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US MIGRATION From 1990 to 2011 By Travis Goldade.

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Presentation on theme: "US MIGRATION From 1990 to 2011 By Travis Goldade."— Presentation transcript:

1 US MIGRATION From 1990 to 2011 By Travis Goldade

2 OUTLINE Brief Overview Past Studies World US Small discussion my plan

3 OVERVIEW Common field Economics, Demography, Resource Management… Many models yet many not widely accepted Most Widely accepted Economical Push & Pull Factors Push Political instability, War, Famine Pull Economics, Population, Cultural, Sociological

4 WORLD MIGRATION

5 From the start All of Africa was populated by 150 thousand Yrs

6 WORLD MIGRATION From the start Moved in Mid East 100 thousand Yrs

7 WORLD MIGRATION From the start Settled Europe 40 thousand Yrs

8 WORLD MIGRATION From the start Bearing Land Crossing ~20 thousand Yrs

9 WORLD MIGRATION From the start Polynesia wasn’t settled till ~1000 A.D. Reason For Migration: Invasions Famine Climate Change Survival

10 WORLD MIGRATION Age of Exploration ~1600 to 1800 First major Migration of people for social needs (Printing Press) Reason For Migration: Religious persecution Nationalism Slave Trade Freedom

11 WORLD MIGRATION Industrial/Modern Migration ~1800 to Today Better Transportation (steam engine) Reason For Migration: Labor Migration (international) Refugees (political & warfare) Urbanization (Internal) Money & War

12 WORLD MIGRATION Trends Migration Follows Change Climatic, Resource Based People had to move to live Renascence Social Revolution Moved for Freedom Industrial Revolution Moved for Money Political Shocks (fall of USSR) It is Accelerating More people are moving 16 th -18 th century 200 thousand people moved to America 19 th century over 50 Million people moved to America People move more for Economic reasons today Product of Globilzation

13 WORLD MIGRATION LITERATURE

14 Two Studies with Complex Network Studied from 1960 – 2000 Used Global Migration Data Base (GMD) Not at all a complete data set only tracks citizen changes Both  Studied from 1960 – 2000  Treated countries As Nodes  Links = number of migrants Key Difference  Use of Network Metrics  i.e. distance, GDP, Linguistic & Social Ties  One used them independently  Other combined metrics Both had very similar results

15 WORLD MIGRATION LITERATURE Combined Results 1960 - 47% of countries were connected 2000 - 62% of the countries were connected Increasing Connections Decrease in Path Length & Increase Clustering Coeff 1960 - length.66 CC.74 2000 – length. 62 CC.76

16 WORLD MIGRATION LITERATURE Combined Results 1960 - 47% of countries were connected 2000 - 62% of the countries were connected Increasing Connections Decrease in Path Length & Increase Clustering Coeff 1960 - length.66 CC.74 2000 – length. 62 CC.76 Random non assortative Network There were hubs (US, Germany ect) Geographic distances limited direct routs Graph of nearest neighbors degree Suggests a random network Gravity Model Applied F= flow G= const D= Distance M=Economic Mass

17 WORLD MIGRATION LITERATURE Combined Results Random non assortative Network There were hubs (US, Germany ect) Geographic distances limited direct routs Graph of nearest neighbors degree Suggests a random network Gravity Model Applied F= flow G= const D= Distance M=Economic Mass Power Law Applies K= undirected connections btw neighbors (cluster) S = Weight of Link

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20 WORLD MIGRATION LITERATURE Things effecting mutual migration + = Common Language = Common Religion x= population

21 WORLD MIGRATION LITERATURE The second study was very similar Only real difference is they combined multiple metrics Language, Religion, Economic power ect They combined these in a 5 point metric Referenced in a book I could not access Log(N) =3.38 in 2000 Log(N) =1.36 in 2000

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23 WORLD MIGRATION LITERATURE

24 Conclusions 1960 – Only Taiwan and Belize had no immigrants 2000 – Every county is has immigrants Strongly Connected Graph People are moving directly to migration sinks The migration paths are creating links, & becoming more direct Most common is North to North & South to South migrations South to North is becoming more common Eating into South to South Hubs include Germany, USA, England Small world behavior is being observed (globalization) Over time Larger Communities Less of them Result of Migrations corridors combining NOT geographically bound Smaller degree countries are becoming more connected

25 MODERN US INTERNAL MIGRATION

26 MODERN US MIGRATION Trends Flow from East to West Economic & Social based People move for leisure Educated young males most likely Not vey well studied Influx migration strong indicator of healthy economy Pull Factors High Employment Larger Populations (Urbanization) Housing Push Factors High Taxes Crime Unemployment… Good Economic times Ordered people go where the jobs are Bad Economic times Chaotic

27 MODERN US MIGRATION LITERATURE Very little has been done Majority are Economic Studies Nothing has been done for Complex Network analyses Majority are study of population increase/decrease Not looking where they are going Practically Nothing about where people go during economic hardship Summery of Results 90’s 2007 Net out flow of people to the sunbelt seeking cheaper homes Pop is more mobile during good times & stagnate during recessions Largest Pulling factors were Housing & Economic factors Population inflow is a strong economic indicator, however outflow is not a weak one Important is % net flux in Only major Pushing factor was Tax rates (government)

28 MY PROPOSAL I will be tracing the migration of people from county to county With data from IRS Migration data They have records of where people are moving from each county from 1990 -2011 I would like to see if any patterns arise In particular I would like to see if there relationship btw net migration and political affiliation during different times This data might not be straight forward

29 SUMMATION Complex Analysis has rarely been applied to migration Historically people move following change & Survival World Scale People are moving to Economic Hubs They move more out of Necessity US Scale People move for leisure Typically follow housing prices & job opportunities Poorly understood People tend to follow money Strong Economic Indicator I propose Map county by county map of the US from 1990 to 2011 Look for patterns Particularly Political Patterns

30 QUESTIONS


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