Competition, Uncertainty, and Misallocation
Transcript of Competition, Uncertainty, and Misallocation
Competition, Uncertainty, and Misallocation
Kaoru Hosono (Gakushuin University) Miho Takizawa (Toyo University)
Kenta Yamanouchi (Keio University)
Summer Workshop on Economic Theory August, 2017
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Composition
1. IntroducJon
2. Literature Review
3. Model and SimulaJon
4. Data and Methodology
5. EsJmaJon Results
6. Conclusion
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1. Introduction
Uncertainty
CompeJJon
MisallocaJon
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• This paper invesJgates the effects of the degree of compeJJon on the negaJve impact of uncertainty on capital misallocaJon across producers.
• Using a large dataset of manufacturing plants in Japan, we find that the impact of uncertainty is stronger when the product market is compeJJve.
• Under favorable producJvity shock, plants adjust their inputs to the opJmal amount.
• If adjustment is insufficient by some reasons, marginal revenue product of capital (MRPK) is deviated from rental rate (E to A, not B).
• If MRPK is dispersed across firms, reallocaJon of capital from low MRPK firms to high would increase aggregate output.
MRPK A Rental Rate E B Productivity shock K
Productivity Shock and Misallocation
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Changes of Productivity and MRPK
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-4-2
02
4ch
ange
in ln
MR
PK
-2 -1 0 1 2change in productivity
• If the amount of capital is adjusted immediately a]er the producJvity shock, MRPK is constant and equal to rental cost.
• But the changes of producJvity and MRPK are posiJvely correlated, so insufficient adjustment is implied.
Uncertainty and Misallocation Larger uncertainty deteriorates allocaJve efficiency of capital across firms. 1. Time-‐to-‐build
• If capital adjustment requires Jme-‐to-‐build, uncertainty directly affects on the deviaJon between actual and opJmal levels of capital.
• Asker, Collard-‐Wexler, and De Loecker (2014)
2. ReducJon of investment • Many papers considers the effects of uncertainty on investment (e.g. Dixit and Pindyck (1994)).
• But all of those studies don’t focus on the effects of allocaJve efficiency.
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Competition Matters • The degree of compeJJon is closely related to the effects of uncertainty on investment.
• While the fierce compeJJon theoreJcally miJgates the negaJve effects of uncertainty, the results of empirical studies are mixed.
• In addiJon, no studies link the effects of compeJJon to uncertainty-‐misallocaJon relaJonship.
• CompeJJon macers for the effects of uncertainty on resource misallocaJon.
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Competition and Allocative Efficiency • Some papers focus on the effects of compeJJon on allocaJve efficiency across producers.
• Olley and Pakes (1996) • Collard-‐Wexler and De Loecker (2015) • Edmond, Midrigan, and Xu (2015)
• Tougher compeJJon promotes the reallocaJon of resources from less producJve firms to producJve firms.
• In other words, producJvity determines the firm size strongly in a compeJJve industry.
• Most of those papers assume immediate adjustment, but the effect of uncertainty is strong under costly adjustment and Jme-‐to build.
• The reducJon of uncertainty complements compeJJon policies to improve allocaJve efficiency.
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This Paper • This paper invesJgate the relaJonship between the degree of product market compeJJon and the adverse effects of uncertainty on resource misallocaJon across plants.
• We conduct numerical simulaJon for investment model and reduced form esJmaJon, using a large panel dataset of manufacturing plants in Japan.
• The results show that the adverse effects of uncertainty are stronger for industries with tougher compeJJon.
• The effects of uncertainty on investment • The dependence of opJmal amount of capital on producJvity
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Research Questions and Results 1. Does greater uncertainty worsen resource allocaJon
across plants in Japan? -‐ Yes, uncertainty increases capital misallocaJon in Japan.
2. How is the product market compeJJon related to the
adverse effects of uncertainty on allocaJve efficiency? -‐ The adverse effects of uncertainty are large for the industries with tougher compeJJon.
3. How does the degree of compeJJon affect on the
adjustment process of capital? -‐ The negaJve effects of uncertainty on investment is stronger in compeJJve industries along both extensive and intensive margin.
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Composition
1. IntroducJon
2. Literature Review
3. Model and SimulaJon
4. Data and Methodology
5. EsJmaJon Results
6. Conclusion
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1. Competition and uncertainty-investment relationship Uncertainty and investment
A. Convexity of MRPK with respect to producJvity: posiJve • Uncertainty increases the expected return from investment by Jensen’s inequality.
• Hartman (1972), Abel (1983) B. Real opJons theory: negaJve
• It is becer to wait and avoid a costly disrupJon in a highly uncertain environment.
• McDonald and Siegel (1986), Pindyck (1988), Dixit and Pindyck (1994)
C. Empirical studies: negaJve • Most but not all studies find negaJve effects of uncertainty on investment.
• Bloom, Bond, and Van Reenen (2007), Bloom (2014)
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Theory A. Capital adjustment cost
• Both of imperfect compeJJon and asymmetric capital adjustment costs are required for the delay of investment.
• Caballero (1991)
B. OpJon exercise games • OpJon values erode under fierce compeJJon because compeJtors may preempt the opportunity of investment.
• Williams (1993), KulaJlaka and Peroj (1998), Grenadier (1996, 2002)
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1. Competition and uncertainty-investment relationship
Evidence A. CompeJJon miJgates the negaJve effects of uncertainty.
• Guiso and Parigi (1999): price-‐cost margin • Bontempi, Golinelli, and Parigi (2010): price-‐cost margin • Bulan (2005): industry concentraJon raJos • Bulan, Mayer, and Somerville (2009): # of compeJtors • Akdogu and MacKay (2008): HHI
B. NegaJve effect is stronger in compeJJve industries. • Ghosal and Loungani (1996, 2000): concentraJon raJo
→No studies focus on the effects of uncertainty on allocaJve efficiency.
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1. Competition and uncertainty-investment relationship
2. Resource Misallocation across producers
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Baseline framework
A. Perfect compeJJon
• Even in the U.S., the allocaJon of inputs across plants are severely distorted.
• Restuccia and Rogerson (2008)
B. MonopolisJc compeJJon
• Compared with the U.S., the allocaJve efficiency is very low in China and India.
• Hsieh and Klenow (2009)
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CompeJJon
• Increased compeJJon reduces markup distorJon across plants.
• Edmond, Midrigan, and Xu (2015)
Uncertainty
• Higher Jme-‐series volaJlity contributes to larger cross-‐secJonal dispersion of MRPK.
• Asker, Collard-‐Wexler, and De Loecker (2014)
→The effects of compeJJon and uncertainty are not simultaneously explored.
2. Resource Misallocation across producers
Composition
1. IntroducJon
2. Literature Review
3. Model and SimulaJon
4. Data and Methodology
5. EsJmaJon Results
6. Conclusion
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Model Simple dynamic investment model • Asker, Collard-‐Wexler, and De Loecker (2014) • Demand
• ProducJon
• Sales
• Profit Si =ΩiKi
βK LiβLMi
βM , ��βX = 1− 1ε
#
$%
&
'(αX
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Qi = BPi−ε
Qi = AiKiαK Li
αLMiαM , �αK +αL +αM =1
π (Ωit,Kit ) = (βK +ε−1) βL
pL
#
$%
&
'(
βL(βK+ε
−1 ) βMpM
#
$%
&
'(
βM(βK+ε
−1 )Ωit1/(βK+ε
−1 )KitβK /(βK+ε
−1 )
Model • Dynamic process
• Value funcJon • Capital adjustment cost
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ωit = ρωit−1 +σκ it, �κ it ~ N(0,1)
Kit = δKit−1 + Iit−1
V (Ωit,Kit ) =maxIitπ (Ωit,Kit )−C(Iit,Kit,Ωit )+β V (Ωit+1,δKit+1 + Iit )ϕ(Ωit+1 Ωit )dΩit+1
Ωit+1
∫
C(Iit,Kit,Ωit ) = Iit +1 Iit>0{ } CKF+π (Ωit,Kit )+CK
Q+KitIitKit
"
#$
%
&'
2(
)**
+
,--+1 Iit<0{ } CK
F−π (Ωit,Kit )+CKQ−Kit
IitKit
"
#$
%
&'
2(
)**
+
,--
MisallocaJon Uncertainty CompeJJon OpJmal amount of capital
lnMRPKi = ln(βK )+ si − ki
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Volatility =σ
ε = 2, 4, 6
Misallocation = SD lnMRPKi( )
kit* = cons+εωit
Simulation
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Simulation result 1 • Large uncertainty increases capital misallocaJon. • When the compeJJon is tough, the effects of uncertainty are large. • The amount of opJmal producJon strongly depends on producJvity
in the case of tougher compeJJon, so the volaJlity of producJvity is largely reflected into large dispersion of MRPK.
02
46
8SD
(lnM
RPK
)
0 .5 1 1.5volatility
ε = 2 ε = 4 ε = 6
Symmetric costs
02
46
8SD
(lnM
RPK
)
0 .5 1 1.5volatility
ε = 2 ε = 4 ε = 6
Asymmetric costs
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Simulation result 2 • In the case of symmetric costs, the fracJon of posiJve investment is
high under large volaJlity due to the Hartman-‐Abel effect. • On the other hand, uncertainty reduces the fracJon of posiJve
investment when adjustment costs are asymmetric.
0.1
.2.3
.4.5
.6.7
.8.9
1Fr
actio
n of
pos
itive
inve
stm
ent
0 .5 1 1.5volatility
ε = 2 ε = 4 ε = 6
Asymmetric costs
0.1
.2.3
.4.5
.6.7
.8.9
1Fr
actio
n of
pos
itive
inve
stm
ent
0 .5 1 1.5volatility
ε = 2 ε = 4 ε = 6
Symmetric costs
Composition
1. IntroducJon
2. Literature Review
3. Model and SimulaJon
4. Data and Methodology
5. EsJmaJon Results
6. Conclusion
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Data
• Source: Census of Manufacturing published by METI
• Coverage: All manufacturing plants with more than 30 employees located in Japan
• Period: 1986-‐2013 • Industry: 4 digit (491 industries)
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Measurement (plant-level variables) Log-‐linearized producJon funcJon:
• : TFPR • Dynamic panel esJmaJon: Blundell and Bond (1998, 2000)
(Log of) MRPK:
sit = βKskit +βLslit +βMsmit +ηi + yeart + ωit +ζ itωit = ρ ωit−1 +ξit
MRPKit = ln∂Sit∂Kit
"
#$
%
&'= ln(βKs )+ sit − kit
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ωit =ηi + yeart + ωit +εit
sit = π1kit +π 2kit−1 +π3lit +π 4lit−1 +π 5mit +π 6mit−1 +π 7sit−1 +ηi* + yeart
* +ωit
E xit−sΔωit( ) = 0
E Δxit−s ηi* +ωit( )( ) = 0
s ≥ 3
Measurement (industry-level variables) Uncertainty:
• VolaJlity of producJvity shocks MisallocaJon:
• Dispersion in MRPK results in aggregate producJvity losses from the staJc view point.
• Hsieh and Klenow (2009) CompeJJon:
• Constant return to scale is imposed. • We also check the method of De Loecker and Warzynski (2012).
Volatilityst = SDst (ωit −ωit−1)
Misallocationst = SDst (MRPKit )
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Markups =εsεs −1
=1
βKs +βLs +βMs
Estimation method 1. Greater uncertainty reduces investment and results in
staJc misallocaJon.
2. The impact of uncertainty on misallocaJon is weaker in
the market where compeJJon is severer.
3. The probability of investment and the investment rate is related to uncertainty and compeJJon.
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Misallocationst = βVolatilityst +FEs +ust
Misallocationst = γ1Volatilityst +γ2Volatilityst *Markups +FEs +ust
1{I /K>0.05}it = λ1 lnMRPKit +λ2Volatilityst +λ3 lnMRPKit *Volatilityst +FEi +FEt +uitIit /Kit = λ1 lnMRPKit +λ2Volatilityst +λ3 lnMRPKit *Volatilityst +FEi +FEt +uit
Summary statistics
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Capital misallocation
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• Capital misallocaJon has increased within industry in Japan.
Change of misallocation by investment status
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• MisallocaJon is reduced a]er investment among posiJve investment plants.
Composition
1. IntroducJon
2. Literature Review
3. Model and SimulaJon
4. Data and Methodology
5. EsJmaJon Results
6. Conclusion
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Volatility and misallocation
• The measures of volaJlity and capital misallocaJon are posiJvely correlated.
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Volatility and misallocation
• The effects of volaJlity on misallocaJon are stronger in small markup industries.
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Estimation results 1 • SD(MRPK) is posiJvely correlated with volaJlity measure. • The effects of volaJlity are strong in the industries with small markup.
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Estimation results 2 • The results are not changed even if the measures of volaJlity and markup are changed.
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Markup2st =medianβMs
PMstMit / Sit
!
"#
$
%&Volatility2st = SDst (ωit −
ρωit−1)
Estimation results 3 • Large MRPK plants are more likely to conduct posiJve investment. • When uncertainty is large, the investment is less likely to be made even if MRPK is large.
• The negaJve effects of uncertainty are not observed in the industries with tough compeJJon.
• NegaJve investment are not affected by uncertainty.
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Estimation results 4 • Large MRPK plants tend to conduct more investment. • Under large uncertainty, the investment rate is less affected by MRPK. • The negaJve effects of uncertainty are observed in the industries with tough compeJJon.
• CompeJJon affects misallocaJon both through the opJmal amount of capital and through the reducJon of investment.
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Composition
1. IntroducJon
2. Literature Review
3. Model and SimulaJon
4. Data and Methodology
5. EsJmaJon Results
6. Conclusion
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Summary • This paper invesJgates the effect of compeJJon to the uncertainty-‐misallocaJon relaJonship.
• SimulaJon results show that the negaJve effects of uncertainty are severe in the industries with tougher compeJJon.
• These results are confirmed in the esJmaJon, using a large dataset of Japanese manufacturing plants.
• The negaJve effects of uncertainty on investment are strong in the compeJJve market.
• Some papers showed compeJJon improves allocaJve efficiency, but our results suggest compeJJon induces fragility to uncertainty.
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Future work
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-.15
-.1-.0
50
.05
.1.1
5.2
.25
.3.3
5M
ean(
lnM
RPK
) in
next
yea
r
1985 1990 1995 2000 2005 2010 2015Year
zero positivenegative
-.2-.15
-.1-.05
0.05
.1.15
.2Mean(lnMRPK
)
1985 1990 1995 2000 2005 2010 2015Year
zero positivenegative
• While this study sheds new lights on the role of compeJJon in the uncertainty-‐misallocaJon relaJonship, we have not yet explored the durability of uncertainty-‐driven misallocaJon.
• If the major source of such misallocaJon is Jme-‐to-‐build, then uncertainty-‐driven misallocaJon may be short-‐lived.
• We find a relaJvely small quanJtaJve impact of volaJlity, which may reflect the short-‐run effect of uncertainty.