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Added more data, made graph and reg

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Alex Gebben Work 2026-03-04 17:20:31 -07:00
parent ea6fe16b04
commit 6187a3bffa
2 changed files with 56 additions and 14 deletions
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4
Employment_Est.r Normal file
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@ -0,0 +1,4 @@
AVG_VALUE <- (0.15 +0.20)/2
YEARLY_CAPACITY <- c(256,750,1000,1500)
NUM_OPERATING_STAFF <- round(AVG_VALUE*YEARLY_CAPACITY)
NUM_OPERATING_STAFF

66
Scale.r
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@ -1,5 +1,7 @@
library(tidyverse) library(tidyverse)
library(fixest) library(fixest)
NAMES <- c("Trumbull Energy Center","Orange County Advanced Power Station","Shady Hills Combined Cycle Facility","Cumberland (TN)","Kingston","Lincoln Land Energy Center","Delta Blues Advanced Power Station","Homer","Vicksburg","Cheyenne Prairie","Legend and Lone Star","Wolf Summit Energy","Franklin Farms","Viola Generating Station","CPV Basin Ranch Energy Center","Smarr Combined Cycle Energy Facility","Waterford 5 & 6","Lake Charles","Jefferson Power Station")
CAP <- c(308.7*2+360, CAP <- c(308.7*2+360,
453*2+400, 453*2+400,
612, 612,
@ -8,23 +10,59 @@ CAP <- c(308.7*2+360,
638.4*2, 638.4*2,
477+341.7, 477+341.7,
4678, 4678,
819.4) 819.4,
132,
754+453,
600,
1560,
705,
1490,
1425,
1640,
994,
754
)
NAMES <- c("Trumbull Energy Center","Orange County Advanced Power Station","Shady Hills Combined Cycle Facility","Cumberland (TN)","Kingston","Lincoln Land Energy Center","Delta Blues Advanced Power Station","Homer","Vicksburg") DETAILED_REPORT <- c(1,1,1,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0)
EMP <- c(25,27,12.5,30,NA,34,21,250,21) EMP <- c(25,27,12.5,30,NA,34,21,250,21,12,73,30,44,30,45,30,30,30,22)
PEAK_CONST <- c(920,NA,600,NA,300,500,300,2500,560) PEAK_CONST <- c(920,NA,600,NA,300,500,300,2500,560,400,NA,400,(1500+1800)/2,500,1000,1200,700,1100,NA)
DATE <- c(2017,2018,2018,2022,2015,2020,2024,2025,NA) DATE <- c(2017,2018,2018,2022,2015,2020,2024,2025,2025,2012,2024,2025,2024,2024,2026,2026,2025,2020,2025)
DATA <- cbind(CAP,EMP,PEAK_CONST,DATE) %>% as.matrix %>% as_tibble DATA <- cbind(CAP,EMP,PEAK_CONST,DETAILED_REPORT,DATE) %>% as.matrix %>% as_tibble
DATA$NAMES <- NAMES DATA$NAMES <- NAMES
DATA
colnames(DATA ) <- c("Capacity","Emp","Peak_Const","Report_Year","Plant") colnames(DATA ) <- c("Capacity","Emp","Peak_Const","Report_Quality","Report_Year","Plant")
feols(log(Emp)~log(Capacity),DATA %>% filter(Plant!='Homer')) REG_DATA <-DATA %>% select(Emp,Capacity,Report_Quality,Report_Year)
feols(log(Emp)~log(Capacity),DATA %>% filter(Plant!='Homer')) REG_DATA_TRIMMED <-DATA %>% filter(Plant!='Homer') %>% select(Emp,Capacity,Report_Quality,Report_Year)
DATA
feols(log(Emp)~log(Capacity),DATA) MOD1 <- feols(log(Emp)~Capacity+Report_Quality+Report_Year,REG_DATA,vcov='hetero')
feols(log(Emp)~Capacity+Report_Quality+Report_Year,REG_DATA,vcov='hetero')
feols(log(Peak_Const)~log(Capacity)+Report_Year,DATA) PRED_DATA <- DATA[1:4,]
plot(CAP,PEAK_CONST) PRED_DATA$Capacity <- c(250,750,1000,1500)
PRED_DATA$Report_Year <- 2026
PRED_DATA$Plant <- 'Enyo'
PRED_DATA$Emp<- NA
round(exp(predict(MOD1,newdata=PRED_DATA)))
#PRED_DATA$Capacity<- c(640,1280,1280,3680) #Larger number includes the single cyle turbines that look to be turned off most of the time
round(exp(predict(MOD1,newdata=PRED_DATA)))
ggplot(REG_DATA,aes(x=Capacity,y=log(Emp)))+geom_point()+geom_smooth(method='lm')
#feols(log(Emp)~Capacity+Report_Quality+Report_Year,REG_DATA_TRIMMED,vcov='hetero')
feols(Peak_Const~Capacity+Report_Year ,DATA,vcov='hetero')
DATA
feols(Peak_Const~Capacity+Report_Year+Report_Quality,DATA,vcov='hetero')
MOD1 <- feols(log(Emp)~Capacity,REG_DATA,vcov='hetero')
MOD1
PRED_DATA <- DATA[1:4,]
b