agent based simulation of gentrification

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Post on 24-May-2015

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  • 1. Gentrification Production side Consumption sideexplanationsexplanations Rent-gap theory (N.Smith, Post-industrial shift1979) G. depends on the Predominance of white collarmovement of capital from one workarea of the city to the other inpursuit of higher profit Creative classesUrban development, technological shift, Fashion effects (NY loftdepreciation create localized mismatch living)between current and potential land use

2. This model So far... Implements the rent-gap theory Wishes to Couple economic and cultural/diversity dynamics. Gentrification affects the cultural other than economical identity of places. Embed + compare production and consumptionfactors theoretical synthesis Predict the future! :-) 3. Agent model Income level [0-1] (random) Mobility propensity (Poisson distribution 0.06/year) String culture (n=10) |_|_|_|_|_|_|_|_|_|_| 01001010111011011001 0 1 0 0 0 0 1 0 1 0 Long-time neighbours interact Cultures mix Interaction more likely when common traits exist 4. City model Individual dwelling Condition [0-1] random Price [0-1] = cond + 0.15 Neighbourhood Allure (sticky and approximate) |_|_|_|_|_|_|_|_|_|_| Price-gap: difference between a propertys price and mean price of surrounding properties 5. Parameters Kapital level Number of properties receiving investment eachyear Decay factor Constant monthly decay. Set at 0.0015 Immigration rate Set at 3% per year 6. Economic processes Decay Constant decay (0.0015/step) Empty properties decay 1.5x faster Price is lowered as consequence of decay and ifempty for 6 consecutive months Investment K properties with wider price-gap receive investment Price = mean neighbours price + 15% Condition = 0.95 7. Residential choice process 8. Decision to move Dissonance Poor dwellings Spatial cognitive Prolonged stay indissonance when slum increasesneighbours too mobility propensitydifferent Price increase High dissonanceincreases mobility Price increase putspropensity the agent in seek- new-place mode 9. Results 10. Spatial dynamicsK=10 (2.2%)K=15 (3.5%) K=20 (4.5%)K=25 (5.6%)K=30 (6.8%) K=35 (8%) 11. Population dynamicsK=15Gini = 47; Slum 62% 12. K=25 Population dynamics Neighbourhoods steadily increasing the mean income, while the population decreases and increases in waves, signal gentrification + displacement: the poor go, the richGini = 40; move in.Slum = 30% 13. K=25 Cultural dynamics Cultural uniformity ismaximized in areas whereprices have been stable for along time at a high level Little clustering happens inpoor areas: the "slum" is atransition zone for poorimmigrants, who quickly enterand leave. 14. Population dynamicsK=35 Higher capital = higher prices = lower population Cycles of investment and disinvestment Rat race around the city Reminds of Smiths definition 15. Cultural dynamicsCulture uniforms whenprices are steady forsome time, allowing for residents to stay put cultures mix self-selection of in-movers via allure 16. Future More realistic residential mobility More heterogeneous agents Classes of agents: gentrifiers and non-gentrifiers Population dynamics Actual city land values