this is comparison test 3 with minotor fixed effect
# library
library(stargazer)##
## Please cite as:## Hlavac, Marek (2022). stargazer: Well-Formatted Regression and Summary Statistics Tables.## R package version 5.2.3. https://CRAN.R-project.org/package=stargazerlibrary(lmtest)## Loading required package: zoo##
## Attaching package: 'zoo'## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numericlibrary(plm)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:plm':
##
## between, lag, lead## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union## load and rearrange data
test.dat <- load("D:/yang7916/Ozone_Drought_Final.RData/Ozone_Drought_Final.RData")
test.dat <- combinedAir.final
names(combinedAir.final)## [1] "MonitorID" "Longitude" "Latitude"
## [4] "Date..Local." "GEOID" "month"
## [7] "Year" "State.Code" "County.Code"
## [10] "Site.Number" "Parameter.Code" "POC"
## [13] "Parameter.Name" "Day.In.Year..Local." "Exceptional.Data.Type"
## [16] "Observation.Count" "Observation.Percent" "Arithmetic.Mean"
## [19] "First.Maximum.Value" "First.Maximum.Hour" "AQI"
## [22] "State.Name" "County.Name" "Local.Site.Name"
## [25] "Max.Ozone" "USDM.categorical" "spei_12_DR_CAT"
## [28] "eddi_12_DR_CAT" "Urban.2013.full" "ppt"
## [31] "tdmean" "tmean" "elevation"test.dat$USDM.categorical <- factor(test.dat$USDM.categorical, levels = c("NoDrought", "ModerateDrought", "SevereDrought"))
test.dat$USDM.categorical <- relevel(test.dat$USDM.categorical, ref = "NoDrought")
## model 1
md1_random <- plm(Max.Ozone ~USDM.categorical, data = test.dat, model = "random", index = c("MonitorID", "Year","month"))## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")md1_fix <- plm(Max.Ozone ~USDM.categorical, data = test.dat, effect=("twoways"),model = "within", index = c("MonitorID", "Year","month"))## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")stargazer(md1_random, md1_fix, type = "text", title = "Comparison of Random and Fixed Effect Models 1", align = TRUE,
add.lines = list(c("Model Name", "Random Effect Model", "Fixed Effect Model")),
dep.var.labels.include = FALSE)##
## Comparison of Random and Fixed Effect Models 1
## ===================================================================================
## Dependent variable:
## ---------------------------------------------------
## (1) (2)
## -----------------------------------------------------------------------------------
## USDM.categoricalModerateDrought 1.262*** 1.348***
## (0.014) (0.014)
##
## USDM.categoricalSevereDrought 2.529*** 2.921***
## (0.020) (0.021)
##
## Constant 42.415***
## (0.116)
##
## -----------------------------------------------------------------------------------
## Model Name Random Effect Model Fixed Effect Model
## Observations 6,608,332 6,608,332
## R2 0.006 0.003
## Adjusted R2 0.006 0.003
## F Statistic 19,007.910*** 11,454.870*** (df = 2; 6606349)
## ===================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01## model 2
md2_random<- plm(Max.Ozone ~ USDM.categorical +elevation+ Longitude + Latitude,
data=test.dat,
index = c("MonitorID", "Year","month"),
model = ("random"))## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")md2_fix<- plm(Max.Ozone ~ USDM.categorical +elevation+ Longitude + Latitude,
data=test.dat,
index = c("MonitorID", "Year","month"),
effect = "twoway")## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")stargazer(md2_random, md2_fix, type = "text", title = "Comparison of Random and Fixed Effect Models 2", align = TRUE,
add.lines = list(c("Model Name", "Random Effect Model", "Fixed Effect Model")),
dep.var.labels.include = FALSE)##
## Comparison of Random and Fixed Effect Models 2
## ==================================================================================
## Dependent variable:
## --------------------------------------------------
## (1) (2)
## ----------------------------------------------------------------------------------
## USDM.categoricalModerateDrought 1.261*** 1.348***
## (0.014) (0.014)
##
## USDM.categoricalSevereDrought 2.528*** 2.922***
## (0.020) (0.021)
##
## elevation 0.004*** 0.004***
## (0.0002) (0.001)
##
## Longitude 0.044*** -3.812***
## (0.007) (0.928)
##
## Latitude -0.191*** -4.697*
## (0.024) (2.819)
##
## Constant 51.871***
## (1.199)
##
## ----------------------------------------------------------------------------------
## Model Name Random Effect Model Fixed Effect Model
## Observations 6,608,332 6,608,332
## R2 0.006 0.003
## Adjusted R2 0.006 0.003
## F Statistic 19,589.350*** 4,591.235*** (df = 5; 6606346)
## ==================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01## model 3
md3_random <- plm(Max.Ozone ~ USDM.categorical + tmean +
elevation + Longitude + Latitude,
data=test.dat,
index = c("MonitorID", "Year","month"),
model = "random")## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")md3_fix <- plm(Max.Ozone ~ USDM.categorical + tmean+
elevation + Longitude + Latitude,
data=test.dat,
index = c("MonitorID", "Year","month"),
model = "within",
effect = "twoways"
)## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")stargazer(md3_random, md3_fix, type = "text", title = "Comparison of Random and Fixed Effect Models 3", align = TRUE,
add.lines = list(c("Model Name", "Random Effect Model", "Fixed Effect Model")),
dep.var.labels.include = FALSE)##
## Comparison of Random and Fixed Effect Models 3
## ====================================================================================
## Dependent variable:
## ----------------------------------------------------
## (1) (2)
## ------------------------------------------------------------------------------------
## USDM.categoricalModerateDrought 1.138*** 1.213***
## (0.013) (0.013)
##
## USDM.categoricalSevereDrought 1.392*** 1.738***
## (0.019) (0.019)
##
## tmean 0.644*** 0.639***
## (0.001) (0.001)
##
## elevation 0.006*** -0.001
## (0.0002) (0.001)
##
## Longitude 0.050*** -6.629***
## (0.006) (0.861)
##
## Latitude 0.180*** -5.105*
## (0.020) (2.614)
##
## Constant 27.028***
## (0.999)
##
## ------------------------------------------------------------------------------------
## Model Name Random Effect Model Fixed Effect Model
## Observations 6,608,332 6,608,332
## R2 0.147 0.143
## Adjusted R2 0.147 0.142
## F Statistic 1,102,463.000*** 183,286.600*** (df = 6; 6606345)
## ====================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01## model 4
md4_random <- plm(Max.Ozone ~ tmean+elevation + Longitude + Latitude,
data=test.dat,
index = c("MonitorID", "Year","month"),
model = "random")## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")md4_fix <- plm(Max.Ozone ~ tmean+elevation + Longitude + Latitude,
data=test.dat,
index = c("MonitorID", "Year","month"),
model = "within",
effect = "twoways"
)## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")stargazer(md4_random, md4_fix, type = "text", title = "Comparison of Random and Fixed Effect Models 4", align = TRUE,
add.lines = list(c("Model Name", "Random Effect Model", "Fixed Effect Model")),
dep.var.labels.include = FALSE)##
## Comparison of Random and Fixed Effect Models 4
## =================================================================
## Dependent variable:
## ----------------------------------------------------
## (1) (2)
## -----------------------------------------------------------------
## tmean 0.646*** 0.642***
## (0.001) (0.001)
##
## elevation 0.006*** -0.002**
## (0.0002) (0.001)
##
## Longitude 0.040*** -6.478***
## (0.006) (0.861)
##
## Latitude 0.163*** -10.136***
## (0.020) (2.616)
##
## Constant 27.019***
## (1.030)
##
## -----------------------------------------------------------------
## Model Name Random Effect Model Fixed Effect Model
## Observations 6,608,332 6,608,332
## R2 0.145 0.141
## Adjusted R2 0.145 0.141
## F Statistic 1,090,206.000*** 271,194.500*** (df = 4; 6606347)
## =================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01## model 5
md5_random <- plm(Max.Ozone ~ ppt+elevation + Longitude + Latitude,
data=test.dat,
index = c("MonitorID", "Year","month"),
model = "random")## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")md5_fix <- plm(Max.Ozone ~ ppt+elevation + Longitude + Latitude,
data=test.dat,
index = c("MonitorID", "Year","month"),
model = "within",
effect = "twoways"
)## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")stargazer(md5_random, md5_fix, type = "text", title = "Comparison of Random and Fixed Effect Models 5", align = TRUE,
add.lines = list(c("Model Name", "Random Effect Model", "Fixed Effect Model")),
dep.var.labels.include = FALSE)##
## Comparison of Random and Fixed Effect Models 5
## ================================================================
## Dependent variable:
## ---------------------------------------------------
## (1) (2)
## ----------------------------------------------------------------
## ppt -0.230*** -0.228***
## (0.001) (0.001)
##
## elevation 0.004*** 0.002
## (0.0002) (0.001)
##
## Longitude 0.043*** -3.275***
## (0.008) (0.921)
##
## Latitude -0.225*** -12.533***
## (0.025) (2.798)
##
## Constant 54.158***
## (1.241)
##
## ----------------------------------------------------------------
## Model Name Random Effect Model Fixed Effect Model
## Observations 6,608,332 6,608,332
## R2 0.021 0.018
## Adjusted R2 0.021 0.018
## F Statistic 122,290.100*** 30,122.480*** (df = 4; 6606347)
## ================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01## model 6
md6_random <- plm(Max.Ozone ~ tdmean+elevation + Longitude + Latitude,
data=test.dat,
index = c("MonitorID", "Year","month"),
model = "random")## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")md6_fix <- plm(Max.Ozone ~ tdmean+elevation + Longitude + Latitude,
data=test.dat,
index = c("MonitorID", "Year","month"),
model = "within",
effect = "twoways"
)## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")stargazer(md6_random, md6_fix, type = "text", title = "Comparison of Random and Fixed Effect Models 6", align = TRUE,
add.lines = list(c("Model Name", "Random Effect Model", "Fixed Effect Model")),
dep.var.labels.include = FALSE)##
## Comparison of Random and Fixed Effect Models 6
## ================================================================
## Dependent variable:
## ---------------------------------------------------
## (1) (2)
## ----------------------------------------------------------------
## tdmean 0.321*** 0.318***
## (0.001) (0.001)
##
## elevation 0.006*** 0.001
## (0.0002) (0.001)
##
## Longitude -0.003 -3.977***
## (0.008) (0.914)
##
## Latitude -0.078*** -7.205***
## (0.025) (2.776)
##
## Constant 40.112***
## (1.236)
##
## ----------------------------------------------------------------
## Model Name Random Effect Model Fixed Effect Model
## Observations 6,608,332 6,608,332
## R2 0.037 0.033
## Adjusted R2 0.037 0.033
## F Statistic 230,301.800*** 56,814.670*** (df = 4; 6606347)
## ================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01## model 7
md7_random <- plm(Max.Ozone ~ tdmean+tmean+ppt+elevation + Longitude + Latitude,
data=test.dat,
index = c("MonitorID", "Year","month"),
model = "random")## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")md7_fix <- plm(Max.Ozone ~ tdmean+tmean+ppt+elevation + Longitude + Latitude,
data=test.dat,
index = c("MonitorID", "Year","month"),
model = "within",
effect = "twoways"
)## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")stargazer(md7_random, md7_fix, type = "text", title = "Comparison of Random and Fixed Effect Models 7", align = TRUE,
add.lines = list(c("Model Name", "Random Effect Model", "Fixed Effect Model")),
dep.var.labels.include = FALSE)##
## Comparison of Random and Fixed Effect Models 7
## =================================================================
## Dependent variable:
## ----------------------------------------------------
## (1) (2)
## -----------------------------------------------------------------
## tdmean -0.850*** -0.858***
## (0.001) (0.001)
##
## tmean 1.364*** 1.367***
## (0.001) (0.001)
##
## ppt -0.134*** -0.131***
## (0.001) (0.001)
##
## elevation 0.004*** -0.004***
## (0.0002) (0.001)
##
## Longitude 0.143*** -8.219***
## (0.006) (0.820)
##
## Latitude 0.211*** -21.447***
## (0.020) (2.492)
##
## Constant 31.869***
## (1.023)
##
## -----------------------------------------------------------------
## Model Name Random Effect Model Fixed Effect Model
## Observations 6,608,332 6,608,332
## R2 0.223 0.221
## Adjusted R2 0.223 0.220
## F Statistic 1,865,932.000*** 311,826.400*** (df = 6; 6606345)
## =================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01## model 8
md8_random <- plm(Max.Ozone ~ USDM.categorical+ tdmean+tmean+ppt+elevation + Longitude + Latitude,
data=test.dat,
index = c("MonitorID", "Year","month"),
model = "random")## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")md8_fix <- plm(Max.Ozone ~ USDM.categorical+tdmean+tmean+ppt+elevation + Longitude + Latitude,
data=test.dat,
index = c("MonitorID", "Year","month"),
model = "within",
effect = "twoways"
)## Warning in pdata.frame(data, index): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")stargazer(md8_random, md8_fix, type = "text", title = "Comparison of Random and Fixed Effect Models 8", align = TRUE,
add.lines = list(c("Model Name", "Random Effect Model", "Fixed Effect Model")),
dep.var.labels.include = FALSE)##
## Comparison of Random and Fixed Effect Models 8
## ====================================================================================
## Dependent variable:
## ----------------------------------------------------
## (1) (2)
## ------------------------------------------------------------------------------------
## USDM.categoricalModerateDrought 0.489*** 0.640***
## (0.012) (0.012)
##
## USDM.categoricalSevereDrought 0.277*** 0.657***
## (0.018) (0.018)
##
## tdmean -0.847*** -0.854***
## (0.001) (0.001)
##
## tmean 1.361*** 1.362***
## (0.001) (0.001)
##
## ppt -0.134*** -0.131***
## (0.001) (0.001)
##
## elevation 0.004*** -0.004***
## (0.0002) (0.001)
##
## Longitude 0.146*** -8.204***
## (0.006) (0.820)
##
## Latitude 0.217*** -19.220***
## (0.020) (2.492)
##
## Constant 31.849***
## (0.998)
##
## ------------------------------------------------------------------------------------
## Model Name Random Effect Model Fixed Effect Model
## Observations 6,608,332 6,608,332
## R2 0.223 0.221
## Adjusted R2 0.223 0.221
## F Statistic 1,868,030.000*** 234,361.500*** (df = 8; 6606343)
## ====================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01