# Schelling Model

## Schelling Model of Housing Segregation

https://ees4760.jgilligan.org/models/class_24/segregation.nlogo

## Model Overview

• Turtles represent households.
• Two colors of turtles: red and blue
• Turtles have one state-variable: happy? (true or false)
• There is a global variable %-similar-wanted and a turtle is happy? if at least this fraction of its neighbors have the same color as its own.
• At each tick, unhappy turtles move to a random empty patch.
• When all turtles are happy?, the model stops.

# Experiments

## Experiments

Vary %-similar-wanted and the density of turtles on the patches.

## Suggestions:

• Try extreme values of parameters:
• Set density and %-similar-wanted to different combinations near maximum, minimum, and in the middle.
• What do you see?

## Extreme Values

• Set density to 75% and set %-similar-wanted to 95%
• Press setup and then press go
• What happens?
• Now, with go still pushed, slowly reduce %-similar-wanted.
• Now what happens?

## Systematic experiment:

• Using Behaviorspace, create a new experiment to vary %-similar-wanted
• Set _time limit to 1000
• Set density to 75
• Measure percent-similar
• What do you see?
• Try adjusting both %-similar-wanted and _density

## Visualizing Structures

• Add the following to the procedure to update-turtles, after set happy?

ifelse happy? [ set shape "square" ] [ set shape "square-x" ]
• Repeat the exercise of:
• set density = 75% and %-similar-wanted = 95%,
• press _setup and go
• Is it easier to see the emerging patterns now?

# Heuristics

## Another Heuristic

• When you’re at an interesting value for one parameter (e.g., %-similar-wanted = 75%), vary other paremters (density).

## Other heuristics:

• Use several currencies to evaluate models
• Statistical analysis of spatial patterns and time-series
• Analyze agent properties: Are they unimodal or multimodal (e.g., are turtles divided into distinct groups of rich/poor, healthy/sick, etc., or distributed continuously around one dominant value of state variables?)
• Stability: Does system return quickly to steady state after it’s disturbed?
• Simplify models:
• Make all patches the same
• Make all turtles the same
• Reduce places where you use stochasticity
• Use fewer turtles and patches
• Explore unrealistic scenarios
• See book for heuristics for statistical analysis of model output…