Stock Flow Consistent Modeling session at 12th International Conference

1. Innovation, Demand, and Finance in an Agent
Based-Stock Flow Consistent model"
Eugenio Caverzasi
e.caverzasi@univpm.it
Uiversita Politecnica delle Marche
PK Conference, Kansas City
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 1 / 14

2. Let's give some numbers
I Project

3. nanced by the INET
I 3 institutions: (1) Marche Polytechnic University; (2) University of
Limerick; (3) Columbia University.
I 3 researchers: Alessandro Caiani, Antoine Godin, Eugenio Caverzasi
I 2 outcomes:
1 The Model: Innovation, Demand, and Finance in an Agent
Based-Stock Flow Consistent model
2 JMAB
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 2 / 14

4. Outline
1 Methodology
2 the Model
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 3 / 14

5. AB Macro Models
AB Macro Models conceive the economy as a complex system in which
market dynamics emerge from the interaction of heterogeneous
adaptive agent [see Epstein and Axtell, 1996, Tesfatsion and Judd, 2006,
Delli Gatti et al., 2010].
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 4 / 14

6. AB Macro Models
AB Macro Models conceive the economy as a complex system in which
market dynamics emerge from the interaction of heterogeneous
adaptive agent [see Epstein and Axtell, 1996, Tesfatsion and Judd, 2006,
Delli Gatti et al., 2010].
Some Key Concepts:
I Heterogeneity: may be ex ante (endowment, behavioural rules,
position) and ex post (stochastic component...).
I Interactions: taking place in networks of local interaction.
I Adaptivity: agents adapt their decisions in light of its neighbours'
and aggregate outcome.
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 4 / 14

7. AB Macro Models
AB Macro Models conceive the economy as a complex system in which
market dynamics emerge from the interaction of heterogeneous
adaptive agent [see Epstein and Axtell, 1996, Tesfatsion and Judd, 2006,
Delli Gatti et al., 2010].
Some Key Concepts:
I Heterogeneity: may be ex ante (endowment, behavioural rules,
position) and ex post (stochastic component...).
I Interactions: taking place in networks of local interaction.
I Adaptivity: agents adapt their decisions in light of its neighbours'
and aggregate outcome.
) Complexity in economics.
I Emergence: arising of orderly aggregate structures from simple
adaptive individual rules of conduct.
=) Bottom up Macro: continuous interactions between Micro, Meso and
Macro levels.
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 4 / 14

8. Implementing SFC
The SFC is ensured the transaction mechanism:
I Each agent is endowed with a Balance Sheet matrix with two columns
(assets vs liabilities)
I The transaction mechanism make sure that all

9. nancial
ows arising
out of the transaction respect Copeland's quadruple entry
principle.
I The transaction mechanisms further ensures total stock-
ow
consistency by updating reserves of banks when modelling a deposit
transfer.
What we get:
I dynamic network of agents' balance sheets evolving through time !
network and fragility analysis
I We obtain a fully scalable view of models dynamics ! the
researcher can browse through all the possible levels of aggregation
according to his needs.
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 5 / 14

10. Outline
1 Methodology
2 the Model
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 6 / 14

11. Objectives
I analyze the endogenous emergence of growth, business
uctuations, and the possible emergence of

12. nancial instability.
I analyze innovation dynamics and its impact on the structure of
production processes, the evolution of industrial market structures,
and the employment dynamics.
I Schumpeterian Competition
I Capital

13. rms compete by producing equipments entailing dierent
levels of productivities
I Consumption

14. rms compete in an homogeneous good market trying to
lower production costs through investment in (new) vintages of capital.
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 7 / 14

15. Flow Diagram
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 8 / 14

16. Matching mechanisms on markets
5 markets and 1 matching mechanism
I Common decentralised matching mechanism: [Riccetti et al., 2014]
agents on the demand side of the markets see the price/interest
oered by a randomly chosen subset (parameter c which proxies
the degree of imperfect information) of agents on the supply side and
they choose the best one (market speci

17. c).
I Markets speci

18. c component:
I Cheapest: consumption goods market; Labor market; Credit market.
I Higher interest rate: deposit market.
I Trade o productivity-price: capital goods market.
The probability of switching increases with the dierence between the
previous and potential suppliers.
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 9 / 14

19. Production planning:
both kind of

20. rms set their desired level of production based on individual
sales expectations in order to attain a target level of inventories n,
yT,t
i = se,t
i (1 + n) inv t1
i with i = fc, kg (1)
xe
t = xe
t1 + l(xt1 xe
t1) (2)
Price setting
Both types of

21. rms

22. x the price of their output in each period following a
simple adaptive rule based on inventories level.
pt
i =
8
:
pt1
t
(1 + gFN) if inv i
i st1
i
n
pt1
t
(1 gFN) if inv i
i st1
i
n
(3)
where i = c, k, g is a parameter representing the maximum percentage change of the
price, and NF is a random number picked from a Folded Normal distribution in the
interval (0, 1).
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 10 / 14

23. Consumption

24. rms' investment:
Inspired by Dosi et al. [2010]: capital

25. rms send a brochure with the price
and the productivity of its manufactured machines to a random sample of
N potential customers.
Each consumption

26. rm then compares the brochures received from capital

27. rms in order to rank them, given advertised prices and productivity levels.
Capital j is preferred to capital i if:
durationK (UCe
i UCe
j ) pt
j pt
i (4)
UCe,t
i =
we,t
k
priK
lK
, UCe,t
j =
we,t
k
pr j
KlK
(5)
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 11 / 14

28. Why combining AB and SFC
AB gains
I More realistic monetary system.
I Financial-Real sides interactions.
I New complexity layer ( possibility of tracking complex balance
sheets interactions.
I Macroeconomics.
I Consistency.
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 12 / 14

29. Why combining AB and SFC
SFC gains
I Micro Level
I Adaptability
I Network
I Heterogeneity application

30. nancial fragility, inequality...
The possibility for a realization crisis is inherent in the chaos of
decentralized decision making. (There must be heterogeneous
agents in the circuit!)
We must have heterogeneity of banks and borrowers.
Again, heterogeneity matters.
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 13 / 14

31. Why combining AB and SFC
SFC gains
I Micro Level
I Adaptability
I Network
I Heterogeneity application

32. nancial fragility, inequality...
The possibility for a realization crisis is inherent in the chaos of
decentralized decision making. (There must be heterogeneous
agents in the circuit!)
We must have heterogeneity of banks and borrowers.
Again, heterogeneity matters.
[Wray, 2011, p.6]
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 13 / 14

33. Why combining AB and SFC
SFC gains
I Micro Level
I Adaptability
I Network
I Heterogeneity application

34. nancial fragility, inequality...
The possibility for a realization crisis is inherent in the chaos of
decentralized decision making. (There must be heterogeneous
agents in the circuit!)
We must have heterogeneity of banks and borrowers.
Again, heterogeneity matters.
[Wray, 2011, p.6] L. R. Wray. Is there room for bulls, bears, and states in
the circuit? Levy Economics Institute, Working Paper, (700), December
2011.
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 13 / 14

35. References I
D. Delli Gatti, E. Gaeo, and M. Gallegati. Complex Agent-Based
Macroeconomics: a Manifesto for a New Paradigm. Journal of
Economic Interaction and Coordination, 5-2:111{135, 2010.
G. Dosi, G. Fagiolo, and A. Roventini. Schumpeter Meeting Keynes: A
Policy-Friendly Model of Endogenous Growth and Business Cycles.
Journal of Economic Dynamics and Control, 34(9):1748{1767, 2010.
J. Epstein and R. Axtell. Growing Arti

36. cial Societies: Social Science from
the Bottom-Up. MIT Press and Brooking Press, Washington D.C., 1996.
L. Riccetti, A. Russo, and M. Gallegati. An agent-based decentralized
matching macroeconomic model. Journal of Economic Interaction and
Coordination, Forthcoming, 2014.
L. Tesfatsion and K. Judd. Handbook of Computational Economics.
Volume 2: Agent-Based Computational Economics. North Holland,
Amsterdam., 2006.
L. R. Wray. Is there room for bulls, bears, and states in the circuit? Levy
Economics Institute, Working Paper, (700), December 2011.
E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 14 / 14