A New Approach to Social Mobility Models: Simulation as “Reverse Engineering”

A New Approach to Social Mobility Models: Simulation as “Reverse

Engineering”

Edmund Chattoe and Anthony HeathDepartment of Sociology

University of Oxford3 George Street Mews

Oxford OX1 2AAhttp://www.sociology.ox.ac.uk

[email protected]

Plan of the Presentation

• Why are sociologists so hard to convince about simulation?

• What is social mobility?• A description of MOBSIM• Initialising populations with structure: a

simulation puzzle

Sociology and Simulation

• Fundamental split: “qualitative” versus “quantitative” approaches

• Qualitative sociologists don’t like simulation because they don’t like any modelling

• What about quantitative sociology?• That shares a view of regularities as social

phenomena not “laws”.

“Real Problems”

• Quantitative sociologists want to study “real” problems:– Lots of data, direct and surrounding– Social institutions (schools, factories) and

social structure (family relations)– Problems set by academic consensus

(tradition) rather than choice

Two Kinds of “Theory”

MACRO MACRO MACRO

Statistical Model World Simulation

MICRO MICRO MICRO?

?

Problems with Statistical Models

• Curve fitting (rather than cross checking at different levels) is not real testing

• “Theories” of micro behaviour compatible with statistical approaches must either be very “tidy” (RCT) or run the risk that the macro behaviour emerging from it not what was anticipated

Reverse Engineering

• “Pick apart” dependent variables and set in order: the problem of “scope”

• Do “normal simulation stuff”: experiments, validation, exploring theory lacunae

• Generate original patterns (and ideally others) thus producing a simulation that is both “relevant” and falsifiable

The Scope of Models

Labour Markets

Demography

Education

??

What is Social Mobility?– Movement between classes over time:

• Inter and intra generational• Relative and absolute mobility

– Motivations for study:• Efficiency• Social Stability• Morality

– Findings• Meritocracy and myth• Comprehensive schools• Considerable constancy of ASM

MOBSIM• A microsimulation with behaviour• Initialised at “1901”• Key Features

– Identities– Classes (equated with jobs)– Education (“epoints”)– Status– “Institutions” and “Biology”– Labour market

Constructive Surprise Example• Models of more than minimal complexity

are falsifiable• People with less education can hold better

jobs• This occurs because even though hiring is

meritocratic, firing is probabilistic• Observers might attribute this to

discrimination• It also suggests new research

Distribution of Education Points By Class

0

0.5

1

1.5

2

2.5

0 200 400 600 800 1000 1200Education Points

Series1

Developing the Model• Endogenising norms• Disaggregating the school sector• Dealing with anachronisms• Disaggregating the labour market• Removing “arbitrary” parameters• Adding material resources• Adding spatial location• Adding social networks

Possible Experiments I: Cultural Shifts

• Homogamy• Women’s labour market participation

and higher education• Divorce• Birth control, demography and genetics• Deliberate policy• Ascription and meritocracy

Possible Experiments II

• Validating Statistical Assumptions– Class Aggregates– Time at Measurement– Transmission through the father

• “Exogenous” Factors– War– Sectoral Change and International Adjustment

The Problem of Structured Populations I

• Three kinds of structure– No structure: agents with separable attributes

initialised randomly– Some structure: microsimulations in which

attributes like “number of children” matter– Detailed structure: social mobility, attributes

like “my father” matter• Again an unremarked feature of these

models

The Problem of Structured Populations II

Pseudo Histories Pseudo Parents

TWO POSSIBLE SOLUTIONS

The Problem of Structured Populations III

• Pseudo Histories– Consistency of pseudo history distributions

with actual run distributions– Problem of “linking” pseudo histories to each

other• Pseudo Parents

– Hard to generate stable populations– Large “overhead” of lead time and boom and

slump in initial pseudo population

The Problem of Structured Populations IV

• Should we worry that this problem has never come up before?

• Just how much structure is plausible for real social systems?

What is Microsimulation?

• Agents and attributes• Environment and different updating rules• Initialisation

A New Approach to Social Mobility Models: Simulation as “Reverse Engineering”

Education

Transcript of A New Approach to Social Mobility Models: Simulation as “Reverse Engineering”