By Foster, Haltiwanger & Krizan, (ReStat, 2006) The Link Between Aggregate And Micro Productivity Growth: Evidence From Retail Trade Presented by David Lagakos, Nov 15, 2006

Why Link Aggregate Productivity Growth to Micro Data? Reallocation of inputs is important determinant of aggregate productivity - Shrinking (exiting) of less productive firms - Evidence from manufacturing: - Expanding (entering) of more productive firms - Around 1/3 of productivity growth due to reallocation (The other 2/3 comes from productivity gains within plants)

Why Link Aggregate Productivity Growth to Micro Data? Reallocation of inputs is important determinant of aggregate productivity - Shrinking (exiting) of less productive firms - Evidence from manufacturing: - Expanding (entering) of more productive firms - Around 1/3 of productivity growth due to reallocation (The other 2/3 comes from productivity gains within plants) Why do we care whether productivity growth due to reallocation or not? - Effects on Y/L of policies that prevent reallocation (say firing taxes) - Understanding technological adoption

Why Retail Trade? Structural changes over last 50 years Important industry (~15% of private non-farm employment) - emergence of large chain retailers - decline of the “mom & pop” shop Technology improvements over the 1990s Importance of reallocation on productivity growth largely undocumented - improved inventory control (Levinsohn & Petropoulos, 2001) - more efficient distribution & advertising (Holmes, 2006) - adoption of scanners & other IT equipment (Sieling et al, 2006)

This Paper Quantifies role of reallocation in retail labor productivity Quantifies role of entry of chain stores Documents establishment level productivity dynamics in retail - Census of retail trade,

Census of Retail Trade Survey of 10% of all retail establishments Conducted every five years (1987, 1992, 1997) Establishment-level data available - employment - total sales - parent firm -4-digit SIC industry code (e.g. supermarket, car dealership)

Census of Retail Trade Survey of 10% of all retail establishments Conducted every five years (1987, 1992, 1997) Establishment-level data available - employment - total sales Establishment-level data unavailable - capital or land inputs - cost of goods purchased - cost of other intermediate goods/services - parent firm -4-digit SIC industry code (e.g. supermarket, car dealership)

Measure of Productivity Real output per worker (Y/L) - Numerator : total sales deflated by 4-digit industry-level price index - Denominator : Number of employees x 4-digit industry average hours Issues: - Within retail, across-industry productivity comparisons are meaningless - Other inputs excluded - Deflated by common price deflator - Higher service/higher price establishments show up as higher Y/L - Y/L growth could reflect increases in capital intensity

Establishment-Level Productivity Dynamics Object of interest : distribution of Y/L changes from 1987 to 1997 Of establishments present in 1987, possible states in 1997 are - Alive, in productivity quintile #1, #2, … #5 - Dead Of establishments present in 1997, possible states in 1987 are - Not born yet - Alive, in productivity quintile #1, #2, … #5 Productivity measurement - Express every establishment’s Y/L in deviation from 4-digit industry mean - Allows us to look at all retail industries simultaneously

Productivity Transition Matrix

Establishment Productivity Dynamics Comparison with manufacturing - Baily, Hulton & Campbell (1992): - manufacturing plant survival much more likely Summary: entry & exit plays crucial role in retail - Most likely outcome in 1997 for any establishment in 1987 = death - Less productive establishments much more likely to die - conditional on survival, persistence is similar to retail

Retail-Sector Productivity Growth Decomposition Object of interest : retail sector productivity growth, Goal : decompose productivity growth into - growth due to continuing establishments - growth due to entering/exiting establishments

Retail-Sector Productivity Growth Decomposition within-establishment growth changing shares cross term entering establishments exiting establishments C = set of continuing establishments N = set of entering establishments X = set of exiting establishments ‘e’ indexes an establishment ‘i’ indexes the industry = establishment employment share

Retail-Sector Productivity Growth Decomposition 1.8% 2.8% -4.5% 6.2% 5.1% C = set of continuing establishments N = set of entering establishments X = set of exiting establishments ‘e’ indexes an establishment ‘i’ indexes the industry = establishment employment share 11.4% Total:

Retail-Sector Productivity Growth Decomposition 1.8% 2.8% -4.5% 6.2% 5.1% C = set of continuing establishments N = set of entering establishments X = set of exiting establishments ‘e’ indexes an establishment ‘i’ indexes the industry = establishment employment share 11.4% Total: 0.1% 11.3%

Retail-Sector Productivity Growth Accounting Retail productivity growth entering establishments more productive than average - Entry & exit accounts for virtually all productivity growth Comparison with manufacturing - Entry & exit accounts for just 1/3 of productivity growth (Baily, Hulten & Campbell, 1992) - exiting establishments less productive than average

Questions about these Findings What role do chain stores play in this reallocation process? Are entering stores more efficient? Or just more K/L intensive? Why would retail be so different from manufacturing?

Role of Chain Stores Firm types: - Single-unit establishments - Local chain (multi-establishment, one state) - Regional chain (multi-establishment, 2 -5 states) - National chain (multi-establishment, >5 states)

Role of Chain Stores Firm types: - Single-unit establishments - Local chain (multi-establishment, one state) - Regional chain (multi-establishment, 2 -5 states) - National chain (multi-establishment, >5 states) Classification of establishments: - Single-unit establishment - Part of local chain - Part of regional chain - Part of national chain

Role of Chain Stores Establishment-level productivity regression: Parameters of interest:

Role of Chain Stores

Highest Y/L - Entering national & regional chain stores Lowest Y/L - Exiting single-establishment stores - Continuing national & regional chain stores Y/L gap between national chain store and exiting single-establishment log points ~ 50%

Capital Intensity How much do Y/L differences just reflect K/L differences? Census of retail -> no data on capital Alternate data source: Business Expenditure Survey, Book value of capital by establishment - Can look only at retail establishments

Capital Intensity Capital Per Worker

Capital Intensity Capital Per Worker ~50% more K/L in chains

Conclusions Y/L growth in retail trade explained by reallocation “Reallocation dynamics are an important part of the story in manufacturing, and in retail trade they are the whole story over the 1990s” Preliminary evidence on K/L suggest K/L differences play a big role - I agree with authors that better data needed here - Unclear that TFP higher in chain stores than individual stores - If TFP not higher in chains, how come they have displaced the individual stores?