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Economic Distributions in Monopolistic competition André de Palma, Ecole Nomale Supérieure de Cachan Coauthored with Simon Anderson, University of Virginia, CEPR 2016 EAJ Conference Claude Lefèvre Day – Research conference September 5, 2017

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Page 1: Economic Distributions in Monopolistic competition · 2018-01-23 · Economic Distributions in Monopolistic competition André de Palma, EcoleNomaleSupérieure de Cachan Coauthored

Economic Distributions in Monopolistic competition

André de Palma, Ecole Nomale Supérieure de CachanCoauthored with Simon Anderson, University of Virginia, CEPR

2016 EAJ ConferenceClaude Lefèvre Day – Research conference

September 5, 2017

Page 2: Economic Distributions in Monopolistic competition · 2018-01-23 · Economic Distributions in Monopolistic competition André de Palma, EcoleNomaleSupérieure de Cachan Coauthored

Former title: Economic distributions and primitive distributions in Industrial Organization and International Trade

Keywords: CES, Logit, IIA, monopolistic competition, primitive and economic distributions, Pareto, (log‐)normal, exponential, 

mark‐ups, demand form, …

Page 3: Economic Distributions in Monopolistic competition · 2018-01-23 · Economic Distributions in Monopolistic competition André de Palma, EcoleNomaleSupérieure de Cachan Coauthored

My collaboration with Claude Lefèvre

• Mathematical sociology: probabilistic decision models, search, cross‐nested, logit  with interactions  Social network & Search Logit models

• Transportation (with Ben‐Akiva, and P. Kanaroglou & N. Litinas):  ; 1st day‐to‐day dynamic congestion modelNew paradigm in transportation

05/09/2016 Claude Lefèvre's Day 2016 3

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My collaboration with Claude Lefèvre

• Marketing (with Droesbeke, Rosinski): diffusion of innovation with negative         feed‐back

Information congestion• Urban Economics : compartmental analysis with (non)extensive interactions 

MFD

05/09/2016 Claude Lefèvre's Day 2016 4

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This was for the dean, ….

truth is a bit different

05/09/2016 Claude Lefèvre's Day 2016 5

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(Mathematical) sociology

05/09/2016 Claude Lefèvre's Day 2016 6

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Transportation in practice

05/09/2016 Claude Lefèvre's Day 2016 7

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05/09/2016 Claude Lefèvre's Day 2016 8

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05/09/2016 Claude Lefèvre's Day 2016 9

Shared modes

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Synthetic measure of  Claude’s friendliness

05/09/2016 Claude Lefèvre's Day 2016 10

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Autonomous vehicles – 1981

05/09/2016 Claude Lefèvre's Day 2016 11

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.. In 2009

05/09/2016 Claude Lefèvre's Day 2016 12

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Marketing

05/09/2016 Claude Lefèvre's Day 2016 13

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New urban economics

05/09/2016 Claude Lefèvre's Day 2016 14

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Jaipur

05/09/2016 Claude Lefèvre's Day 2016 15

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La machine magiqueAu XVIIIe siècle en Inde sous le règne du puissant maharajah Jai Singh, à l'ombre du fameux observatoire de Jaipur, un jeune brahmane raconte sa double éducation sensuelle et scientifique. Tandis que son maître l'initie à la cosmogonie traditionnelle, il découvre les mystères de l'amour avec une jolie gitane. Des savants d'une mission européenne lui ouvriront des horizons nouveaux. Alerte, bondissant comme son héros, ce roman nous conduit de harems en bibliothèques, d'une culture à l'autre avec une verve qui semble emprunter autant à Voltaire qu'à une fable paradoxalement moderne.La machine Magique, Luc Leruth, Gallimard

05/09/2016 Claude Lefèvre's Day 2016 16

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Khajuraho

05/09/2016 Claude Lefèvre's Day 2016 17

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Gange @ Varanasi

05/09/2016 Claude Lefèvre's Day 2016 18

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1er avril 2010, école obligatoire en Inde pour les enfants de 6 à 14 ans

05/09/2016 Claude Lefèvre's Day 2016 19

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1981: Les enfants privilégiés allaient à l’école

05/09/2016 Claude Lefèvre's Day 2016 20

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2016: Kalkeri School of Music (Karnataka)

05/09/2016 Claude Lefèvre's Day 2016 21

Mallikriyan

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“Statistical mechanics” approach in IO and Trade 

Shift attention from standard IO & Trade models based on “point values” on an approach based on “distribution” How consumers and Firms (in an industry) can be described with distributions?Distribution of cost, quality Distribution of consumers’ preferencesDistribution of price, mark‐up, output, profits 

05/09/2016 Claude Lefèvre's Day 2016 22

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From Physics to Statistical mechanics 

05/09/2016 Claude Lefèvre's Day 2016 23

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Bose‐Einstein statistics

05/09/2016 Claude Lefèvre's Day 2016 24

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Fermi‐Dirac statistics

• Energy ; potential ; Boltzmann constant: k, temperature:  T

05/09/2016 Claude Lefèvre's Day 2016 25

exp 1

ii

i

gnA

kT

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Two objectives (here)

1. Establish logical relations between distribution of quality ‐ costs of demand/preference 

2. How moments (means, variance, …) of one distribution can explain moments of other distributions?

05/09/2016 Claude Lefèvre's Day 2016 26

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And a third one….

Economists should explain how to elicit  consumer behavior, technological features, competition rules from large data sets ?

3. Back‐up demand functions

We propose an operational approach to do that!

05/09/2016 Claude Lefèvre's Day 2016 27

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Backdrop• Build or reverse engineer a model with distributions

• Primitive distributions (h&c; h&v‐c) beget economic ones (y, p‐c, )

• Distribution belong to “classes”, which are linkedE.g. price (p) & cost (c) distrns in same family, linked thru mark‐up; bridged to output (y)  and profit (distrinsvia quality‐cost function (c) 

• Illustrations : CES, Logit, etc.05/09/2016 Claude Lefèvre's Day 2016 28

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Earlier• “Is the quality of consumer goods too low?”[JIE ~ 2001, Anderson & de Palma]• Asymmetric Bertrand logit oligopoly

• Underlying “ranking” Higher quality‐cost have higher mark‐up and higher equilibrium demand (hence profits)

05/09/2016 Claude Lefèvre's Day 2016 29

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Two simplifying hypothesis

• Monopolistic competition – OK since continuum of firms

• Unidimensional ranking of firms– E.g. 20% most efficient firms are also the 20% most profitable one

05/09/2016 Claude Lefèvre's Day 2016 30

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Our approach : summary

• Cost, prices,  qualities, output are described as distributions.

• We will uncover – the logical links between these distributions– the basic distribution driving the others

• Scope of this research: provide theoretical foundations of empirical distributions?

05/09/2016 Claude Lefèvre's Day 2016 31

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Outline• Mon. competition with cost differences• Recovering demand from economic distribution  

• Demand observed +? : deriving all distributions

• CES, Pareto Circle, breaking the circle  • Mon. competition with q‐c differences• Logit : log‐linear model of mon. comp. • Comparative statics on Distributions• Extensions: long run, generalization…05/09/2016 32Claude Lefèvre's Day 2016

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MONOPOLISTIC COMPETITION WITH COST DIFFERENCES 

05/09/2016 Claude Lefèvre's Day 2016 33

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The demand function

= : price; : quality ; : - marAssumption 1: h . ; . 0, ' . 0, '' exists, 1 -conc

k-up

ave.h

y h p

p c h

h

p mh m cp c m m p c

h

05/09/2016 Claude Lefèvre's Day 2016 34

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Property of the monopolistic competition model with fixed mc

05/09/2016 Claude Lefèvre's Day 2016 35

Theorem 1: Under Assumption 1, there is a unique mark‐up (c)>0, with ’(c)>‐1, log‐convex.’(c)>0, if h(.) is log‐convex’(c)<0, if h(.) is log‐concave Equilibrium demand h*(c)=h((c)+c) is decreasing in c as is profit, with *’(c)=‐h*(c).

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Recover demand functionfrom mark‐ups

05/09/2016 Claude Lefèvre's Day 2016 36

Theorem 2: consider a positive mark‐up, (c), with ’(c)>‐1. Then there exists an equilibrium demand, h*(c), h*’(c)<0, and a demand function, h(.) satisfying Assumption 1.h(.) is :

log‐convex if ’(c)>0log‐concave if ’(c)<0.

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RECOVERING DEMAND FROM ECONOMIC DISTRIBUTION

05/09/2016 Claude Lefèvre's Day 2016 37

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Combining CFD with monotonicity (only for economists!)

05/09/2016 Claude Lefèvre's Day 2016 38

2 1

2 1

X1 1 X2 2

1 2

2 2

2 2

Consider two distributions F and F strictly increasing.

Let X , then

F if g' . 0, and

F

Lemm

1 if

a

g

1

' . 0.

X X

X X

x x

g X

x F g x

x F g x

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Recover demand (and the rest) from cost and price distributions

Theorem 3: There is a continuum of firms with demand satisfying Ass. 1, but not observable. Assume FC and Fp are known. Then demand, mark‐up and  output and profits distributions are recovered (up to a positive multiplicative factor). 

05/09/2016 Claude Lefèvre's Day 2016 39

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Recover demand (and the rest) from output and profit distributions

Theorem 4: There is a continuum of firms with demand satisfying Ass. 1, but not observable. Assume Fy and F are known. Then demand, mark‐up, and cost distributions are recovered (up to a shift factor for the scale of c). 

05/09/2016 Claude Lefèvre's Day 2016 40

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Key relation

Using monotonicity, we have: 

05/09/2016 Claude Lefèvre's Day 2016 41

1

10

1We find:

c .

C Y

z

Y

F c F y F z

F rz c dr

F r

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Recover demand (and the rest) from price and profit distributions

Theorem 5: There is a continuum of firms with demand satisfying Ass. 1, but not observable. Assume FP and F are known. Then demand, mark‐up, and the other distributions are recovered.

05/09/2016 Claude Lefèvre's Day 2016 42

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Recover demand (and the rest) from c&y,c& or p&y

Theorem 6: There is a continuum of firms with demand satisfying Ass. 1, but not observable. Assume {FC, FY} or {FC, F} or {FP,FY} is known.Then, demand, mark‐up, and the other distributions are recovered.

05/09/2016 Claude Lefèvre's Day 2016 43

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DEMAND OBSERVED + ? : DERIVING ALL DISTRIBUTIONS

05/09/2016 Claude Lefèvre's Day 2016 44

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Demand known: 1 distribution suffices!

Theorem 7: There is a continuum of firms with observed demand satisfying Ass. 1. Assume FC or FP or FY or F is known.Then, all the other distributions are recovered.

05/09/2016 Claude Lefèvre's Day 2016 45

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CES PARETO CIRCLE

05/09/2016 Claude Lefèvre's Day 2016 46

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MONOPOLISTIC COMPETITION WITH  COST AND QUALITY DIFFERENTIATION

05/09/2016 Claude Lefèvre's Day 2016 47

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Notation quality‐cost and markup

,

.

: (1) . Equilibrim mark-up is .

This key formula relates demand (.) to mark-up

'

.

i i

i i i

i i i i i i i i

i

x m

i ii

i

h x mm

y h v p

h v p h v c p c h x m

FOC x

h

h x m

x

05/09/2016 Claude Lefèvre's Day 2016 48

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The demand function

A

[most of the time the ^ is dropped]

= ( ) : price;

ssumption 2:

0; ' . 0, '' exists, 1 -concave

Assumption 2':

0; ' . 0, ''

v: qual

exis

ity; : cost

ts, log -co

.

ncave

y

h v p h h

h v p h h

h v p

p c h v p mh x m x v cp c

05/09/2016 Claude Lefèvre's Day 2016 49

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From scale value h(x) toequilibrium mark‐up (x)

Assume Ass 2 holds. Under monopolistic competition there exists a unique >0, ' 1.

Then, equilibrium demand *

is increasing, as is * ,

Theorem 8:

* ' * .

x x

h x h x x

x x h x

05/09/2016 Claude Lefèvre's Day 2016 50

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Monotonicity matters!

Corollary 2If Ass 2 holds: higher quality‐cost (v) are associated with higher output (y) and higher profit (); If Ass 2’ holds: higher v are also have higher mark‐ups ().

05/09/2016 Claude Lefèvre's Day 2016 51

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From equilibrium mark‐up (x) to (equilibrium) demand h(x)

05/09/2016 Claude Lefèvre's Day 2016 52

1

Consider an equilibrium mark-up , ,

' 1. Then the equilibrium demand is given by :

1 'h* =h* exp , , .

Let: . The demand function is:

h h*

Theorem

9

,

:

x

x

x x x x

x

x x

vx x dv x x x

v

u x

x

x x

and obeys Assumption 2.x

Hence, we recover first the maximized value function, then the primitive, on the support for which we have observations. Outside there, we only know it should not be too convex as to violate the observed profit maximum. Note we get Logit for µ’(x) = 0

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Demand known: Two  legs and one bridge

05/09/2016 Claude Lefèvre's Day 2016 53

Assume that demand is known and satisfies A2. If 1 element is known from two of of the following 3 legs, they are all known: ( ) , ,( )( ) strict monotone relation between c a

Theorem 10:

nd x

X Y

C

i F F Fii Fiii

.If ' 0, then can be added to leg (ii),

where x(=v-c)= .Px F

c

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05/09/2016 Claude Lefèvre's Day 2016 54

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05/09/2016 Claude Lefèvre's Day 2016 55

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LOGIT: LOG‐LINEAR MODEL  MONOPOLITIC COMPETITION

05/09/2016 Claude Lefèvre's Day 2016 56

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The exponential h(.) function

0

In this case: exp .

exp, .

exp exp

The total number of consumers is normalized to one (N=1).

i i

i

uh u

v p

y iv p vd

05/09/2016 57Claude Lefèvre's Day 2016

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Discussion

This is the most standard IIA function (along with the CES function).Start‐point in structural empirical IO (BLP)Here used as a  Monopolistic Competition model.

Assume here that the mark‐up  is known.

05/09/2016 58Claude Lefèvre's Day 2016

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Monopolistic competition in non‐symmetric case

i

i

*

Profit: ,

, Monopolistic competition hypothesis

1 0, (Nash)

Equilibrium price: Absolute mark-up (versus Percentage mark-up):, .

Note for oli

i i i

i ii

i

i

i i

i

i

dy yd

p c y i

i

p cd y id

p

p

p c i

*ipololy: as y 1.

1i i ii

p c cy

05/09/2016 59Claude Lefèvre's Day 2016

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Distribution of quality‐cost

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*

Density: Quality-cost

0

* *

Equilibrium output

exp, mass of firms, where:

exp V

V exp 1 .

Equilibrium profits:

x

X Ox

O

v c

y MxM f x dx

v

y

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Comparative statics

PROPOSITION 3 In the Logit model of monopolistic competition, all firms set the same absolute mark‐up. Higher quality firms have higher equilibrium outputs and higher profits

Cf. Melitz: all same % mark‐up in CES 

05/09/2016 61Claude Lefèvre's Day 2016

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LOGIT WITH QUALITY‐COST, OUTPUT AND PROFIT DISTRIBUTION

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X

Y

number and X=Random variable = quality-cost =(V ): ; pdf: f .

Similar definitions for F and F .

exp expOutput : , with ,

D the Logit denomin

X

x CCDF F x x

y

x x

y y yD D

Notations and key relations

000

ator:

, where V =exp 1 .exp VXx x

x f u d vD M u

05/09/2016 63Claude Lefèvre's Day 2016

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Quality‐costOutput and ProfitsPROPOSITION 4 : For the Logit Monopolistic Competition model, the distribution of quality‐costs, FX(x), generates the distribution of equilibrium…

05/09/2016 64Claude Lefèvre's Day 2016

O u t p u t : l n

P r o f i t : l n ,

w h e r e : i s t h e L o g i t d e n o m i n a t o r .

Y X

X

F y F y D

DF F

D

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Output or Profits Quality‐cost

: The quality-cost distribution for the Logit model of Monopolistic Competition, , with V >0 can be generated

from the equilibrium output distribution via the relation:

X O

Y

F x

F y

F

PROPOSITION 4 (cn't)

1

1

exp , D V / 1 .

It can also be generated from the equilibrium profit distribution as:

exp , D V / 1 .

X Y y y O av

X O av

xx F D My

x MF x F D

05/09/2016 65Claude Lefèvre's Day 2016

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COMPARATIVE STATICS ON DISTRIBUTIONS

Equilibrium Properties:

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Increase in quality‐cost

Recall x =v‐c (quality minus cost)PROPOSITION 7 A f.o.s.d increase in x  or a mean preserving spread in x increases mean output and mean profits.

(Strict increase if market not fully covered, i.e. V0 >0)

‐‐ Take more from outside option‐‐ Spread ‐ because exp(x) convex (plays more at top); better firms do much better than worse lose

05/09/2016 67Claude Lefèvre's Day 2016

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Increase taste for variety, µ

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* *i i

: The indirect utility function is ln .More heterogenity, , generates more consumer benefit:

ln

Lemma

P ln P 0 (Shannon measure)

D

d Dd

Ancillary result; note entropy associated to logit (“rational inattention” link)

Not clear a priori that more “noise” makes better off because Type 1 EV isn’t symmetric, and worse (negative) draws make worse off.

Here, more noise is better: expected value of Max goes up  

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Outside good and heterogeneityProposition 8:Higher V0 fosd decreases output and profits.

Higher  fosd increases output and profit, for low xand………fosd deceases output and profit for high x. 

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SPECIFIC DISTRIBUTIONS

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Truncated Pareto distribution

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Let the quality-cost X [ , ) be distributedwith parameter >0. Then the

truncated Pareto truncated General profit, has a

distribution:

1 1 logF

ized Log-Pareto

1

x

x

xx

COROLLARY 2

, , .

where is the mimimum (resp. maximum) profit corresponding to the miniumum (resp. maximum) quality-cost (resp. ).Truncation guarentees that exists.

x xD

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GENERATING THE PARETO DISTRIBUTION FOR PROFIT AND OUTPUT

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Generating empirical Pareto distribution for profit and output

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5 Let F =1- exp(- ( - )), 0, 0, [ , ), with µ>1. Th

x be exponetially distributed:

equilibrium p

en

(1) the 1rofit is Pareto

equilibrium output is Par

;

(2) the diste o rt

X x x xx x x

F

Proposition

ibuted:

1 , y y, , = .

A Pareto distribution for equilibrium output can only be generated by an exponential quality-cost distribution i > . 1f

yyF y y

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Interpretation

• The condition needed to bound D is μ>1/:  taste heterogeneity should be larger than the average quality‐cost.

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Next….

• Free entry equilibrium: how?• Multi‐dimensional cases• Empirical validation,..

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Thank you all for your attention  

thank you Claude for such prolific academic career!

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