19/12/16: Income Polarization in the U.S.: Building Blocks of Trumplitics

Having just reviewed some fresh evidence on the trends and underlying drivers of declining wage growth rates in the U.S. post-Global Financial Crisis (GFC) in the previous post here: , now let’s take a look at some current state of research on income inequality dynamics. In general, relative income dynamics can be driven by increases in income at the top of the income distribution relative to the rest of the distribution - the so-called 1% effect or inequality factor; or by decreases in income distribution at the bottom of distribution - another inequality factor; or they can be driven by the decline in incomes in the middle of income distribution relative to both top earners and bottom earners (polarisation).

A new study from the IMF concerns with the latter type of dynamic. Titled “Income Polarization in the United States” and authored by Ali Alichi, Kory Kantenga, Kory and Juan Solé, study documents “the rise of income polarization - what some have referred to as the 'hollowing out' of the income distribution - in the United States, since the 1970s.”

The key findings are:

“While in the initial decades more middle-income households moved up, rather than down, the income ladder, since the turn of the current century, most of polarization has been towards lower incomes.” In other words, the middle class is increasingly joining the poor, rather than the upper classes.

And this holds for all demographic cohorts or the U.S. population:

CHARTS: Middle-Income Population 1970-2014 (percent of total population with the same characteristic)

 So the younger cohorts are now experiencing more hollowing out of the middle class than the older cohorts and this trend started manifesting itself around 2000.

 Education no longer protects the middle class, either.

And in racial terms, there is more marked decline in the fortunes of the middle class for the whites, whilst the recovery of the 1990s-2007 period in the fortune of the African-Americans  has been reduce by more than 50 percent since the onset of the GFC.

Similarly to race trends, gender trends offer nothing to be proud of.

“…after conditioning on income and household characteristics, the marginal propensity to consume from permanent changes in income has somewhat fallen in recent years.” Put differently, when today’s middle class workers receive a wage increase, they tend to save more and spend less out of that increase than before. This can only occur if today’s middle class workers are saving more from wages increases. Incidentally, the authors also show that the same has taken place for higher income households.

Secular decreases in MPC can reflect either increased investment (from savings) or increased precautionary savings (including savings used to buffer against liquidity risks). Unfortunately, the authors do not look into which effect is at play here, or (if both are) which effect dominates.

And here is another conclusion from the authors worth noting: “Income polarization has risen substantially in the past four decades—much the same, if not even faster than inequality.”

Which, of course, helps explain why we are witnessing activist voting by the disenchanted, angry middle class voters. You can blame political candidates, you can blame the media, you can blame outside forces and powers. But you can't avoid one simple conclusion: the U.S. middle class is pis*ed off with the status quo. For one very good reason that the status quo doesn't work for them.


Full study here: Alichi, Ali and Kantenga, Kory and Solé, Juan A., Income Polarization in the United States (June 2016). IMF Working Paper No. 16/121. https://ssrn.com/abstract=2882555

23/9/16: The Future of Work: Uncharted Policy Waters

My presentation on economic and social challenges of the emerging Gig-economy (contingent workforce) from earlier this year: http://cxccorporateservices.com/blog/the-future-of-work-uncharted-policy-waters-video/.

10/6/16: Italian Manufacturing Capacity post-crisis

A third paper on manufacturing capacity, also from Italy is by Libero Monteforte and Giordano Zevi, titled “An Inquiry into Manufacturing Capacity in Italy after the Double-Dip Recession” (January 21, 2016, Bank of Italy Occasional Paper No. 302: http://ssrn.com/abstract=2759786).

Here, the authors “…investigate the effects of the prolonged double-dip recession on the productive capacity of the Italian manufacturing sector”. The authors “…estimate that between 2007 and 2013 capacity contracted by 11–17%, depending on the method.”

In addition, the authors “…conduct an exercise to quantify the loss with respect to a counterfactual evolution of capacity in a ‘no-crisis’ scenario in which pre-2008 trends are extrapolated: in this case the loss is close to 20% for all methods.”

Summary of the results:

And here is decomposition of the potential output drop by factor of production:

Per authors: “In terms of factor determinants, about 60% of the cumulated drop of potential output in 2007-13 came from labour, while around 25% was attributable to the TFP (Chart above). The reason why the contribution of capital is comparatively small is twofold: first, the industrial
sector is characterized by a large wage share (close to 70%), therefore the contribution of K in the production function is limited; second, capital is a highly persistent variable and the fall in investments recorded during the two recessions, even if remarkably large, has not (so far)
resulted in a dramatic drop of the capital stock.”

The key lessons from all of this are: potential output in Italy fell precipitously across the manufacturing economy in the wake of the Global Financial Crisis. Meanwhile, counterfactual extension of pre-crisis trends was strongly signalling to the upside in manufacturing.

Majority of metrics used suggest that productive capacity in Italy declined by 15-18 percent through 2013, while counterfactual estimates for pre-crisis trend would have implied an average rise of ca 5 percent.

Last, but not least, “Firms producing basic metals, fabricated metal products and machinery and equipment are found to be the ones that were most penalized by the crisis of the last six years; by contrast, sectors that were already shrinking before 2008, such as the manufacture of textiles, appear not to have performed significantly worse during the double-dip recessions than they had in the early 2000s.”

10/6/16: Italian Industrial Production: 2007-2013

Staying with the earlier theme of industrial / manufacturing sector trends, here is a paper from the Banca d’Italia, authored by Andrea Locatelli, Libero Monteforte, and Giordano Zevi, titled “Heterogeneous Fall in Productive Capacity in Italian Industry During the 2008-13 Double-Dip Recession” (January 21, 2016, Bank of Italy Occasional Paper No. 303: http://ssrn.com/abstract=2759788) looks at the two periods of shocks, separated by one period of brief recovery.

Per authors, “between 2008 and 2013 productive capacity was considerably downsized in the Italian manufacturing sector” based on micro data from the Bank of Italy surveys across “the whole 2008-13 period and in four sub-periods (pre-crisis 2001-07, first phase of the crisis 2008-09, recovery 2010-11, and second crisis 2012-13).”

The study main findings are:
i) “losses of productive capacity varied widely across manufacturing sub-sectors with differences in pre-crisis trends tending to persist in a few sub-sectors during the double-dip recession”;
ii) “large firms were more successful in avoiding major capacity losses, especially in the first phase of the crisis”;
iii) “the share of sales on foreign markets was negatively correlated with performance in 2008-09, but the correlation turned positive in 2012-13”;
iv) “among the Italian macro-regions, the Centre weathered the long recession better” (see charts below);
v) “subsidiaries underperformed firms not belonging to any group”; and
vi) “the negative effects on productive capacity of credit constraints, which discouraged investments, were felt by Italian firms particularly in 2012-13”.

Very interesting outrun by region, presented here in two charts:

Some beef on that point: “The decline in [productive capacity] was not evenly distributed across the Italian macro-regions. The macro-regions more exposed to foreign demand were severely hit by the global financial crisis, with [productive capacity] declining by 8.6% in the North West and 7.0% in the North East.” Now, here’s the irony: Italy was (barely) able to sustain long-term Government borrowing on foot of its extremely strong exporters. During the recent twin crises, this very strength of the Italian economy turned against it. Which sort of raises few eyebrows: strong exporting capacity of Italy led the country to experience sharper shock than in many other states. Yet, the core prescription for growth from across the EU members states is - export!; and core prescription for recovery from the status quo main stream economists is - beef up current ace t surpluses (aka, raise exports relative to imports). Italian evidence does not really sound that supportive of these two ‘solutions’…

“During the temporary recovery, the South under-performed the rest of the country, losing 4.0% of its [productive capacity], while [productive capacity] stagnated in the other macro-regions.”

“The sovereign debt crisis affected the entire country more evenly. As a result, between 2010 and 2013 the loss of [productive capacity] in the South (-8.0%) was roughly twice as large as that recorded in the rest of the country (-4.7%)… The gap reflects the within-country heterogeneity in firms’ characteristics : …South Italy has mainly small firms, with an average of 100 employees (roughly constant during the double-dip crisis). Average firm size is larger in the Centre, just below 150, and in the North East, around 180, and even more so in the North West (consistently above 200). …southern regions have smaller export shares (about 20%), which are higher everywhere else (around 35% at the beginning of the sample); the export share shows a positive trend in all macro-regions.” You can see these reflected in the charts above.

In summary, thus, “the degree of foreign exposure helps to explain why the North suffered more during the global financial crisis. Also, the continuing decline of [productive capacity] in the South since 2007 is consistent with the smaller firm size in that macro-area (discussed above) and the larger decline of domestic demand there”.


So the key lesson here is: in the current environment characterised by rising regionalisation of trade flows and weak global demand, the exports-led recovery is more likely to trigger a negative shock to the economy than support economic growth.

Unless you are talking about a country like Ireland, where exports are booming despite global demand slowdown. Which, of course, cannot be explained by anything other than beggar-thy-neighbour tax optimisation policies.

10/6/16: Wither Manufacturing? Evidence from Denmark

Couple of posts relating to most current research on the recovery and longer term prospects in global manufacturing. As usual here, we shall focus on the advanced economies.

A recent NBER paper, by Andrew Bernard, Valerie Smeets, and Frederic Warzynski, titled “Rethinking Deindustrialization” (March 2016, NBER Working Paper No. w22114: http://ssrn.com/abstract=2755386) looked at decline in manufacturing activity in Denmark, showing that “manufacturing employment and the number of firms have been shrinking as a share of the total and in absolute levels.” The authors examine this phenomena over the period of 1994 to 2007.

“While most of the decline can be attributed to firm exit and reduced employment at surviving manufacturers, we document that a non-negligible portion is due to firms switching industries, from manufacturing to services.”

Here is an interesting list of related findings based on looking closer at the “last group of firms before, during, and after their sector switch”:

• “Overall this is a group of small, highly productive, import intensive firms that grow rapidly in terms of value-added and sales after they switch.”
• “By 2007, employment at these former manufacturers equals 8.7 percent of manufacturing employment, accounting for half the decline in manufacturing employment.”
• “…we identify two types of switchers: one group resembles traditional wholesalers and another group that retains and expands their R&D and technical capabilities.”

Net result? Quite surprising conclusion that the “findings emphasize that the focus on employment at manufacturing firms overstates the loss in manufacturing-related capabilities that are actually retained in many firms that switch industries.”

30/5/16: On-shoring Russian start ups into Ireland

My comment for the Irish Independent on some aspects of the reported increases in Russian tech start ups presence in Ireland: http://www.independent.ie/business/technology/russian-advance-into-irish-tech-sector-facilitated-by-bonoenda-double-act-34754317.html.

Must add that the EI are doing excellent job in Russian marketplace in sourcing some really exciting business development opportunities and providing huge support for Irish companies exporting into the market.

Also, note: Ireland Russia Business Association has merged with i-Cham at the beginning of 2016.

27/5/16: Ifo on the Effects of German Minimum Wage on Internships

Germany's Ifo institute issued the following press release concerning the effects of the recently introduced minimum wage law on internships (emphasis is mine):

"Munich, 27 May 2016 - The new minimum wage law in Germany has eliminated numerous internship positions. This is the result of the latest Ifo Personnel Manager Survey, conducted for Randstad Deutschland, which was published on Friday.

The number of companies offering internships has roughly halved. Before the introduction of the minimum wage, 70% of the companies said they offered voluntary internships, a number which has now fallen to 34%. This is also the case for compulsory internships, where the percentage of companies likewise fell from 62% to 34%.

The decline in internships is evident in companies of all sizes. For companies with more than 500 employees, the proportion of firms with voluntary internships decreased from 88% to 52% and for compulsory internships from 91% to 68%. In companies with fewer than 50 employees, the shares fell from 59% to 26% (voluntary) and from 49% to 21% (compulsory internships).

More than a few human resource managers indicated that because of personnel budget constraints the number of internships offered has been, in part, significantly reduced. Other companies now only offer compulsory internships or have reduced the duration of voluntary internships to three months. Some companies expressed complaints about the additional documentation requirements as well as uncertainty over the distinction between voluntary and mandatory internships.

Excluded from the minimum wage since 1 January 2015 are only internships that are compulsory as part of study or training regulations as well as voluntary internships of up to three months before or during vocational training or higher education. Additional exemptions from the minimum wage are the long-term unemployed for the first six months on the job."

Note: German labour markets are currently relatively tight when it comes to supply of skills, so reductions in internships, if confirmed by other sources, would be even more significant in such a setting.

4/5/16: Talent Is a Problem, But so Is Financial Services Model

When it comes to talent, hedge funds tend to hoover highly skilled and human capital-rich candidates like no other sub-sector. Which means that if we are to gauge the flow of talent into the general workforce, it is at the Wall Street, not the Main Street, where we should be taking measure of the top incoming labour pool. And here, Roger, we have, allegedly, a problem.

Take Steven Cohen, a billionaire investor hedge fund manager of Point72 (USD11 billion AUM). The lad is pretty good thermometer for ‘hotness’ of the talent pool because: (a) he employs a load of talented employees in high career impact jobs; (b) he tends to train in-house staff; (3) he operates in highly competitive industry, where a margin of few bad employees can make a big difference; and (4) courtesy of the U.S. regulators, he ONLY has his own skin in the game.

Cohen was speaking this Monday at the Milken Institute Global Conference about how he is "blown away by the lack of talent" of qualified incoming staff, saying that it is ”not easy to find great people. We whittle down the funnel to maybe 2 to 4 percent of the candidates we're interested in… Talent is really thin."

His fund hires only approximately 1/5th of its analysts and fund managers externally, with the balance 4/5ths coming from internal training and promotion channels.

The sentiment Cohen expressed is not new. International Banker recently featured an article by a seasoned Financial Services recruiter, who noted that “…many firms are finding it hard to attract the right candidates—and also failing to comprehend the true cost of finding the “right hire”” (see here: http://internationalbanker.com/finance/financial-services-need-put-culture-centre-organisations/).

Some interesting insights into shifting candidates preferences and attitudes and the mismatch these create between the structure and culture of Financial Services employment can be gleaned from this article: http://chapmancg.com/news/thought-leadership/2015/08/three-way-mirror-global-talent-challenges-in-financial-services. In particular, notable shifts in candidates’ culture with gen-Y entering the workforce are clearly putting pressure on Financial Services business model.

2015 study by Deloitte (see here: http://www2.deloitte.com/global/en/pages/financial-services/articles/gx-talent-in-insurance.html) summed up changes in Generational preferences for jobs in a neat graph:

And the business graduates’ career goals? Why, they are less pinstripes and more hipster:

In simple terms, it is quite unsurprising that Cohen is finding it difficult to attract talent. While supply of graduates might be no smaller in size, it is of different quality in expectations (and thus aptitude). Graduates’ expectations and values have shifted in the direction where majority are simply no longer willing to spend 5 years as junior analysts working 20 hour days 7 days a week in a sector that does pay well, but also faces huge uncertainties in terms of forward career prospects (to see this, read: http://linkis.com/constantcontact.com/9JrQd).

Which means, High Finance is in trouble: its business model does not quite allow for accommodating changing demographic trends in career development preferences. Until, that is, the tech bubble blows, leaving scores of talented but heavily hipsterized graduates no other option but to bite the bullet and settle into one of those 5-years long bootcamps.



NB: Incidentally, recently I was a witness to a bizarre conversation between a graduate and a senior professor. A graduate - heading by her own admission into a Government sector job in international policy insisted that the job requires her to be entrepreneurial, 'almost running [her] own business’. The faculty member supported her assertion and assured that she teaches students how to run their own businesses in courses she provides on... international diplomacy and policy. Not surprisingly, neither one of the two ever ran a business.

The hipster haven ideals of ‘we are all so creative, we can run a business from our college dorms’ run deep. And they are not about the blood and sweat of actually running a business, nor the risk of going into the world penniless and earning nothing for years on end while the business is growing. Instead, entrepreneurship for the young is all about perceived fun of doing so.

There will be tears upon collision with reality.

18/4/16: Taxing 1%?.. Make My Day...

An interesting paper on the dynamics of income inequality from Xavier Gabaix, Jean-Michel Lasry, Pierre-Louis Lions and Benjamin Moll (December 2015, CEPR Discussion Paper No. DP11028: http://ssrn.com/abstract=2714268).

Take in the abstract alone for key conclusion:

“The past forty years have seen a rapid rise in top income inequality in the United States. While there is a large number of existing theories of the Pareto tail of the long-run income distributions, almost none of these address the fast rise in top inequality observed in the data. We show that standard theories, which build on a random growth mechanism, generate transition dynamics that are an order of magnitude too slow relative to those observed in the data. We then suggest two parsimonious deviations from the canonical model that can explain such changes: "scale dependence" that may arise from changes in skill prices, and "type dependence," i.e. the presence of some "high-growth types." These deviations are consistent with theories in which the increase in top income inequality is driven by the rise of "superstar" entrepreneurs or managers.”

So the key to alleviating inequality increases (if the key were to be found in income / wealth tax territory so frequently inhabited by socialstas) is not to tax all high earners, but to tax the very left tail of the high earners’ distribution, or so-called “"superstar" entrepreneurs or managers”. It’s not a 1% tax, nor a tax on wealth (capital), nor a tax on “anyone earning more than EUR100,000” (the latter being commonly bandied around the countries like Ireland), that is a panacea. It is, rather, a tax on Zuckerbergs and Bloombergs, Bezoses and Ellisons et al.

Which, sort of, means taxing exactly those who create own wealth, rather than inherit it from mommy or daddy… Perverse? If it is the “high-growth types” that are the baddies, not the Rothschilds or the Kochs who inherited wealth, at fault, then the entrepreneurs should be taken out and fiscally shot.

And if you do, here’s what you will be fiscally shooting at: innovation (see http://www.nber.org/papers/w21247). The linked paper conclusion: “our findings vindicate the Schumpeterian view whereby the rise in top income shares is partly related to innovation-led growth, where innovation itself fosters social mobility at the top through creative destruction”.

Dust out that ‘tax the 1%’ argument, again… please.

17/4/16: Start Ups, Manufacturing Jobs and Structural Changes in the U.S. Economy

In the forthcoming issue of the Cayman Financial Review I am focusing on the topic of the declining labour productivity in the advanced economies - a worrying trend that has been established since just prior to the onset of the Global Financial Crisis. Another trend, not highlighted by me previously in any detail, but related to the productivity slowdown is the ongoing secular relocation of employment from manufacturing to services. However, the plight of this shift in the U.S. workforce has been centre stage in the U.S. Presidential debates recently (see http://fivethirtyeight.com/features/manufacturing-jobs-are-never-coming-back/).

An interesting recent paper on the topic, titled “The Role of Start-Ups in Structural Transformation” by Robert C. Dent, Fatih Karahan, Benjamin Pugsley, and Ayşegül Şahin (Federal Reserve Bank of New York Staff Reports, no. 762, January 2016) sheds some light on the ongoing employment shift.

Per authors, “The U.S. economy has been going through a striking structural transformation—the secular reallocation of employment across sectors—over the past several decades. Most notably, the employment share of manufacturing has declined substantially, matched by an increase in the share of services. Despite a large literature studying the causes and consequences of structural transformation, little is known about the dynamics of reallocation of labor from one sector to the other.”

“There are several margins through which a sector could grow and shrink relative to the rest of the economy”:

1. “…Differences in growth and survival rates of firms across sectors could cause sectoral reallocation of employment”
2. “…differences in sectors' firm age distribution could affect reallocation since firm age is an important determinant of growth or survival behavior” 
3. “…the allocation of employment at the entry stage which we refer to as the entry margin could contribute to the gradual shift of employment from one sector to the other.”
4. “…because the speed at which differences in entry patterns are reflected in employment shares depends on the aggregate entry rate, changes in the latter could affect the extent of structural transformation.”

Factors (1) and (2) above are referenced as “life cycle margins”.

The study “dynamically decomposed the joint evolution of employment across firm age and sector”, focusing on three sectors: manufacturing, retail trade, and services.

Based on data from the Longitudinal Business Database (LBD) and Business Dynamic Statistics (BDS), the authors found that “…at least 50 percent of employment reallocation since 1987 has occurred along the entry margin.” In other words, most of changes in manufacturing jobs ratio to total jobs ratio in the U.S. economy can be accounted for by new firms creation being concentrated outside manufacturing sectors.

Furthermore, “85 percent of the decline in manufacturing employment share is predictable from the average life cycle dynamics and the early 1980s distribution of startup employment across sectors. Further changes over time in the distribution of startup employment away from manufacturing, while having a relatively small effect on manufacturing where entry is less important, explain almost one-third of the increase in the services employment share.”

Again, changed nature of entrepreneurship, as well as in the survival rate of new firms created in the services sector, act as the main determinants of the jobs re-allocation across sectors.

Interestingly, the authors found “…little role for the year-to-year variation in incumbent behavior conditional on firm age in explaining long-term sectoral reallocation.” So legacy firms have little impact on decline in manufacturing sector jobs share, which is not consistent with the commonly advanced thesis that outsourcing of American jobs abroad is the main cause of losses of manufacturing sector jobs share in the economy.

Lastly, the study found that “…a 30-year decline in overall entry (which we refer to as the \startup deficit) has a small but growing effect of dampening sectoral reallocation through the entry margin.”

These are pretty striking results.

The idea that the U.S. manufacturing (in terms of the sector importance in the economy and employment) is either in a decline or on a rebound is not as straight forward as some political debates in the U.S. suggest.

Reality is: in order to reverse or at least arrest the decades-long decline of manufacturing jobs fortunes in America, the U.S. needs to boost dramatically capex in the sector, as well as shift the sector toward greater reliance on human capital-complementary technologies. It is a process that combines automation with more design- and specialist/on-specification manufacturing-centric trends, a process that is likely to see accelerated decline in lower skills manufacturing jobs before establishing (hopefully) a rising trend for highly skilled manufacturing jobs.

17/4/16: Human Capital, Management & Value-Added

The value of management to a given firm rests not only in more efficient use of physical resources and financial capital, as well as corporate / business strategy, but also in the ability of the firm to identify, hire, retain and enable high quality human capital. This is a rather common sense conclusion that might be drawn by any analyst of management systems and any business student.

However, the question always remains as to how much of the firm value-added arises from managerial inputs, as opposed to actual human capital inputs.

Stefan Bender, Nicholas Bloom, David Card, John Van Reenen, and Stephanie Wolter decided to attempt to quantify these differences. In their paper “Management Practices, Workforce Selection and Productivity” (March 2016, NBER Working Paper No. w22101: http://ssrn.com/abstract=2752306) they note that “recent research suggests that much of the cross-firm variation in measured productivity is due to differences in use of advanced management practices.”

“Many of these practices – including monitoring, goal setting, and the use of incentives – are mediated through employee decision-making and effort. To the extent that these practices are complementary with workers’ skills, better-managed firms will tend to recruit higher-ability workers and adopt pay practices to retain these employees.”

The authors then use a survey data on the management practices of German manufacturing firms, as well as data on earnings records for their employees “to study the relationship between productivity, management, worker ability, and pay”.

Per authors: “As documented by Bloom and Van Reenen (2007) there is a strong partial correlation between management practice scores and firm-level productivity in Germany. In our preferred TFP [total factor productivity] estimates only a small fraction of this correlation is explained by the higher human capital of the average employee at better-managed firms. A larger share (about 13%) is attributable to the human capital of the highest-paid workers, a group we interpret as representing the managers of the firm. And a similar amount is mediated through the pay premiums offered by better-managed firms.”

Human capital value-added is neither uniform across types of employees, nor is it independent of the management systems, which means that increasing the value of human capital in the economy requires more emphasis on the structure of the overall utilisation of talent, not just acquisition of talent. This is exactly consistent with the C.A.R.E. framework for human capital-centric economy that I outlined some years ago, here http://trueeconomics.blogspot.com/2013/11/14112013-human-capital-age-of-change.html, the framework of Creating, Attracting, Retaining and Enabling human capital.

The study also confirms that “looking at employee inflows and outflows, … better-managed firms systematically recruit and retain workers with higher average human capital.”

Overall, the authors concluded that “workforce selection and positive pay premiums explain just under 30% of the measured impact of management practices on productivity in German manufacturing.”

These results should add to questions about the ability of the Gig-economy firms, e.g. online platforms providers for labour utilisation, such as Uber, to significantly improve productivity in the economy. The reason for this is simple: contingent workforce talent pool is at least one step further removed from management than in the case of traditional employees. As the result, it is quite possible that contingent workforce productivity does not benefit directly from management quality. If so, that sizeable, ‘just under 30% of the measured impact’ in terms of improved productivity, arising from better management practices, workforce selection and pay premiums can be out of reach for Gig-economy firms and their contingent workers.

Again, as I noted repeatedly, including in my recent presentation at the CXC Global “Future of Work” Summit (see here: http://trueeconomics.blogspot.com/2016/04/7416-globalization-and-future-of-work.html), the key to developing a productive and sustainable Gig-economy will be in our ability to develop institutional, regulatory and strategic frameworks for improving management of human capital held by contingent workforce.

17/4/16: Peer Effects in Classroom: The Value of Better Discipline?

In workplace, as well as in education, peer-pressure and competition, peer-linked cooperation and collaboration and other peer-linked effects of have been important contributors to work- and learning-related outcomes. Ditto for entrepreneurship, as collaborated by the effects of clusters, such as the Silicon Valley. However, we tend to think of peer effects as arising from more mature, adult-level interactions in either third level education, or career-linked workplaces.

As noted by Scott Carrell, Mark Hoekstra and Elira Kuka in their paper “The Long-Run Effects of Disruptive Peers” (February 2016 as NBER WP No. w22042: http://ssrn.com/abstract=2739567), “there is relatively little evidence on the long-run educational and labor market consequences of childhood peers.”

So the authors examined “administrative data on elementary school students” and students’ “subsequent test scores, college attendance and completion, and earnings” to identify any potential effects of childhood peers on educational outcomes.

“To distinguish the effect of peers from confounding factors, we exploit the population variation in the proportion of children from families linked to domestic violence, who were shown by Carrell and Hoekstra (2010, 2012) to disrupt contemporaneous behavior and learning.”

The end results show that “exposure to a disruptive peer in classes of 25 during elementary school reduces earnings at age 26 by 3 to 4 percent. We estimate that differential exposure to children linked to domestic violence explains 5 to 6 percent of the rich-poor earnings gap in our data, and that removing one disruptive peer from a classroom for one year would raise the present discounted value of classmates' future earnings by $100,000.”

These are striking numbers. Accumulated over life-cycle of employment, gains from reducing classroom-level disruptive behaviour of peers can lead to a significant uplift in both, economic welfare and individual financial wellbeing. It can also, potentially, help closing the income inequality gaps. The question, however, is how does one achieve such an outcome in the real world, where even disruptive students have a right to education.

23/1/16: Non-Cognitive Human Capital

In my 2011 paper on the role of Human Capital in the emerging post-ICT Revolution economy, human capital will simultaneously:

1. Play increasingly more important role in determining returns to technical and processes innovation;
2. Become more diverse in its nature - or more diversified - spanning measurable and unmeasurable skills, traits, knowledge, attitudes to risk and innovation, capabilities etc.; and
3. Form the critical foundation of entrepreneurship and core employment base in the so-called Type 1 Gig-Economy - economy based on contingent workforce compered of highly skilled, highly value-additive professionals.

An interesting paper relating to the matter, especially to the last point, is a recent IZA Working paper (October 2015) titled “Non-Cognitive Skills as Human Capital” by Shelly Lundberg.

Per Lundberg: “In recent years, a large number of studies have shown strong positive associations between so-called “non-cognitive skills” — a broad and ill-defined category of metrics encompassing personality, socio-emotional skills, and behaviors — and economic success and wellbeing. These skills appear to be malleable early in life, raising the possibility of interventions that can decrease inequality and enhance economic productivity.”

Lundberg discusses “the extensive practical and conceptual barriers to using non-cognitive skill measures in studies of economic growth, as well as to developing or evaluating relevant policies. …There is a lack of general agreement on what non-cognitive skills are and how to measure them across developmental stages, and the reliance on behavioral measures of skills ensures that both skill indicators themselves, and their payoffs, will be context-dependent. The empirical examples show that indicators of adolescent skills have strong associations with educational attainment, but not subsequent labor market outcomes, and illustrate some problems in interpreting apparent skill gaps across demographic groups.”

From the Gig-Economy point of view, development of all (cognitive and non-cognitive) skills requires time and resources. In traditional workplace setting - of old variety - some of these resources and time allocations are supported / subsidised by employers (e.g. gym memberships, formal paid time off, formal paid career breaks, formal 'team building' activities, actual employer-paid training and education, employer-supported psychological wellness programmes for employees, and so on). In a Gig-Economy setting, these are not available, generally, to contingent workers.

Aside from having impact on contingent workforce skills and human capital, there are more 'trivial' considerations that should be put to analysis. Take, for example, health and psychological well-being. If a contingent workforce using company fails to assure the latter for its contingent workers, who is liable for any damages caused by over-worked, over-stressed, psychologically unwell contingent worker to the company clients?

Again, setting aside humanitarian, social and personal considerations, this question has implications for businesses using contingent workers:

• Insurance costs and coverage for businesses;
• Legal costs and coverage for business;
• Reputational risks for businesses;
• Counter-party risks for businesses; and so on

In a world where there is no such thing as a free lunch, Gig-Economy based companies should seriously consider how they are going to deal with potential costs of disruption from the Gig-Economy type of employment to life-cycle work practices and financial wellbeing of their contingent workers.


Note: More on the subject of non-cognitive skills and human capital:

• Early childhood: "Non Cognitive Skills and Personality Traits: Labour Market Relevance and their Development in Education & Training Systems" by Giorgio Brunello and Martin Schlotter, IZA DP No. 5743
• Early childhood and education: "Formulating, Identifying and Estimating the Technology of Cognitive and Noncognitive Skill Formation", by Flavio Cunha and James Heckman, University of Michigan Working Paper.
• Adult development: “Do Sporty People Have Access to Higher Job Quality?” by Charlotte Cabane, DIW working paper, 2010. 
• Related to sports and extracurricular activities: “Sports and Child Development” by Christina Felfe, Michael Lechner and Andreas Steinmayr, IZA Working Paper, 2011. And “Unemployment Duration and Sport Participation” by Charlotte Cabane,International Journal of Sport Finance, un-gated version ftp://mse.univ-paris1.fr/pub/mse/CES2011/11049R.pdf from 2011.
• Income effects: “Income Comparisons and Non-cognitive Skills” by Santi Budria and Ada Ferrer-i-Carbonell, DIW Working Paper, 2012.

13/12/15: Strelka Institute: Interview

Recently, I gave an interview (in Russian) to Strelka Institute in Moscow. The interview covered the importance of linking economic development and urban design to sustain a C.A.R.E system of supports for human capital-intensive economy. Here is the interview link: http://www.strelka.com/ru/magazine/2015/12/01/gurgiev.

7/12/15: CX Future of Work Summit: Dublin

Another excellent video from the CXC Corporate's "Future of Work" summit on the Gig Economy: https://vimeo.com/148042205.

You can see more on the event, including my slides here: http://trueeconomics.blogspot.ie/2015/11/111115-gig-economy-challenge.html

11/11/15: The Gig Economy: A Challenge

Last week, I spoke at CXC Corporate event “Globalization & The Future of Work Summit” in Dublin covering the topic of major economic disruption coming on foot of the evolving Gig Economy. I covered some of the background aspects of my presentation in an earlier blogpost here.

Here are my slides from the presentation (I will be posting a video link once it becomes available).

22/10/15: Gig Economy and Human Capital: Evidence from Entrepreneurship and Self-Employment

In a couple of weeks, I will be speaking about the role of human capital in the emergence of the new economy at the CXC Corporate event “Globalization & The Future of Work Summit” in Dublin.

Without preempting what I am going to say, here are some key points of interest.

Human capital-centric growth is overlapping, but distinct from the so-called “Gig Economy”, primarily because of the different definition of what constitutes two respective workforces.

Take, for example, the U.S. data. Based on research by the American Action Forum by Rinehart and Gitis (2015) we can define three types of the broadly-speaking “Gig Economy” workers: “For our most narrow measurement of gig workers (labeled Gig 1) we simply include independent contractors, consultants, and freelancers. Our middle measurement (Gig 2) includes all Gig 1 workers plus temp agency workers and on-call workers. Our broadest measurement (Gig 3) includes all Gig 2 workers plus contract company workers.”

The respective numbers engaged in three categories in 2014 range between 20.5 million and 29.7 million with growth rates over the recent years outpacing economy-wide jobs expansion rates across all categories of the Gig Economy workers.

Still, the key problem with identifying underlying trends in the development of the Gig Economy is the lack of data on specifics of occupational choices of the self-employed individuals and the relationship between these choices and human capital held by the Gig Economy participants relative to the traditional employees.

To see the indicators of links between the Gig Economy and human capital, we have to look at the more established literature concerning transition to entrepreneurship.

One interesting set of studies here comes from the Italian Survey of Household Income and Wealth (SHIW), a large biannual household survey conducted by the Banca d’Italia. A 2007 paper by Federici, Ferrante and Vistocco looked at the links between institutional structures, technological innovation and human capital in determining the propensity to transition from employment to entrepreneurship. Looking at the general literature on the subject, the authors state that “…institutions are more important than technology (i.e., technological specialization and/or industry composition) in fostering or restricting entrepreneurship and that the interactions between institutions and occupational choices may be complex and non linear”. The authors caution against directly linking self-employment rates with entrepreneurship rates, as “countries displaying the same self-employment rates, might be endowed with very different amounts and qualities of entrepreneurial skills devoted to innovation and business ventures (or, on the other hand, they might not)”.

To better pinpoint the link between entrepreneurship, self-employment and the institutional and technological drivers for risk taking, Federici, Ferrante and Vistocco augment the survey data with a set of variables describing the social and institutional environment in which self-employed and traditional workers are operating. Crucially, “in addition to standard indexes of economic and social infrastructure at the local level, [the authors] include a measure of creativity developed by Florida (2004).”

The conclusions are strong: “in Italy, both institutional and technological factors have shaped entrepreneurial opportunities requiring, tacit knowledge embedded in social networks and in the cultural background of families… Hence, well-educated people lacking privileged access to tacit knowledge and, in particular, an appropriate family background, could find themselves up against a considerable barrier to entrepreneurship and occupational mobility.” In simple terms, the Gig Economy-related value added can and should be considered within the context of family and cultural institutions as much as technological enablement environment.

As per traditional metrics of human capital, the study conclusions appear to be contradicting the core literature on entrepreneurship. “The evidence of the highly significant negative role of education in entrepreneurial selection is very strong in comparison with the majority of international studies showing that education has either a positive impact (Blanchflower, 1998) or a statistically non-significant effect on occupational choices”. In other words, formal education seems to be more conducive to employment choices in traditional environments (e.g. full time jobs),w it exception, perhaps, of professional skills-based activities.

The negative links between education and propensity to engage in entrepreneurial activity is, however, in line with other Italian study based on the same data, authored by Sabatini (2006).

However, U.S. data-based studies frequently find existence of a U-shaped relationship between income and propensity to transition to self-employment, with highest propensities concentrated around low income earners and high income earners, while lower propensities occurring for middle income earners. One recent example of this evidence is Moutray (2007). In so far as formal education is an instrument for income, especially for sub-populations excluding very high income earners, this suggests that the negative relationship between self-employment and education found in the case of Italy can be culturally conditioned and does not translate to other economies.

Another interesting aspect of transition to the ‘Gig Economy’ relating to the links between human capital and creativity or cultural institutions was uncovered by a 2011 paper by Mitra and Abubakar who looked at data from the Local Authority Districts of Thames Gateway South Essex (TGSE) in East of England. The study attempted “to explore and identify key determinants of business formation in Knowledge Intensive sectors (which include the creative industries) of regions outside the major metropolitan conurbations, and their possible differences with other Non-Intensive Sectors.”

The authors found that human capital is “positively correlated with new business entry in Knowledge intensive sectors”, but at the same time, it is “negatively correlated with new startups in non-knowledge intensive sectors”. Per authors: “This finding suggests that while entrepreneurship in knowledge based and creative industries requires highly skilled labour, in non knowledge based industries, low skilled labour is the primary determinant of new firm creation. Our findings also appear to suggest the need for higher skills/educated base in order to boost the growth of new businesses” in high knowledge-intensity sectors.

Werner and Moog (2009) use data from the German Socio-Economic Panel (SOEP) to map out significant linkages between entrepreneurial learning (and entrepreneurial human capital) and the probability of transition from traditional employment to self-employment. One interesting aspect of their findings is that learning-by-doing occurring (in their sample) during tenure of working for an SME has positive impact on ability to transition to entrepreneurship, confirming similar findings from other European countries. This also confirms findings that show that working for SMEs results in more frequent exits into self-employment and that such exits more frequently result in transition to full entrepreneurship than for self-employment entered from employment in larger firms.

The learning-by-doing effect of pre-transition experience for starting entrepreneurs and self-employed is also confirmed by the UK study by Panos, Pouliakas and Zangelidis (2011) who looked at the self-employment transition dynamics for individuals with dual job-holding and the links between this transition and human capital and occupational choice between primary and secondary jobs. The study used a wide (1991-2005) sample of UK employees from the British Household Panel Survey (BHPS). The authors investigated, sequentially, “first, the determinants of multiple job-holding, second, the factors affecting the occupational choice of a secondary job, third, the relationship between multiple-job holding and job mobility and, lastly, the spillover effects of multiple job-holding on occupational mobility between primary jobs.” The findings indicate that “dual job-holding may facilitate job transition, as it may act as a stepping-stone towards new primary jobs, particularly self-employment.” An interesting aspect of the study is that whilst the major effects are present in the lower skilled distribution of occupations, there is also a significant and positive effect of dual-jobs holding on transition to self-employment for professional (highly skilled) grade of workers.

Finally, there is a very interesting demographic dimension to transition to self-employment, explored to some extent in the U.S. data by Zhang (2008). The paper focused on the topic of elderly entrepreneurship. The author conjectures that in modern (ageing) demographic setting, “the “knowledge economy” could elevate the value of elderly human capital as the “knowledge economy” is less physically demanding and more human-capital- and knowledge-based.” Zhang (2008) largely finds that professional, skills-based self-employment and entrepreneurship amongst the older generations of workers can act as an important force in reducing adverse impact of ageing on modern economies.


The common thread connecting the above studies and indeed the rest of the vast literature on entrepreneurship, self-employment and transition from traditional employment to more projects-based or client-focused forms of engagement in the labour markets is increasingly shifting toward the first type of the ‘Gig Economy’ engagement. This typology of the ‘Gig Economy’ is becoming more human capital and skills-intensive and is better aligned with the ‘knowledge economy’ and the ‘creative economy’ than ever before. In simple terms, therefore, the ‘Gig Economy’ not only reaches deeper than the traditional view of the shared services (Uber et al) growth trends suggest.

While both increasing in importance and broadening the set of opportunities for economic development, the modern ‘Gig Economy’ is presenting significant challenges to social, cultural and policy norms that require swift addressing. These challenges are broadly linked to the need to Create, Attract, Retain and Enable key human capital necessary to sustain long term development and growth of the ‘Gig Economy’.

With that, tune in to my talk at the CXC Corporate event “Globalization & The Future of Work Summit” (link: http://cxccorporateservices.com/cxc-future-of-work/) in few weeks time for the details as to what should be done to put global ‘Gig Economy’ onto the sustainable development and growth track.


Sources:

Will Rinehart, Ben Gitis, “Independent Contractors and the Emerging Gig Economy” July 29, 2015,

Federici, Daniela and Ferrante, Francesco and Vistocco, Domenico, "On the Sources of Entrepreneurial Talent in Italy: Tacit vs. Codified Knowledge" (July 24, 2007)

Sabatini, Fabio, "Educational Qualification, Work Status and Entrepreneurship in Italy: An Exploratory Analysis" (June 2006). FEEM Working Paper No. 87.2006

Velamuri, S. Ramakrishna and Venkataraman, S., "An Empirical Study of the Transition from Paid Work to Self-Employment". Journal of Entrepreneurial Finance and Business Ventures, Vol. 10, No. 1, pp. 1-16, August 2005

Moutray, Chad M., "Educational Attainment and Other Characteristics of the Self-Employed: An Examination Using Data from the Panel Study of Income Dynamics" (December 11, 2007). Hudson Institute Research Paper No. 07-06.

Mitra, Jay and Abubakar, Yazid, "Entrepreneurial Growth and Labour Market Dynamics: Spatial Factors in the Consideration of Relevant Skills and Firm Growth in the Creative, Knowledge-Based Industries" (August 23, 2011). University of Essex CER Working Paper No. 1.

Werner, Arndt and Moog, Petra M., "Why Do Employees Leave Their Jobs for Self-Employment? – The Impact of Entrepreneurial Working Conditions in Small Firms" (November 1, 2009).

Panos, Georgios A. and Pouliakas, Konstantinos and Zangelidis, Alexandros, "Multiple Job Holding as a Strategy for Skills Diversification and Labour Market Mobility" (August 23, 2011). University of Essex CER Working Paper No. 4.

Zhang, Ting, "Elderly Entrepreneurship in an Aging U.S. Economy: It's Never Too Late" (September 8, 2008). Series on Economic Development and Growth, Vol. 2.

4/10/15: IBM: Some Tough Numbers on Higher Education Success

IBM Institute for Business Value Higher Education Survey 2015 with results published in June 2015 has been quite an interesting read. The report “Pursuit of relevance How higher education remains viable in today’s dynamic world” is available here.

Take the following Question: “To what extent do you believe the current higher education system in your country is meeting the needs of the following groups?”

Chart below plots percentages of respondents by group across three core categories of ‘customers’: students, employers and society at large.

One thing that jumps out is that corporate recruiters are relatively more positive than education providers (excluding university staff) when it comes to assessing the education system performance.

Another conclusion that jumps out is that with exception of one sub-group in one category, overall assessment of education systems is pretty grim - no >50% support for the proposition that education system meets the needs of either students, employers or society.

Third conclusion is that, on average, higher education systems serve better the needs of students, followed by society, than industry.

More damning, “Survey results also point to higher education shortfalls in other areas. In terms of economic value, only 51 percent of industry and academic leaders believe higher education is providing value for money, and just 49 percent view it as contributing to economic growth and competitiveness.”

There is also a very interesting gap across respondents categories in terms of what is perceived to be the most important metrics of success of modern education system. Chart below illustrates:

As can be glimpsed from above, educators are literally falling over themselves in pursuit of jobs placements. While corporate recruiters and learning executives are less warm about this objective.

Very interesting findings, some counter-intuitive, some potentially arising from the sample selection biases (after all,  we don't have much to go by in terms of actual corporate leaders, and data reported is limited, as for example the chart above clearly shows). Nonetheless, the questions raised are of great importance.

25/7/15: Irish Migration Policies: Welcoming the Skilled & the Enterprising

My recent article for the Irish Independent on the topic of human capital, migration and Irish policies on attracting skilled labour and foreign entrepreneurs: http://www.independent.ie/opinion/comment/we-should-be-paving-the-way-not-putting-up-barriers-to-foreign-talent-and-investment-31397773.html

7/6/15: Secular Stagnation: A Double-Threat

Recent evidence on long term growth dynamics and drivers decomposition across the advanced economies presents a striking paradox relating to the post-recessionary experience around the world. In a traditional business cycle, recovery period growth exhibits certain historical regularities, that are no longer present in the current cycle. These regularities involve the following stylised facts:

1) Following a recessionary contraction in aggregate output, advanced economies enter a stage of recovery associated with strong growth in investment and domestic demand;

2) Gains in factors' productivity, especially in labour productivity, are amplified in the early stages of post-recessionary recovery compared to their pre-crisis trend levels; and

3) Rates of growth in the recovery cycle are in excess of pre-recessionary growth.

These facts are patently absent from the data for the major advanced economies today, some four to five years into the recovery. This realization has prompted some economic and financial analysts to speculate about the potential structural decline in long term growth rates, the thesis commonly termed "secular stagnation".

Currently, there are two prevailing theses of secular stagnation, linked to two long-term cycles gaining prominence in the global economy: the demand side and the supply side theses.

Investment-Savings Mismatch

The first theory suggests that secular stagnation is linked to a structural decline in aggregate demand, manifesting itself though a decades-long mismatch between aggregate savings and investment and more broadly related to the demographic effects of ageing.

This theory traces back to the 1930s suggestion by Alvin Hansen that the U.S. Great Depression aftermath was coinciding with decreasing birth rates, resulting in oversupply of savings and a fall off in demand for investment. The thesis was salient throughout the 1930s and the first half of the 1940s, but was overrun by the war and subsequently forgotten in the years of the post-WW2 baby boom and investment uplift. Large scale increase in public investment, linked to rebuilding destroyed (in Europe and Japan) or neglected (in the war years in the U.S.) public infrastructure, helped to push Hansen's forecasts of a structural growth slowdown aside.

The thesis of demand-driven secular stagnation made its first return to the forefront of macroeconomic thinking back in the 1990s, in the context of Japan. As in Hansen's 1930s U.S., by the early 1990s, Japan was suffering from a demographics-linked glut of savings, and a structural drop off in investment. Suppressed domestic demand has led to a massive contraction in labour productivity. During the 1980-1989 period, Japan's real GDP per worker averaged 3.2 percent per annum. In the following decade, the rate of growth was just over 0.82 percent and over the period of 2000-2009 it fell below 0.81 percent. Meanwhile, Japan's investment as a percentage of GDP fell from approximately 29-30 percent in the 1980s and the 1990s to under 23 percent in the 2000s and to just over 20 percent in 2010-2015.

Following Japan's experience and the shock of the Great Recession, the theory that the entire developed world is set for a structural growth slowdown has gained traction. Between 1980 and 2014, the gap between savings and investment as percentage of GDP has widened in Canada, Japan, and the Euro area. Controlling for debt accumulation in the real economy, the widening of savings surplus over investment over each decade since the 1980s is now present in all major advanced economies, including the U.S.

In line with this, labour productivity also fell precipitously across all major advanced economies. As shown in the chart below, even a period of unprecedented rise in unemployment in the U.S. and the euro area over the recent Great Recession did not shift the trend for declining labour productivity growth.

CHART: Five-year Cumulated Growth in Real GDP per Employee

Percentage Points

Source: Author own calculations based on data from the IMF

Worse, current zero rates monetary policy environment is reinforcing the savings-investment mismatch, rendering the monetary policy impotent, if not damaging, in stimulating the return to higher long term growth.

Traditionally, low interest rates create incentives for investment and reduced saving by lowering the cost of the former and increasing the opportunity cost of the latter.

However, today's ageing demographics and rising dependency ratios offset these 'normal' effects. This means that for the older generations, retirement pressures work through both insufficient reserves built in pensions portfolios, and also through lower yields on retirement portfolios, incentivising more aggressive savings.

For the working age population, the pressures are more complex. On the one hand, middle age workers today face severe pressures to deleverage their balance sheets, aggressively reducing liabilities accumulated before the crisis. On the other hand, growing proportions of middle-age adults are facing twin financial pressures from the rising demand for support for ageing parents and, simultaneously, for increasing number of satay-at-home younger adults who continue to rely on family networks for financial and housing subsidies. A recent Pew Research study found that 64 percent of Italian middle-aged generations find themselves sandwiched between ageing parents and children. In the U.S. this proportion is 47 percent and in Germany 41 percent. All along, the same households are under pressure to build up their pensions, as retirement security and social provision of pensions are now highly uncertain.

In his speech to the NABE Policy Conference in February 2014, Lawrence H. Summers (http://larrysummers.com/wp-content/uploads/2014/06/NABEspeech-

Lawrence-H.-Summers1.pdf) outlined six  core sources of this demand side-driven slowdown:

1) Existent legacy of the private debt overhang;

2) Demographics of ageing;

3) Rising income inequality that induces greater financial insecurity today and into the future, thus creating incentives for increased ordinary and precautionary savings;

4) Access to low cost capital;

5) Positive real interest rates that continue to prevail despite historically low policy rates; and

6) Large scale holdings of banks' reserves on central banks balance sheets.

All of these factors are currently at play in the U.S., UK and the euro area, as well as Japan. With a lag of about 3-5 years, they are also starting to manifest themselves in other advanced economies.

Tech Investment: Value-Added  Miss

The supply side of secular stagnation thesis is a relatively new idea coming from the cyclical view of historical development of physical and ICT-linked technologies. First formulated by Robert Gordon some years ago it is summarised in his August 2012 NBER paper, titled "Is the US Economic Growth Over? Faltering Innovation Confronts the Six Headwinds" (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2133145).

Gordon looks at long-term - very long-term - trends in growth from the point of challenging the traditional view of macroeconomists that perpetual economic progress is subject to no time constraints. In Gordon's view, U.S. economy over the period through the 2050s is likely to face an uphill battle. Per Gordon, "The frontier established by the U.S. for output per capita, and the U. K. before it, gradually began to grow more rapidly after 1750, reached its fastest growth rate in the middle of the 20th century, and has slowed down since.  It is in the process of slowing down further."

The reason for this, according to the author, is the exhaustion of economic returns to the most recent technological / industrial 'revolution'.  "A useful organizing principle to understand the pace of growth since 1750 is the sequence of three industrial revolutions. The first with its main inventions between 1750 and 1830 created steam engines, cotton spinning, and railroads. The second was the most important, with its three central inventions of electricity, the internal combustion engine, and running water with indoor plumbing, in the relatively short interval of 1870 to 1900.  Both the first two revolutions required about 100 years for their full effects to percolate through the economy. …After 1970 productivity growth slowed markedly, most plausibly because the main ideas of [the second revolution] had by and large been implemented by then. The computer and Internet revolution began around 1960 and reached its climax in the dot.com era of the late 1990s, but its main impact on productivity has withered away in the past eight years. …Invention since 2000 has centered on entertainment and communication devices that are smaller, smarter, and more capable, but do not fundamentally change labor productivity or the standard of living in the way that electric light, motor cars, or indoor plumbing changed it."

Gordon’s argument is not about the levels of activity generated by the new technologies, but about the rate of growth in value added arising form them. In basic terms, ongoing slowdown in the U.S. (and global) economy is a function of six headwinds, including the end of the baby boom generation-linked demographic dividend; rising income and wealth inequality; factor price equalisation; lower net of cost returns to higher education; the impact of environmental regulations and taxes; and real economic debt overhangs across public and non-financial private sectors.

Gordon estimates that future growth in consumption per capita for the bottom 99 percent of the income distribution is likely to fall below 0.5 percent per annum over the period of some five decades.

The supply-side thesis, implying persistently falling returns to technological innovation and resulting reduced rates of productive investment in technological capital, is supported by some top thinkers in the tech sector, notably the U.S. entrepreneur and investor Peter Thiel (see http://www.ft.com/intl/cms/s/0/8adeca00-2996-11e2-a5ca-00144feabdc0.html).

A recent study from IBM, titled "Insatiable Innovation: From sporadic to systemic", attempted to debate the thesis, but ended up confirming Gordon’s assertion that incremental and atomistic innovation is the driver for today's technological progress. In other words, the third technological revolution is delivering marginal returns on investment: significant and non-negligible from the point of individual enterprises, but hardly capable of sustaining rapid rates of growth in economic value added over time.

Disruptive Change Required

The problem is that both theses of secular stagnation are finding support not only in the past historical data, but also in the more recent trends. Even the most recent World Economic Outlook update by the IMF (April 2015) shows that the ongoing economic slowdown is structural in nature and traces back to the period prior to the onset of the Great Recession.

As both, the demand and supply side theses of secular stagnation allege, the core drivers identified by the IMF as the force behind this trend are adverse demographics, decline in investment, a pronounced fall off in total factor productivity growth (the tech factor), as well as the associated decline in labour and human capital contributions to productivity. IMF evidence strongly suggests that during the pre-crisis spike in global growth, much of new economic activity was driven not by expansion on intensive margin (technological progress and labour productivity expansion), but by extensive margin (increased supply of physical capital and emergence of asset bubbles).

Like it or not, to deliver the growth momentum necessary for sustaining the quality of life and improvements in social and economic environment expected by the ageing and currently productive generations will require some serious and radical solutions. The thrust of these changes will need to focus on attempting to reverse the decline in returns to human capital investment and on generating radically higher economic value added growth from technological innovation. The former implies dramatic restructuring of modern systems of taxation and public services provision to increase incentives for human capital investments. The latter implies an equally disruptive reform of the traditional institutions of entrepreneurship and enterprise formation and development.

Absent these highly disruptive policy reforms, we will find ourselves at the tail end of technological growth frontier, with low rates of return to technology and innovation and, as the result, permanently lower growth in the advanced economies.