69 lines
2.3 KiB
R
69 lines
2.3 KiB
R
library(tidyverse)
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library(fixest)
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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")
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CAP <- c(308.7*2+360,
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453*2+400,
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612,
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454.8+323,
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323,
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638.4*2,
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477+341.7,
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4678,
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819.4,
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132,
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754+453,
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600,
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1560,
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705,
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1490,
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1425,
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1640,
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994,
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754
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)
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DETAILED_REPORT <- c(1,1,1,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0)
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EMP <- c(25,27,12.5,30,NA,34,21,250,21,12,73,30,44,30,45,30,30,30,22)
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PEAK_CONST <- c(920,NA,600,NA,300,500,300,2500,560,400,NA,400,(1500+1800)/2,500,1000,1200,700,1100,NA)
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DATE <- c(2017,2018,2018,2022,2015,2020,2024,2025,2025,2012,2024,2025,2024,2024,2026,2026,2025,2020,2025)
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DATA <- cbind(CAP,EMP,PEAK_CONST,DETAILED_REPORT,DATE) %>% as.matrix %>% as_tibble
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DATA$NAMES <- NAMES
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DATA
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colnames(DATA ) <- c("Capacity","Emp","Peak_Const","Report_Quality","Report_Year","Plant")
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REG_DATA <-DATA %>% select(Emp,Capacity,Report_Quality,Report_Year)
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REG_DATA_TRIMMED <-DATA %>% filter(Plant!='Homer') %>% select(Emp,Capacity,Report_Quality,Report_Year)
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DATA
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MOD1 <- feols(log(Emp)~Capacity+Report_Quality+Report_Year,REG_DATA,vcov='hetero')
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feols(log(Emp)~Capacity+Report_Quality+Report_Year,REG_DATA,vcov='hetero')
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PRED_DATA <- DATA[1:4,]
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PRED_DATA$Capacity <- c(250,750,1000,1500)
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PRED_DATA$Report_Year <- 2026
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PRED_DATA$Plant <- 'Enyo'
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PRED_DATA$Emp<- NA
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round(exp(predict(MOD1,newdata=PRED_DATA)))
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#PRED_DATA$Capacity<- c(640,1280,1280,3680) #Larger number includes the single cyle turbines that look to be turned off most of the time
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round(exp(predict(MOD1,newdata=PRED_DATA)))
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ggplot(REG_DATA,aes(x=Capacity,y=log(Emp)))+geom_point()+geom_smooth(method='lm')
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#feols(log(Emp)~Capacity+Report_Quality+Report_Year,REG_DATA_TRIMMED,vcov='hetero')
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feols(Peak_Const~Capacity+Report_Year ,DATA,vcov='hetero')
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DATA
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feols(Peak_Const~Capacity+Report_Year+Report_Quality,DATA,vcov='hetero')
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MOD1 <- feols(log(Emp)~Capacity,REG_DATA,vcov='hetero')
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MOD1
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PRED_DATA <- DATA[1:4,]
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b
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