Innovation, Demand, and Finance in an Agent-Based Stock-Flow Consistent Model

“Innovation, Demand, and Finance in an AgentBased-Stock Flow Consistent model”

Eugenio [email protected]

Uiversita Politecnica delle Marche

PK Conference, Kansas City

E. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 1 / 14

Let’s give some numbers

I Project financed by the INET

I 3 institutions: (1) Marche Polytechnic University; (2) University ofLimerick; (3) Columbia University.

I 3 researchers: Alessandro Caiani, Antoine Godin, Eugenio CaverzasiI 2 outcomes:

1 The Model: “Innovation, Demand, and Finance in an AgentBased-Stock Flow Consistent model”

2 JMAB


Outline

1 Methodology

2 the Model


AB Macro ModelsAB Macro Models conceive the economy as a complex system in whichmarket dynamics emerge from the interaction of heterogeneousadaptive 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 simpleadaptive individual rules of conduct.

=⇒ Bottom up Macro: continuous interactions between Micro, Meso andMacro levels.



Some Key Concepts:









Some Key Concepts:








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 financial flows arisingout of the transaction respect Copeland’s quadruple entryprinciple.

I The transaction mechanisms further ensures total stock-flowconsistency by updating reserves of banks when modelling a deposittransfer.

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 → theresearcher can browse through all the possible levels of aggregationaccording to his needs.


Outline

1 Methodology

2 the Model


Objectives

I analyze the endogenous emergence of growth, businessfluctuations, and the possible emergence of financial instability.

I analyze innovation dynamics and its impact on the structure ofproduction processes, the evolution of industrial market structures,and the employment dynamics.

I Schumpeterian CompetitionI Capital firms compete by producing equipments entailing different

levels of productivitiesI Consumption firms compete in an homogeneous good market trying to

lower production costs through investment in (new) vintages of capital.


Flow Diagram

Figure : Flow Diagram of the modelE. Caverzasi (Ancona) PK - 2014 Kansas City September the 11th, 2014 8 / 14

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/interestoffered by a randomly chosen subset (parameter χ which proxiesthe degree of imperfect information) of agents on the supply side andthey choose the best one (market specific).

I Markets specific component:I Cheapest: consumption goods market; Labor market; Credit market.I Higher interest rate: deposit market.I Trade off productivity-price: capital goods market.

The probability of switching increases with the difference between theprevious and potential suppliers.


Production planning:

both kind of firms set their desired level of production based on individualsales expectations in order to attain a target level of inventories ν,

yT ,ti = se,t

i (1 + ν)− inv t−1i with i = {c , k} (1)

xet = xe

t−1 + λ(xt−1 − xet−1) (2)

Price setting

Both types of firms fix the price of their output in each period following asimple adaptive rule based on inventories level.

pti =

pt−1i (1 + γFN) if

inv ti

st−1i

≤ ν

pt−1i (1− γFN) if

inv ti

st−1i

> ν(3)

where i = c, k, γ 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).


Consumption firms’ investment:

Inspired by Dosi et al. [2010]: capital firms send a brochure with the priceand the productivity of its manufactured machines to a random sample ofN potential customers.Each consumption firm then compares the brochures received from capitalfirms in order to rank them, given advertised prices and productivity levels.Capital j is preferred to capital i if:

durationK (UC ei − UC e

j ) > ptj − pt

i (4)

UC e,ti =

w e,tk

pr iK lK, UC e,t

j =w e,tk

pr jK lK(5)


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 balancesheets interactions.

I Macroeconomics.

I Consistency.



SFC gains

I Micro Level

I Adaptability

I Network

I Heterogeneity application financial fragility, inequality...

The possibility for a realization crisis is inherent in the chaos ofdecentralized decision making. (There must be heterogeneousagents 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 inthe circuit? Levy Economics Institute, Working Paper, (700), December2011.



SFC gains

I Micro Level

I Adaptability

I Network





[Wray, 2011, p.6]

L. R. Wray. Is there room for bulls, bears, and states inthe circuit? Levy Economics Institute, Working Paper, (700), December2011.



SFC gains

I Micro Level

I Adaptability

I Network





[Wray, 2011, p.6] L. R. Wray. Is there room for bulls, bears, and states inthe circuit? Levy Economics Institute, Working Paper, (700), December2011.


References I

D. Delli Gatti, E. Gaffeo, and M. Gallegati. Complex Agent-BasedMacroeconomics: a Manifesto for a New Paradigm. Journal ofEconomic Interaction and Coordination, 5-2:111–135, 2010.

G. Dosi, G. Fagiolo, and A. Roventini. Schumpeter Meeting Keynes: APolicy-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 Artificial Societies: Social Science fromthe Bottom-Up. MIT Press and Brooking Press, Washington D.C., 1996.

L. Riccetti, A. Russo, and M. Gallegati. An agent-based decentralizedmatching macroeconomic model. Journal of Economic Interaction andCoordination, 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? LevyEconomics Institute, Working Paper, (700), December 2011.


Economy & Finance

Innovation, Demand, and Finance in an Agent-Based Stock-Flow Consistent Model