lsdv (version 1.0)

fixed.default: Fixed effect panel data regression

Description

Fit a least square dummy variable regression model.

Usage

## S3 method for class 'default':
fixed(x, y, n, T, ...)

Arguments

x

a numeric design matrix for the model.

y

a numeric vector of responses.

n

number of cross-sections

T

times periods

...

not used

Value

• coefficients
  a named vector of coefficients
• fitted.values
  fitted values
• residuals
  residuals

Examples

#Create some data 
pib<-as.matrix(c(12,3,4,0.4,0.7,5,0.7,0.3,0.6,89,7,8,45,7,4,5,0.5,5),nrows=18,ncols=1)
tir<-as.matrix(c(12,0.3,4,0.4,7,12,3.0,6.0,45,7.0,0.8,44,65,23,4,6,76,9),nrows=18,ncols=1)
inf<-as.matrix(c(1.2,3.6,44,1.4,0.78,54,0.34,0.66,12,0.7,8.0,12,65,43,5,76,65,8),nrows=18,ncols=1)
npl<-as.matrix(c(0.2,3.8,14,2.4,1.7,43,0.2,0.5,23,7.8,88,36,65,3,44,65,7,34),nrows=18,ncols=1)
# create a data frame 
mdata<-data.frame(p=pib,t=tir,int=inf,np=npl)
# create the designed matrix for the model
d<-matrix(c(mdata$p,mdata$int,mdata$np),18, 3)
#fit the model
pp<-pfm(d,mdata$p,n=6,T=3)
pp