what drives markups?p.seppecher.free.fr/jamel/pdf/presentation-afep-20170706.pdf · afep rennes...

What drives markups?Evolutionary pricing in an agent-based,

stock-flow consistent, macroeconomic model

Pascal Seppecher1, Isabelle Salle2, Marc Lavoie1

1Université de Paris 13, CEPN, 2Utrecht University School of Economics

Congrès de l’Association Française d’Economie Politique

Thursday, July 6th, 2017

P. Seppecher, I. Salle, M. Lavoie What drives markups? AFEP Rennes 2017 1 / 29

En guise d’introduction

How markups move, in response to what, and why, is howevernearly terra incognita for macro. . . we are a long way fromhaving either a clear picture or convincing theories, and this isclearly an area where research is urgently needed.

Blanchard (2008) The State of the Macro


Contents

1 ModelA stock-flow consistent agent-based modelA model of collective adaptation

2 SimulationsBaselineTechnological shockBehavioral shock

3 Conclusion


Model

1 ModelA stock-flow consistent agent-based modelA model of collective adaptation

2 Simulations

3 Conclusion


Model A stock-flow consistent agent-based model

Jamel: an agent-based post-Keynesian model

Agent-based:

multiple agents (hundreds of firms, thousands of households —but only one bank),

heterogenous agents, endogenous heterogeneity,

radical decentralisation: no planner, no auctionneer, no access toany macro-information, all interactions are direct and individual.

Post-Keynesian:

procedural rationality,

fundamental uncertainty,

endogenous money,

stock-flow consistency.


Model A stock-flow consistent agent-based model

Structure of real flows

Sector 2(consumption

goods)

Sector 3(investment

goods)

Sector 1(intermediate

goods)

Workers

labor

consumption goods

intermediary goods

investment goods

investment goods

investment goods

labor

labor

Capitalists

consumption goods


Model A model of collective adaptation

Endogenous heterogeneity of behaviors

Dynamic, endogenous heterogeneity, resulting from the action of twosimultaneous opposing forces:

Differentiation, by innovations and errors,

Homogenization, by selection and imitation.



Collective (non-intentional) adaptation

Three mechanisms of collective adaptation:

Short-run: heterogeneity.If the diversity of behaviors is large enough, the set contains theadapted behavior to new conditions.

Medium-run: self-reinforcement.The firms with the adapted behaviors grow faster, thus they gainand play a heavier role in the resulting macro behavior.

Long-run: selection and imitation.Competitive pressures force firms that have an inadequatebehavior to adopt observed successful behaviors or to disappear.



Endogeneisation of the markups ϕ

Heterogenous markups (each firm i has its own markup ϕi ),

The markup of each firm ϕi changes continuously following arandom walk (small random mutations),There are two motives of bankruptcy:

I If the firm becomes insolvent (ie if liabilities > assets),I It the firm loses all its fixed capital.

If a firm i goes bankrupt:I The bank refunds the firm,I The firm gives up its markup,I It adopts a new markup copied on the one of a surviving firm j

ϕi = ϕj



Resolution of the high-margins/market-sharestrade-off

⇒ For each firm, there is a trade-off between high margins andmarket shares;

⇒ This trade-off will be solved collectively, ie by endogenouslyeliminating the markups incompatible with market conditions.


Simulations

1 Model

2 SimulationsBaselineTechnological shockBehavioral shock

3 Conclusion


Simulations Baseline

Baseline Simulation:an Emergent Structure of Markups

(a) Baseline simulation

S1 S2 S3

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,0000

0.1

0.2

0.3

0.4

0.5

(b) 100 replications

0 500 1000 1500 20000.0

0.1

0.2

0.3

0.4

0.5

0.6

period

mark-up (S1) mark-up (S2) mark-up (S3)



Markups Selection & Endogenous Heterogeneity

−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4−0.5

0

0.5

1

Markup

Return

OnAssets

−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4−0.5

0

0.5

1

Markup

Return

OnAssets

−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4−0.5

0

0.5

1

Markup

Return

OnAssets

−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.40

0.05

0.1

0.15

0.2

Markup

Market

shares

(%)

−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.40

0.05

0.1

0.15

0.2

Markup

Market

shares

(%)

−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.40

0.05

0.1

0.15

0.2

Markup

Market

shares

(%)

−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.40

0.05

0.1

0.15

0.2

Markup

Inventories

(%)

−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.40

0.05

0.1

0.15

0.2

Markup

Inventories

(%)

−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.40

0.05

0.1

0.15

0.2

Markup

Inventories

(%)



Stability of Relative Prices(a) Sector 1 to Sector 2

Relative price

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,0000

0.1

0.2

0.3

0.4

0.5

(b) Sector 2 to Sector 3

Relative price

0 500 1,000 1,500 2,0000

0.5

1

1.5

2

2.5

(c) Sector 3 to Sector 1

Relative price

0 500 1,000 1,500 2,0000

0.2

0.4

0.6

0.8

1



Amounts of Labor and ‘Natural Prices’

We calculate l1; l2; l3, which are the amounts of labor, direct, indirect andhyper-indirect, required for the production of one unit of good in eachsector S1;S2;S3.

l1 =1q1

(1+

k1l3u1dk

)(1)

l2 =1q2

(1+

k2l3u2dk

)+ j2l1 (2)

l3 =u3dk

q3u3dk − k3(3)



Relative Prices and Natural Prices(a) Sector 1 to Sector 2

Relative price Natural price

0 500 1,000 1,500 2,0000

0.1

0.2

0.3

0.4

0.5



0 500 1,000 1,500 2,0000

0.5

1

1.5

2

2.5



0 500 1,000 1,500 2,0000

0.2

0.4

0.6

0.8

1


Simulations Technological shock

Technological Shock on Sector 2

What: simulation of a dramatic, exogenous, technological shock;

Where: Sector 2 (consumption goods);

How: productivity goes from 100 to 200;

When: t = 1000.



Macro-Consequences(a) Labor Market

S1 S2 S3

0 500 1,000 1,500 2,0000

50

100

150

200 Shock

(b) Labor Market

Capacity Labor demand Labor Supply Employed

0 500 1,000 1,500 2,0000

2,000

4,000

6,000

8,000

10,000

12,000

14,000 Shock

(c) Workforce Distribution

S1 S2 S3

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000

0.2

0.3

0.4

0.5

0.6

0.7 Shock

(d) Ponzi firms

S1 S2 S3

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,0000

0.2

0.4

0.6

0.8

1 Shock



Relative Prices and Natural Prices(a) Sector 1 to Sector 2


0 500 1,000 1,500 2,0000

0.1

0.2

0.3

0.4

0.5

0.6

0.7 Shock



0 500 1,000 1,500 2,0000

0.5

1

1.5

2

2.5 Shock



0 500 1,000 1,500 2,0000

0.2

0.4

0.6

0.8

1 Shock



Adaptation of markups

(a) Shock on Baseline

S1 S2 S3

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,0000

0.1

0.2

0.3

0.4

0.5

Shock

(b) 100 replications

0 500 1000 1500 2000

0.0

0.1

0.2

0.3

0.4

0.5

0.6

period

shock on productivity in S2

mark-up (S1) mark-up (S2) mark-up (S3)


Simulations Behavioral shock

Behavioral Shock on Sector 2

What: simulation of a dramatic, exogenous, behavioral shock;

Where: Sector 2 (consumption goods);

How: markup goes from approx. 0.2 (on average) to 0.6;

When: t = 1000.



Adaptation of markups

(a) Average markups (weighted by market shares)

S1 S2 S3

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,0000

0.1

0.2

0.3

0.4

0.5

Shock

(b) Average markups (arithmetic)

S1 S2 S3

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,0000

0.1

0.2

0.3

0.4

0.5

Shock



Relative Prices and Values(a) Sector 1 to Sector 2


0 500 1,000 1,500 2,0000

0.1

0.2

0.3

0.4

0.5 Shock



0 500 1,000 1,500 2,0000

0.5

1

1.5

2

2.5 Shock



0 500 1,000 1,500 2,0000

0.2

0.4

0.6

0.8

1

Shock



Deformation of the production structure

(a) Relative capacities of production

1.1 1.2 1.3 1.4 1.5

S2/S1

0.4

0.5

0.6

0.7

0.8

(S1+

S2)/

S3


Conclusion

1 Model

2 Simulations

3 Conclusion


Conclusion

Conclusion (1/4)

Our model is a complex system, it includes several interdependentsectors.

These interdependencies are both real (labor and commodities)and monetary (money and debts).

Thanks to the radical decentralization principle of ABM, and guidedby the observations of Alchian (1950), we simulate theendogenous evolution of individual and aggregate pricingbehaviors under the pressure of competition.


Conclusion

Conclusion (2/4)

As the model includes three industrial sectors, we can observe theemergence of a structure of relative prices.

Relative prices appear to “gravitate” around their “natural prices”,that is, around the ratio of the quantities of labor required for theproduction of the merchandises.

Thus, the system of the “natural prices” dominates the evolution ofthe relative prices (and thus the evolution of the markups, since atthe microeconomic level, markups determine prices).


Conclusion

Conclusion (3/4)

Last but not least, it is worth noting that our model is definitivelyeclectic, featuring ingredients from different and sometimes competingschools of thought.

The model includes the post-Keynesian theory of endogenousmoney and its stock-flow consistent approach;

it includes the concerns of Leontief for industrial interdependence;

it is consistent with the classical idea that industrial prices gravitatetowards values that are roughly proportional with the sum of thedirect and indirect quantities of necessary labor, as can be found inSraffa, Pasinetti and Lee;

it also relies on Simon’s procedural rationality and on Alchian’sevolutionary behavior.


Conclusion

Conclusion (4/4)

Yet, our model is not a chimera. Every ingredient is used because itplays a judicious role in the construction of the model, and results in acoherent synthesis that goes beyond the theoretical borders thatfragment economics. This type of models has then the strongadvantage of (re)activating the dialog and the exchanges betweenparallel and competing schools of thoughts in order to contribute to theemergence of a new, alternative paradigm in (macro)economics.


what drives markups?p.seppecher.free.fr/jamel/pdf/presentation-afep-20170706.pdf · afep rennes...

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