From d87fa1ea6a8a4c8dcd021a09abafeec5c41d7434 Mon Sep 17 00:00:00 2001 From: Alex Gebben Work Date: Tue, 24 Mar 2026 16:32:42 -0600 Subject: [PATCH] Included regression models of natural gas figures --- REMI_Inputs.r | 25 ++++++++++++++++++++++++- 1 file changed, 24 insertions(+), 1 deletion(-) diff --git a/REMI_Inputs.r b/REMI_Inputs.r index af3cba3..d4e663e 100644 --- a/REMI_Inputs.r +++ b/REMI_Inputs.r @@ -1,5 +1,10 @@ library(tidyverse) +library(scales) library(fixest) +#### +OUTPUT_DIR <- './Results/Tables_and_Figures/' +dir.create(OUTPUT_DIR,recursive=TRUE,showWarnings=FALSE) + ##########################Direct cost estimates 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 @@ -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_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') PRED_DATA <- DATA[1:4,] PRED_DATA$Capacity <- c(640,1280,1280,3680) @@ -104,12 +111,28 @@ ALL_VALUES <- DOLLAR_VALUES ALL_VALUES$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') #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 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