7.7% shift in white voters towards Nixon in the 1968 election; counties that saw non-violent protests saw a +1.3-1.6% shift to democrats. Wasow initial research was from 2017 but this was just released

“…Evaluating black-led protests between 1960 and 1972, I find nonviolent activism, particularly when met with state or vigilante repression, drove media coverage, framing, Congressional speech and public opinion on civil rights. Counties proximate to nonviolent protests saw presidential Democratic vote share among whites increase 1.3-1.6%.Protester-initiated violence, by contrast, helped move news agendas, frames, elite discourse and public concern toward “social control.”In 1968, using rainfall as an instrument, I find violent protests likely caused a 1.6-7.9% shift among whites towards Republicans and tipped the election…....finds violent protests caused a significant negative shift in the county-level vote share of about 5.6 to 7.9 percentage points

Kate Wong, “How Scientists Discovered The Staggering Complexity Of Human Evolution,” Scientific American, September 2020, https://www.scientificamerican.com/article/how-scientists-discovered-the-staggering-complexity-of-human-evolution/

“…The brain evolved on quite a different schedule. Over the course of human evolution, brain size has more than tripled. A comparison of the braincase ofA. afarensiswith that of the much olderSahelanthropus, however, shows thathardly any of that growth occurred in the first few million years of human evolution. In fact, most of the expansion took place in the past two million years, perhaps enabled by a feedback loop in which advances in technology—stone tools and the like—gave hominins access to more nutritious foods such as meat, which could fuel a larger and thus more energetically demanding brain, which in turn could dream up even better technology, and so on. Shifts in the shape and structure of the brain accompanied these gains, with more real estate allocated to regions involved in language and long-range planning, among other advanced cognitive functions…. From the rich assortment of fossils and artifacts recovered from around the world in the past century, however, paleoanthropologists can now reconstruct something of the timing and pattern of human evolution. The finds clearly show that this single-file scheme is no longer tenable. Evolution does not march steadily toward predetermined goals. And many hominin specimens belong not in our direct line of ancestry but on side branches of humankind—evolutionary experiments that ended in extinction…From the outset, our defining traits evolved not in lockstep but piecemeal….”

The universe self organizes beyond just gravity coalescing matter into stars where the push of fusion balances the offsetting pull of gravity and radiates energy that powers evolution, that seems to follow a sequence, that eventually self organizes itself into Ford Motor Company. Yes mutation is random and seemingly without purpose, but what it gradually discovers seem sequenced and organized. Evolutionist seem to see only the tail (random mutation) and not the dog--the thing that organize the sequence of discovery, which scythe structure of value.

And yet clearly the positive feedback loop is driven by the value of discovering and using things of value—the value of bigger brains, weapons, more calories and good ideas, none of which would evolve were it not the case.

“Evolution does not march steadily toward predetermined goals.”

And then in the next:

“Perhaps enabled by a feedback look, in which advances in technology -stone tools and the like—gave hominins access to more nutritious food such as meat, which could fuel a larger and thus more energetically demanding brain, which in turn could dream up better technology, and so forth.”

Erin Crust, Mary Daly and Bart Hobijn, “The Illusion of Wage Growth,“ Federal Reserve Bank Of San Francisco, August 31, 2020, https://www.frbsf.org/economic-research/publications/economic-letter/2020/august/illusion-of-wage-growth/

“…Recent data show that median usual weekly earnings of full-time workers have grown 10.4% over the four quarters preceding the second quarter of 2020. This is a 6.4 percentage point acceleration compared with the fourth quarter of 2019. The median usual weekly earnings measure that we focus on here is not an exception. Other measures of wage growth—like average hourly earnings and compensation per hour—show similar spikes…. we dig deeper into the data and show that this spike in wage growth primarily reflects the departure of low-wage workers who have been laid off due to coronavirus disease 2019 (COVID-19) and are no longer counted in the aggregate wage series….

Wage statistics are being skewed by the disproportionate lay-offs of low-wage workers. good FRBSF chart looking at growth in median wages for workers continuously employed. Not that surprising, but interesting the effect wasn’t more pronounced during the Financial Crisis

A married couple with two average earners (103,800) who retires in 2020 year will receive $1,167,00 in Medicare and Social Security benefits, in exchange they will have paid $760,000 in taxes for a net benefit of $407,000 over their lifetime.

For that same couple retiring in 2030 the net benefit is $529,000, for 2040 the net benefit is $718,000

"...The following tables show the expected present value at age 65 of benefits received in retirement and taxes paid over a career for households with different earnings and marriage histories. The underlying data come from the 2018 Social Security and Medicare trustees’ reports (Social Security Board of Trustees 2018; Medicare Boards of Trustees 2018) and supplemental data published by the Social Security Administration and Centers for Medicare & Medicaid Services (CMS). For Medicare lifetime benefits, we use an alternative cost scenario that CMS developed based on its concern that measures in current law would result in a rate of decline in reimbursement rates relative to private health insurance that were not sustainable. (See the discussion of the Medicare cost scenario on page 23. In calculating expected present values, we use sex-adjusted probabilities to account for chance of death after age 65 and a discount rate of 2 percent plus inflation...."

Robert Gordon and Hassan Sayed, "Transatlantic Technologies: The Role of ICT in the Evolution of U.S. and European Productivity Growth," National Bureau Of Economic Research, June 2020, https://www.nber.org/papers/w27425

“…. Stepping back and viewing the postwar growth experience more broadly, the EU-10 started out in 1950-72 with rapid productivity growth of 4.86 percent per year, which we have previously interpreted as reflecting a process of catching up to the benefits of innovations that had buoyed U.S. productivity growth during the interwar and wartime periods…. Then the EU-10 transitioned to a slower productivity growth path of 2.31 percent in 1972-95, mimicking the 2.54 percent growth rate that the U.S. had previously achieved during 1950-72. Skipping over the very different experiences of 1995-2005, the EU-10 wound up in 2005-2015 with a productivity growth rate of a mere 0.63 percent, little different from the U.S. rate for the same interval of 0.87 percent. The remarkable similarity of the U.S. slowdown to 2005-15 from 1950-72 with the EU-10 slowdown to the same late interval from 1972-95 is, we think, more than a coincidence. The same process of the diminishing potency of ongoing innovation was occurring on both sides of the Atlantic. In short the postwar transatlantic productivity experience can be boiled down to three issues - the causes of the overall joint early-to-late slowdown, the sources of the temporary U.S. 1995-2005 acceleration, and the factors that held Europe back from enjoying a similar 1995-2005 revival. Our diagnosis of the first is the diminished impact of innovation over the postwar period that operated on both sides of the Atlantic, of the second is the U.S. success during 1995- 2005 in achieving a one-time boost in the level of efficiency in the production and use of ICT, and of the third is the multi-faceted failure of the EU-10 to mimic the U.S. achievement in producing ICT hardware, in making a similar level of investment in ICT, and in capturing the efficiency gains of the lower level of investment that actually occurred.….”

Looking at the two growth experiences overall Gordon argues they broadly mirror each other and support his thesis of the declining impact of innovation in contrast with previous waves of innovation:

“…Why did the EU-10 fail to benefit from the ICT revolution and instead why did it experience a two-step slowdown in labor productivity and TFP growth? The diagnosis has four components. First, despite all the U.S.-led innovation that drove its ICT-hardware EM industry to register a 17 per cent annual rate of productivity growth in 1995-2005, that same industry in the EU-10 actually experienced a productivity growth slowdown during the same decade. Second, the EU-10 had substantially lower values of the contribution-based ICT-use-intensity indicator variable, indicating less rapid growth of ICT investment. Third, the regressions reveal virtually no difference in the extent of the EU growth slowdown experienced by ICT-intensive versus non-intensive industries, indicating a failure of EU-10 industries to exploit the efficiency opportunities provided by the limited ICT investment that did occur. And fourth, the EU-10 shortfall in productivity growth during 1995-2005 can be traced to particular industries in which performance fell far short of the same industries in the U.S.These outlier industries include not just ICT-producing electric machinery but also agriculture, petroleum refining, and the large wholesale and retail sector where for many reasons EU nations lagged behind the U.S in adopting the big-box retail format which exploited the opportunities provided by the ICT revolution….”

They also examine why the EU10 failed to benefit from the diffusion of ICT:

We find that additionalproductivity growth in ICT intensive industries drove almost all of the post-1995 revival in U.S. productivity growth. However,this change in growth occurred almost entirely in services-producing industries rather than commodities-producing industries except for the electric machinery industry that produces computer hardware. This makes sense because the most intensive users of ICT were industries in the services sector. The EU-10 story is quite different. Productivity growth in producing computer hardware in the EU-10 actually slowed after 1995 in contrast to its explosive growth in the U.S. Further in the EU-10 there was little difference between the productivity growth slowdown after 1995 and after 2005 in industries that were intensive in ICT use versus the non-ICT industries. Europe not only invested less in ICT hardware but failed to reap its benefits even in industries that were heavy ICT users….”

He then looks the drivers of the decline in terms of sectors:

“…A retardation in the growth of labor productivity and of total factor productivity (TFP) has characterized both the United States and western Europe, in the sense that on both sides of the Atlantic growth has been slower since 2005 than it was before 1995. The notable difference in performance occurred in the middle interval of 1995-2005, when a sharp acceleration of growth in the U.S. contrasted to a growth slowdown in western Europe. As a result, the story of U.S. productivity growth since the mid-1970s has been one of slow-fast-slow over the three intervals divided at 1995 and 2005, in contrast to a two-step deceleration in Europe.…”

His research finds the decline in productivity growth was a three step process in the US (with an uptick btw 1995-2005) versus a steady decline in the EU10:

New Gordon argues that the ICT Revolution (Information-Communication Technology) is best understood as a temporary technological shock due to the lag in productivity growth after 1995. The uptick in productivity growth btw 1995-2005 was driven by the electronics manufacturing industry and ICT using service sector. Europe is a disaster, the E10 was unable to reap benefits (in terms of productivity growth) from ICT due to lack of response to ICT investment, as opposed to sheer absence of ICT investment.