| dynpanel-package {dynpanel} | R Documentation |
Dynamic Panel Data Models
Description
This package computes the first stage GMM estimate of a dynamic linear model with p lags of the dependent variables.
Details
| Package: | dynpanel |
| Type: | Package |
| Version: | 1.0 |
| Date: | 2016-08-26 |
| License: | GPL-3 |
In this package, we apply the generalized method of moments to estimate the dynamic panel data models.
Author(s)
Taha Zaghdoudi
Taha Zaghdoudi <zedtaha@gmail.com>
References
Anderson, T. W.; Hsiao, Cheng (1981). Estimation of dynamic models with error components. ournal of the American Statistical Association. 76 (375) ,pp. 598-606.
Arellano, Manuel; Bond, Stephen (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies. 58, pp.2)-277. Cameron, A. Colin; Trivedi, Pravin K. (2005). Dynamic Models. Microeconometrics: Methods and Applications. New York: Cambridge University Press. pp. 763-768.
Hsiao, Cheng (2014). Dynamic Simultaneous Equations Models. Analysis of Panel Data. New York: Cambridge University Press. pp. 397-402.
Munnell AH (1990). Why has Productivity Growth Declined? Productivity and Public Investment, New England Economic Review, pp. 3-22.
Examples
# Load data
data(Produc)
# Fit the dynamic panel data using the Arellano Bond (1991) instruments
reg<-dpd(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,Produc,index=c("state","year"),1,4)
summary(reg)
# Fit the dynamic panel data using an automatic selection of appropriate IV matrix
#reg<-dpd(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,Produc,index=c("state","year"),1,0)
#summary(reg)
# Fit the dynamic panel data using the GMM estimator with the smallest set of instruments
#reg<-dpd(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,Produc,index=c("state","year"),1,1)
#summary(reg)
# Fit the dynamic panel data using a reduced form of IV from method 3
#reg<-dpd(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,Produc,index=c("state","year"),1,2)
#summary(reg)
# Fit the dynamic panel data using the IV matrix where the number of moments grows with kT
# K: variables number and T: time per group
#reg<-dpd(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,Produc,index=c("state","year"),1,3)
#summary(reg)