在r上使用panel数据集的Diff中的Diff

Question

我有一个面板数据集，我想在diff上进行diff。现在这是我的回归:

fit3 <- glm(df$empstat ~ factor(year) + factor(stateicp) + migrant_category + treated*post + treated*migrant_category
+ post*migrant_category + treated*post*migrant_category + race + educ + age +
marst, data = df, weights = perwt, family = 'gaussian'
)

，但这会使R假设每个观测值是相互独立的吗?如果是，我应该怎么做才能让R意识到这是一个面板数据?

Answer 1

如果您对固定效果模型和差异感兴趣，请使用plm包。以下是Christopher Zorn的一个例子:

# Panel data 
WDI<-read_csv("https://github.com/PrisonRodeo/GSERM-Ljubljana-APD-git/raw/main/Data/WDI3.csv")
# Add a "Cold War" variable:
WDI$ColdWar <- with(WDI,ifelse(Year<1990,1,0))
# Keep a numeric year variable (for -panelAR-):
WDI$YearNumeric<-WDI$Year
# Make the data a panel dataframe:
WDI<-pdata.frame(WDI,index=c("ISO3","Year"))
# Pull out *only* those countries that, at some
# point during the observed periods, instituted
# a paid parental leave policy:
WDI<-WDI %>% group_by(ISO3) %>%
filter(any(PaidParentalLeave==1))
# Create a better trend variable:
WDI$Time<-WDI$YearNumeric-1950
# FE models...
fe1<-plm(ChildMortality~PaidParentalLeave+Time+
PaidParentalLeave*Time,data=WDI,
effect="individual",model="within")
fe2<-plm(ChildMortality~PaidParentalLeave+Time+
PaidParentalLeave*Time+log(GDPPerCapita)+
log(NetAidReceived)+GovtExpenditures,
data=WDI,effect="individual",model="within")
fe3<-plm(ChildMortality~PaidParentalLeave+Time+
PaidParentalLeave*Time,data=WDI,
effect="twoway",model="within")
fe4<-plm(ChildMortality~PaidParentalLeave+Time+
PaidParentalLeave*Time+log(GDPPerCapita)+
log(NetAidReceived)+GovtExpenditures,
data=WDI,effect="twoway",model="within")
# TABLE TIME
stargazer(fe1,fe2,fe3,fe4,
title="DiD Models of log(Child Mortality)",
column.separate=c(1,1,1),align=TRUE,
dep.var.labels.include=FALSE,
dep.var.caption="",
covariate.labels=c("Paid Parental Leave","Time (1950=0)",
"Paid Parental Leave x Time",
"ln(GDP Per Capita)",
"ln(Net Aid Received)",
"Government Expenditures"),
header=FALSE,model.names=FALSE,
model.numbers=FALSE,multicolumn=FALSE,
object.names=TRUE,notes.label="",
column.sep.width="-15pt",
omit.stat=c("f","ser"),type="text")
DiD Models of log(Child Mortality)
=====================================================================
fe1        fe2        fe3        fe4   
---------------------------------------------------------------------
Paid Parental Leave        -15.500*** -26.200*** -12.500*** -17.300* 
(2.420)    (7.220)    (2.960)    (9.360) 

Time (1950=0)              -0.838***  -1.480***                      
(0.025)    (0.094)                       

Paid Parental Leave x Time            -7.110***              -4.910* 
(2.290)               (2.600) 

ln(GDP Per Capita)                    -1.780***             -3.020***
(0.471)               (0.552) 

ln(Net Aid Received)                   0.873***             0.842*** 
(0.139)               (0.146) 

Government Expenditures     0.310***   0.524***   0.247***   0.319*  
(0.044)    (0.128)    (0.056)    (0.169) 

---------------------------------------------------------------------
Observations                 2,360       622       2,360       622   
R2                           0.496      0.717      0.009      0.143  
Adjusted R2                  0.485      0.701      -0.035     0.014  
=====================================================================
*p<0.1; **p<0.05; ***p<0.01