Skip to main content
zenodoopen

FUME projection data

<p># FUME data</p> <p>Population data and migration flows from FUME projections</p> <p>## Update 1.0.0</p> <p>Major corrections of the projections</p> <p>## Update 0.3.0</p> <p>- Corrected error in No Migration scenario data</p> <p>- Added IGC (Intensifying Global Competition) scenario</p> <p>- Updated scenario names</p> <p>## Update 0.2.0</p> <p>Updated input rates</p> <p>## Introduction</p> <p>International projection model with dimensions Age, Sex, Education and Country of Birth.</p> <p>Projected from 2015 to 2050, four different scenarios; Benchmark, Ukraine War, Recovery in Europe and Rise of the East. Additional scenario with no migration also included.</p> <p>Benchmark scenario: Identical to SSP2 from Koch &amp; Leimbach (2022), including COVID<br> shock but not Ukraine war.</p> <p>Ukraine War (previously called Short-War) scenario: Same as the benchmark scenario but we use the latest IMF GDP estimates till the year 2027 which include the Ukraine war. Afterwards, a linear transition over 1 years back to SSP2 growth rates is implemented. Exception: Ukraine is estimated to have a 35% decrease in GDP in 2022 and the IMF does not provide estimates for the following year. Using a linear transition to SSP2 growth rates till 2028 would reduce Ukraines GDP very<br> drastically. Instead we assume that in 2023 Ukraine has another 17.5% GDP&nbsp; decrease and in 2024 the growth is zero. Afterwards (2025&nbsp; and ongoing), we estimate Ukraine to again follow the SSP2 growth rates.</p> <p>Recovery in Europe (Scenario B): The same as the Ukraine War scenario till 2027 but afterwards European countries will transition towards the SSP with highest growth rates and developing countries will transition towards the SSP with lowest growth rates. All other countries will transition towards SSP2.</p> <p>Rise of the East (Scenario C): The same as the Ukraine War scenario till 2027 but afterwards developing countries will transition towards the SSP with highest growth rates and European countries will transition towards the SSP with lowest growth rates. All other countries will transition towards SSP2.</p> <p>IGC (Intensifying Global Competition): The same as the Ukraine War scenario till 2027 but afterwards every country with a projected GDPc less than 15000$ in 2040 will linearly transition to 15000$ in 2040 and afterwards keep on growing with SSP2 growth rates. All countries with a GDPc higher than 15000$ will behave the same as in the short-war scenario. This &ldquo;catch-up&rdquo; behaviour of poorer countries is inspired by the &ldquo;CAP&rdquo; and &ldquo;FAIR&rdquo; GDP scenarios in Bodirsky et al., 2022.</p> <p>No Migration: Same as Benchmark scenario but with no international migration.</p> <p>## Variables</p> <p>### Population data</p> <p>period: Start year of projection step</p> <p>dest: Country of residency / Migration destination country</p> <p>CoB: Country of Birth</p> <p>area: ISO3 numeric country code of destination</p> <p>age: Age, five year groups, 0 - 100+</p> <p>edu: Education, 6 levels, (e1 = No Education, e2 = Some Primary, e3 = Primary, e4 = Lower Secondary, e5 = Upper<br> Secondary, e6 = Post Secondary)</p> <p>sex: Sex, two categories</p> <p>pop: Population</p> <p><br> ### Migration rate data specific variable names</p> <p>POB: Place Of Birth (Country of Birth)</p> <p>Orig: Country of origin</p> <p>Dest: Country of destination</p> <p>flow: Migration rate</p> <p>Skill: Skill categories, (Low (Secondary and Less) and High (Post secondary+))</p> <p>age: Age groups (1 (0-24), 2 (25-64), 3 (65+))</p> <p>flowM: Male specific migration rate</p> <p>flowF: Female specific migration rate</p> <p>## Countries</p> <p>Countries currently included in the model are in total 171 (given in ISO3 country codes):</p> <p>```<br> &quot;AFG&quot; &quot;AUT&quot; &quot;BEL&quot; &quot;BGR&quot; &quot;CYP&quot; &quot;CZE&quot; &quot;DEU&quot; &quot;DNK&quot; &quot;ESP&quot; &quot;EST&quot; &quot;FIN&quot; &quot;FRA&quot; &quot;GBR&quot;<br> &quot;GRC&quot; &quot;HRV&quot; &quot;HUN&quot; &quot;IRL&quot; &quot;ITA&quot; &quot;LTU&quot; &quot;LUX&quot; &quot;LVA&quot; &quot;MLT&quot; &quot;NLD&quot; &quot;POL&quot; &quot;PRT&quot; &quot;ROU&quot;<br> &quot;SVK&quot; &quot;SVN&quot; &quot;SWE&quot; &quot;AGO&quot; &quot;ALB&quot; &quot;ARE&quot; &quot;ARG&quot; &quot;ARM&quot; &quot;AUS&quot; &quot;AZE&quot; &quot;BDI&quot; &quot;BEN&quot; &quot;BFA&quot;<br> &quot;BGD&quot; &quot;BHR&quot; &quot;BHS&quot; &quot;BIH&quot; &quot;BLR&quot; &quot;BLZ&quot; &quot;BOL&quot; &quot;BRA&quot; &quot;BTN&quot; &quot;BWA&quot; &quot;CAF&quot; &quot;CAN&quot; &quot;CHE&quot;<br> &quot;CHL&quot; &quot;CHN&quot; &quot;CIV&quot; &quot;CMR&quot; &quot;COD&quot; &quot;COG&quot; &quot;COL&quot; &quot;COM&quot; &quot;CPV&quot; &quot;CRI&quot; &quot;CUB&quot; &quot;DOM&quot; &quot;DZA&quot;<br> &quot;ECU&quot; &quot;EGY&quot; &quot;ETH&quot; &quot;FJI&quot; &quot;GAB&quot; &quot;GEO&quot; &quot;GHA&quot; &quot;GIN&quot; &quot;GMB&quot; &quot;GNB&quot; &quot;GNQ&quot; &quot;GTM&quot; &quot;GUY&quot;<br> &quot;HKG&quot; &quot;HND&quot; &quot;HTI&quot; &quot;IDN&quot; &quot;IND&quot; &quot;IRN&quot; &quot;IRQ&quot; &quot;ISL&quot; &quot;ISR&quot; &quot;JAM&quot; &quot;JOR&quot; &quot;JPN&quot; &quot;KAZ&quot;<br> &quot;KEN&quot; &quot;KGZ&quot; &quot;KHM&quot; &quot;KOR&quot; &quot;KWT&quot; &quot;LAO&quot; &quot;LBN&quot; &quot;LBR&quot; &quot;LCA&quot; &quot;LKA&quot; &quot;LSO&quot; &quot;MAC&quot; &quot;MAR&quot;<br> &quot;MDA&quot; &quot;MDG&quot; &quot;MDV&quot; &quot;MEX&quot; &quot;MKD&quot; &quot;MLI&quot; &quot;MMR&quot; &quot;MNE&quot; &quot;MNG&quot; &quot;MOZ&quot; &quot;MUS&quot; &quot;MWI&quot; &quot;MYS&quot;<br> &quot;NAM&quot; &quot;NER&quot; &quot;NGA&quot; &quot;NIC&quot; &quot;NOR&quot; &quot;NPL&quot; &quot;NZL&quot; &quot;OMN&quot; &quot;PAK&quot; &quot;PAN&quot; &quot;PER&quot; &quot;PHL&quot; &quot;PRI&quot;<br> &quot;PRY&quot; &quot;PSE&quot; &quot;QAT&quot; &quot;RUS&quot; &quot;RWA&quot; &quot;SAU&quot; &quot;SDN&quot; &quot;SEN&quot; &quot;SGP&quot; &quot;SLB&quot; &quot;SLE&quot; &quot;SLV&quot; &quot;SOM&quot;<br> &quot;SRB&quot; &quot;STP&quot; &quot;SUR&quot; &quot;SWZ&quot; &quot;SYR&quot; &quot;TCD&quot; &quot;TGO&quot; &quot;THA&quot; &quot;TJK&quot; &quot;TKM&quot; &quot;TLS&quot; &quot;TTO&quot; &quot;TUN&quot;<br> &quot;TUR&quot; &quot;TZA&quot; &quot;UGA&quot; &quot;UKR&quot; &quot;URY&quot; &quot;USA&quot; &quot;VCT&quot; &quot;VEN&quot; &quot;VNM&quot; &quot;VUT&quot; &quot;WSM&quot; &quot;YEM&quot; &quot;ZAF&quot;<br> &quot;ZMB&quot; &quot;ZWE&quot;<br> ```</p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
8

Dataset details

Repository
zenodo
Published
August 30, 2022
License
cc-by-4.0
DOI
10.5281/zenodo.7033061

Scored with release 0.9.0

ScienceDex for faculty

Your academic CV and NIH biosketch

Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.