library(tidyverse)
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,
	 453*2+400,
	 612,
	 454.8+323,
	323,
	 638.4*2,
	 477+341.7,
	 4678,
	 819.4,
	 132,
	754+453,
	600,
	1560,
	705,
	1490,
	1425,
	1640,
	994,
	754
)

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,34,21,250,21,12,73,30,44,30,45,30,30,30,22)
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(2017,2018,2018,2022,2015,2020,2024,2025,2025,2012,2024,2025,2024,2024,2026,2026,2025,2020,2025)
DATA <- cbind(CAP,EMP,PEAK_CONST,DETAILED_REPORT,DATE)  %>% as.matrix %>% as_tibble 
DATA$NAMES <- NAMES
DATA

colnames(DATA ) <- c("Capacity","Emp","Peak_Const","Report_Quality","Report_Year","Plant")
REG_DATA <-DATA %>% select(Emp,Capacity,Report_Quality,Report_Year)
REG_DATA_TRIMMED <-DATA %>% filter(Plant!='Homer') %>% select(Emp,Capacity,Report_Quality,Report_Year)
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')
PRED_DATA <- DATA[1:4,]
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,]



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