Wednesday, May 23, 2018

23/5/18: Contingent Workforce, Online Labour Markets and Monopsony Power


The promise of the contingent workforce and technological enablement of ‘shared economy’ is that today’s contingent workers and workers using own capital to supply services are free agents, at liberty to demand their own pay, work time, working conditions and employment terms in an open marketplace that creates no asymmetries between their employers and themselves. In economics terms, thus, the future of technologically-enabled contingent workforce is that of reduced monopsonisation.

Reminding the reader: monopsony, as defined in labour economics, is the market power of the employer over the employees. In the past, monopsonies primarily were associated with 'company towns' - highly concentrated labour markets dominated by a single employer. This notion seems to have gone away as transportation links between towns improved. In this context, increasing technological platforms penetration into the contingent / shared economies (e.g. creation of shared platforms like Uber and Lyft) should contribute to a reduction in monopsony power and the increase in the employee power.

Two recent papers: Azar, J A, I Marinescu, M I Steinbaum and B Taska (2018), “Concentration in US labor markets: Evidence from online vacancy data”, NBER Working paper w24395, and Dube, A, J Jacobs, S Naidu and S Suri (2018), “Monopsony in online labor markets”, NBER, Working paper 24416, dispute this proposition by finding empirical evidence to support the thesis that monopsony powers are actually increasing thanks to the technologically enabled contingent employment platforms.

Online labour markets are a natural testing ground for the proposition that technological transformation is capable of reducing monopsony power of employers, because they, in theory, offer a nearly-frictionless information and jobs flows between contractors and contractees, transparent information about pay and employment terms, and low cost of switching from one job to another.

The latter study mentioned above attempts to "rigorously estimate the degree of requester market power in a widely used online labour market – Amazon Mechanical Turk, or MTurk... the most popular online micro-task platform, allowing requesters (employers) to post jobs which workers can complete for."

The authors "provide evidence on labour market power by measuring how sensitive workers’ willingness to work is to the reward offered", by using the labour supply elasticity facing a firm (a standard measure of wage-setting (monopsony) power). "For example, if lowering wages by 10% leads to a 1% reduction in the workforce, this represents an elasticity of 0.1." To make their findings more robust, the authors use two methodologies for estimating labour supply elasticities:
1) Observational approach, which involves "data from a near-universe of tasks scraped from MTurk" to establish "how the offered reward affected the time it took to fill a particular task", and
2) Randomised experiments approach, uses "experimental variation, and analyse data from five previous experiments that randomised the wages of MTurk subjects. This randomised reward-setting provides ‘gold-standard’ evidence on market power, as we can see how MTurk workers responded to different wages."

The authors "empirically estimate both a ‘recruitment’ elasticity (comparable to what is recovered from the observational data) where workers see a reward and associated task as part of their normal browsing for jobs, and a ‘retention’ elasticity where workers, having already accepted a task, are given an opportunity to perform additional work for a randomised bonus payment."

The findings from both approaches are strikingly similar. Both "provide a remarkably consistent estimate of the labour supply elasticity facing MTurk requesters. As shown in Figure 2, the precision-weighted average experimental requester’s labour supply elasticity is 0.13 – this means that if a requester paid a 10% lower reward, they’d only lose around 1% of workers willing to perform the task. This suggests a very high degree of market power. The experimental estimates are quite close to those produced using the machine-learning based approach using observational data, which also suggest around 1% reduction in the willing workforce from a 10% lower wage."


To put these findings into perspective, "if requesters are fully exploiting their market power, our evidence implies that they are paying workers less than 20% of the value added. This suggests that much of the surplus created by this online labour market platform is captured by employers... [the authors] find a highly robust and surprisingly high degree of market power even in this large and diverse spot labour market."

In evolutionary terms, "MTurk workers and their advocates have long noted the asymmetry in market structure among themselves. Both efficiency and equality concerns have led to the rise of competing, ‘worker-friendly’ platforms..., and mechanisms for sharing information about good and bad requesters... Scientific funders such as Russell Sage have instituted minimum wages for crowd-sourced work. Our results suggest that these sentiments and policies may have an economic justification. ...Moreover, the hope that information technology will necessarily reduce search frictions and monopsony power in the labour market may be misplaced."

My take: the evidence on monopsony power in web-based contingent workforce platforms dovetails naturally into the evidence of monopolisation of the modern economies. Technological progress, that held the promise of freeing human capital from strict contractual limits on its returns, while delivering greater scope for technology-aided entrepreneurship and innovation, as well as the promise of the contingent workforce environment empowering greater returns to skills and labour are proving to be the exact opposites of what is being delivered by the new technologies which appear to be aiding greater transfer of power to technological, financial and even physical capital.

The 'free to work' nirvana ain't coming folks.

23/5/18: American Exceptionalism, Liberty and... Amazon


"And the star-spangled banner in triumph shall wave
O'er the land of the free and the home of the brave!"

The premise of the American Exceptionalism rests on the hypothesis of the State based on the principles of liberty.

Enter Amazon, a corporation ever hungry for revenues, and the State, a corporation ever hungry for power and control. Per reports (https://www.aclunc.org/blog/amazon-teams-law-enforcement-deploy-dangerous-new-face-recognition-technology), Amazon "has developed a powerful and dangerous new facial recognition system and is actively helping governments deploy it. Amazon calls the service “Rekognition."

As ACLU notes (emphasis is mine): "Marketing materials and documents obtained by ACLU affiliates in three states reveal a product that can be readily used to violate civil liberties and civil rights. Powered by artificial intelligence, Rekognition can identify, track, and analyze people in real time and recognize up to 100 people in a single image. It can quickly scan information it collects against databases featuring tens of millions of faces, according to Amazon... Among other features, the company’s materials describe “person tracking” as an “easy and accurate” way to investigate and monitor people."

As I noted elsewhere on this blog, the real threat to the American liberal democracy comes not from external challenges, attacks and shocks, but from the internal erosion of the liberal democratic institutions, followed by the decline of public trust in and engagement with these institutions. The enemy of America is within, and companies like Amazon are facilitating the destruction of the American liberty, aiding and abetting the unscrupulous and power-hungry governments, local, state and beyond.


Tuesday, May 22, 2018

22/5/18: Poor Showing by the U.S. Cities


Mercer 2018 Quality of Living rankings are out: https://mobilityexchange.mercer.com/Portals/0/Content/Rankings/rankings/qol2018i321456/index.html. Summary of key results:


  • Top 25:

  • Not a single U.S. city makes it into top 25.
  • Highest-ranked U.S. city, San Francisco, ranks 30th in the world, Boston and Honolulu - second and third highest ranked U.S. cities are in 35th and 36th places.
  • Canada dominates North American rankings with 5 cities in top 35 against U.S. two cities.
  • Only one North American city, Vancouver, makes it in top 10 globally.
  • Switzerland and Germany (3 cities each) dominate top 10 rankings.
  • Dublin ranks 34th in the world and London 41st, competitive relative to the U.S. cities, and against key peer European cities.


Quality of urban life is a key determinant of economic development, competitiveness and growth potential in the advanced economies. From this perspective, U.S. cities are lagging behind their global counterparts due to low value for money in quality of housing, poor transportation and connectivity systems, poor public safety, underinvestment in social and public amenities, and lower quality of schools. Controlling for private education and healthcare (benefits of which are highly concentrated at the top of income distributions), the U.S. cities competitiveness would be even less impressive than the above rankings suggest.

Monday, May 21, 2018

21/5/18: Truth Decay and Fake News: Four Links


Some useful links on recent research  concerning the relationship between empirical/factual evidence, newsflows and policy discourse in the West:




21/5/18: Italian Sovereign Risks Are Blowing Up


As I noted in my comment to ECR / Euromoney and in my article for Sunday Business Post (see links here: http://trueeconomics.blogspot.com/2018/05/21518-risk-experts-take-flight-over.html and http://trueeconomics.blogspot.com/2018/05/21528-trouble-is-brewing-in-euro.html), the ongoing process of Government formation in Italy represents a fallout from the substantial VUCA events arising from the recent elections, and as such warrants a significant (albeit delayed) repricing of country sovereign risks. This process is now underway:

Source: Holger Zschaepitz @Schuldensuehner

Per chart above, Italy's 10 year bonds risk premium over Germany jumped to 181 bps on markets concerns with respect to fiscal dynamics implied by the new Government formation. This, however, is just a minor side show compared to the VUCA environment created by the broader dynamics of political populism and opportunism. And in this respect, Italy is just another European country exposed to these risks. In fact, as the latest data from the Timbro's Authoritarian Populism Index, Europe-wide, political populism is on the rise:



21/5/18: Risk experts take flight over Italy's political risk


Euromoney and ECR are covering the story of Italian political risk, with my comments on the rise of populism in Italy and its effects on sovereign risk with respect to the Italian Government formation negotiations: https://www.euromoney.com/article/b187w50chyvhbl/risk-experts-take-flight-over-italys-political-shock


21/5/28: Trouble is brewing in the Euro paradise


My article for the Sunday Business Post on the continued risk/VUCA from politics of populism to the Euro area reforms and stability: https://www.businesspost.ie/business/trouble-brewing-euro-paradise-416876.


Sunday, May 20, 2018

19/5/18: Leverage risk in investment markets is now systemic


Net margin debt is a measure of leverage investors carry in their markets exposures, or, put differently, the level of debt accumulated on margin accounts. Back at the end of March 2018, the level of margin debt in the U.S. stock markets stood at just under $645.2 billion, second highest on record after January 2018 when the total margin debt hit an all-time-high of $665.7 billion, prompting FINRA to issue a warning about the unsustainable levels of debt held by investors.

Here are the levels of gross margin debt:

Source: https://wolfstreet.com/2018/04/23/an-orderly-unwind-of-stock-market-leverage/.

And here is the net margin debt as a ratio to the markets valuation - a more direct measure of leverage, via Goldman Sachs research note:
Which is even more telling than the absolute gross levels of margin debt in the previous chart.

Per latest FINRA statistics (http://www.finra.org/investors/margin-statistics), as of the end of April 2018, debit balances in margin accounts rose to $652.3 billion, beating March levels

And things are even worse when we add leveraged ETFs to the total margin debt:

In simple terms, we are at systemic levels of risk relating to leverage in the equity markets.

Saturday, May 19, 2018

19/5/18: The Scary Inefficiency & Environmental Costs of Bitcoin


Bitcoin is just one of the cryptocurrencies, albeit the dominant one by market capitalisation and mining assets deployment. The cryptocurrency is best known for volatility of its exchange rate to key fiat currencies and other commodities, but the more interesting aspect of the Bitcoin (and other cryptos) is their hunger for energy. Cryptos are based on blockchain technologies that promise a range of benefits (majority unverified or untested or both), amongst which the high degree of security and peer-to-peer data registry, both of which are supported by the mining processes that effectively require deployment of  a vast amount of hash/algorithmic calculations in order to create data storage units, or blocks. In a sense, energy (electricity) is the main input into creation of blockchain records of transactions.

As the result, it is important to understand Bitcoin (and other cryptos) energy efficiency and utilisation, from three perspectives:
1) Direct efficiency - value added by the use of energy in mining Bitcoin per unit of BTC and unit of information recorded on a blockchain;
2) Economic efficiency or opportunity cost of using the energy expended on mining; and
3) Environmental efficiency - the environmental impact of energy used.

To-date, estimating the total demand for electricity arising from Bitcoin mining (let alone from mining of other cryptos) has been a huge challenge, primarily because Bitcoin miners are too often located in secretive jurisdiction, do not report any data about their operations and, quite often, can be highly atomistic. Although Bitcoin mining is a concentrated activity - with a small number of mega-miners and mining pools dominating the market - there is still a cottage industry of amateur and smaller scale miners sprinkled around the globe.

Thus, to-date, we have only very scant understanding of just how much of the scarce resource (energy) does the new industry of cryptos mining consume.

A new paper, published in a peer-reviewed journal, Joule, which is a reputable academic journal, titled "Bitcoin's Growing Energy Problem" and authored by Alex de Viries (Experience Center of PwC, Amsterdam, the Netherlands) attempts exactly this. The paper is the first in the literature to be peer-reviewed and uses a new methodology to discern trends in Bitcoin's electric energy consumption. The paper does not cover other cryptos, so its conclusions need to be scaled to estimate the entire impact of cryptocurrencies energy use.

The findings of de Viries are striking. He estimates the current Bitcoin usage of energy at 2.55 gigawatts, close to that of Ireland (3.1GW), approaching 7.67GW that "could already be reached in 2018", comparable to Austria (8.2GW). When reached, this will amount to 0.5% of the total world electricity consumption.

Per 'efficiency of blockchain', a single transaction on Bitcoin network uses as much electricity as an average household in the Netherlands uses in a month. Which is, put frankly, mad, wasteful and utterly unrealistic as far as transactions costs go for the network.

Per de Viries: "As per mid-March 2018, about 26 quintillion hashing operations are performed every second and non-stop by the Bitcoin network (Figure 1). At the same time, the Bitcoin network is only processing 2–3 transactions per second (around 200,000 transactions per day). This means that the ratio of hash calculations to processed transactions is 8.7 quintillion to 1 at best. The primary fuel for each of these calculations is electricity."


The key to the above numbers is that they vastly underestimate the true costs of Bitcoin and other cryptos to the global economy. The paper focuses solely on energy used on mining. However, other activities that sustain Bitcoin and blockchains are also energy-intensive, including trading in coins/tokens, storage of information blocks, etc. Worse, mining and processing / servicing of the networks required use of constant electricity supply, which means that the energy mix that goes to sustain cryptocurrencies operations is the worst from environmental quality perspective and must rely on heavy use of fossil fuels in the top up range of electricity demand spectrum. The environmental costs of Bitcoin and cryptos is staggering.

Scaling up Bitcoin figures from de Viries; paper to include other major cryptocurrencies would require factoring in the BTC's share of the total crypto markets by energy use. A proxy (an imperfect one) for this is BTC's total share of the cryptocurrencies publicly traded markets which stood at around 37.3% as of May 16, 2018. Assuming this proxy holds for mining and servicing costs, total demand for electricity from the cryptocurrencies and blockchain use around the world is more than 2.55GW/0.37 or more than 6.9GW, with de Viries' model implying that by year end, the system of cryptocurrencies can be burning through a staggering 1.35% of total electricity supply around the world.

The problem with the key cryptocurrencies proposition is that the system of blockchain-based public networks can deliver lower cost, higher efficiency alternatives to current records creation and storage. This proposition simply does not hold in the current energy demand environment.



The full paper can be read here: de Vries: "Bitcoin's Growing Energy Problem" http://www.cell.com/joule/fulltext/S2542-4351(18)30177-6.

Friday, May 18, 2018

18/5/18: Euro area current accounts 1980-2017


What happened to the Euro area current accounts since the introduction of the Euro?

Periodically, I update my charts on the Euro effects on the external balances of the EA-12, the original economies of the Euro area. Here are the updates:

Considering first cumulated current account balances over 1980-2017 period, the chart below aggregates the EA12 into two sub-groups:

  • The 'periphery' defined as a group composed of Italy, Greece, Spain and Portugal
  • The 'core' group composed of the remaining EA12 countries

The chart shows several interesting facts
  1. Current account deficits in the 'peripheral' states predate the introduction of the Euro
  2. Since the introduction of the Euro through 2013 there was a consistent increase in the current account deficits amongst the 'periphery' states, with acceleration in deficits staring exactly at the point of the introduction of the Euro
  3. Current account deficits in the Euro area 'peripheral' states were rapidly accelerating into 2009
  4. Since 2014, current account deficits in the 'peripheral' states have been drawn down, at a moderate rate, as consistent with the internal deleveraging of these economies
  5. Meanwhile, the introduction of the Euro accelerated accumulation of current account surpluses within the 'core' group of EA12
  6. The rate of current account surpluses acceleration increased dramatically around 2004 and then again starting with 2009
In terms of external balances, the creation of the Euro area clearly resulted in compounding pre-Euro era existent structural imbalances in the EA12 economies.

Meanwhile, there is no discernible impact of the Euro on supporting growth in trade within the Euro area (here, we use changing countries composition of the Eurozone):

  As per above chart:
  • From 2000 and prior to 2014, Eurozone performance in terms of growth rates in exports of goods and services largely underperformed other advanced economies (ex-G7) and was in line with G7 performance
  • Before 2000, Eurozone was broadly in line with both the G7 and other advanced economies in terms of growth rates in exports of goods and services
  • Lastly, starting with 2014, the Euro area has been outperforming both the G7 and other advanced economies in terms of growth in exports of goods and services - a development that is more consistent with the fallout from the twin Global Financial Crisis (2007-2009) and the Euro Area Sovereign Debt Crisis (2011-2013), as the process of internal devaluation forced a number of Eurozone countries into more aggressive exporting
On the net, there remains no current account-linked evidence to support an argument that the creation of the Euro has been a net positive for the Eurozone member states in terms of improving their external balances and exports flows. On the other hand, there is little evidence that the Euro has hindered trade flows growth rates, whilst there is strong evidence to claim that the Euro has exacerbated current account imbalances between the 'core' and the 'periphery' states.

17/5/18" Timeline of Russian Growth 1992-2023 (forecasts)


I have annotated the timeline of Russia's GDP per capita from 1992 through forecast (IMF) out to 2023 with the inflation dynamics and presidential terms. For comparison, BRICS ex-Russia GDP per capita dynamics are presented as well.

Draw any conclusions you want:


Thursday, May 17, 2018

17/5/18: U.S. Labour Markets and the Trump Administration Record


The Global Macro Monitor have published an exhaustive study of the U.S. labour market trends over the first 15-16 months of the President Trump's tenure. The  post is long, brilliantly detailed, and empirically and intuitively flawless (yeah, I know, I don't think I ever used this descriptor of an economics research piece before). So read it in full here: https://macromon.wordpress.com/2018/05/15/deconstructing-the-u-s-jobs-market/.

Top line conclusions are:

  • Comparing the "first 15 [monthly] payroll reports of the Trump administration to the last 15 of the Obama administration",  "as of the end of April 2018, the Trump economy has generated 2.7 million jobs versus 3.1 million in Obama’s economy, or 373k fewer workers added to payrolls"
  • Growth in employment was of lower quality during the Trump tenure to-date too: "the private sector has also added 124k fewer jobs in the Trump economy. Net job creation in the government sector under President Trump is relatively flat." The latter metric puts a boot into the arguments that President Trump is a fiscal conservative aiming to reduce public sector weight in the economy. 
  • Earnings comparatives are also wobbly: "There is relatively little difference in the growth of average hourly earnings in the Trump and Obama employment reports." Which is more striking when one recognises that the Trump Administration inherited a tightening labour market, in which, normally, one would expect more wages inflation.
  • "Job creation in President Trump’s economy outperforms the Obama economy in 5 of the 13 private sector industry groups, most significantly in manufacturing and mining", but "Almost all of the relative outperformance in mining is the result of the reversal in oil prices. Coal mining and auto manufacturing employment has not recovered". In other words, even in the core industries targeted by the Administration for growth, the Administration efforts have little to do with any recovery in the mining sector./ 
  • Cyclically, the authors note that "The results are surprising as GDP growth was significantly higher during the Trump payroll reports, averaging of 2.53 percent on an annual basis, versus 1.56 percent during the last five quarters of the previous administration". However, this also means that current jobs creation is coming toward the end of the expansion cycle, and can be expected to be lower due to constraints of labour supply.
  • Key observation, from macroeconomic environment point of view is that "the economy continues to reward capital over labor disproportionately". There is a fundamental problem with this development. The U.S. labour markets flexibility represents a net positive for the private sector productivity in the short run. However, as capital and technological deepening of production processes progresses, the very same flexibility leads to lower degree of upskilling and re-training of the existent workforce. This is a huge source of risk and uncertainty for the U.S. economy forward in terms of longer run potential growth and productivity growth.

In short, read the original post - it is packed with highly informative and very important data and observations!

Source: https://macromon.wordpress.com/2018/05/15/deconstructing-the-u-s-jobs-market/