Description Details Author(s) References Examples
This package computes the first stage GMM estimate of a dynamic linear model with p lags of the dependent variables.
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.
Taha Zaghdoudi
Taha Zaghdoudi <zedtaha@gmail.com>
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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | # 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)
|
GMM-Estimation of the Dynamic Panel Data Models:
Instruments according to method:
Arellano Bond (1991)
Estimate SE t-value Pvalue
log(pcap) -0.12647074 0.02552762 -4.9543 2.427e-06 ***
log(pc) 0.20800175 0.02104102 9.8855 < 2.2e-16 ***
log(emp) 0.75427377 0.03330868 22.6450 < 2.2e-16 ***
unemp -0.00622789 0.00069247 -8.9938 4.496e-15 ***
LagDep 0.18584312 0.02667405 6.9672 1.921e-10 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Number of groups : 48 Number of obs : 720
R-square : 0.6190713
Hansen's J-statistic: 884.9453 Pvalue: 0
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