1. Nick Bloom, Econ 247, 2011 Nick Bloom Productivity and Reallocation

2. Nick Bloom, Econ 247, 2011 Big Overview Economists started looking at establishment data in the 1990s (Haltiwanger, Davis, Bartelsman, Bailey etc.) There was surprise over: High levels of turnover Heterogeneity within industries The lumpiness of micro-economic activity The importance of reallocation in driving productivity

3. Nick Bloom, Econ 247, 2011 Why should you be interested in this? First, this is important to understanding macroeconomic activity – e.g. 3/4 productivity growth is reallocation, unemployment driven by rates of churn Second, this is a fertile area of research: It is new – many open questions It is hard – typically needs mix of empirics, simulation and modeling, so barriers to entry high Third, the NBER has a Census node. Census data is painful to access, but this also deters – so still low-hanging fruit (like my Grandma’s attic – some amazing stuff in there)

4. Nick Bloom, Econ 247, 2011 High levels of turnover Heterogeneity within industries The lumpiness of micro-economic activity The importance of reallocation in driving productivity

5. Nick Bloom, Econ 247, 2011 Turnover About 15% of jobs are destroyed and 20% created in the private sector every year. About 80% of this turnover occurs within the same SIC-4 digit industry This is robust across countries (US, Europe, Asia and SA) But, before I show data a couple of point on definitions: This is turnover in “jobs”, defined in terms of establishment employment changes, e.g. CES A linked (but distinct concept) is turnover in “employment” – which is two to three times higher – defined in terms of workers changes, e.g. CPS

6. Nick Bloom, Econ 247, 2011 Turnover in “Jobs” versus “Employment” – Expanding Firm example Source: John Haltiwanger Note: Worker flow=14, Job flow=4

7. Nick Bloom, Econ 247, 2011 Source: John Haltiwanger Turnover in “Jobs” versus “Employment” – Contracting Firm example Note: Worker flow=15, Job flow=9

8. Nick Bloom, Econ 247, 2011 Quarterly Job Flows in Private Sector, 1990-2005, BED data Source: John Haltiwanger (1) Net jobs flows equal change in employment ≈ change in unemployment (2) Gross flows are much bigger than net flows (3) Reduction in job churn that (in manufacturing) part of a longer trend (4) Job destruction does not necessarily mean firing – could be not hiring a replacement for a separation.

9. Nick Bloom, Econ 247, 2011 JOLTS monthly worker turnover data Source: John Haltiwanger Depth of post 9/11 recession: 1)Figures don’t add up (JOLTS is not good for employment – CES survey more accurate) 2)Still massive churn – including quits – in depths of the recession (I quit a job in December 2001)

10. Nick Bloom, Econ 247, 2011 Job Flows and Employment Flows, total private Source: John Haltiwanger

11. Nick Bloom, Econ 247, 2011 Much of the turnover is creation/destruction in same SIC4 industry Source: John Haltiwanger, Changes defines as % over average base & end years Excess reallocation = |job creation| + |job destruction| - |job creation-job destruction|

12. Nick Bloom, Econ 247, 2011 This is very much in the spirit of Schumpeter

13. Nick Bloom, Econ 247, 2011 This is very much in the spirit of Schumpeter Although probably his most famous quote was: “Early in life I had three ambitions. I wanted to be the greatest economist in the world, the greatest horseman in Austria, and the best lover in Vienna. Well, I never became the greatest horseman in Austria“ To which the (un-attributed) response was: “Those we knew Schumpeter as an Economist, Lover or a Horseman presumed his skills were in the other two fields” “The fundamental impulse that keeps the capital engine in motion comes from the new consumers’ goods, the new methods of production and transportation, the new markets... [The process] incessantly revolutionizes from within, incessantly destroying the old one, incessantly creating a new one. This process of Creative Destruction is the essential fact of capitalism.” Schumpeter (p. 83, 1942)

14. Nick Bloom, Econ 247, 2011 High levels of turnover Heterogeneity within industries The lumpiness of micro-economic activity The importance of reallocation in driving productivity

15. Nick Bloom, Econ 247, 2011 Heterogeneity basic facts Typical gap between 10 th and 90 th percentiles of productivity within same industry is 200% (Syverson,2004) These spreads are very persistent: About 70% to 80% annual job-flows are persistent About 60% to 70% annual productivity growth is persistent

16. Nick Bloom, Econ 247, 2011 What could cause this heterogeneity? One possibility is pure measurement error, but: Productivity is strongly linked with exit and LR growth When looking at micro-industries where we measure plant prices (e.g. boxes, bread, block ice, concrete, plywood, etc.) still see this spread (Foster, Haltiwanger and Syverson, 2008 AER)

17. Nick Bloom, Econ 247, 2011 Explanations of this heterogeneity? Several possible economic models of the spread are: Mistakes/learning (Jovanovic, 1982 Econometrica) Mis-measurement: “Hard” technology (e.g. R&D) Skills Other inputs (computers) or utilization Management and managers

18. Nick Bloom, Econ 247, 2011 High levels of turnover Heterogeneity within industries The lumpiness of micro-economic activity The importance of reallocation in driving productivity

19. Nick Bloom, Econ 247, 2011 Lumpiness of growth The share of employment growth generated by large adjustments is big (Davis and Haltiwanger, 1992 QJE) More than 2/3 manufacturing job creation/destruction accounted for by +25% changes For non-manufacturing even greater Same is true, but more extreme, for investment (Doms and Dunne, 1998 RED). Suggests substantial adjustment-costs in factor changes

20. Nick Bloom, Econ 247, 2011 Lumpiness of employment growth Source: John Haltiwanger, annual data manufacturing

21. Nick Bloom, Econ 247, 2011 High levels of turnover Heterogeneity within industries The lumpiness of micro-economic activity The importance of reallocation in driving productivity

22. Nick Bloom, Econ 247, 2011 Measuring productivity (ω i,t ) Labor Productivity: Three factor TFP: Five factor TFP: Note: va=log(value added), l=log(labor force), k=log(tangible capital), m=log(materials, e=log(energy), c=log(IT). If IT included need to remove from tangible capital.

23. Nick Bloom, Econ 247, 2011 Defining industry (or aggregate) productivity Define a simple industry productivity index: P t Where: ω i,t is the productivity of establishment i in period t (i.e. log(labor productivity) or log (TFP)) s i,t is the share of establishment i in the industry in period t (i.e. the share of employment or sales in industry employment or sales)

24. Nick Bloom, Econ 247, 2011 Industry productivity can increase through two channels Within Firms (Traditional view) –The same firms become more productive (e.g. new technology spreads quickly to all firms, like Internet) Between Firms (“Schumpeterian”view) –Low TFP firms exit and resources are reallocated to high TFP firms High TFP firms expand (e.g. more jobs) & low TFP firms contract (e.g. less jobs) Exit/entry 24

25. Nick Bloom, Econ 247, 2011 These two effects are well known to cricket fans Within batsman (each batsman improves) Between batsman (more time for your best batsman) 25

26. Nick Bloom, Econ 247, 2011 Decomposing productivity (1) Productivity growth for a balance panel of establishments can be broken down into three terms: Within term is included in representative agent models, while the between and cross terms would not be Reallocation

27. Nick Bloom, Econ 247, 2011 Decomposing productivity (2) Allowing for entry and exit requires two more terms: This is the Bailey, Hulten and Campbell (1992) decomposition

28. Nick Bloom, Econ 247, 2011 * Source: John Haltiwanger Total reallocation (between, entry and exit) accounts for about ½ of manufacturing TFP growth *Combines -0.08 “between” and 0.34 “cross”

29. Nick Bloom, Econ 247, 2011 (A) Treats all reallocation within establishments as “within” growth Large establishments in balanced panel (500 employees) (B) Reallocation terms most likely to be downward biased by miss measured prices (Foster, Haltiwanger and Syversson, 2008) So in manufacturing re-allocation of factors probably accounts for the majority of productivity growth This is probably even an underestimate

30. Nick Bloom, Econ 247, 2011 Source: Foster, Haltiwanger & Krizan (2000 and 2006) Reallocation (including entry) accounts for almost all Retail TFP growth

31. Nick Bloom, Econ 247, 2011 Source: Hsieh and Klenow (2008); mean=1 Differences in reallocation also a factor in explaining cross country TFP gaps