The Rise of Market Power and the Macroeconomic Implications · The Rise of Market Power and the...
Transcript of The Rise of Market Power and the Macroeconomic Implications · The Rise of Market Power and the...
The Rise of Market Powerand the Macroeconomic Implications
Jan De Loecker1 Jan Eeckhout2
1Princeton and University of Leuven2University College London and UPF
NBER Summer Institute18 July, 2017
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 data2. Estimation methods: demand approach uses model of
consumer behavior and competition
• This paper:
1. Document time-series and cross section of markup 1950-20142. Cost-based method; no inference from demand; mkt structure3. Illustrate how this can explain 7 secular trends since 1980
• We have nothing (little) to say about causes of change markup
MotivationSecular Increase since 1980: markup 1.18→ 1.67
1.1
1.2
1.3
1.4
1.5
1.6
1.7Sh
are
wei
ghte
d M
arku
p
1960 1970 1980 1990 2000 2010year
Figure: The Evolution of Average Markups (1950–2014), weighted
Data
• Compustat data on publicly listed firms:• Long time series: 1950–2014• Broad Cross Section: average 5,000 firms per year
• Selection?• Large firms; miss many small firms• Small subset of all firms• Publicly traded 6= 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
Producer Behavior
• Production technology
Qit(VVV it ,Kit ,Ωit) = Fit(VVV it ,Kit)Ωit ,
where• VVV it : variable inputs (labor, intermediate inputs)• Kit : capital stock• Ωit : Hicks-neutral productivity term (TFP)
• Associated Lagrangian function (with one composite input):
L(Vit ,Kit , λit) = PVit Vit + ritKit − λit(Qit(·)− Qit)
• Consider FOC wrt the variable input V :
∂Lit∂Vit
= PVit − λit
∂Qit(·)∂Vit
= 0
• Rearranging ⇒ expression of output elasticity of input Vit :
θVit ≡∂Qit(·)∂Vit
Vit
Qit=
1
λit
PVit Vit
Qit
Producer Behavior
• Lagrangian multiplier λ is a direct measure of marginal cost
• Define markup µ = Pλ or
µit = θVitPitQit
PVit Vit
.
depending on Sales Sit = PitQit and expenditure share θVit ,which is specific to technology
• Method: Hall (1988): aggregate data; De Loecker-Warzynski(2012): micro data
Robustness
Benchmark Industry-Specific CD
1.1
1.2
1.3
1.4
1.5
1.6
1.7
Shar
e w
eigh
ted
Mar
kup
1960 1970 1980 1990 2000 2010year
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1960 1970 1980 1990 2000 2010year
Share weighted Markup Markup (ind techn.)
Census Manufacturing Translog
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1960 1970 1980 1990 2000 2010year
Share weighted Markup Share weighted markup (Manufacturing)
1.2
1.3
1.4
1.5
1.6
1.7
Shar
e w
eigh
ted
Mar
kup
1.5
2
2.5
Mar
kup
(ind
tech
n. T
rans
log)
1960 1970 1980 1990 2000 2010year
Markup (ind techn. Translog)Share weighted Markup
Cross-Sectional DecompositionHigher Markups for Smaller Firms
Ut =∑i
sitµit
= µt +∑i
(sit − st)(µit − µt)
where:
Ut : weighted average markupµt : unweighted average markupµit : firm i ’s individual markupsit : firm i ’s market share of sales
Cov(sit , µit) < 0⇒ Higher Markups for Smaller Firms
Cross-Sectional DecompositionHigher Markups for Smaller Firms
1
1.5
2
2.5
1960 1970 1980 1990 2000 2010year
Share weighted Markup mu_mean
Figure: Unweighted vs. Weighted Average Markup
Time-Series DecompositionPredominantly Within Industry, in All Industries
∆Ut =∑s
ss,t−1∆µst︸ ︷︷ ︸∆ within
+∑s
µs,t−1∆ss,t︸ ︷︷ ︸∆ between
+∑s
∆µs,t∆ss,t︸ ︷︷ ︸∆ reallocation
.
Markup ∆ Markup ∆ Within ∆ Between ∆ Realloc.
1964 1.319 0.135 0.067 -0.011 0.0791974 1.231 -0.088 -0.084 0.042 -0.0461984 1.236 0.004 -0.008 0.025 -0.0121994 1.360 0.124 0.126 0.004 -0.0072004 1.519 0.159 0.116 0.031 0.0122014 1.667 0.151 0.187 -0.018 -0.020
Table: Decomposition 10 year change in Markup at 4-digit industry
Dispersion of MarkupAll Action in Upper Half Distribution
1
1.5
2
2.5
1960 1970 1980 1990 2000 2010year
Share weighted Markup p90 (ms) p50 (ms)p75 (ms)
• Harberger (1954): roughly equally distributed profits; not now
Dispersion of MarkupAll Action in Upper Half Distribution
1
1.5
2
2.5
1960 1970 1980 1990 2000 2010year
Share weighted Markup p90 (ms) p50 (ms)p75 (ms)
• Harberger (1954): roughly equally distributed profits; not now
Markup = Market Power?Dividends and Market Value
500000
1000000
1500000
2000000
Shar
e w
eigh
ted
Div
iden
d1.1
1.2
1.3
1.4
1.5
1.6
1.7
Mar
kup
1960 1970 1980 1990 2000 2010year
Markup Share weighted Dividend
0
2.00e+07
4.00e+07
6.00e+07
8.00e+07
Shar
e w
eigh
ted
Mar
ket V
alue
1.1
1.2
1.3
1.4
1.5
1.6
1.7
Mar
kup
1960 1970 1980 1990 2000 2010year
Markup Share weighted Market Value
Markup = Market Power?Aggregate Profit Rate
• External validation: compare increase in aggregate profit ratewith increase in profit rate from micro data
• Incomplete comparison:
1. aggregate has profits of all firms vs. micro data only publiclytraded firms (large; 40% of GDP)
2. total profits Π versus variable profits ΠV (levels are different!)
• Microdata
ΠV
GDP=
ΠV
PQ
GNI
GDP=
(1− 1
µ
)GNI
GDP⇒
ΠV2014
GDP2014
ΠV1980
GDP1980
= 2.34
• Aggregate Data: Total Profits Π increase by factor 4
• Even bigger increase in aggregate profits. Either:
1. Smaller firms have even bigger markups2. or, capital expenditure has increased less than variable costs
Markup = Market Power?Aggregate Profit Rate
.02
.04
.06
.08
.1.1
2
1950q1 1960q1 1970q1 1980q1 1990q1 2000q1 2010q1 2020q1time
Figure: Profit rates. Data FRED, from national accounts. Quarterly.
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
A Simple ModelUnskilled Labor is Variable Input
Let V = L, demand P(Q) and quantity
Qi = ΩiLθi K
1−θi
where:
Ωi : firm productivityLi : quantity of efficiency units of laborSi = PiQi
FOCwLiSi
=θ
µi
Inverse relation labor share and markup µi
1. Decline in Labor Share
70
80
90
100
110
1940 1960 1980 2000 2020Data 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 (Twomeasures: weighted by Sales, and weighted by Employment)
2. Decline in Capital Share
• K is capital investment and r is the user cost. FOC (long run):
rKi
S i=θkµi
• Accounting identity:
wL + rK + Πi = Si
⇐⇒ wLiSi
+rKi
Si+
Πi
Si= 1
⇐⇒ (θl + θk)1
µi= 1− πi
• If profit share ↑ ⇒ labor and capital share ↓ (provided Qi iscomplementary in Li ,Ki )
2. Decline in Capital Share
.6
.65
.7
.75
.8
.85
MAR
KUP_INV
.06
.08
.1
.12
.14
.16
k_share_agg
1960 1980 2000 2020year
k_share_agg MARKUP_INV
Figure: The Evolution of the capital share (own computations), andinverse of the markup (weighted by Sales Share) (1980 - 2014). GrossCapital adjusted by the input price deflator, the federal funds rate, andan exogenous depreciation rate of 12%.
Market PowerConduct Parameter λ
• Follow Bresnahan (1982)
• Pricing equation (given a marginal cost c):
P(Q) = c + λh(Q)
where Q =∑
i Qi and where h(Q) = −∂P(Q)∂Q Q; Linear
demand P(Q) = a− bQ for example, h(Q) = bQ
• Our measure for markup µ = Pc can then be written as:
µ = 1 + λh(Q)
c
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 λ2. Number of firms per market N = 1
λ3. In a given market, all N firms have same technology Ωi
4. Linear Demand, to capture incomplete pass-through ( 6= CES)
Equilibrium Impact of Market Power
• Constant returns θ = 1, identical firms within market Ω• Firm objective:
maxLi
P(Q)Qi − wLi , where Qi = ΩiLi
• First-order Condition:
P(Q) = c + λh(Q) ⇐⇒ a− (1 + λ)bQ=w
Ωθ
⇒ L =a− w
Ω
(1 + λ)bΩ, Li =
λ
1 + λ
a− wΩ
bΩ
⇒ ∂L
∂λ=
a− wΩ
bΩ
−1
(1 + λ)2< 0 and
∂Li∂λ
=a− w
Ω
bΩ
1
(1 + λ)2> 0.
LemmaFor a given wage and a given market Ω, the market labor demandL is decreasing in market power λ; and an individual firm’s labordemand Li is increasing in market power λ.
Compustat DataFirm Size and Number of Firms
0
2000
4000
6000
8000
10000
nrfir
ms
5000
10000
15000
20000
L_m
ean
1940 1960 1980 2000 2020Data Year - Fiscal
L_meannrfirms
Equilibrium Impact of Market Power
• Labor Demand: aggregate over different markets Ωi ∼ F (Ωi )
LD =
∫ Ω
ΩL(Ωi ;w ;λ)dF (Ωi ) =
1
(1 + λ)b
∫ Ω
Ω
(a
Ωi− w
Ω2i
)dF (Ωi )
• Labor Supply: heterogeneous workers z ∼ G (z) supplyefficiency units of labor; outside option is U
LS =
∫ 1
Uw
zdG (z)
∴ Equilibrium: LD = LS ⇒ w?, L?
Equilibrium Impact of Market Power
⇒ Labor Force: ∂L?
∂λ < 0; and Nominal Wages: ∂w?
∂λ < 0; Ω = 1
L
P,w
LDλ=0
LS
Pλ=0 = w?λ=0
L?λ=0
LDλ=1
w?λ=1
Pλ=1
L?λ=1
Equilibrium Impact of Market Power
⇒ Labor Force: ∂L?
∂λ < 0; and Nominal Wages: ∂w?
∂λ < 0; Ω = 1
L
P,w
LDλ=0
LS
Pλ=0 = w?λ=0
L?λ=0
LDλ=1
w?λ=1
Pλ=1
L?λ=1
Equilibrium Impact of Market Power
⇒ Labor Force: ∂L?
∂λ < 0; and Nominal Wages: ∂w?
∂λ < 0; Ω = 1
L
P,w
LDλ=0
LS
Pλ=0 = w?λ=0
L?λ=0
LDλ=1
w?λ=1
Pλ=1
L?λ=1
Equilibrium Impact of Market Power
⇒ Labor Force: ∂L?
∂λ < 0; and Nominal Wages: ∂w?
∂λ < 0; Ω = 1
L
P,w
LDλ=0
LS
Pλ=0 = w?λ=0
L?λ=0
LDλ=1
w?λ=1
Pλ=1
L?λ=1
3. Decline in (Low Skill) WagesEvidence
• 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.
3. Decline in (Low Skill) WagesReal Median Wages and Relative to GDP
310
320
330
340
350
1980q1 1990q1 2000q1 2010q1 2020q1
.6.8
11.
21.
4
1980q1 1990q1 2000q1 2010q1 2020q1
4. Decline in Labor Force ParticipationEvidence
.58
.6.6
2.6
4.6
6.6
8
1950m1 1960m1 1970m1 1980m1 1990m1 2000m1 2010m1 2020m1time
Notes. From CPS.
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 lessthan proportional increase/decrease in Q and L
• Linear demand: pass-through decreasing in market power λ
⇒ Market power ↑ → labor market adjustment ↓ for same shock
Labor Reallocation and Pass-through
ΩL
P
LDλ=0
∆Lλ=0
wΩ
wΩ
Pλ=0(Ω) =
Pλ=0(Ω) =
LDλ=1
∆Lλ=1
Pλ=1(Ω)
Pλ=1(Ω)
Labor Reallocation and Pass-through
ΩL
P
LDλ=0
∆Lλ=0
wΩ
wΩ
Pλ=0(Ω) =
Pλ=0(Ω) =
LDλ=1
∆Lλ=1
Pλ=1(Ω)
Pλ=1(Ω)
Labor Reallocation and Pass-through
ΩL
P
LDλ=0
∆Lλ=0
wΩ
wΩ
Pλ=0(Ω) =
Pλ=0(Ω) =
LDλ=1
∆Lλ=1
Pλ=1(Ω)
Pλ=1(Ω)
5. Decline in Labor Market Flows
.015
.025
.03
.04
.06
.08
tota
l
1975q1 1980q1 1985q1 1990q1 1995q1 2000q1 2005q1 2010q1 2015q1dq
(UE+NE)/( U+N) (left axis) ee (right axis)
6. Decline in Migration Rates
.01
.015
.02
.025
.03
.035
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
Migration Rates
Migration Rate, between MSA’s (1962 - 2016). CPS Data.
7. Slowdown in aggregate output growth
7.5
88.
59
9.5
10
1950q1 1960q1 1970q1 1980q1 1990q1 2000q1 2010q1 2020q1
7. Slowdown in aggregate output growthProductivity Growth
• Firm’s FOC for Labor:
PΩiLθ−1i K 1−θ
i θµ−1i = w ⇒ Ωi = µi
w
P
1
θL1−θi K 1−θ
i .
• Constant Marginal Product of Labor: θ = 1
Ωi = µiw
P
• Hall (1988)
7. Slowdown in aggregate output growthProductivity Growth
-.1
-.05
0
.05
.1
1960 1980 2000 2020
omega_gamma_gr TFP_gamma_grlpoly smooth: omega_gamma_gr lpoly smooth: TFP_gamma_gr
-.04
-.02
0
.02
.04
.06
wed
ge
1960 1980 2000 2020Data Year - Fiscal
90% CI wedge lpoly smooth
Conclusions
1. Sharp rise in Market Power since 1980
2. Significant macroeconomic implications: 7 secular trends
ConclusionsOpen Questions
1. Causes? Technology, M&A,...
2. Other secular trends?
1. decrease in startup rate of new firms2. decrease long term interest rate: capital D ↓, S ↑3. increase in wage inequality: profit sharing managers4. the great moderation...
3. 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 6= economic growth
ConclusionsM&A
0
5000
10000
15000
20000
1.2
1.3
1.4
1.5
1.6
1.7
Shar
e-w
eigh
ted
Mar
kup
(DLW
)
1960 1980 2000 2020Year
Share-weighted Markup (DLW)Nr M&AAverage value M&A (10,000 USD)
ConclusionsOpen Questions
1. Causes? Technology, M&A,...
2. Other secular trends?
1. decrease in startup rate of new firms2. decrease long term interest rate: capital D ↓, S ↑3. increase in wage inequality: profit sharing managers4. the great moderation...
3. 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 6= economic growth
ConclusionsOpen Questions
1. Causes? Technology, M&A,...
2. Other secular trends?
1. decrease in startup rate of new firms2. decrease long term interest rate: capital D ↓, S ↑3. increase in wage inequality: profit sharing managers4. the great moderation...
3. 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 6= economic growth
ConclusionsStock Market Valuation
0
5000
10000
15000
20000
DOW
JO
NES
(Defl
ated
CPI
)
1.2
1.3
1.4
1.5
1.6
1.7
Shar
e we
ight
ed M
arku
p
1960 1970 1980 1990 2000 2010year
Share weighted MarkupDOW JONES (Deflated CPI)
ConclusionsOpen Questions
1. Causes of Market Power? Technology, M&A,...
2. Other secular trends?
1. decrease in startup rate of new firms2. decrease long term interest rate: capital D ↓, S ↑3. increase in wage inequality: profit sharing managers4. the great moderation...
3. 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 6= economic growth
Whenever a theory appears to you as the only possibleone, take this as a sign that you have neither understoodthe theory nor the problem which it was intended to solve
Karl Popper
The Rise of Market Powerand the Macroeconomic Implications
Jan De Loecker1 Jan Eeckhout2
1Princeton and University of Leuven2University College London and UPF
NBER Summer Institute18 July, 2017
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
Translog Production Technology
• Unusually long sample period: 1950-2014
• Industry-specific, time-varying output elasticities
• Preserves identification results, De Loecker-Warzynski (2012)
• Moment conditions from static optimization of variable inputs:
E(ξit(βββ)
[vit−1
v2it−1
])= 0,
• With translog production function for each industry:
qit = βv1vit + βk1kit + βv2v2it + βk2k
2it + ωit + εit
• Variation output elasticity over time (or firms), no longerattributed to markup variation
• Output elasticity of the composite variable input:
θvit = βv1 + 2βv2vit
• Markup defined as before; level difference, but normalization
Cross-Sectional DecompositionAcross All Industries
1.2
1.3
1.4
1.5
1.6
1.7
1940 1960 1980 2000 2020year
Markup Mean 4digit
Figure: Industry disaggregation
Markup = Market Power?Dividends
• Individual firm level: firm-level average markup (all years) andthe share of total dividends in total sales
1.5
2
2.5
3
3.5
mar
kupm
ean_
firm
0 .2 .4 .6 .8 1divmargin_av
kernel = epanechnikov, degree = 0, bandwidth = .05
Local polynomial smooth
Growth Accounting
• First order approach: no productivity slowdown
• Solow residual: shows a decrease in productivity since 2000
4.6
4.7
4.8
4.9
55.
1
1980 1990 2000 2010 2020
01
23
4
1980 1990 2000 2010 2020
Growth Accounting
• Solow residual based on aggregate production technology
Q = ΩSLθK 1−θ ⇒ ΩS =Q
LθK 1−θ
where L =∑
i Li and K =∑
i Ki
• Micro data:
Ω =∑i
Ωi =∑i
Qi
Lθi K1−θi
↔∑
Qi∑i Lθi
∑i K
1−θi
= ΩS
→ Level difference, but does not affect growth rate of Ω as longas distribution of firm inputs and output remains unchanged
Growth AccountingStandard Deviation of Employment Size
20
30
40
50
emp_
sd
1940 1960 1980 2000 2020Data Year - Fiscal
Growth AccountingDistribution of Qi
Liand Qi
Ki
0
2.000e-06
4.000e-06
6.000e-06
8.000e-06
.00001
kden
sity
s_l
0 500000 1000000 1500000x
1960 1970 19801990 2000 2014
0
.1
.2
.3
kden
sity
s_k
0 5 10 15x
1960 1970 19801990 2000 2014
Growth AccountingDistribution of Qi
Lθi K1−θi
0
.0001
.0002
.0003
.0004
kden
sity
s_l
k
0 5000 10000 15000 20000 25000x
1960 1970 19801990 2000 2014