New Approaches to Environmental Challenges

What do we learn from the long-run evolution of technological systems?

François Lafond

Key points

• There are increasing returns in technology investmentè Do not wait to invest in climate mitigation technologies

• Technologies are interdependentè Support the knowledge base and technologies that fit well the

current era

• Technologies are disruptiveè Anticipate and mitigate negative consequences

There are increasing returns in technology investment

è Do not wait to invest in climate mitigation technologies

Trends are persistent

1900 1950 2000 2050

pric

e in

$/k

Wh

0.01

0.1

1

10

100

0.17$/kWh= 2013 price in $/Wp5c/kWh (~ coal electricity)

coal fuel price for electricity generation ~ 40% of cost

Hinkley Point

US nuclearelectricity

solar photovoltaic modules

0.1

0.51

510

50100

pric

e in

$/W

p

Updated from Farmer and Lafond (2016), Research Policy.

Experience curves for conditional prediction

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MWp of PV modules

PV m

odul

e pr

ice

in 2

016

$/W

p0.05

0.2

0.512

51020

50

1 102 104 106

●●●●●●●●●●± 1 std. dev.

± 1.5 std. dev.± 2 std. dev.

Lafond, François, Aimee Gotway Bailey, Jan David Bakker, Dylan Rebois, Rubina Zadourian, Patrick McSharry, and J. Doyne Farmer. "How well do experience curves predict technological progress? A method for making distributional forecasts." Technological Forecasting and Social Change 128 (2018): 104-117.

What will be the price of solar energy if we decide to produce x more?

But is this really a causal relationship?

“Experience causes cost improvement”

“Lower prices causeincreased demand”

World War II as a natural experiment

Cheaper solar panels

More demand for solar panels

5 50 500 5000

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monthlyproduction

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Willow Run plant, Detroit

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MWp of PV modules

PV m

odul

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in 2

016

$/W

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1 102 104

annualproduction

cumulativeproduction

Cheaper bombers

More demand for bombers

Lafond, Greenwald and Farmer, Does stimulating demand drive costs down? WWII as a natural experiment, in progress

Energy portfolio

• Technologies follow uncertain experience curves • Applied to energy

transition: costs may be lower than business as usual.

Way, Lafond, Lillo, Panchenko & Farmer (2019), Wright meets Markowicz, J. of Econ. Dynamics and Control. Way, Mealy & Farmer, The net cost of green energy transition, in progress. Farmer et al. (2019), Sensitive Intervention points in the post-carbon transition, Science.

solarwind hydro

gas

coalbiomass

nuclear

slow transition scenario in Way et al. (2019, in progress)

Technologies are interdependent

è Support the knowledge base and technologies that fit well the current era

Automobile and

ChemistryTools andinstruments

Machines and Agriculture

Data and networks

1850 1900 1950 2000

• Some groups of technologies reinforce each other

• Groups of technologies have their golden age where they concentrate most of the activity

• Technological eras: groups of technologies are central at the same time

Technological eras

Asano, Wary, Lafond, Farmer and Beguerrise Díaz, Uncovering technological eras, in progress

Knowledge base of green technologies

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●geo

hydrowind

tidal

solarthermal

pv

nuclear

nuclear engineering

wind motors

hydro turbines

diagnosticdevices

electric digitalprocessing

mechanical powerfrom heat

heatcollectors

heat exchangeapparatus

semi−conductors

• There are clusters of interrelated technologies

• Some technology clusters are overall more isolated than others

• PV, and to some extend wind, rely on digital and semiconductor technologies.

• Green technologies are often found to produce higher spillovers

Schematic depiction of a subset of the technological ecosystem, based on Pichler, Lafond and Farmer, Predicting innovation dynamics in the technological ecosystem, in progressOn spillovers, see Barbieri et al, Dechezlepretre et al

Technologies are disruptive

è Anticipate and mitigate negative consequences

Challenges to labor markets

• Sustainability transition requires the decline of some industries and the rise of others

• But other forces can balance or accentuates this• Automation • Demography Healthcare

ProductionConstruction and Extraction Food

preparation and serving

Office and Administrative

support

Life, Physical & Social Science

Computer, engineering and science

Management

Empirical network of occupational mobility, US 2010-2017. From del Rio-Chanona, R. Maria, Penny Mealy, Mariano Beguerisse-Díaz, Francois Lafond, and J. Doyne Farmer. "Automation and occupational mobility: A data-driven network model." arXiv preprint arXiv:1906.04086 (2019).

Challenges to measurement systems

Intangibles• Computerized

information• Intellectual

property• Economic

Competencies• Etc.e.g. Corrado, Hulten and Sichel (2009)

Natural Capital• Natural assets• Ecosystem services• Pollution• Waste management• Etc.

e.g. https://seea.un.org/

Well-being• Health and

Education• Personal activities• Political voice• Social capital• Security• Inequality• Etc.e.g. Fitoussi, Sen, Stiglitz (2009)

Thanks

Thanks to all my co-authors and the Complexity Economics team (J. Doyne Farmer) at INET Oxfordhttps://www.inet.ox.ac.uk/research/programmes/complexity-economics/

BibliographyAsano, Y., Wary, S., Lafond, F., Farmer J.D. and Beguerrise Díaz, M. (2019), Uncovering technological eras, in

progressBarbieri, N., Marzucchi, A., & Rizzo, U. (2018). Knowledge sources and impacts on subsequent inventions: Do green

technologies differ from non-green ones?. SPRU WP 2018-11.Corrado, C., Hulten, C., and Sichel, D. (2009). Intangible capital and US economic growth. Review of Income and

Wealth 55(3): 661-685.Dechezleprêtre, Antoine, Ralf Martin, and Myra Mohnen. "Knowledge spillovers from clean and dirty

technologies." (2014).

del Rio-Chanona, R. Maria, Penny Mealy, Mariano Beguerisse-Díaz, Francois Lafond, and J. Doyne Farmer (2019), Automation and occupational mobility: A data-driven network model, arXiv preprint arXiv:1906.04086.

Farmer et al. (2019), Sensitive Intervention points in the post-carbon transition, Science.Farmer, J. D., and Lafond, F. (2016), How predictable is technological progress? Research Policy 45, no. 3

(2016): 647-665. Freeman, C., & Soete, L. (1997). The economics of industrial innovation, Routledge.Goldin, I., Koutroumpis, P., Lafond, F. Winkler, J. (2019), Why is productivity slowing down?, Oxford Martin

School working paper.Lafond, F., Bailey, A.G., Bakker, J. D. , Rebois, D., Zadourian, R.. McSharry, P., and Farmer, J. D. (2018) How well

do experience curves predict technological progress? A method for making distributional forecasts. Technological Forecasting and Social Change 128: 104-117.

Lafond, F., Greenwald, D., and Farmer, J.D. (2019) Does stimulating demand drive costs down? WWII as a natural experiment, draft

Pichler, A., Lafond,F. and Farmer, J.D. (2019), Predicting innovation dynamics in the technological ecosystem, in progress

Stearns, P. N. (2018). The industrial revolution in world history. Routledge. Stiglitz, J. E., Sen, A., & Fitoussi, J. P. (2009). Report by the commission on the measurement of economic

performance and social progress.Way, R., Lafond, F., Lillo, F., Panchenko, V., and Farmer, J.D. (2019), Wright meets Markowitz: How standard

portfolio theory changes when assets are technologies following experience curves., Journal of Economic Dynamics and Control 101: 211-238.

Way, R. and Mealy, P. & Farmer, J.D. (2019), The net cost of green energy transition, in progress.

Science Museum refers to the Science Museum in London (visited 2018)Source of undocumented images: Wikimedia commons

Key points

• There are increasing returns in technology investmentè Do not wait to invest in climate mitigation technologies

• Technologies are interdependentè Support the knowledge base and technologies that fit well the

current era

• Technologies are disruptiveè Anticipate and mitigate negative consequences