235 Reallocation

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Information about 235 Reallocation
Business-Finance

Published on April 14, 2008

Author: Christian

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MACRO TOPICS Nick Bloom Heterogeneity and Reallocation:  MACRO TOPICS Nick Bloom Heterogeneity and Reallocation Slide2:  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 Slide3:  Why should you be interested in this? First, this is important to understanding macroeconomic activity – e.g. 2/3 productivity growth is reallocation, unemployment driven by rates of churn Second, “micro to macro” is a fertile area of research: It is new – many open questions It is hard – so barriers to entry high, particularly for RA trained macro-economists Third, Stanford has recently set up a Census node (next to the golf course). Census data is painful to access, but this also deters – so still low-hanging fruit Slide4:  High levels of turnover Heterogeneity within industries The lumpiness of micro-economic activity The importance of reallocation in driving productivity Slide5:  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 A linked (but distinct concept) is turnover in “employment” – which is two to three times higher” – defined in terms of workers. Slide6:  Turnover in “Jobs” versus “People” – Expanding Firm example Source: John Haltiwanger Note: Worker flow=14, Job flow=4 Slide7:  Source: John Haltiwanger Turnover in “Jobs” versus “People” – Contracting Firm example Note: Worker flow=15, Job flow=9 Slide8:  Quarterly Job Flows in Private Sector, 1990-2005, BED data Source: John Haltiwanger Note: (1) Net jobs flows equal change in employment ≈ change in unemployment (2) Gross flows are much bigger than net flows Slide9:  Job Flows and Employment Flows, total private Source: John Haltiwanger Slide10:  JOLTS monthly worker turnover data Source: John Haltiwanger Depth of post 9/11 recession: Figures don’t add up (JOLTS is not good for employment) Still massive churn – including quits – in depths of the recession (I quit a job in December 2001) Slide11:  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| Slide12:  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) Slide13:  High levels of turnover Heterogeneity within industries The lumpiness of micro-economic activity The importance of reallocation in driving productivity Slide14:  Heterogeneity basic facts Only about 10% of cross-establishment spread in output, employment, capital and productivity growth is explained by SIC 4-digit controls Typical gap between 10th and 90th percentiles of productivity within same industry is 50% These spreads are very persistent: About 70% to 80% annual job-flows are persistent About 60% to 70% annual productivity growth is persistent Slide15:  What could cause this heterogeneity? One possibility is pure measurement error, but: Productivity is strongly linked with exit and LR growth Spreads are persistent & inter-linked across measures Several possible economic models of the spread are: Learning (Jovanovic, 1982 Econometrica) Uncertainty and adjustment costs (Dixit and Pindyck, 1994 book; Abel and Eberly 1996 REStud) Omitted factors - knowledge, vintages, skills etc… Or even management (eg Bloom & Van Reenen, 2007 QJE) Slide16:  High levels of turnover Heterogeneity within industries The lumpiness of micro-economic activity The importance of reallocation in driving productivity Slide17:  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 Slide18:  Lumpiness of employment growth Source: John Haltiwanger, annual data manufacturing Slide19:  High levels of turnover Heterogeneity within industries The lumpiness of micro-economic activity The importance of reallocation in driving productivity Slide20:  Re-allocation Recent studies highlight role of reallocation for productivity growth in market economies: Large pace of output and input reallocation This is productivity enhancing (market forces) But, the magnitude depends upon sector, country and period Slide21:  Defining productivity Define a simple industry productivity index: Pt Where: ωi,t is the productivity of establishment i in period t (i.e. log(labor productivity) or log (TFP)) si,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) Slide22:  Measuring productivity (ωi,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. Slide23:  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 Slide24:  Decomposing productivity (2) Allowing for entry and exit requires two more terms: This is the Bailey, Hulten and Campbell (1992) decomposition Slide25:  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” Slide26:  (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 Slide27:  Source: Foster, Haltiwanger & Krizan (2000 and 2005) Reallocation (including entry) accounts for almost all Retail TFP growth Slide28:  Massive amounts of micro-heterogeneity – does this effect macro outcomes: Consensus on employment is yes i.e. Shimer and Hall My view on productivity is yes: Most aggregate TFP growth not “within”, but not much literature (Cabellero, Engel & Mico, 2006, Bloom, 2006) Debate on impact adjustment costs: Caballero, Engel, Thomas, Veracierto... – another class Conclusions Slide29:  BIBLIOGRAPHY Main sources: Foster, Haltiwanger and Krizan (2000), “Aggregate productivity growth: lessons from microeconomic evidence” Also see: Davis and Haltiwanger (1992), “Gross Job Creation, Gross Job Destruction, and Employment Reallocation”, QJE, 107(3), pp. 819-63. Foster, Haltiwanger and Krizan (2005), “Market selection, reallocation and restructuring in US retail”

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