Europe’s sprawling new financial law enters into force
A disaster-free launch of MiFID 2 is not the end of the worries
Jan 6th 2018
AFTER years of rule-drafting, industry lobbying and plenty of last-minute wrangling, Europe’s massive new financial regulation, MiFID 2, was rolled out on January 3rd. Firms had spent months dreading (in some cases) or eagerly awaiting (in others) the “day of the MiFID” when the law’s new reporting requirements would enter into force. One electronic-trading platform, Tradeweb, even gave its clients a “MiFID clock” to count down to it.
Apprehension was understandable. The new EU law, the second iteration of the Markets in Financial Instruments Directive (its full, unwieldy name), affects markets in everything from shares to bonds to derivatives. It seeks to open up opaque markets by forcing brokers and trading venues to report prices publicly, in close to real time for those assets deemed liquid. It also requires them to report to regulators up to 65 separate data points on every trade, with the aim of avoiding market abuse.
The changes are greatest for markets, like those in bonds and derivatives, that are now largely conducted “over the counter” (ie, not on exchanges). But the law also restricts share trading in “dark pools” closed to retail investors, provides for access to European markets for non-EU firms, and requires investment banks to start charging separately for research, among myriad other provisions. It is perhaps the biggest regulatory change to European financial markets since the financial crisis.
For all the jitters, the first hours of trading under the new regime went fairly smoothly, though trading volumes were lower than usual. Financial firms had collectively spent $2.1bn preparing for MiFID 2 in 2017 alone, according to one estimate by Expand, part of the Boston Consulting Group, and IHS Markit, a data provider.
Some banks had people up all the night before the 3rd. The preparations paid off. But regulatory reprieves also helped. In late December the European Securities and Markets Authority (ESMA), an EU regulator, granted a six-month reprieve from the requirement that every counterparty to a trade must have a “legal-entity identifier”, a unique number, after many firms failed to obtain these in time. It also let trading continue across the EU even though 17 of its members had not yet fully transposed the rules into national law. And ESMA clarified that trading on non-EU venues could continue while it finishes its assessment of which jurisdictions will be deemed “equivalent”. This avoided a worst-case scenario, in which European traders suddenly lost access to the New York Stock Exchange, say, or the Chicago Mercantile Exchange.
Early on January 3rd itself, Germany’s and Britain’s regulators allowed three large futures exchanges—Eurex Clearing in Frankfurt, and ICE Futures Europe and the London Metal Exchange in Britain—to delay implementation of “open access” provisions until mid-2020. These rules, divorcing the execution of futures contracts from the clearing of them (they now occur at the same exchange), were contentious when passed, with Britain reportedly a strong proponent and Germany staunchly opposed. A London lawyer thinks the long delay, to past the date in 2019 when Britain is to leave the EU, may well mean these provisions “never see the light of day”.
Significant as they may be for parts of the market, such reprieves do not amount to a delay of the overall law, says Jonathan Herbst of Norton Rose Fulbright, a law firm. Nonetheless, a disaster-free implementation day does not mean the end of the worries. As Enrico Bruni of Tradeweb points out, market participants will adjust their trading patterns over time, and emerging problems will need to be resolved. It will take even longer to see if the structural changes the new framework is forecast to encourage—such as consolidation among brokers or asset managers—materialise. And the law may yet play a role in the Brexit negotiations. Its rules on financial-market access for third countries, after all, will apply to Britain. There are many more days of the MiFID to come.
Economists grapple with the future of the labour market
The battle between techno-optimists and productivity pessimists continues
Print edition | Finance and economics
Jan 11th 2018| PHILADELPHIA AND WASHINGTON, DC
WHY is productivity growth low if information technology is advancing rapidly? Prominent in the 1980s and early 1990s, this question has in recent years again become one of the hottest in economics. Its salience has grown as techies have become convinced that machine learning and artificial intelligence will soon put hordes of workers out of work (among tech-moguls, Bill Gates has called for a robot tax to deter automation, and Elon Musk for a universal basic income). A lot of economists think that a surge in productivity that would leave millions on the scrapheap is unlikely soon, if at all. Yet this year’s meeting of the American Economic Association, which wound up in Philadelphia on January 7th, showed they are taking the tech believers seriously. A session on weak productivity growth was busy; the many covering the implications of automation were packed out.
Recent history seems to support productivity pessimism. From 1995 to 2004 output per hour worked grew at an annual average pace of 2.5%; from 2004 to 2016 the pace was just 1%. Elsewhere in the G7 group of rich countries, the pace has been slower still. An obvious explanation is that the financial crisis of 2007-08 led firms to defer productivity-boosting investment. Not so, say John Fernald, of the Federal Reserve Bank of San Francisco, and co-authors, who estimate that in America, the slowdown began in 2006. Its cause was decelerating “total factor productivity”—the residual that determines GDP after labour and capital have been accounted for. Productivity has stagnated despite swelling research spending (see chart). This supports the popular idea that fewer transformative technologies are left to be discovered.
Others take almost the diametrically opposed view. A presentation by Erik Brynjolfsson of MIT pointed to recent sharp gains in machines’ ability to recognise patterns. They can, for instance, outperform humans at recognising most images—crucial to the technology behind driverless cars—and match dermatologists’ accuracy in diagnosing skin cancer. Mr Brynjolfsson and his co-authors forecast that such advances will eventually lead to a widespread reorganisation of jobs, affecting high- and low-skilled workers alike.
Productivity pessimism remains the norm among official forecasters, but more academics are trying to understand how automation may affect the economy. In a series of papers, Daron Acemoglu of MIT and Pascual Restrepo of Boston University present new theoretical models of innovation. They propose that technological progress be divided into two categories: the sort that replaces labour with machines; and that which creates new, more complex tasks for humans. The first, automation, pushes down wages and employment. The second, the creation of new tasks, can restore workers’ fortunes. Historically, the authors argue, the two types of innovation seem to have been in balance, encouraged by market forces. If automation leads to a labour glut, wages fall, reducing the returns to further automation, so firms find new, more productive ways to put people to work instead. As a result, previous predictions of technology-induced joblessness have proved mostly wrong.
However, the two forces can, in theory, fall out of sync. For example, if capital is cheap relative to wages, the incentive to automate could prevail permanently, leading the economy to robotise completely. The authors speculate that, for now, biases towards capital in the tax code, or simply an “almost singular focus” on artificial intelligence, might be tilting firms towards automation, and away from thinking up new tasks for people. Another risk is that much of the workforce lacks the right skills to complete the new-economy tasks that innovators might dream up.
These ideas shed light on the productivity paradox. Mr Brynjolfsson and his co-authors argue that it can take years for the transformative effects of general-purpose technologies such as artificial intelligence to be fully felt. If firms are consumed by efforts to automate, and such investments take time to pay off, it makes sense that productivity growth would stall. Investment has not been unusually low relative to GDP in recent years, but it has shifted away from structures and equipment, towards research-and-development spending.
If research in automation does start yielding big pay-offs, the question is what will happen to the displaced workers. Recent trends suggest the economy can create unskilled jobs in sectors such as health care or food services where automation is relatively difficult. And if robots and algorithms become far cheaper than workers, their owners should become rich enough to consume much more of everything, creating more jobs for people.
The risk is that without sufficient investment in training, technology will relegate many more workers to the ranks of the low-skilled. To employ them all, pay or working conditions might have to deteriorate. If productivity optimists are right, the eventual problem may not be the quantity of available work, but its quality.
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