1. Nick Bloom, Econ 247, 2015 Nick Bloom Productivity and Reallocation

2. Nick Bloom, Econ 247, 2015 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, 2015 Why should you be interested in this? Important to understanding growth – e.g. 3/4 productivity growth is reallocation, unemployment driven by churn etc 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, Stanford 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, 2015 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, 2015 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, 2015 Turnover in “Jobs” versus “Employment” – Expanding Firm example Source: John Haltiwanger Note: Worker flow=14, Job flow=4

7. Nick Bloom, Econ 247, 2015 Source: John Haltiwanger Turnover in “Jobs” versus “Employment” – Contracting Firm example Note: Worker flow=15, Job flow=9

8. Nick Bloom, Econ 247, 2015 Quarterly Job Flows in Private Sector, 1990-2005, BED data Source: John Haltiwanger (2005) (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. Updated: quarterly job flows continued falling in the Great Recession, particularly the creation margin Source: Business Employment Dynamics (BED) and CPS Source: Grimm, Haltiwanger and Foster (2013), “Reallocation in the Great Recession: Cleansing or Not?” Change in unemployment rate

10. Young/Small plants have much higher flows Source: Business Dynamics Statistics (BDS) Source: Grimm, Haltiwanger and Foster (2013), “Reallocation in the Great Recession: Cleansing or Not?”

11. Nick Bloom, Econ 247, 2015 Current recession – challenge is falling labor force participation (mainly low skilled men)

12. Nick Bloom, Econ 247, 2015 Job Flows and Employment Flows, total private (% of total) Source: John Haltiwanger

13. Nick Bloom, Econ 247, 2015 Source: John Haltiwanger, Changes defines as % over average base & end years Excess reallocation = |job creation| + |job destruction| - |job creation-job destruction| Much of the turnover is creation/destruction in same SIC4 industry

14. Nick Bloom, Econ 247, 2015 This is very much in the spirit of Schumpeter

15. Nick Bloom, Econ 247, 2015 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)

16. Nick Bloom, Econ 247, 2015 High levels of turnover Heterogeneity within industries The lumpiness of micro-economic activity The importance of reallocation in driving productivity

17. Nick Bloom, Econ 247, 2015 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

18. Nick Bloom, Econ 247, 2015 18 Big TFP dispersion across firms: for example, US ready mix concrete plants: Source: Syverson (2004) High competition Low competition

19. Nick Bloom, Econ 247, 2015 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, carbon black etc.) still see this spread (Foster, Haltiwanger and Syverson, 2008 AER)

20. Nick Bloom, Econ 247, 2015 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

21. Nick Bloom, Econ 247, 2015 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, 2015 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

23. Nick Bloom, Econ 247, 2015 Lumpiness of employment growth Source: John Haltiwanger, annual data manufacturing

24. Nick Bloom, Econ 247, 2015 High levels of turnover Heterogeneity within industries The lumpiness of micro-economic activity The importance of reallocation in driving productivity

25. Nick Bloom, Econ 247, 2015 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.

26. Nick Bloom, Econ 247, 2015 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)

27. Nick Bloom, Econ 247, 2015 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 27

28. Nick Bloom, Econ 247, 2015 These two effects are well known to cricket fans Within batsman (each batsman improves) Between batsman (more time for your best batsman) 28

29. Nick Bloom, Econ 247, 2015 Decomposing productivity (1) Productivity growth for a balanced 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

30. Nick Bloom, Econ 247, 2015 Decomposing productivity (2) Allowing for entry and exit requires two more terms: This is the Bailey, Hulten and Campbell (1992) decomposition

31. Nick Bloom, Econ 247, 2015 * 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”

32. Nick Bloom, Econ 247, 2015 (A) Treats all reallocation within establishments as “within” growth (large establishments in balanced panel have 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

33. Nick Bloom, Econ 247, 2015 Source: Foster, Haltiwanger & Krizan (2000 and 2006) Reallocation (including entry) accounts for almost all Retail TFP growth

34. Nick Bloom, Econ 247, 2015 Source: Hsieh and Klenow (2008); mean=1 Differences in reallocation also a factor in explaining cross country TFP gaps

35. Nick Bloom, Econ 247, 2015 BACK-UP

36. Reallocation also appears to vary over the cycle: Usually higher in recessions except for the Great Recession (maybe because finance dictated growth rather than TFP during this?) Normal is Zero Change in Unemployment, Mild is 0.01 Change, Sharp is 0.03 Change. High Productivity is 1 std dev above mean, Low Productivity is 1 std dev below mean. Source: Grimm, Haltiwanger and Foster (2013), “Reallocation in the Great Recession: Cleansing or Not?”

37. The recession (falling output) is now over but the recovery (return to levels) is very slow Unemployment rate, seasonally adjusted (Source BLS) Unemployment is still 4% above “normal” levels

38. Things look even worse in California Unemployment rate, seasonally adjusted (Source BLS)

39. Unemployment is particularly a low-skill issue Unemployment rate, seasonally adjusted

40. Although the recession could have been worse Industrial production, normalized to 100 at the start of the recessions (Source FRB) December 2007 May 2009

41. Similar persistence of TFP & management Source: Bloom, Sadun and Van Reenen (2012), “Management as a technology: new empirics and old theories”, Stanford mimeo

42. JOLTS monthly worker turnover data Source: John Haltiwanger Still massive churn – including quits – in depths of the recession (I quit a job in December 2001)

43. Jolts – updated to 2012