The wild bootstrap was originally developed for regression models with heteroskedasticity of unknown form. Over the past thirty years, it has been extended to models estimated by instrumental variables and maximum likelihood, and to ones where the error terms are (perhaps multi-way) clustered....

For the first time, we obtain a general formula for the <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$n^{-2}$$</EquationSource> </InlineEquation> asymptotic covariance matrix of the bias-corrected maximum likelihood estimators of the linear parameters in generalized linear models, where <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$$n$$</EquationSource> </InlineEquation> is the sample size. The usefulness of the formula is illustrated in order to...</equationsource></inlineequation></equationsource></inlineequation>

This paper proposes the use of the bootstrap when the system Wald test is employed to test for linear restrictions in a stationary vector autoregressive (VAR) model. The bootstrap test is conducted using the estimated generalised least square estimator for VAR parameters, which considers...

This paper discusses two alternative two-part models for fractional response variables that are defined as ratios of integers. The first two-part model assumes a Binomial distribution and known group size. It nests the one-part fractional response model proposed by Papke and Wooldridge (1996)...

The preliminary test ridge regression estimators (P T R R E) based on the Wald (W), Likelihood Ratio (L R) and Lagrangian Multiplier (L M) tests for estimating the regression parameters has been considered in this paper. Here we consider the multiple regression model with student t error...

This paper develops Wald-type tests for general (possibly nonlinear) restrictions in the context of a weakly-identified heteroskedastic IV regression. In particular, it is first shown that, in a framework with many weak instruments, consistency and asymptotic normality can be obtained when...

We consider linearity testing in a general class of nonlinear time series model of order 1, involving a nonnegative nuisance parameter which (i) is not identified under the null hypothesis and (ii) gives the linear model when equal to zero. This paper studies the asymptotic distribution of the...

Applied researchers often use tests based on contingency tables in preliminary data analysis and diagnostic testing. We show that many of such tests may be alternatively implemented by testing for coecient restrictions in linear regression systems (as a rule, employing the Wald test). This unies...

The asymptotic properties of the quasi-maximum likelihood estimator (QMLE) of vector autoregressive moving-average (VARMA) models are derived under the assumption that the errors are uncorrelated but not necessarily independent. Relaxing the independence assumption considerably extends the range...