The Rise of Market Power and the Macroeconomic Implications

Transcription

1 The Rise of Market Power and the Macroeconomic Implications Jan De Loecker 1 Jan Eeckhout 2 1 Princeton and University of Leuven 2 University College London and UPF NBER Summer Institute 18 July, 2017

2 Motivation Several secular trends in last decades: wages, LF participation, labor share, labor mobility, migration rates, capital share, output growth slowdown Propose common cause: the rise in market power since 1980 Little known about evolution & cross-section markup in macro 1. Data needed: long time series of firm-level data 2. Estimation methods: demand approach uses model of consumer behavior and competition This paper: 1. Document time-series and cross section of markup Cost-based method; no inference from demand; mkt structure 3. Illustrate how this can explain 7 secular trends since 1980 We have nothing (little) to say about causes of change markup

3 Motivation Secular Increase since 1980: markup Share weighted Markup year Figure: The Evolution of Average Markups ( ), weighted

4 Data Compustat data on publicly listed firms: Long time series: Broad Cross Section: average 5,000 firms per year Selection? Large firms; miss many small firms Small subset of all firms Publicly traded privately held firms But: Covers all sectors and industries (contrast: Cens. of Manuf.) 40-45% GDP; 35% employment (Cens. of Manuf. 8.8%) Allow for markup variation across producers and time; heterogeneity has substantial economic implications

5 Production technology Producer Behavior Q it (V it, K it, Ω it ) = F it (V it, K it )Ω it, where V it : variable inputs (labor, intermediate inputs) K it : capital stock Ω it : Hicks-neutral productivity term (TFP) Associated Lagrangian function (with one composite input): L(V it, K it, λ it ) = P V it V it + r it K it λ it (Q it ( ) Q it ) Consider FOC wrt the variable input V : L it = P V Q it ( ) it λ it = 0 V it V it Rearranging expression of output elasticity of input V it : θ V it Q it( ) V it V it = 1 Pit V V it Q it λ it Q it

6 Producer Behavior Lagrangian multiplier λ is a direct measure of marginal cost Define markup µ = P λ or µ it = θit V P it Q it Pit V V. it depending on Sales S it = P it Q it and expenditure share θ V it, which is specific to technology Method: Hall (1988): aggregate data; De Loecker-Warzynski (2012): micro data

7 Robustness Benchmark Industry-Specific CD Share weighted Markup year year Share weighted Markup Markup (ind techn.) Census Manufacturing Translog Markup (ind techn. Translog) Share weighted Markup year Share weighted Markup Share weighted markup (Manufacturing) year Markup (ind techn. Translog) Share weighted Markup

8 Cross-Sectional Decomposition Higher Markups for Smaller Firms U t = i s it µ it = µ t + i (s it s t )(µ it µ t ) where: U t : weighted average markup µ t : unweighted average markup µ it : firm i s individual markup s it : firm i s market share of sales Cov(s it, µ it ) < 0 Higher Markups for Smaller Firms

9 Cross-Sectional Decomposition Higher Markups for Smaller Firms year Share weighted Markup mu_mean Figure: Unweighted vs. Weighted Average Markup

10 Time-Series Decomposition Predominantly Within Industry, in All Industries U t = s s,t 1 µ st + µ s,t 1 s s,t + µ s,t s s,t. s s s }{{}}{{}}{{} within between reallocation Markup Markup Within Between Realloc Table: Decomposition 10 year change in Markup at 4-digit industry

11 Dispersion of Markup All Action in Upper Half Distribution year Share weighted Markup p90 (ms) p50 (ms) p75 (ms)

12 Dispersion of Markup All Action in Upper Half Distribution year Share weighted Markup p90 (ms) p50 (ms) p75 (ms) Harberger (1954): roughly equally distributed profits; not now

13 Markup = Market Power? Dividends and Market Value e+07 Markup Share weighted Dividend Markup e e e+07 Share weighted Market Value year year Markup Share weighted Dividend Markup Share weighted Market Value

14 Markup = Market Power? Aggregate Profit Rate External validation: compare increase in aggregate profit rate with increase in profit rate from micro data Incomplete comparison: 1. aggregate has profits of all firms vs. micro data only publicly traded firms (large; 40% of GDP) 2. total profits Π versus variable profits Π V (levels are different!) Microdata Π V ( GDP = ΠV GNI PQ GDP = 1 1 ) GNI µ GDP Π V 2014 GDP 2014 = 2.34 Π V 1980 GDP 1980 Aggregate Data: Total Profits Π increase by factor 4 Even bigger increase in aggregate profits. Either: 1. Smaller firms have even bigger markups 2. or, capital expenditure has increased less than variable costs

15 Markup = Market Power? Aggregate Profit Rate q1 1960q1 1970q1 1980q1 1990q1 2000q1 2010q1 2020q1 time Figure: Profit rates. Data FRED, from national accounts. Quarterly.

16 Summary of Facts 1. Sharp increase in Markup since 1980: 42% 2. High markup firms tend to be smaller 3. Only in the upper half of Markup distribution (espec. at top) 4. Mostly within industry (in all; no particular industries) 5. Markup = Market Power: total profits 4

17 Macroeconomic Implications

18 A Simple Model Unskilled Labor is Variable Input Let V = L, demand P(Q) and quantity Q i = Ω i L θ i K 1 θ i where: Ω i : firm productivity L i : quantity of efficiency units of labor S i = P i Q i FOC wl i S i = θ µ i Inverse relation labor share and markup µ i

19 1. Decline in Labor Share Data Year - Fiscal Share weighted (Inverse) Markup (1950==100) Share weighted (Inverse) Markup (labor) (1950==100) Labor Share (Fred) (1950==100) Figure: Labor share of GDP (BLS), and inverse of the markup (Two measures: weighted by Sales, and weighted by Employment)

20 2. Decline in Capital Share K is capital investment and r is the user cost. FOC (long run): Accounting identity: rk i = θ k S i µ i wl + rk + Π i = S i wl i S i + rk i S i + Π i S i = 1 (θ l + θ k ) 1 µ i = 1 π i If profit share labor and capital share (provided Q i is complementary in L i, K i )

21 2. Decline in Capital Share k_share_agg MARKUP_INV year.6 k_share_agg MARKUP_INV Figure: The Evolution of the capital share (own computations), and inverse of the markup (weighted by Sales Share) ( ). Gross Capital adjusted by the input price deflator, the federal funds rate, and an exogenous depreciation rate of 12%.

22 Market Power Conduct Parameter λ Follow Bresnahan (1982) Pricing equation (given a marginal cost c): P(Q) = c + λh(q) where Q = i Q i and where h(q) = P(Q) Q Q; Linear demand P(Q) = a bq for example, h(q) = bq Our measure for markup µ = P c µ = 1 + λ h(q) c can then be written as:

23 Market Power Market power can change with technology, externalities, network goods, entry barriers, preferences (Dixit-Stiglitz), market structure, consumer behavior (Burdett-Judd),... Our model: change in λ = Cournot 1. Market power changes exogenously with λ 2. Number of firms per market N = 1 λ 3. In a given market, all N firms have same technology Ω i 4. Linear Demand, to capture incomplete pass-through ( CES)

24 Market Power P a Market Power λ [0, 1] P = a bq MR = a (1 + λ)bq a 2b a b Q

25 Market Power P a Monopoly Market Power λ = 1 P = a bq MR = a 2bQ a 2b a b Q

26 Market Power P a Perfect Competition Market Power λ = 0 P = a bq MR = a bq a b Q

27 Equilibrium Impact of Market Power Constant returns θ = 1, identical firms within market Ω Firm objective: First-order Condition: max L i P(Q)Q i wl i, where Q i = Ω i L i w P(Q) = c + λh(q) a (1 + λ)bq = Ωθ L = a w Ω (1 + λ)bω, L i = λ a w Ω 1 + λ bω L λ = a w Ω bω 1 (1 + λ) 2 < 0 and L i λ = a w Ω bω 1 (1 + λ) 2 > 0. Lemma For a given wage and a given market Ω, the market labor demand L is decreasing in market power λ; and an individual firm s labor demand L i is increasing in market power λ.

28 Compustat Data Firm Size and Number of Firms L_mean nrfirms Data Year - Fiscal L_mean nrfirms 0

29 Equilibrium Impact of Market Power Labor Demand: aggregate over different markets Ω i F (Ω i ) L D = Ω Ω L(Ω i ; w; λ)df (Ω i ) = 1 (1 + λ)b Ω Ω ( a Ω i w Ω 2 i Labor Supply: heterogeneous workers z G(z) supply efficiency units of labor; outside option is U L S = 1 Equilibrium: L D = L S w, L U w zdg(z) ) df (Ω i )

30 Equilibrium Impact of Market Power Labor Force: L λ < 0; and Nominal Wages: w λ < 0; Ω = 1

31 Equilibrium Impact of Market Power Labor Force: L λ P, w w < 0; and Nominal Wages: λ < 0; Ω = 1 P λ=0 = w λ=0 L S L D λ=0 L λ=0 L

32 Equilibrium Impact of Market Power Labor Force: L λ P, w w < 0; and Nominal Wages: λ < 0; Ω = 1 P λ=1 P λ=0 = w λ=0 L S w λ=1 L D λ=1 L D λ=0 L λ=1 L λ=0 L

33 Equilibrium Impact of Market Power Labor Force: L λ P, w w < 0; and Nominal Wages: λ < 0; Ω = 1 P λ=1 P λ=0 = w λ=0 L S w λ=1 L D λ=1 L D λ=0 L λ=1 L λ=0 L

34 3. Decline in (Low Skill) Wages Evidence Without Growth: nominal wages decline With Growth: nominal wages relative to GDP decline Double Impact since 1980: 1. Nominal wages 2. P 42%: real wages w P further relative to perf. comp.

35 3. Decline in (Low Skill) Wages Real Median Wages and Relative to GDP q1 1990q1 2000q1 2010q1 2020q q1 1990q1 2000q1 2010q1 2020q1

36 4. Decline in Labor Force Participation Evidence m1 1960m1 1970m1 1980m1 1990m1 2000m1 2010m1 2020m1 time Notes. From CPS.

37 Labor Reallocation and Pass-through Labor adjustments: in response to productivity shocks (Jovanovic, Hopenhayn-Rogerson) Evidence (Davis-Haltiwanger); Theory/Calibration (Schaal) Then if pass-through is incomplete, a shock leads to a less than proportional increase/decrease in Q and L Linear demand: pass-through decreasing in market power λ Market power labor market adjustment for same shock

38 Labor Reallocation and Pass-through P P w λ=0 (Ω) = Ω w P λ=0 (Ω) = Ω L D λ=0 L λ=0 ΩL

39 Labor Reallocation and Pass-through P P λ=0 (Ω) = w Ω w P λ=0 (Ω) = Ω L D λ=1 L D λ=0 L λ=1 L λ=0 ΩL

40 Labor Reallocation and Pass-through P P λ=1 (Ω) P λ=1 (Ω) P λ=0 (Ω) = w Ω w P λ=0 (Ω) = Ω L D λ=1 L D λ=0 L λ=1 L λ=0 ΩL

41 5. Decline in Labor Market Flows total q1 1980q1 1985q1 1990q1 1995q1 2000q1 2005q1 2010q1 2015q1 dq (UE+NE)/( U+N) (left axis) ee (right axis)

42 6. Decline in Migration Rates Migration Rates Migration Rate, between MSA s ( ). CPS Data.

43 7. Slowdown in aggregate output growth q1 1960q1 1970q1 1980q1 1990q1 2000q1 2010q1 2020q1

44 7. Slowdown in aggregate output growth Productivity Growth Firm s FOC for Labor: PΩ i L θ 1 i K 1 θ i θµ 1 w 1 i = w Ω i = µ i P Constant Marginal Product of Labor: θ = 1 Hall (1988) Ω i = µ i w P θ L1 θ i K 1 θ i.

45 7. Slowdown in aggregate output growth Productivity Growth wedge omega_gamma_gr TFP_gamma_gr lpoly smooth: omega_gamma_gr lpoly smooth: TFP_gamma_gr Data Year - Fiscal 90% CI wedge lpoly smooth

46 Conclusions 1. Sharp rise in Market Power since Significant macroeconomic implications: 7 secular trends

47 Conclusions Open Questions 1. Causes? Technology, M&A, Other secular trends? 1. decrease in startup rate of new firms 2. decrease long term interest rate: capital D, S 3. increase in wage inequality: profit sharing managers 4. the great moderation Two (uncomfortable) Consequences Food for Thought 1. Inflation is too high: 42% increase price level; 1% per year Policy: anti-trust, not Federal Reserve! 2. Stock market over-valued (compared to Perfect Competition) Stock market increase economic growth

48 Conclusions M&A Share-weighted Markup (DLW) Year Share-weighted Markup (DLW) Nr M&A Average value M&A (10,000 USD)

49 Conclusions Open Questions 1. Causes? Technology, M&A, Other secular trends? 1. decrease in startup rate of new firms 2. decrease long term interest rate: capital D, S 3. increase in wage inequality: profit sharing managers 4. the great moderation Two (uncomfortable) Consequences Food for Thought 1. Inflation is too high: 42% increase price level; 1% per year Policy: anti-trust, not Federal Reserve! 2. Stock market over-valued (compared to Perfect Competition) Stock market increase economic growth

50 Conclusions Great Moderation q1 1960q1 1970q1 1980q1 1990q1 2000q1 2010q1 2020q1 time

51 Conclusions Open Questions 1. Causes? Technology, M&A, Other secular trends? 1. decrease in startup rate of new firms 2. decrease long term interest rate: capital D, S 3. increase in wage inequality: profit sharing managers 4. the great moderation Two (uncomfortable) Consequences Food for Thought 1. Inflation is too high: 42% increase price level; 1% per year Policy: anti-trust, not Federal Reserve! 2. Stock market over-valued (compared to Perfect Competition) Stock market increase economic growth

52 Conclusions Stock Market Valuation Share weighted Markup year DOW JONES (Deflated CPI) Share weighted Markup DOW JONES (Deflated CPI)

53 Conclusions Open Questions 1. Causes of Market Power? Technology, M&A, Other secular trends? 1. decrease in startup rate of new firms 2. decrease long term interest rate: capital D, S 3. increase in wage inequality: profit sharing managers 4. the great moderation Two (uncomfortable) Consequences Food for Thought 1. Inflation is too high: 42% increase price level; 1% per year Policy: anti-trust, not Federal Reserve! 2. Stock market over-valued (compared to Perfect Competition) Stock market increase economic growth

54 Whenever a theory appears to you as the only possible one, take this as a sign that you have neither understood the theory nor the problem which it was intended to solve Karl Popper

55 The Rise of Market Power and the Macroeconomic Implications Jan De Loecker 1 Jan Eeckhout 2 1 Princeton and University of Leuven 2 University College London and UPF NBER Summer Institute 18 July, 2017

56 Causes? Production Technology: Big Retail vs. manufacturing and services Network goods Finance: Mergers and Acquisitions Cross-ownership of competitors Private Equity under the radar Vertical Integration Preferences: Price Differentiation improved through technology Brand dependence

57 Translog Production Technology Unusually long sample period: Industry-specific, time-varying output elasticities Preserves identification results, De Loecker-Warzynski (2012) Moment conditions from static optimization of variable inputs: E ( ξ it (β) [ vit 1 vit 1 2 ]) = 0, With translog production function for each industry: q it = β v1 v it + β k1 k it + β v2 v 2 it + β k2 k 2 it + ω it + ɛ it Variation output elasticity over time (or firms), no longer attributed to markup variation Output elasticity of the composite variable input: θ v it = β v 1 + 2β v2 v it Markup defined as before; level difference, but normalization

58 Cross-Sectional Decomposition Across All Industries year Markup Mean 4digit Figure: Industry disaggregation

59 Markup = Market Power? Dividends Individual firm level: firm-level average markup (all years) and the share of total dividends in total sales 3.5 Local polynomial smooth markupmean_firm divmargin_av kernel = epanechnikov, degree = 0, bandwidth =.05

60 Growth Accounting First order approach: no productivity slowdown Solow residual: shows a decrease in productivity since

61 Growth Accounting Solow residual based on aggregate production technology Q = Ω S L θ K 1 θ Ω S = where L = i L i and K = i K i Micro data: Q L θ K 1 θ Ω = i Ω i = i Q i L θ i K 1 θ i Qi i Lθ i i K 1 θ i = Ω S Level difference, but does not affect growth rate of Ω as long as distribution of firm inputs and output remains unchanged

62 Growth Accounting Standard Deviation of Employment Size emp_sd Data Year - Fiscal

63 Growth Accounting Distribution of Q i L i and Q i K i kdensity s_l 8.000e e e e-06 kdensity s_k x x

64 Growth Accounting Distribution of Q i L θ K 1 θ i i kdensity s_lk x

65 Growth Accounting Estimated Labor Productivity Growth lpoly smoothing grid lpoly smooth: JJ_gr lpoly smooth: SOLOW_gr