We consider inference in models defined by approximate moment conditions. show that near?optimal confidence intervals (CIs) can be formed taking a generalized method of moments (GMM) estimator, and adding subtracting the standard error times critical value takes into account potential bias from misspecification In order to optimize performance under misspecification, weighting matrix for this G...

Generalized Method of Moments (GMM) estimators in their various forms, including the popular Maximum Likelihood (ML) estimator, are frequently applied for evaluation complex econometric models with not analytically computable moment or likelihood functions. As objective functions GMM- and ML-estimators themselves constitute approximation an integral, more precisely expected value over real worl...

We propose the “generalized min-max” (GMM) kernel as a measure of data similarity, where data vectors can have both positive and negative entries. GMM is positive definite as there is an associate hashing method named “generalized consistent weighted sampling” (GCWS) which linearizes this (nonlinear) kernel. A natural competitor of GMM is the radial basis function (RBF) kernel, whose correspond...

Life expectancy marks the success of efforts to provide basic rights, such as access good health services. Lack improvement in conditions or stagnation is often considered a cause for concern because it can lead decline profile population driven by adverse socioeconomic status trends. Consequently, determinants modeling life males and females Indonesia was carefully selected collecting data 34 ...

We 1 develop some theoreti al results for a robust similarity measure named generalized minmax (GMM). This similarity has dire t appli ations in ma hine learning as a positive de nite kernel and an be e iently omputed via probabilisti hashing. Owing to the dis rete nature, the hashed values an also be used for e ient near neighbor sear h. We prove the theoreti al limit of GMM and the onsisten y...

Maximum likelihood (ML) estimation of the autoregressive parameter of a dynamic panel data model with fixed effects is inconsistent under fixed time series sample size and large cross section sample size asymptotics. This paper proposes a general, computationally inexpensive method of bias reduction that is based on indirect inference, shows unbiasedness and analyzes efficiency. Monte Carlo stu...