24 lines
1.5 KiB
R
24 lines
1.5 KiB
R
#Takes the added jobs table and downshift for people living outside of Kemmerer but in Lincoln
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#DF <- OPERATOR_MIGRATION
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#MIN_LOCAL=0.85
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#MAX_LOCAL=1
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LOCAL_WORK_ADJ <- function(DF,MIN_LOCAL,MAX_LOCAL=1){
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DF <- runif(1,MIN_LOCAL,MAX_LOCAL)*DF#Random range people choosing to live outside of Kemmerer assumed to be between 85% and 100%
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DF <-round(DF)
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return(DF)
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}
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#Find the expected total of new induced jobs from TerraPower (Includes construction entering and leaving, and operators entering)
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INDUCED_SIMULATION <- function(CONSTRUCTION_MIGRATION,OPERATOR_MIGRATION,INDUCED_MIGRATION_TABLE){
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ADDED_FROM_BASELINE <- runif(1) #The percentage of the possible growth in industries like restaurants to add compared to the Kemmerer IMPLAN model which understates possible structural growth
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EST_CONST_INDUCED <- round(CONSTRUCTION_MIGRATION* as.numeric(INDUCED_MIGRATION_TABLE[INDUCED_MIGRATION_TABLE$Job_Type=="Construction",2]+ADDED_FROM_BASELINE *INDUCED_MIGRATION_TABLE[INDUCED_MIGRATION_TABLE$Job_Type=="Construction",3]))
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EST_CONST_INDUCED[7] <- EST_CONST_INDUCED[7]-sum(EST_CONST_INDUCED) #Make sure the sums are still zero after rounding takes place, if not make the last year make up the difference
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#########Induced migration from operating
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EST_OP_INDUCED <- round(OPERATOR_MIGRATION * as.numeric(INDUCED_MIGRATION_TABLE[INDUCED_MIGRATION_TABLE$Job_Type=="Operator",2]+ADDED_FROM_BASELINE*INDUCED_MIGRATION_TABLE[INDUCED_MIGRATION_TABLE$Job_Type=="Operator",3]))
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INDUCED <- EST_OP_INDUCED +EST_CONST_INDUCED
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return(INDUCED)
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}
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