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 Sussex
t.ciarli@sussex.ac.uk
New tools and methods for policy making
OECD-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: structural
change
Radical change in the share of employment and value added from agriculture
to services (Maddison, 1989)
Radical change in the structure of gross domestic expenditure, from food and
basic needs to education, health and leisure (Maddison, 2003)
Product discovery and transition on the product space (Hidalgo and
Hausmann, 2008a)
⇒ We need to understand how to combine these difference dynamics of
growth, development, technological change, and structural change, which are
disequilibrating 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 other
agents
Diversity Possibly heterogeneous, but di-
versity does not matter for aggre-
gate dynamics
Persistently heterogeneous, di-
versity matters for aggregate dy-
namics
Time and
Aggregate
Dynamics
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 of
behaviour, 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 → evolution) (Nelson and Winter, 1982a)

Complex evolving systems Agent based computational economics
Structure of ABM
Time 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) GNP
Source: Giorgio Fagiolo

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 sector
compositions of output and employment, the organization of industry, the ﬁnancial system,
income and wealth distribution, demography, political institutions, and even the society’s
value system” (Citation omitted, 2008)
“[...] a change in the structure of the economic system, that is, in its components and in
their interactions. Components are [...] particular goods or services, and other activities
and institutions, such as technologies, types of knowledge, organizational forms etc. What
does it mean for a system to be in equilibrium when its composition keeps changing due to
the 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 and
Parente, 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 ⇒ technology
embedded 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 of
income growth

Structural change and economic development More Evidence
Product variety, demand and economic growth
“Growth and development typically involve the creation of new economic
activities.” (Burgess and Venables, 2004, p. 3)
▶ Product variety relative to the US is correlated with relative per capita
income (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 to
export complexity (Hidalgo and Hausmann, 2009, 2008b; Hidalgo et al.,
2007; Felipe et al., 2011)
▶ But also, most economies grow successfully concentrating in a small
number 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 the
structure of an economy (Ciarli et al., 2012, 2010)
S–1 Organisation of production [structure of labour and earnings
disparities]
S–2 Technology of production [speed of change in capital innovation, the
share of R&D, and its success]
S–3 Composition of production [exploration of new sectors, quality of
new products, and share of R&D]
D–1 Income distribution [proﬁts]
D–2 Consumption patterns [change in consumption shares and changes
in consumer preferences]
All aspects are interrelated

Structural change and economic development The model (in two slides)
Basic setup
▶ Manufacturing ﬁrms: product technology, process technology, labour
organisation, 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 growth
to 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 on
Output
Rate of convergence to expenditure shares concentrated on luxury ‘needs’ has
a 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 of
the aspects of structural change: negligible structural changes VS large
structural changes in all economic aspects
The initial differences that determine growth divergence are those that deﬁne
the 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, but
magnitude varies substantially
▶ 1. Income distribution, 2. rate of change in production technology, 3.
Emergence of new sectors, 4. Organisation of production, 5. Consumption
patterns (barely signiﬁcant)
Most relevant aspects determine growth irrespective of all other aspects, if the
economy 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, persistent
routinised behaviour, heterogeneity, disequilibria: we observe an emerging
order
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 structural
change)

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. different
aspects of inequality (profit shares, firms organisation, earnings)
Open up research avenues: with no assumptions on the macro behaviour, all
emergent 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 and
combinations
▶ 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 on
the 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
▶ Growth: Nelson and Winter (1982a), Silverberg, Verspagen, Dosi,
Howitt, Llerena and Lorentz (2004); Dawid and Fagiolo (2008); Dosi
et al. (2010); Ciarli et al. (2010); Ciarli (2012); Ciarli et al. (2012); Fagiolo
and 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
▶ 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 and
Parente, 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 ⇒ technology
embedded 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 of
income growth

The model Supply side
Firm’s output .. Back
Each ﬁrm produces one good, satisfying one consumer need (= sector), with
price (ip) and quality (iq).
Output constrained by labour and capital (Leontief PF):
Qt = min
{
Qd
t ; At−1L1
t−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 L1
t adjusts to desired output and productivity.
Higher tiers workers co-ordinate a batch of ν subordinates
L2
t = L1
t ν−1
...
LΛ
t = 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
ke
t = (1 + u)
Y e
t
D
− Kt−1
u: reserve; 1/D: K intensity.
Investment increases the efﬁciency of production incorporating new capital
vintages
At =
t∑
τ=0
kτ (1 − δ)t−τ
Kt
aτ
δ: depreciation; aτ : vintage productivity

Factors of production: Capital Stock .. Back
S–2 Production technology
Capital good firms innovate improving the productivity of the supplied
vintages proportionally to profits/sales:
▶ Spend a share ρk of cumulated profits Πg,t to hire R&D engineers
▶ Probability of success: Pinn
g,t = 1 − e−ζLE
g,t−1
▶ New vintage’s productivity increase depends on the variance of a
stochastic variable: εa
g,t ∼ N(0; σa)
Large ρk → more process innovation
Large ζ → higher prob of success
Large 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 by
ιRf,t
3. Select the sector/need n′ with the largest excess demand Y x
n,t
4. Develop a new prototype with stochastic quality qn′,f,t = f
(
ϑ
1−|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 innovation
Large ι → faster change in sectors
Large ϑ → larger increase in product quality Large θ → quicker diffusion of
new 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
w1
t = ωwm
t−1
w2
t = bw1
t
...
wΛ
t = bΛw1
t .
ω: firm bargain; b: executive multiplier
Executives receive bonuses ψl from residual profit shares (1 − ρ)
Large b → higher wage differences

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 wage
and bonus)
Consumers in a class also consume according to the same expenditure
shares and preferences.
Expenditure shares cn,z change across classes: satiation
cn,z = cn,z−1 (1 − η (cn,z−1 − ¯cn))
¯cn: 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 10
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
Need n
Expendituresharesc
n,z Asymptitic shares
Households class z=1

Implicit Engel curves: evolution of consumption shares
Change in consumption share for η = 3 and ten consumer classes. In the
model consumption classes emerge endogenously .Init

Consumer behaviour .. Back
For each need, given the perceived characteristics of a good
i∗
fn,m = N
(
ifn,m, σiifn,m
)
(quality and price), a consumer selects all the
firms 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 characteristic
defines 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 design
2k 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 of
structural 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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