Generalized Method of Moment (GMM) estimation is one of two developments in econometrics in the 80ies that revolutionized empirical work in macroeconomics. (The other being the understanding of unit roots and cointegration.) The path breaking articles on GMM were those of Hansen (1982) and Hansen and Singleton (1982). For introductions to GMM, Davidson and MacKinnon (1993) have comprehensive ch...

In this paper, by employing the Generalized Method of Moment (GMM) techniques and Chinese provincial level data from 1991 to 2003, we empirically investigate the relationship between finance and growth in post-reform China. We find that financial development significantly promotes economic growth in coastal regions but not in inland regions; the weak finance-growth nexus in inland provinces has...

In this paper we introduce the Extended Method of Moments (XMM) estimator. This estimator accommodates a more general set of moment restrictions than the standard Generalized Method of Moments (GMM) estimator. More specifically, the XMM differs from the GMM in that it can handle not only uniform conditional moment restrictions (i.e. valid for any value of the conditioning variable), but also lo...

This paper proposes a misspecification-robust iid bootstrap for the generalized method of moment estimators and establishes asymptotic refinements of the symmetric percentile-t bootstrap confidence interval. The paper extends results of Hall and Horowitz (1996) and Andrews (2002). In particular, the proposed method does not involve recentering the moment function in implementing the bootstrap, ...

This paper investigates a generalized method of moments (GMM) approach to the estimation of autoregressive roots near unity with panel data and incidental deterministic trends. Such models arise in empirical econometric studies of Þrm size and in dynamic panel data modeling with weak instruments. The two moment conditions in the GMM approach are obtained by constructing bias corrections to the ...

Procedures based on the Generalized Method of Moments (GMM) (Hansen, 1982) are basic tools in modern econometrics. In most cases, the theory available for making inference with these procedures is based on first order asymptotic theory. It is well-known that the (first order) asymptotic distribution does not provide accurate p-values and confidence intervals in moderate to small samples. Moreov...

Panel data allow correction for measurement error without assuming a known measurement error covariance matrix or using additional validation/replication data to estimate the measurement error covariance matrix. Griliches and Hausman (1986) proposed using the generalized method of moments (GMM) or optimal weighting to efficiently combine instrumental variable (IV) estimators. Wansbeek (2001) ap...

Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. Two step GMM is biased. Generalized empirical likelihood (GEL) has smaller bias but the usual standard errors are too small in instrumental variable settings. In this paper we give a new variance estimator for GEL that addresses this problem. It is consistent under the usual asymptotics and under ...