Macro Roundup

Merkel:”… It is a concern shared by Angela Merkel, Germany’s chancellor. In an interview with the FT this month, she said that software companies were inserting themselves into producer-customer relationships, becoming essential “intermediaries” between businesses and their clients. German companies, she warned, had missed out on this development and were now at risk of falling behind. “It’s no longer enough to merely sell a product,” she said. “One also needs to develop new products from the data on these products.” Her fear: that without this expertise, Germany could end up becoming nothing more than an “extended workbench”, a kind of glorified assembly line….”

“We have, I would say, disadvantages here,” Mr Diess tells the FT. “We don’t have the big tech companies here... and you need tech companies to partner with. So either we can go to the west coast or we can go to China. We don’t have the software skill and size. We don’t have a software industry.”

Patrick McGee and Guy Chazan, "The Apple effect: Germany fears being left behind by Big Tech,"Financial Times, January 29, 2020, https://www.ft.com/content/6f69433a-40f0-11ea-a047-eae9bd51ceba

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.”