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Included regression models of natural gas figures

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Alex Gebben Work 2026-03-24 16:32:42 -06:00
parent 86c9c7a6fa
commit d87fa1ea6a
1 changed files with 24 additions and 1 deletions
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REMI_Inputs.r
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@ -1,5 +1,10 @@
library(tidyverse) library(tidyverse)
library(scales)
library(fixest) library(fixest)
####
OUTPUT_DIR <- './Results/Tables_and_Figures/'
dir.create(OUTPUT_DIR,recursive=TRUE,showWarnings=FALSE)
##########################Direct cost estimates ##########################Direct cost estimates
TOTAL_COMPUTER_CAPITAL_INVEST <- 1156875000/10^6 #Total "Computer" capital cost in terms of millions of dollars TOTAL_COMPUTER_CAPITAL_INVEST <- 1156875000/10^6 #Total "Computer" capital cost in terms of millions of dollars
#Split of spending at data centers https://jlarc.virginia.gov/pdfs/reports/Rpt598.pdf #Split of spending at data centers https://jlarc.virginia.gov/pdfs/reports/Rpt598.pdf
@ -89,6 +94,8 @@ colnames(DATA ) <- c("Capacity","Emp","Peak_Const","Report_Quality","Report_Year
REG_DATA <-DATA %>% select(Emp,Capacity,Report_Quality,Report_Year) REG_DATA <-DATA %>% select(Emp,Capacity,Report_Quality,Report_Year)
REG_DATA_TRIMMED <-DATA %>% filter(Plant!='Homer') %>% select(Emp,Capacity,Report_Quality,Report_Year) REG_DATA_TRIMMED <-DATA %>% filter(Plant!='Homer') %>% select(Emp,Capacity,Report_Quality,Report_Year)
MOD1 <- feols(log(Emp)~Capacity+Report_Quality+Report_Year,REG_DATA,vcov='hetero') MOD1 <- feols(log(Emp)~Capacity+Report_Quality+Report_Year,REG_DATA,vcov='hetero')
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')
PRED_DATA <- DATA[1:4,] PRED_DATA <- DATA[1:4,]
PRED_DATA$Capacity <- c(640,1280,1280,3680) PRED_DATA$Capacity <- c(640,1280,1280,3680)
@ -104,12 +111,28 @@ ALL_VALUES <- DOLLAR_VALUES
ALL_VALUES$POWER_OPERATORS <- POWER_OPERATORS ALL_VALUES$POWER_OPERATORS <- POWER_OPERATORS
#ggplot(REG_DATA,aes(x=Capacity,y=log(Emp)))+geom_point()+geom_smooth(method='lm') OP_PLOT <- ggplot(REG_DATA,aes(x=Capacity,y=log(Emp)))+geom_point()+geom_smooth(method='lm',color="orange")+theme_bw()+ylab("Operating Employment (Natural Log)" )+scale_x_continuous(breaks=seq(0,5000,by=200),labels = scales::comma)+scale_y_continuous(breaks=seq(0,7,by=0.25))+theme(text=element_text(size=16))
CONST_PLOT <- ggplot(DATA,aes(x=Capacity,y=Peak_Const))+geom_point()+geom_smooth(method='lm')+theme_bw()+ylab("Peak Construction Employment" )+scale_x_continuous(breaks=seq(0,5000,by=200),labels = scales::comma)+scale_y_continuous(breaks=seq(0,20000,by=200),labels = scales::comma)+theme(text=element_text(size=16))
png(paste0(OUTPUT_DIR,"Operating_Employment_Fit.png" ) , units = "in", width = 1.25*12, height = 1.25*8, res = 600)
OP_PLOT
dev.off()
png(paste0(OUTPUT_DIR,"Peak_Construction_Employment_Fit.png" ) , units = "in", width = 1.25*12, height = 1.25*8, res = 600)
CONST_PLOT
dev.off()
MOD2 <- feols(Peak_Const~Capacity+Report_Year+Report_Quality,DATA,vcov='hetero') MOD2 <- feols(Peak_Const~Capacity+Report_Year+Report_Quality,DATA,vcov='hetero')
#ggplot(DATA,aes(x=Capacity,y=Peak_Const))+geom_point()+geom_smooth(method='lm') #ggplot(DATA,aes(x=Capacity,y=Peak_Const))+geom_point()+geom_smooth(method='lm')
DICT <- c("log(Emp)"="Operating Employment (ln)",Peak_Const="Peak Construction Employment",Report_Quality='Government Source',Report_Year='Data Year',Capacity='Capacity (MW)' )
NOTES <- c("Data found for natural gas power plants listed in EIA860 fillings as planned.","Data Year: is the date a report was released","Government Source: is a dummy variable that is one if the source of data came from a government filing and not a company report.")
etable(MOD1,MOD2,style.tex=style.tex(yesNo="$\\checkmark$"),dict=DICT,notes=NOTES,file=paste0(OUTPUT_DIR,"Reg.tex") ,export=paste0(OUTPUT_DIR,"Reg.png"),replace=TRUE,tpt=TRUE,adjustbox=TRUE,order="!Constant")
###Construction Data ###Construction Data
CONST_SCHEDULE_HISTORIC <- c(45,75,90,115,175,235,285,350,400,350,255,175,95,65) #Employment by month in the most recent 2011 Wyoming application for a generator (See one drive data) CONST_SCHEDULE_HISTORIC <- c(45,75,90,115,175,235,285,350,400,350,255,175,95,65) #Employment by month in the most recent 2011 Wyoming application for a generator (See one drive data)
PEAK_CONST_EMP_HISTORIC <- 400 #Historic peak employment rate PEAK_CONST_EMP_HISTORIC <- 400 #Historic peak employment rate