2014.05.19 - OECD-ECLAC Workshop_Session 2_Tomaso CIARLI

Structural change and long run growth:Agent based models of economic development

Tommaso Ciarli1

1SPRU, University of [email protected]

New tools and methods for policy makingOECD-ECLAC Workshop

Paris May 19, 2014

Ciarli (SPRU, Sussex) Structural change and long run growth OECD-ECLAC 0 / 22

Introduction

Overview

Economic growth, development, technological change and structural change

Modelling complex systems: Agent Based Models

Modelling structural changes and economic development

Discussion


Introduction Economic development macro regularities

Economic growth and development: technological change

Long term income 1000-2001: huge divergences (Maddison, 2001)

Science and technology (Szirmai, 2005):▶ share of developing countries USPTO patents in 2001: 0.8%▶ R&D as % of GDP (pre 2000): 0.1%-0.7% (OECD 2.1%)

Technological capabilities and GDP per capita (Fagerberg and Srholec, 2010)▶ Various measure of education: positive non linear▶ Research base, advanced training, exploitation of innovation: positive

linear


Introduction Economic development macro regularities

Economic growth and development: structuralchange

Radical change in the share of employment and value added from agricultureto services (Maddison, 1989)

Radical change in the structure of gross domestic expenditure, from food andbasic needs to education, health and leisure (Maddison, 2003)

Product discovery and transition on the product space (Hidalgo andHausmann, 2008a)

⇒ We need to understand how to combine these difference dynamics ofgrowth, development, technological change, and structural change, which aredisequilibrating by definition


Complex evolving systems Properties of a Complex System

Main properties of a Social System

Emergence▶ No given macro dynamics: emerges from lower level interactions

Rationality: micro entities with simple and routinised behaviour (heuristics)

Heterogeneity▶ Structural and behavioural differences▶ Hierarchical organisations (different weights)

Interactions▶ Local (there is a topology)▶ Within and between different levels of aggregation

Time and dynamics▶ Equilibrium is a particular condition▶ Interactions lead to persistent evolution (no Nash equilibria)


Complex evolving systems Properties of a Complex System

Economic models and Complex Evolving Systems

Standard Economic models Complex Evolving Systems

Individuals 1,2 or infinite, fully rational, so-phisticated learning

N large but finite, simple entities,adaptive, routine behaviour

Interactions Extreme cases, trivial patterns(full or empty/star graphs)

Non trivial patterns, local in-teractions with subset of otheragents

Diversity Possibly heterogeneous, but di-versity does not matter for aggre-gate dynamics

Persistently heterogeneous, di-versity matters for aggregate dy-namics

T i m e a n dAggregateDynamics

Static (not truly dynamic) mod-els, only equilibrium states count

Truly dynamic systems, equi-libria possibly irrelevant, meta-stable states and emergent (self-organized) properties


Complex evolving systems Agent based computational economics

A broad definition of ACE

Population of heterogeneous (economic) ‘agents’

Agents live in complex systems evolving through time (Kirman, 1998).True dynamics: non reversible

“Hyper-rationality” not viable (Dosi et al., 1996): internal states, rules ofbehaviour, and adaptive expectations

Agents are autonomous or semi–autonomous

Agents interact with one another and possibly with an environment(local/social interactions)

Endogenous and persistent novelty (technological change): open-ended spaces

Aggregate structure emerges from agent interactions (Tesfatsion, 1997)

Generations of agents emerge from the interactions of their ancestors (selection, retention,innovation 7→ evolution) (Nelson and Winter, 1982a)


Complex evolving systems Agent based computational economics

Structure of ABMTime t = 0, 1, 2, ..., (T ) Discrete

Sets of Agents It = 1, 2, ..., Nt Often Nt = N

Sets of Micro States i→ xi,t Firm’s output

Vectors of Micro-Parameters i→θi Res. Wage

Vector of Macro-Parameters Θ ∈ ℜm Min. Wage

Interaction Structures Gt ∈ ℘(It) Networks

Micro Decision Rules Ri,t(·|·) Innovation rule

Aggregate variables Xt = f(x1,t, ..., xNt,t) GNPSource: Giorgio Fagiolo

A very large number of application in Economics and Business and othersocial sciences .. Check here


Structural change and economic development Introduction

A definition of structural change

Structural change involves many aspects of the economy

“[...] complementary changes in various aspects of the economy, such as the sectorcompositions of output and employment, the organization of industry, the financial system,income and wealth distribution, demography, political institutions, and even the society’svalue system” (Citation omitted, 2008)

“[...] a change in the structure of the economic system, that is, in its components and intheir interactions. Components are [...] particular goods or services, and other activitiesand institutions, such as technologies, types of knowledge, organizational forms etc. Whatdoes it mean for a system to be in equilibrium when its composition keeps changing due tothe emergence of qualitatively different entities? ” (Saviotti and Gaffard, 2008)


Structural change and economic development More Evidence

E.g. the industrial revolution in England

Firm size growth & concentration in large capital intensive firms (Desmet andParente, 2009)

Increase in the number of goods for final consumption (Berg, 2002)

Closer involvement of science in technological change (Mokyr, 2002)

Increased use of capital in agriculture and manufacturing ⇒ technologyembedded in machines ⇒ overall increases in productivity (Kuznets, 1973)

Urbanisation, income inequality and changes in social class composition(McCloskey, 2009)...

Some changes precede income growth, others unfold as a consequence ofincome growth


Structural change and economic development More Evidence

Product variety, demand and economic growth

“Growth and development typically involve the creation of new economicactivities.” (Burgess and Venables, 2004, p. 3)

▶ Product variety relative to the US is correlated with relative per capitaincome (Funke and Ruhwedel, 2001)

▶ Related export variety (within sectors) predicts short run growth (OECD)(Saviotti and Frenken, 2008)

▶ Growth is related to moving to the core of sophisticated products and toexport complexity (Hidalgo and Hausmann, 2009, 2008b; Hidalgo et al.,2007; Felipe et al., 2011)

▶ But also, most economies grow successfully concentrating in a smallnumber of products (sectors) (Hausmann and Rodrik, 2003)


Structural change and economic development Examples of research questions

1. What variety? (Ciarli and Lorentz, 2011)

Qualify (and possibly quantify) the variety-growth thesis▶ How relevant is the dynamics of product innovation for growth? Is the

relation linear?

Which aspect of product innovation is more relevant?▶ firm’s capacity to explore consumer needs / sectors▶ firm’s capacity to improve the quality of goods▶ the frequency at which new products are marketed

Which role for demand: changes in consumer tastes, needs and shares?


Structural change and economic development Examples of research questions

2. Comparing sources of structural change (Ciarli, 2012)

Which aspects of structural change are more relevant (for growth)?

Do the different aspects interact? If yes to which extent?


Structural change and economic development The model (in two slides)

Modelling structural change

(Agent-based) Model of complementary changes in various aspects of thestructure of an economy (Ciarli et al., 2012, 2010)

S–1 Organisation of production [structure of labour and earningsdisparities]

S–2 Technology of production [speed of change in capital innovation, theshare of R&D, and its success]

S–3 Composition of production [exploration of new sectors, quality ofnew products, and share of R&D]

D–1 Income distribution [profits]

D–2 Consumption patterns [change in consumption shares and changesin consumer preferences]

All aspects are interrelated


Structural change and economic development The model (in two slides)

Basic setup

▶ Manufacturing firms: product technology, process technology, labourorganisation, R&D =⇒ product innovation

▶ Capital suppliers: R&D =⇒ capital vintage, labour organisation▶ Consumers: preferences, consumer classes, expenditure shares▶ Wages setting: min wage (macro), labour hierarchies, bonuses

.. Model details


Structural change and economic development Results

Validation

Long term endogenous growth in output with a transition from linear growthto exponential growth (Maddison, 2001; Galor, 2010)

Kuznets curve

S-shaped curve of growth in sectoral output from birth to diffusion

Kaldor-Verdoorn law: output growth and labour productivity growth

Capital deepening

Autocatalytic productivity

Price short run fluctuations



1. What variety? Summary of results

Variety as exploration of new markets/needs, and introduction of new goods,has a significant positive effect on growth

Variety in innovation result (product quality) has a negligible positive effect onOutput

Rate of convergence to expenditure shares concentrated on luxury ‘needs’ hasa negative effect on Output

▶ Demand and Supply distribute across markets ↓ firm concentration▶ ⇒ No time for development (K accumulation) of industry



2. Comparing sources of structural change

Full factorial DOE: scenarios (different countries).

⇒ 210 economies starting from the same initial conditions except for one ofthe aspects of structural change: negligible structural changes VS largestructural changes in all economic aspects

The initial differences that determine growth divergence are those that definethe structure of an economy and the way in which this evolves through time

Different aspects of the structure of an economy: organisation, product,production, consumption, distribution

Interacting aspects

.. Factorial design details



Assessing factors of structural change

Most aspects of structural change are significant determinants of output, butmagnitude varies substantially

▶ 1. Income distribution, 2. rate of change in production technology, 3.Emergence of new sectors, 4. Organisation of production, 5. Consumptionpatterns (barely significant)

Most relevant aspects determine growth irrespective of all other aspects, if theeconomy experiences slow structural change

Most aspects strongly interact

Implications▶ Account for a number of economic aspects to understand long term patterns of

divergence▶ Micro interactions: some aspects may be more relevant for some economies


Wrapping up

Wrapping up

An economy is a complex system with many direct interactions, persistentroutinised behaviour, heterogeneity, disequilibria: we observe an emergingorder

Economic growth and development are characterised by structural changes

Currently a wealth of Agent Based models of growth: from Nelson and Winter(1982b) to Dosi et al. (2013)

A few models of development (adapted to economies facing deep structuralchange)


Wrapping up Discussion

Further contributions of the model

General-to-specific approach to (ABM) modelling▶ Simplify the model: e.g. irrelevant aspects of structural change

Focus on the most relevant aspects and investigate them in depth: e.g. differentaspects of inequality (profit shares, firms organisation, earnings)

Open up research avenues: with no assumptions on the macro behaviour, allemergent properties require an explanations


Wrapping up Discussion

The advantages of ABM

Represent nuanced micro behaviour that depart form perfect rationality

Represent complex interactions between the agents

Analyse the macro dynamics as an emergent properties

Allow for radical uncertainty

Evolutionary dynamics▶ Adaptation▶ Lock-in at the micro and at the macro level


Wrapping up Policy implications

Quantitative scenarios

Build experimental design with policy makers: parameter spaces andcombinations

▶ For example Robust Decision Making (Lempert et al., 2003)▶ Graph visualisations showing scenarios▶ Allow the policy maker to play with parameters and assumption to

visualise different scenarios

Open up the policy options (Stirling and Scoones, 2009): outcomes depend onthe state of the word that the policy maker assumes are correct

Allowing for radical uncertainty▶ The desired outcome is only one of the possible outcomes: minor events

can have unexpected effects


ABM Examples

Some applications in economics and business

▶ Evolutionary-Games: P. Young, Kandori et al., Blume, Ellison▶ (Local) Interaction Models: Kirman, Weisbuch, Lux▶ Endogenous Network Formation: Vega-Redondo, Cowan, Goyal,

Jackson-Watts...)▶ Innovation (Polya-Urn Schemes): Arthur, Dosi, Kaniovski, Lane,

Marengo▶ Complexity: Frenken, Valente, Marengo▶ Strategy and organisations: Carley and Pietrula, Lomi and Larsen▶ Technological modularity, firm and industry organisation: Ethiraj et al.

(2007); Frenken et al. (1999); Kauffman et al. (2000); Marengo and Dosi(2005); Ciarli et al. (2008)


ABM Examples

Some applications in economics and business

▶ Growth: Nelson and Winter (1982a), Silverberg, Verspagen, Dosi,Howitt, Llerena and Lorentz (2004); Dawid and Fagiolo (2008); Dosiet al. (2010); Ciarli et al. (2010); Ciarli (2012); Ciarli et al. (2012); Fagioloand Roventini (2012)

▶ Firms location: David et al. (1998)▶ Firms and technological change: Dawid (2006); Teitelbaum and

Dowlatabadi (2000); Yildizoglu (2002)▶ Markets: Axtell, Epstein, Tesfatsion, Kirman and Vriend (2000)▶ Electricity markets: Tesfatsion▶ Sectoral studies: Malerba et al▶ Environmental economics: van den Bergh, Safarzynska, Windrum et al.

(2009a,b)


ABM Examples

Some applications in economics and business▶ Industrial life cycle cycles: Windrum and Birchenhall (2005), Malerba et

al▶ Labour market: Tesfatsion, Fagiolo et al. (2004), Richiardi and

Leombruni▶ Financial markets (a huge number): Delli Gatti et al. (2004), Delli Gatti

and Stiglitz, Cont, econophisycs▶ Macro instability: Bak et al. (1993); Dosi et al. (2006), Weisbuch and

Battiston, Ciarli and Valente (2007)▶ Macro: Howitt, Duffy, Arifovic▶ Firms coalition and network formation: Cowan and Jonard, Ozman,

Page, Huberman, Axtell, Vega-Redondo, Jackson, Watts▶ Foresight: Lempert▶ Other social sciences: Politics (state cooperation, conflict), Sociology,

Anthropology, ...

.. Back to structure


Structural changes

Structural change, economic and social transformations: e.g.

the industrial revolution in England

Firm size growth & concentration in large capital intensive firms (Desmet andParente, 2009)

Increase in the number of goods for final consumption (Berg, 2002)

Closer involvement of science in technological change (Mokyr, 2002)

Increased use of capital in agriculture and manufacturing ⇒ technologyembedded in machines ⇒ overall increases in productivity (Kuznets, 1973)

Urbanisation, income inequality and changes in social class composition(McCloskey, 2009)...

Some changes precede income growth, others unfold as a consequence ofincome growth


The model Supply side

Firm’s output .. Back

Each firm produces one good, satisfying one consumer need (= sector), withprice (ip) and quality (iq).

Output constrained by labour and capital (Leontief PF):

Qt = min{Qd

t ;At−1L1t−1;DKt−1

}At−1 is the labour productivity embedded in K vintages

Price is determined as a fixed mark–up µ on variable costs▶ Firm organisations/size (S-1)▶ Labour productivity (S-2)

Large µ→ Larger bonuses for executives



Factors of production: Labour .. Back

S–1 Organisation of production

Demand for first tier workers L1t adjusts to desired output and productivity.

Higher tiers workers co-ordinate a batch of ν subordinates

L2t = L1

t ν−1

...LΛt = L1

t ν1−Λ

where Λ is the total number of firms’ layers

Large ν → less workers per executive



Factors of production: Capital Stock .. Back

S–2 Production technology

Investment decision of new capital units is unconstrained

ket = (1 + u)Y et

D−Kt−1

u: reserve; 1/D: K intensity.

Investment increases the efficiency of production incorporating new capitalvintages

At =

t∑τ=0

kτ (1− δ)t−τ

Ktaτ

δ: depreciation; aτ : vintage productivity



Factors of production: Capital Stock .. Back

S–2 Production technology

Capital good firms innovate improving the productivity of the suppliedvintages proportionally to profits/sales:

▶ Spend a share ρk of cumulated profits Πg,t to hire R&D engineers

▶ Probability of success: P inng,t = 1− e−ζLE

g,t−1

▶ New vintage’s productivity increase depends on the variance of astochastic variable: εag,t ∼ N(0;σa)

Large ρk → more process innovationLarge ζ → higher prob of successLarge σa → larger change in vintage productivity



Product innovation .. Back

S–3 Product technology

1. Spend a share ρ of non invested profits in R&D: Rf,t

2. Research in a neighbourhood of the current sector/need n, limited byιRf,t

3. Select the sector/need n′ with the largest excess demand Y xn,t

4. Develop a new prototype with stochastic quality qn′,f,t = f(

ϑ1−|n−n′|

)5. Add to the prototypes basket

6. Market a new product with probability f(− θ

∆Yf,t

),

moving to a new sector/need only if competition pressure is lower

Large ρ→ more product innovationLarge ι→ faster change in sectorsLarge ϑ→ larger increase in product quality Large θ→ quicker diffusion ofnew products


The model Income generation & consumption

Income structure .. Back

D–1 Income distribution

A minimum wage wm is negotiated at the macro level

▶ labour market – wage + Beveridge curve (continuous)▶ inflation and productivity (discrete)

Exponential wage structure along the organisational pyramid

w1t = ωwm

t−1

w2t = bw1

t...

wΛt = bΛw1

t .

ω: firm bargain; b: executive multiplier

Executives receive bonuses ψl from residual profit shares (1− ρ)

Large b → higher wage differencesCiarli (SPRU, Sussex) Structural change and long run growth OECD-ECLAC 32 / 22


Income classes and evolution of consumption .. Back

D–2 Consumption shares

Consumption level differ by labour/income class.

Each class z is populated by the workers of a corporation’s tier (identical wageand bonus)

Consumers in a class also consume according to the same expenditureshares and preferences.

Expenditure shares cn,z change across classes: satiation

cn,z = cn,z−1 (1− η (cn,z−1 − c̄n))

c̄n: an asymptotic value; η convergence (satiation) speed▶ We assume a need = a consumption category

Large η→ faster convergence to luxury goods



Change in consumption shares

1 2 3 4 5 6 7 8 9 100

0.05

0.1

0.15

0.2

0.25

0.3

0.35

Need n

Expe

nditu

re s

hare

s c n,

z Asymptitic sharesHouseholds class z=1


Implicit Engel curves: evolution of consumption shares

Change in consumption share for η = 3 and ten consumer classes. In themodel consumption classes emerge endogenously .Init


Consumer behaviour .. Back

For each need, given the perceived characteristics of a goodi∗fn,m = N

(ifn,m, σ

iifn,m)

(quality and price), a consumer selects all thefirms that offer a good with equivalent values and shares the demand

i∗fn,m ≡ i∗Bn,m ⇔ |i∗fn,m − i∗B,m| < (1− υz,m) · i∗B,m

υz,m: tolerance level

The tolerance with respect to less–then–optimal quality on each characteristicdefines consumer class preferences.

From low to high income classes the tolerance towards good’s quality reduces,and price becomes relatively indifferent

Total purchases close the model: firms sales.

Large υz,m → larger preference differences across classes



Experimental design2k full factorial design: analysis of k factors at two levels (High and Low),simulating all possible combinations (Montgomery, 2001; Kleijnen et al., 2005)

▶ identify the factors that are more influential▶ study a large number of interactions of different orders between factors▶ minimise the number of simulation runs

Analyse the 10 factors defining the initial structure and the scale ofstructural changes through time: extreme values

⇒ yijlt observations▶ i factor responses: output and other modal variables (Inequality, Productivity,

Concentration, Prices,...)▶ j designs: 1024▶ l replicates: 20▶ t periods: 2000

.. Back



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2014.05.19 - OECD-ECLAC Workshop_Session 2_Tomaso CIARLI