Labour share of income (Part 3 – Causes of wage inequality)

Labour share of income (Part 3 – Causes of wage inequality)

Phuah Eng Chye (9 June 2018)

Technological advances lead to significant changes in the organisation of work which changes the distribution of rewards. Karen Harris, Austin Kimson and Andrew Schwedel note the “tendency of displacement and long-term unemployment to erode earnings may cast a shadow over income distributions for years after the economic shock of automation dissipates.”

“Our base-case scenario, in which automation displaces 20% to 25% of US workers, will hit the lowest end the hardest. Our analysis shows that workers currently making between $30,000 and $60,000 per year are likely to experience the greatest disruption from automation: Up to 30% could be displaced, and many will suffer depressed wage growth. The impact on workers making less than $30,000 a year should be comparable but with slightly lower levels of wage depression. We expect automation to have a lesser impact on those with incomes between $60,000 and $120,000 a year and the least negative impact on those earning more than $120,000.”

Karen Harris, Austin Kimson and Andrew Schwedel anticipates “as automation technologies spread…employment and wage growth to be concentrated in jobs that require high social and analytical skills – jobs that are already relatively highly compensated today. Workers in mid- to low-skill roles who rely on physical labor or analytical skills vulnerable to automation are at higher risk of losing their jobs or facing pressure on wages. If recent history is a guide, those who lose their jobs may face lower incomes throughout their career after being reabsorbed into the workforce, and some may choose to drop out entirely.”

“Automation may also increase income inequality by increasing the share of income going to profits vs. wages…By 2030, we estimate that operating costs at an industry level could decline by as much as 10% to 15%, depending on the industry’s current cost structure (the share of costs that labor represents) and the level of automation expected in the base-case scenario time frame. Under those conditions, increased profitability would largely flow to owners of capital and further reduce the share of national income allocated to labor”.

One important feature is the widening income inequalities is driven by the private sector. In this regard, the ILO points out “changes in wage inequality between enterprises have been key drivers of overall trends in wage inequality”. Research shows “in most countries wages climb gradually across most of the wage distribution and then jump sharply for the top 10 per cent and, especially, for the highest-paid 1 per cent of employees. In Europe, the highest-paid 10 per cent receive on average 25.5 per cent of the total wages paid to all employees in their respective countries, which is almost as much as what the lowest-paid 50 per cent earn (29.1 per cent).…the share of the top 10 per cent is even higher in some emerging economies…In Europe in 2010, wage inequality within enterprises accounted for almost half of total wage inequality.” [1]

One point that needs to be clarified is whether the unequal wage distribution is caused by diminishing or by rising levels of competition. This point needs to be resolved as “our understanding of the causes of a problem inevitably influences our choice of policies for dealing with it.”[2].

The diminishing competition narrative is consistent with the labour monopsony and superstar hypotheses[3]. These views suggest concentration reduces competitive pressure among firms and results in a shift in employers’ bargaining power.  In tandem with greater social acceptance of high salaries, wage differentials widen as high performers and shareholders are rewarded relative to the other employees.

There are three hypotheses based on the opposite proposition; that pay differentials are widening due to intensifying competition. The first is Philip Cook and Robert Frank’s Winner-Take-all (WTA) hypothesis suggesting “the inequality created by the growing prevalence of winner-take-all markets stems from competitive forces having grown stronger, not weaker. This change is the result of technical and other market forces that have made top performers more valuable, and of new rules that facilitate much more open competition for their services – a movement akin to the recent wave of free agency in professional sports.”[4]

Robert Frank explains “runaway professional salaries are the result not of a breakdown of competition but of the spread of markets in which the value of production depends primarily on the efforts of only a handful of top players who are paid accordingly…Before the competition ushered in by free agency in professional sports, for example, star athletes earned only a fraction of their current salaries, despite their enormous economic value. In today’s market, the top player who doesn’t receive his due can simply move to another team…Likewise, it was once the almost universal practice to promote business executives from within, which often enabled companies to retain top executives for less than one-tenth of today’s salaries…Today inter-firm and inter-industry boundaries are more permeable, and the greater mobility of star performers has been accompanied by explosive growth in salaries at the top”.

The WTA thus gives rise to “an important new kind of market failure… top performers typically receive extremely high compensation relative to their rivals, who, as in tennis, are often only marginally less able. The enormous paychecks invariably generate intense contests to choose the winners. Contests of this sort, once confined largely to sports and entertainment, have grown increasingly common in the rest of the economy. For every author who receives a million-dollar advance payment, there are thousands of others, many of them as talented, who never manage even to support themselves.” This results in externalities that “attract too many resources away from markets with more conventional payoff structures” with many hopeful individuals willing to accept little or no pay for an opportunity for success.

Yanhui Wu provides a similar explanation using a framework based on incentive pay as a sorting mechanism for allocating talent and enhancing economic efficiency. He demonstrates that “skill-neutral (i.e. TFP-enhancing) technological progress can generate a substantial impact on wage inequality through the distribution of firm size. In particular, TFP-enhancing technological progress causes disproportionate growth in firm size favouring more-productive firms and also increases the value of managerial efforts in big firms. This induces the reallocation of resources from small firms (run by less talented managers) to big firms (run by more talented managers). In consequence, three effects occur: (1) the shrinkage of small business owners, (2) an expansion of high-talent managers who share firm profits, and (3) an increase in the level of incentives offered to managers. These three effects jointly contribute to a highly skewed wage distribution in favour of top talent.” On this basis, the use of incentive structures to sort labour improves efficiency on one hand but generates wage inequality on the other.  This suggests there is a trade-off between wage inequality and economic efficiency.

The second is David Weil’s fissured workplace which argues “companies are pushing wages closer and closer to what we would think of as marginal productivity. And some of the rents that used to be collected by workers because they were inside a firm, even a nonunion firm and certainly in a unionized setting, are now going back to the companies because the companies are playing close to what they actually need to pay to entice people to do that work…distinction in pay scales for those working at lead companies and those at contractors. So if you are lucky enough to be in the Google mothership, you soar up with that wage structure…And then you have these businesses in the shedded parts of the economy where those pay structures are being pushed downward, closer to the marginal productivity of labor.”[5]

A third perspective comes from Zachary Karabell who observes there has been an “erosion of traditional wage industries in the developed world over the past decades. It is not inequality that has caused the middle class to lag and suffer. Inequality rather is a symptom of a system that reached the limit of what it could provide wage earners performing jobs tied to 20th-century manufacturing.” In this context, “ballooning CEO pay is in turn a product of the globalization of capital, labor, and business without a commensurate evolution of some sort of global government and tax regime. Almost all of the companies that employ the top-paid CEOs are increasingly multinational and answer to no single government.”

Zachary Karabell adds CEOs everywhere were “reaping the greatest rewards of global economic growth” while “many, many people barely earn enough”. But he notes that “obsessing over executive compensation does nothing to contribute toward the hard work of making a generational transition away from the industrial economy that was and toward the information economy that will be.”

It is possible to reconcile all the competing explanations within an information framework. The information effects of concentration-fragmentation[6] polarises the labour market into two segments. The WTA hypothesis basically describes how rewards are concentrated as a result of the intense bidding for a limited pool of “talent” that employers deemed critical to success. The ever-rising premiums incorporates the costs of scarcity (lack of substitutes) of individuals perceived to possess the ability (reputation) to meet high-performance expectations within a short timeframe. The higher rewards for talent also need to build in an insurance premium to cover these individuals for failures as well as to cover their investment costs to become a talent (which includes housing, education and other expenditures).

In contrast, the market for mass labour is commoditised and fragmented. Competition is eased because technology has expanded the range of jobs where labour is substitutable. In the meantime, “shifting labor supply…flagging employment in middle-skill occupations combined with slack macroeconomic conditions spurred middle-skill workers to compete with less-educated workers for manual task-intensive jobs, thus checking the tendency for wages to rise in these occupations.” [7]

Steven Hill observes workers in the sharing economy “- task rabbits, contractors, temps, day laborers, gig-preneurs, practically a new form of indentured labor. What makes the situation frighteningly unfamiliar is that for the most part these are not teenagers or retired housewives looking for extra cash – these are highly educated rabbits who are under- or unemployed: 70 percent have at least a bachelor’s degree, 20 percent a master’s degree and 5 percent a PhD.”

In cases where the jobs are subject to open bidding, supply tends to overwhelm demand and drive marginal wages downward. And in situations where there are many vacancies, employers are unwilling to raise their bid wages upwards and will only activate employment if there are job takers at the low offer prices.

Overall, technology is a major force that increases production flexibilities and labour substitutability. Concentration-fragmentation changes the nature of work and the private sector reacts accordingly. Hence, information disruption is a major cause of wage inequality.

References

David H. Autor (3 September 2014) “Polanyi’s paradox and the shape of employment growth”. NBER Working Paper No. 18629, December. www.kc.frb.org/publicat/sympos/2014/2014093014.pdf

Heather Boushey (22 June 2017) “Equitable Growth in Conversation: David Weil”. Washington Centre for Equitable Growth. http://equitablegrowth.org/labor-markets/equitable-growth-in-conversation-david-weil/

Karen Harris, Austin Kimson, Andrew Schwedel (7 February 2018) “Labor 2030: The collision of demographics, automation and inequality”. Bain & Company. http://www.bain.com/publications/articles/labor-2030-the-collision-of-demographics-automation-and-inequality.aspx?

International Labour Organization (2016) “Global Wage Report 2016/17: Wage inequality in the workplace”. http://www.ilo.org/wcmsp5/groups/public/—dgreports/—dcomm/—publ/documents/publication/wcms_537846.pdf

Phuah Eng Chye (2015) Policy paradigms for the anorexic and financialised economy: Managing the transition to an information societyhttp://www.amazon.com/dp/B01AWRAKJG

Phuah Eng Chye (29 July 2017) “The significance of information effects”. Economicsofinformationsociety.com. http://economicsofinformationsociety.com/the-significance-of-information-effects/

Phuah Eng Chye (26 May 2018) “Labour share of income (Part 1: Theories and measurement)”. Economicsofinformationsociety.com. http://economicsofinformationsociety.com/labour-share-of-income-part-1-theories-and-measurement/

Phuah Eng Chye (2 June 2018) “Labour share of income (Part 2: The difficulty of overcoming wage stagnation)”. Economicsofinformationsociety.com. http://economicsofinformationsociety.com/labour-share-of-income-part-2-the-difficulty-of-overcoming-wage-stagnation/

Robert Frank (1994) “Talent and the Winner-Take-All society”. Prospect.org. http://prospect.org/article/talent-and-winner-take-all-society

Steven Hill (2015) Raw deal: How the Uber economy and runaway capitalism are screwing American workers. St Martin’s Press.

Yanhui Wu (3 March 2018) “Inequalities in managerial pay: The tradeoff between sorting talents and providing incentives”. Voxeu. https://voxeu.org/article/sorting-incentives-and-excessive-managerial-pay

Zachary Karabell (18 April 2014) “Why you need to stop obsessing over exorbitant CEO pay in America”. Slate. http://www.slate.com/articles/business/the_edgy_optimist/2014/04/top_ceo_pay_income_inequality_isn_t_as_harmful_as_we_think.html#ixzz2zFTOFFLe

[1] ILO 2016/7

[2] Robert Frank.

[3] Phuah Eng Chye “Organisation of work: Labour share of income – Theory and measurement”.

[4] Robert Frank.

[5] Heather Boushey

[6] Phuah Eng Chye.

[7] David H. Autor

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