specTest-methods: Methods for Function 'specTest' in Package 'gmm4'
In gmm4: S4 Generalized Method of Moments

Description Usage Arguments Methods References Examples

It computes tests of specification for GMM fit.

## S4 method for signature 'gmmfit,missing'
specTest(object, which, df.adj=FALSE, wObj=NULL)

## S4 method for signature 'sgmmfit,missing'
specTest(object, which, df.adj=FALSE, wObj=NULL)

## S4 method for signature 'gmmfit,numeric'
specTest(object, which)

## S4 method for signature 'gelfit,missing'
specTest(object, which,
                    type = c("All", "LR", "LM", "J"))

`object`	GMM or GEL fit object
`which`	Which sub-moment conditions to test.
`df.adj`	Should we adjust the covariance matrix of the moment conditions for degrees of freedom. If `TRUE` the covariance matrix is multiplied by `n/(n-k)`, where `n` is the sample size and `k` is the number of coefficients. For heteroscedastic robust covariance matrix, adjusting is equivalent to computing HC1 while not adjusting is HC0.
`wObj`	An object of class `gmmWeights`. If NULL (the recommended value), the optimal weights is computed at the fitted coefficient estimates. It is used by `hypothesisTest` if one wants the LR statistics to be computed using the same weights for the restricted and unrestricted model.
`type`	For GEL, three specification tests are available

signature(object = "gmmfit", which="missing")
signature(object = "sgmmfit", which="missing")
signature(object = "gmmfit", which="numeric")

Eichenbaum, M. and Hansen L. and Singleton, K. (1985). A time Series Analysis of Representative Agent Models of Consumption and Leisure Choise under Uncertainty. Quarterly Journal of Economics, 103, 51–78.

Hayashi, F. (2000). Econometrics, New Jersey: Princeton University Press.

data(simData)
model1 <- gmmModel(y~x1, ~z1+z2, data=simData)

res <- modelFit(model1)
specTest(res)

## Hayashi Example 3.3 (there is not result in the book but
## that's how we would do it for YEAR=1967
data(Griliches)
dat <- subset(Griliches, YEAR==67)
model <- gmmModel(LW~S+EXPR+IQ, ~S+EXPR+AGE+MED, data=dat, vcov="MDS")
res <- modelFit(model)
## testing the orthogonality conditions of S
specTest(res, 2)