Category Archives: inequality

23/6/21: Covid19 Deaths and Income Inequality

 

An interesting, although intuitively straight forward note on the determinants of Covid19 deaths: https://twitter.com/youyanggu/status/1407418434955005955

As Youyang Gu @youyanggu states, "I believe income inequality is the single best predictor of total Covid deaths in the US. Not income, but income *inequality*. The R^2 is surprisingly high: 0.35."

There are some potentially important issues with this analysis (some are explored here: https://github.com/jsill/usstatecovidanalysis/blob/main/usStateCovidAnalysis.pdf), but the conclusion seems to be qualitatively robust. 


8/6/20: 30 years of Financial Markets Manipulation


Students in my course Applied Investment and Trading in TCD would be familiar with the market impact of the differential bid-ask spreads in intraday trading. For those who might have forgotten, and those who did not take my course, here is the reminder: early in the day (at and around market opening times), spreads are wide and depths of the market are thin (liquidity is low); late in the trading day (closer to market close), spreads are narrow and depths are thick (liquidity is higher). Hence, a trading order placed near market open times tends to have stronger impact by moving the securities prices more; in contrast, an equally-sized order placed near market close will have lower impact.

Now, you will also remember that, in general, investment returns arise from two sources: 
  1. Round-trip trading gains that arise from buying a security at P(1) and selling it one period later at P(2), net of costs of buy and sell orders execution; and 
  2. Mark-to-market capital gains that arise from changes in the market-quoted price for security between times P(1) and P(2+).
The long-running 'Strategy' used by some institutional investors is, therefore as follows: 
Here is the illustration of the 'Strategy' via Bruce Knuteson paper "Celebrating Three Decades of Worldwide Stock Market Manipulation", available here: https://arxiv.org/pdf/1912.01708.pdf.
  • Step 1: Accumulate a large long portfolio of assets;
  • Step 2: At the start of the day, buy some more assets dominating your portfolio at P(1) - generating larger impact of your buy orders, even if you are carrying a larger cost adverse to your trade;
  • Step 3: At the end of the day, sell at P(2) - generating lower impact from your sell orders, again carrying the cost.

On a daily basis, you generate losses in trading account, as you are paying higher costs of buy and sell orders (due to buy-sell asymmetry and intraday bid-ask spreads differences), but you are also generating positive impact of buy trades, net of sell trades, so you are triggering positive mark-to-market gains on your original portfolio at the start of the day.

Knuteson shows that, over the last 30 years, overnight returns in the markets vastly outstrip intraday returns. 



Per author, "The obvious, mechanical explanation of the highly suspicious return patterns shown in Figures 2 and 3 is someone trading in a way that pushes prices up before or at market open, thus causing the blue curve, and then trading in a way that pushes prices down between market open (not including market open) and market close (including market close), thus causing the green curve. The consistency with which this is done points to the actions of a few quantitative trading firms rather than
the uncoordinated, manual trading of millions of people."

Sounds bad? It is. Again, per Knuteson: "The tens of trillions of dollars your use of the Strategy has created out of thin air have mostly gone to the already-wealthy: 
  • Company executives and existing shareholders benefi tting directly from rising stock prices; 
  • Owners of private companies and other assets, including real estate, whose values tend to rise and fall with the stock market; and 
  • Those in the financial industry and elsewhere with opportunities to privatize the gains and socialize the losses."

These gains to capital over the last three decades have contributed directly and signi ficantly to the current level of wealth inequality in the United States and elsewhere. As a general matter, widespread mispricing leads to misallocation of capital and human effort, and widespread inequality negatively a effects our social structure and the perceived social contract."

3/5/19: The Rich Get Richer when Central Banks Print Money



The Netherlands Central Bank has just published a fascinating new paper, titled "Monetary policy and the top one percent: Evidence from a century of modern economic history". Authored by Mehdi El Herradi and Aurélien Leroy, (Working Paper No. 632, De Nederlandsche Bank NV: https://www.dnb.nl/en/binaries/Working%20paper%20No.%20632_tcm47-383633.pdf), the paper "examines the distributional implications of monetary policy from a long-run perspective with data spanning a century of modern economic history in 12 advanced economies between 1920 and 2015, ...estimating the dynamic responses of the top 1% income share to a monetary policy shock." The authors "exploit the implications of the macroeconomic policy trilemma to identify exogenous variations in monetary conditions." Note: the macroeconomic policy trilemma "states that a country cannot simultaneously achieve free capital mobility, a fixed exchange rate and independent monetary policy".

Per authors, "The central idea that guided this paper’s argument is that the existing literature considers the distributional effects of monetary policy using data on inequality over a short period of time. However, inequalities tend to vary more in the medium-to-long run. We address this shortcoming by studying how changes in monetary policy stance over a century impacted the income distribution while controlling for the determinants of inequality."

They find that "loose monetary conditions strongly increase the top one percent’s income and vice versa. In fact, following an expansionary monetary policy shock, the share of national income held by the richest 1 percent increases by approximately 1 to 6 percentage points, according to estimates from the Panel VAR and Local Projections (LP). This effect is statistically significant in the medium run and economically considerable. We also demonstrate that the increase in top 1 percent’s share is arguably the result of higher asset prices. The baseline results hold under a battery of robustness checks, which (i) consider an alternative inequality measure, (ii) exclude the U.S. economy from the sample, (iii) specifically focus on the post-WWII period, (iv) remove control variables and (v) test different lag numbers. Furthermore, the regime-switching version of our model indicates that our conclusions are robust, regardless of the state of the economy."

In other words, accommodative monetary policies accommodate primarily those with significant starting wealth, and they do so via asset price inflation. Behold the summary of the last 10 years.

8/4/18: Talent vs Luck: Differentiating Success from Failure


In their paper, "Talent vs Luck: the role of randomness in success and failure", A. Pluchino. A. E. Biondo, A. Rapisarda (25 Feb 2018: https://arxiv.org/pdf/1802.07068.pdf) tackle the mythology of the "dominant meritocratic paradigm of highly competitive Western cultures... rooted on the belief that success is due mainly, if not exclusively, to personal qualities such as talent, intelligence, skills, efforts or risk taking".

The authors note that, although "sometimes, we are willing to admit that a certain degree of luck could also play a role in achieving significant material success, ...it is rather common to underestimate the importance of external forces in individual successful stories".

Some priors first: "intelligence or talent exhibit a Gaussian distribution among the population, whereas the distribution of wealth - considered a proxy of success - follows typically a power law (Pareto law). Such a discrepancy between a Normal distribution of inputs, suggests that some hidden ingredient is at work behind the scenes."

The authors show evidence that suggests that "such an [missing] ingredient is just randomness". Or, put differently, a chance.

The authors "show that, if it is true that some degree of talent is necessary to be successful in life, almost never the most talented people reach the highest peaks of success, being overtaken by mediocre but sensibly luckier individuals."

Two pictures are worth a 1000 words, each:

Figure 5 taken from the paper shows:

  • In panel (a): Total number of lucky events and
  • In panel (b): Total number of unlucky events 

Both are shown as "function of the capital/success of the agents"


Overall, "the plot shows the existence of a strong correlation between success and luck: the most successful individuals are also the luckiest ones, while the less successful are also the unluckiest ones."

Figure 7 shows:
In panel (a): Distribution of the final capital/success for a population with different random initial conditions, that follows a power law.
In panel (b): The final capital of the most successful individuals is "reported as function of their talent".

Overall, "people with a medium-high talent result to be, on average, more successful than people with low or medium-low talent, but very often the most successful individual is a moderately gifted agent and only rarely the most talented one.


Main conclusions on the paper are:

  • "The model shows the importance, very frequently underestimated, of lucky events in determining the final level of individual success." 
  • "Since rewards and resources are usually given to those that have already reached a high level of success, mistakenly considered as a measure of competence/talent, this result is even a more harmful disincentive, causing a lack of opportunities for the most talented ones."

The results are "a warning against the risks of what we call the ”naive meritocracy” which, underestimating the role of randomness among the determinants of success, often fail to give honors and rewards to the most competent people."

20/7/16: McKinsey’s "Generation Worse"…


A new study from McKinsey looks at the cross-generational distribution of income as a form of new ‘inequality’, in words of the authors: “an aspect of inequality that has received relatively little attention, perhaps because prior to the 2008 financial crisis less than 2 percent of households in advanced economies were worse off than similar households in previous years. That has now changed: two-thirds of households in the United States and Western Europe were in segments of the income distribution whose real market incomes in 2014 were flat or had fallen compared with 2005.”

In other words, McKinsey folks are looking at the “proportion of households in advanced economies with flat or falling incomes” - the generational cohorts that are no better than their predecessors.

Key findings are frightening: “Between 65 and 70 percent of households in 25 advanced economies, the equivalent of 540 million to 580 million people, were in segments of the income distribution whose real market incomes—their wages and income from capital—were flat or had fallen in 2014 compared with 2005. This compared with less than 2 percent, or fewer than ten million people, who experienced this phenomenon between 1993 and 2005.”

So that promise of the ‘sharing economy’ and the ‘gig-economy’ where people today are enabled to derive income (and thus wealth) from hereto under-utilised ‘assets’… pwah! not doing much. The ‘most empowered’ - web and gig-economy wise cohorts? Ah, they are actually the “worst-hit” ones. “Today’s younger generation is at risk of ending up poorer than their parents. Most population segments experienced flat or falling incomes in the 2002–12 decade but young, less-educated workers were hardest hit”.

For those of us who, like myself, tend to be libertarian in our view of the Government, McKinsey study tests some of our accepted ‘wisdoms’: “Government policy and labor-market practices helped determine the extent of flat or falling incomes. In Sweden, for example, where the government intervened to preserve jobs, market incomes fell or were flat for only 20 percent, while disposable income advanced for almost everyone. In the United States, government taxes and transfers turned a decline in market incomes for 81 percent of income segments into an increase in disposable income for nearly all households.”

Except, may be it did not, because counting in disposable income while allowing for taxes and subsidies is notoriously difficult and imprecise. And may be, just may be, all the fiscal imbalances that were accumulated in the process of achieving these supports in some (many) countries will still have to be paid by someone some day?

There is a reduced connection between current growth metrics and income outcomes on the ground (don’t we know as much here in Ireland, with 26.3% jump in GDP in 2015?): “Before the recession, GDP growth contributed about 18 percentage points to median household income growth, on average, in the United States and Europe. In the seven years after the recession, that contribution fell to four percentage points, and even these gains were eroded by labor market and demographic shifts.”

And the forward outlook? Bleak: “Longer-run demographic and labor trends will continue to weigh on income advancement. Even if economies resume their historical high-growth trajectory, we project that 30 to 40 percent of income segments may not experience market income gains in the next decade if labor-market shifts such as workplace automation accelerate. If the slow growth conditions of 2005–12 persist, as much as 70 to 80 percent of income segments in advanced economies may experience flat or falling market incomes to 2025.”


There are some wrinkles in the study. For example, in the U.S. case - cross time comparatives do not provide for the same data base, as pre-2014 data does not include state and local taxes. VAT and sales taxes are omitted across the board. And some other, but overall, the paper is pretty solid and very interesting.

So here is the key summary chart, positing the massive jump in the numbers of households on the declining side of market incomes:



And the chart showing that the taxes and transfers side of income supports is no longer sustainable over time:


Which brings us to the main problem: on the current trend line, politics of income supports from the fiscal policy side are unlikely to be able to contain growth in political discontent. Advanced economies are heading for serious tests of democratic institutions in years to come. Buckle your seat belts: the ride is going to get much rougher.