Showing posts with label Productivity. Show all posts
Showing posts with label Productivity. Show all posts

Sunday, February 24, 2019

24/2/19: Buybacks vs Capex


U.S. corporates spending or 'investing' over the last 10 years:

  • CapEx ($6.4T), including often non-productive M&As
  • Buybacks ($4.9T) and 
  • Dividends ($3.4T) 


via @mbarna6

Just another reminder why productivity growth is not being aided by cheap credit.

Friday, April 21, 2017

21/4/17: Any evidence that immigrants are undermining welfare of the natives?


Given current debates surrounding the impact of migrant labour on native (and previously arriving migrants) wages, jobs security, career prospects and other major motivations behind a wide range of migration regimes reforms proposed across a number of countries, including the U.S., it is worth revisiting research done by Giovanni Peri of University of California, Davis, USA, and IZA, Germany back in 2014.

Titled “Do immigrant workers depress the wages of native workers?” and published by IZA World of Labor 2014: 42 in May 2014, https://wol.iza.org/articles/do-immigrant-workers-depress-the-wages-of-native-workers/long, the paper reviews 27 original studies published between 1982 and 2013, covering the topic of immigration impact on wages of the natives. Chart below summarises:


In the above, the “values report the effects of a 1 percentage point increase in the share of immigrants in a labor market (whether a city, state, country, or a skill group within one of these areas) on the average wage of native workers in the same market.

For example, an estimated effect of 0.1 means that a 1 percentage point increase in immigrants in a labor market raises the average wage paid to native workers in that labor market by 0.1 percentage point. These studies used a variety of reduced-form estimation and structural estimation methods; all the estimates were converted into the elasticity described here.”

Here’s the summary of Peri’s findings and conclusions:



Monday, April 18, 2016

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.

Tuesday, November 24, 2015

24/11/15: Europe's Dead Donkey of Productivity Growth


Remember the mythology of European productivity miracles:

  1. The EU is at least as competitive as the U.S. (with Lisbon Agenda completed, or rather abandoned);
  2. The EU growth in productivity is structural in nature (i.e. not driven by capital acquisition alone and not subject to cost of capital effects); and
  3. The EU productivity growth is driven by harmonising momentum (common markets etc) at a policy level, with the Euro, allegedly, producing strong positive effects on productivity growth.
Take a look at this chart from Robert J. Gordon's presentation at a recent conference:
The following observations are warranted:
  • EU convergence toward U.S. levels of productivity pre-dates major policy harmonisation drives in Europe and pre-dates, strongly, the creation of the Euro;
  • EU productivity convergence never achieved parity with the U.S.;
  • EU productivity convergence was not sustained from the late 1990s peak on;
  • The only period of improved productivity in the EU since the start of the new millennium was associated with assets bubble period (interest rates and credit supply).
Darn ugly!

But it gets worse. Since the crisis, the EU has implemented, allegedly and reportedly, a menu of 'structural' reforms aiming at improving competitiveness.  Which means that at least since the end of the crisis, we should be seeing improved productivity growth differentials between Europe and the U.S. And the EU case for productivity growth resumption is supported by the massive, deeper than the U.S., jobs destruction during the crisis that took out a large cohort of, supposedly, less productive workers, thereby improving the remainder of the workforce levels of productivity.

Here is a chart from the work by John Van Reenen of LSE:


Apparently, none of this happened:
  • EU structural reforms have been associated (to-date) with much lower productivity growth post-crisis than the U.S. and Japan;
  • EU jobs destruction during the crisis has been associated with lower productivity increases than in the U.S. and Japan;
  • All EU programmes to support growth in productivity, ranging from the R&D supports to investment funding for productivity-linked structural projects have produced... err... the worst outcome for productivity growth compared to the U.S. and Japan.
And the end result?

I know, I know... a Genuine Productivity Union, anyone?...

Monday, May 13, 2013

13/5/2013: Work Hours, Education Years and Wages


A fascinating fact: "An average person born in the United States in the second half of the 19th century completed 7 years of schooling and spent 58 hours a week working in the market. In contrast, an average person born at the end of the 20th century completed 14 years of schooling and spent 40 hours a week working. In the span of 100 years, completed years of schooling doubled and working hours decreased by 30%."

Restuccia, Diego and Vandenbroucke, Guillaume ask "What explains these trends?"

Their paper (link below) quantitatively assessed "the contribution of exogenous variations in productivity (wage) and life expectancy in accounting for the secular trends in educational attainment and hours of work."

And the result? "We find that the observed increase in wages and life expectancy accounts for 80% of the increase in years of schooling and 88% of the reduction in hours of work. Rising wages alone account for 75% of the increase in schooling and almost all the decrease in hours in the model, whereas rising life expectancy alone accounts for 25% of the increase in schooling and almost none of the decrease in hours of work."

Restuccia, Diego and Vandenbroucke, Guillaume, A Century of Human Capital and Hours (July 2013). Economic Inquiry, Vol. 51, Issue 3, pp. 1849-1866, 2013. http://ssrn.com/abstract=2261571

Aside 1: note that higher wages (when aligned with higher productivity) imply higher human capital intensity and lower hours of wrok supplied.

Aside 2: there seem to be no control for the reporting of hours supplied. In mid-19th century and even in first half of 20th century, most of work performed was time-sheeted. Today, majority of us do not have time cards, so on the surface, our contracts say 40 hours per week, in reality this means 60 hours per week.

Saturday, March 6, 2010

Economics 06/03/2010: Do friendships matter in a workplace?

An interesting article on workplace organization/networks and productivity of workers, forthcoming in the next month's issue of Review of Economic Studies, Vol. 77, Issue 2, pp. 417-458, April 2010 (link here; authors: Bandiera, Oriana, Barankay, Iwan and Rasul, Imran, Social Incentives in the Workplace).

The article shows evidence that social incentives in the workplace, namely the effect of the presence of those that workers are socially tied to on their own productivity, matter a great deal.
Controlling for possible workplace externalities, such as co-sharing of tasks and technology, the authors combine data on individual worker productivity with information on each worker’s social network of friends in the firm.

"We find that compared to when she has no social ties with her co-workers, a given worker’s productivity
  • is "significantly higher when she works alongside friends who are more able than her", and
  • significantly lower when she works with friends who are less able than her.
Social incentives imply that
  1. workers who are more able than their friends are willing to exert less effort and forgo 10% of their earnings (in other words - they have 10% lower productivity);
  2. workers who have at least one friend who is more able than themselves are willing to increase their effort and hence productivity by 10%.
The distribution of worker ability is such that the net effect of social incentives on the firm’s
aggregate performance is positive.

These are interesting results and have implications for organizational structure of the workplace. They suggest that
  • workplace arrangements that reduce social interaction between heterogeneous workers (e.g. extremely dis-franchised workplaces with nomadic flows of temporary workers and workers who are not anchored to a specific location) might suboptimally reduce productivity;
  • peer pressure within social networks is mean-convergent, with lower quality human capital being pushed up the quality chain and higher quality human capital being compressed downward;
  • more heterogeneity in social networks would suggest a higher productivity mean; and
  • workplaces that discourage social interactions are also potentially reducing productivity.
The aspects that are descriptive of the strength of social interactions used by the authors include pre-existing friends as co-workers, reciprocal friends, sharing in supermarket shopping, eating together, lending/borrowing money and sharing problems with each other.

Since social effects on productivity can counteract each other (e.g. due to mean convergence, better workers might reduce productivity while poorer workers might increase it), there is a clear need to align pay rewards structures with the nature of the workplace setting and the extent and nature of social interactions that can be supported by the workplace. The results suggest that:
  • more depersonalized, less interactive workplace settings should use greater pay incentives geared toward lower quality workers (wage compression);
  • less depersonalized and more socially interactive workplaces should reward higher performers more (to counter potential quality of worker compression through wage widening)