Category Archives: skills

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:

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: 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: 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.”

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: 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.


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.

23/4/15: Skills and Employment: 1950-2010 Data

A very interesting study, titled "Labor Market Polarization Over the Business Cycle" by
Christopher L. Foote and Richard W. Ryan ( from the Boston Fed postulates that "Job losses during the Great Recession were concentrated among middle-skill workers, the same group that over the long run has suffered the most from automation and international trade." This is what is known as occupational polarisation - the disappearance of mid-range skills and low-end skills jobs and growth in higher skilled occupations.

The study finds "that middle-skill occupations have traditionally been more cyclical than
other occupations, in part because of the volatile industries that tend to employ middle-skill workers. Unemployed middle-skill workers also appear to have few attractive or feasible employment alternatives outside of their skill class, and the drop in male participation rates during the past several decades can be explained in part by an erosion of middle-skill job opportunities."

One hell of a chart illustrating the above across longer time horizon:

Shares of Employment for Four Occupational Groups: