what economists are learning from chess€¦ · e.g.‘kids who learn chess are more...

What Economists Are Learning From Chess

David Smerdond.smerdon@uq.edu.au

London Chess Conference, December 2018

December 6, 2018 0 / 23

Outline

1 Motivation

2 Economics In Two Minutes

3 Case Study: Gender and competitiveness

4 The Future: Why economists and chess educators should worktogether

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Motivation

Girls’ chess is booming in Kenya

...So why do they drop out after high school?

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A Global PuzzleRatings data suggests this is a global issue.

(Source: de Sousa & Hollard, 2018)December 6, 2018 3 / 23

Why Could This Be?

A possible explanation: Family duties. But this is not the whole story...

What about Competitiveness?

Nature: Males are biologically more competitive

Nurture: Girls are discouraged from competing, and/or learn todislike competition

Interesting and important question for chess educators andpolicy-makers. But why would economists care?

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Interlude: Economics in 2 Minutes

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Interlude: Economics in 2 Minutes

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Macroeconomics:

Primarily concerned with National Economies

Topics:

Output (GDP)

Inflation

Unemployment

Terms like:

Fiscal Policy, Monetary Policy, International Trade,Central Banks, Keynesian, Classical/Free Markets, ‘Chicago School’,Quantitative Easing, Business Cycles, Recessions. . .

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Macroeconomics:

Primarily concerned with National Economies

Topics:

Output (GDP)

Inflation

Unemployment

Terms like: Fiscal Policy, Monetary Policy, International Trade,Central Banks, Keynesian, Classical/Free Markets, ‘Chicago School’,Quantitative Easing, Business Cycles, Recessions. . .

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Microeconomics:

→ Most economists work here!

Primarily concerned with individuals, and in particular:

How do people make decisions to do the best they can with theirlimited resources?

For example:

Should I work more hours, or less?

Should I go to university or study a trade?

Should I take the bus to work today?

Should we have a(nother) baby?

Should I get private health insurance?

I have $50 for the supermarket. What should I buy?

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Microeconomics:

→ Most economists work here!

Primarily concerned with individuals, and in particular:

How do people make decisions to do the best they can with theirlimited resources?

For example:

Should I work more hours, or less?

Should I go to university or study a trade?

Should I take the bus to work today?

Should we have a(nother) baby?

Should I get private health insurance?

I have $50 for the supermarket. What should I buy?

December 6, 2018 7 / 23

Microeconomics: Some popular fields

Behavioural economics (psychology)

Game theory (Strategic interactions)

Labour economics

Health economics

Education economics

Development economics (topics in developing countries, e.g.poverty)

Environmental economics (e.g. climate change)

In particular with Applied microeconometrics, economists are veryconcerned with identifying causality, not correlation or ‘somethingelse’.

E.g. ‘Kids who learn chess are more intelligent’ versus ‘Learning chessmakes kids more intelligent’.

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Microeconomics: Some popular fields

Behavioural economics (psychology)

Game theory (Strategic interactions)

Labour economics

Applied microeconometrics (‘Does X cause Y?’)

In particular with Applied microeconometrics, economists are veryconcerned with identifying causality, not correlation or ‘somethingelse’.

E.g. ‘Kids who learn chess are more intelligent’ versus ‘Learning chessmakes kids more intelligent’.

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Case Study: Gender and Competitiveness

This is a very important topic in economics.

It is at the heart of important policy questions such as:

Should we have affirmative action entrance policies or quotas foruniversities and the workplace?

How do we encourage more women to enter and stay in theworkforce?

What are the effects of changing maternity laws?

Why are girls dropping out of STEM fields after secondary school?

What would happen if we had more female politicians?

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Case Study: Gender and Competitiveness

This is a very important topic in economics.

It is at the heart of important policy questions such as:

Should we have affirmative action entrance policies or quotas foruniversities and the workplace?

How do we encourage more women to enter and stay in theworkforce?

What are the effects of changing maternity laws?

Why are girls dropping out of STEM fields after secondary school?

What would happen if we had more female politicians?

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Economics Experiments

Women are more competitive in matriarchal societies (evidence fornurture?)

Women are less likely to apply for leadership positions in anenvironment with a high male/female ratio

Women perform worse in cognitive tasks when told it is amale-favouring skill (stereotype threat)

Female tennis players commit more unforced errors on big pointsthan males

Experiments can shed some light on the mechanisms, but are theresults externally valid?

→ A lack of good, ‘natural’ field data.

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The Difficulties of Gender Research

Three main challenges to empirical analysis:

Problem 1: Hard to find good quality data forgender/competition situations

Problem 2: Hard to rule out ‘selection’: the idea that differenttypes of men/women choose which job, university course etc. toundertake

Problem 3: Hard to measure innate ability in the data

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Why Chess Data?

Very high quality chess data (‘panel’ tracks individuals over a longperiod of time; structured and organised)

A competitive, cognitive domain

Males and females compete against each other (rare in sports data)

Performance is exclusively due to effort and abilityI We can use ELO ratings!

Global sample can break up players by types of countries,expertise, age, gender etc.

Pairings in chess tournaments are ‘exogenous’ (i.e. outside of thecontrol of the players)

I This helps rule out ‘selection effects’

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Gender, Competition and Chess

Three recent papers:

Backus, Cubel, Guid, Sanchez-Pages & Manas (2018, submitted):

Gender, Competition and Performance: Evidence From RealTournaments

Stafford (2018, Psychological Science):

Female Chess Players Outperform Expectations When Playing Men

de Sousa & Hollard (2018, submitted):

Gender Differences: Evidence from Field Tournaments

More details

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Gender, Competition and Chess

Three recent papers:

Backus, Cubel, Guid, Sanchez-Pages & Manas (2018, submitted):

Gender, Competition and Performance: Evidence From RealTournaments

Stafford (2018, Psychological Science):

Female Chess Players Outperform Expectations When Playing Men

de Sousa & Hollard (2018, submitted):

Gender Differences: Evidence from Field Tournaments

More details

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Sources of Data

FIDE ratings data (Stafford, 2018)

I ‘92 month’ dataset has 10 million gamesI Need to petition FIDE for access

Chess databases (Megabase, TWIC) with within-game evaluationdata (Backus et al., 2018; Guid & Bratko, 2011)

I 40 moves per game gives hundreds of millions of observationsI Requires someone with technical/computing skills

Online databases: lichess.org

I Massive database (half a billion games) for free!I Limited biographical data of players

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Sources of Data

FIDE ratings data (Stafford, 2018)I ‘92 month’ dataset has 10 million gamesI Need to petition FIDE for access

Chess databases (Megabase, TWIC) with within-game evaluationdata (Backus et al., 2018; Guid & Bratko, 2011)

I 40 moves per game gives hundreds of millions of observationsI Requires someone with technical/computing skills

Online databases: lichess.orgI Massive database (half a billion games) for free!I Limited biographical data of players

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The Future: Why economists and chess industryshould work together

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The Economic Way of Thinking:

1 Develop theoretical models of behaviour, and especially modellingwhich mechanisms affect how people make choices and react tochanges

I Which mechanisms of chess education are most beneficial? Forwhich outcomes? And for which types of children?

2 Apply sophisticated statistical techniques to real data in order totest the predictions and forecast changes

I Do female quotas in chess leagues boost women’s participation andperformance?

3 Use to results to propose improvements to policies and practices

I Designing scalable interventions with randomised controlledtrials (RCTs).

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The Economic Way of Thinking:

1 Develop theoretical models of behaviour, and especially modellingwhich mechanisms affect how people make choices and react tochanges

I Which mechanisms of chess education are most beneficial? Forwhich outcomes? And for which types of children?

2 Apply sophisticated statistical techniques to real data in order totest the predictions and forecast changes

I Do female quotas in chess leagues boost women’s participation andperformance?

3 Use to results to propose improvements to policies and practicesI Designing scalable interventions with randomised controlled

trials (RCTs).

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RCTs

These days, economists love RCTs, especially when they cananswer an empirically challenging and policy-relevant question

To run an RCT, the researcher needs at a minimum:

1 An intervention2 A randomised treatment group and control group (Can be a

delayed treatment group!)3 Good measures of outcomes4 Baseline (pre-intervention) data and exit (post-intervention) data

F Surveys are good; standardised administrative data are even better!

RCTs are great ways for researchers and chess industry to partner

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RCTs

These days, economists love RCTs, especially when they cananswer an empirically challenging and policy-relevant question

To run an RCT, the researcher needs at a minimum:

1 An intervention2 A randomised treatment group and control group (Can be a

delayed treatment group!)3 Good measures of outcomes4 Baseline (pre-intervention) data and exit (post-intervention) data

F Surveys are good; standardised administrative data are even better!

RCTs are great ways for researchers and chess industry to partner

December 6, 2018 17 / 23

RCTs

These days, economists love RCTs, especially when they cananswer an empirically challenging and policy-relevant question

To run an RCT, the researcher needs at a minimum:

1 An intervention2 A randomised treatment group and control group (Can be a

delayed treatment group!)3 Good measures of outcomes4 Baseline (pre-intervention) data and exit (post-intervention) data

F Surveys are good; standardised administrative data are even better!

RCTs are great ways for researchers and chess industry to partner

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Tips For Working With Applied Economists

Be very clear about making your objectives and expectationsknown at the start

Be flexible to changing minor programme details (‘treatments’) toaccommodate their research question

Be prepared for strange requests! Methodology can be complex

Understand that they will always want a bigger sample

Let the researchers know what are your delivery ‘levers’ (i.e.mechanisms) that won’t affect your overall programme (as well asthose that will!)

Be open-minded to their data-driven findings. They can besurprising and helpful to improving your programme. Ask themhow!

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Tips For Working With Industry

Be very clear about making your objectives and expectationsknown at the start

Don’t over-promise. Be realistic in terms of what you can answer,but do be salient to cost/benefits in framing your discussions

Be flexible in responding to commercial interests/demands withoutcompromising your research agenda

Think about publishing early: Set goals, communicate them, andstick to them. However. . .

. . . Be prepared to continue your partnership beyond youracademic objectives, with non-academic outputs

Be open-minded to their experience and anecdotal insights. Theycan be invaluable to improving your research and generating newideas. Ask them how!

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Symbiosis

Benefits for the ResearchersIdeal testing environment for competition, gender, skill mobility etc.

Excellent data (also secondary data)

Benefits for the EducatorsQuality impact evaluation from scientific research boosts validity, profile

Gain insights into mechanisms beyond the holistic benefits of the wholeprogramme

I Understanding the education ‘production function’ can boost profits

Benefits to BothJoint profile offers increased chances to attract funding

Many research Qs don’t require tangible changes/compromises toprogramme delivery

Partnerships strengthen link between research and practice.

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Symbiosis

Benefits for the ResearchersIdeal testing environment for competition, gender, skill mobility etc.

Excellent data (also secondary data)

Benefits for the EducatorsQuality impact evaluation from scientific research boosts validity, profile

Gain insights into mechanisms beyond the holistic benefits of the wholeprogramme

I Understanding the education ‘production function’ can boost profits

Benefits to BothJoint profile offers increased chances to attract funding

Many research Qs don’t require tangible changes/compromises toprogramme delivery

Partnerships strengthen link between research and practice.

December 6, 2018 20 / 23

Symbiosis

Benefits for the ResearchersIdeal testing environment for competition, gender, skill mobility etc.

Excellent data (also secondary data)

Benefits for the EducatorsQuality impact evaluation from scientific research boosts validity, profile

Gain insights into mechanisms beyond the holistic benefits of the wholeprogramme

I Understanding the education ‘production function’ can boost profits

Benefits to BothJoint profile offers increased chances to attract funding

Many research Qs don’t require tangible changes/compromises toprogramme delivery

Partnerships strengthen link between research and practice.

December 6, 2018 20 / 23

Symbiosis

Benefits for the ResearchersIdeal testing environment for competition, gender, skill mobility etc.

Excellent data (also secondary data)

Benefits for the EducatorsQuality impact evaluation from scientific research boosts validity, profile

Gain insights into mechanisms beyond the holistic benefits of the wholeprogramme

I Understanding the education ‘production function’ can boost profits

Benefits to BothJoint profile offers increased chances to attract funding

Many research Qs don’t require tangible changes/compromises toprogramme delivery

Partnerships strengthen link between research and practice.

December 6, 2018 20 / 23

Finally: Some (academic) ideas

How do gender quotas affect participation and performance ofgirls?

What is the effect of online education innovation on genderparticipation rates?

How do peer effects influence the gender gap in competitiveness?

How do cognitive games affect children’s aspirations and goals indeveloping countries?

Which mechanisms of chess education are most important forcognitive and non-cognitive skill development?

What are the effects of chess on entrepreneurial skills?

And one more...

Does gender equality in a country affect the chess genderparticipation ratio?

(Ideas)

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Thank you.

d.smerdon@uq.edu.au

dsmerdon.wordpress.com

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Appendix 1: Gender and Competitiveness Chess Papers

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Gender, Competition and Chess

Three recent papers:

Backus, Cubel, Guid, Sanchez-Pages & Manas (2018, submitted):

Gender, Competition and Performance: Evidence From RealTournaments

Stafford (2018, Psychological Science):

Female Chess Players Outperform Expectations When Playing Men

de Sousa & Hollard (2018, submitted):

Gender Differences: Evidence from Field Tournaments

December 6, 2018 22 / 23

Gender, Competition and Chess

Three recent papers:

Backus, Cubel, Guid, Sanchez-Pages & Manas (2018, submitted):

Gender, Competition and Performance: Evidence From RealTournaments

Stafford (2018, Psychological Science):

Female Chess Players Outperform Expectations When Playing Men

de Sousa & Hollard (2018, submitted):

Gender Differences: Evidence from Field Tournaments

December 6, 2018 21 / 23

Backus et al. (2018) Women suffer a cognitive ‘stereotype threat’when paired with a man. Men become more competitivewhen paired with a woman.

Stafford (2018) Men suffer a cognitive ‘stereotype threat’ when pairedwith a woman. Women have more experience in FMgames than men (compare with: ‘Southpaw’ boxer effect)

de Sousa & Hollard, 2018 Women suffer when competing against men.Women who are the most sensitive to the gendercompetition effect stop competing and drop out.

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Backus et al., 2018

Data The Week In Chess games from 2012-13.ELO over 2000; Active; Played with both genders(N = 30, 000).Broken into three subsamples: MM (male vs male games),MF and FF

Method Innovative feature is quality of play measure, taken fromthe evaluation error of the played move to the engine’sbest move

Results Women play worse when they play against menMen play the same against either gender (controlling forELO)

Explanations Women suffer a cognitive ‘stereotype threat’ when pairedwith a man.Men become more competitive when paired with awoman.

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Stafford, 2018

Data All FIDE-rated games from 2008-2015.All active players, all ratings (over 5 million games!).Broken into MM, MF and FF

Method Focus on expected performance

Results Women perform BETTER when they play against men!Men perform WORSE against women

Explanations Men suffer a cognitive ‘stereotype threat’ when pairedwith a woman.Women have more experience in FM games than men(compare with: ‘Southpaw’ boxer effect)

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Appendix 2: Gender Ratios By Country

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Which Countries Have High Ratios?

How would you expect the chess participation ratio between male andfemale players to be in these countries:

Denmark

Sweden

Norway

England

Germany

Ecuador

China

United Arab Emirates

Sri Lanka

Georgia

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Which Countries Have High Ratios?

By gender equality score:

Norway

Germany

Sweden

Denmark

England

UAE

Georgia

Sri Lanka

China

Ecuador

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Which Countries Have High Ratios?

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Which Countries Have High Ratios?

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Which Countries Have High Ratios?

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Which Countries Have High Ratios?

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Which Countries Have High Ratios?

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Which Countries Have High Ratios?

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Which Countries Have High Ratios?

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Which Countries Have High Ratios?

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Which Countries Have High Ratios?

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Which Countries Have High Ratios?

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Which Countries Have High Ratios?

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Which Countries Have High Ratios?

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Which Countries Have High Ratios?

By gender equality score:

Norway

Germany

Sweden

Denmark

England

UAE

Georgia

Sri Lanka

China

Ecuador

By chess gender ratio:

China

Georgia

UAE

Sri Lanka

Ecuador

Germany

England

Norway

Sweden

Denmark

Back

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