An additive model-assisted nonparametric method is investigated to estimate the finite population totals of massive survey data with the aid of auxiliary information. A class of estimators is proposed to improve the precision of the well known Horvitz-Thompson estimators by combining the spline and local polynomial smoothing methods. These estimators are calibrated, asymptotically design-unbias...

Estimation of finite population totals in the presence of auxiliary information is considered. A class of estimators based on local polynomial regression is proposed. Like generalized regression estimators, these estimators are weighted linear combinations of study variables, in which the weights are calibrated to known control totals, but the assumptions on the superpopulation model are consid...

This paper concerns regression methodology for assessing relationships between multi-dimensional response variables and covariates that are correlated within a network. To address analytical challenges associated with the integration of network topology into the regression analysis, we propose a hybrid quadratic inference method that uses both prior and data-driven correlations among network no...

A wide range of econometric and statistical models are specified through moment conditions. Efficient estimation of such models essentially employs two distinct ideas: optimally combining estimation equations (e.g., the optimal estimating equations of Godambe (1976), the generalized method of moments of Hansen (1982) and the empirical likelihood of Qin and Lawless (1994)), and optimally combini...

The constant relative risk aversion (CRRA) type utility functions are used in consumption-based capital asset pricing models (C-CAPM) and are estimated by the generalized method of moments (GMM). More realistic hyperbolic absolute risk aversion (HARA) utility functions are analytically inconvenient. We show how to estimate HARA-based CCAPM models by employing Godambe-Durbin \estimating function...

A general theory of efficient estimation for ergodic diffusions sampled at high frequency is presented. High frequency sampling is now possible in many applications, in particular in finance. The theory is formulated in term of approximate martingale estimating functions and covers a large class of estimators including most of the previously proposed estimators for diffusion processes, for inst...

Hyperbolic absolute risk aversion (HARA) utility, (See is a more Carroll and Kimball, 1996), realistic alternative to the power utility used in consumption-based capital asset pricing models (CCAPM). We propose a new estimator for the HARA based on Godambe-Durbin “estimating functions” and small sigma asymptotics (SSA). This is an alternative to the generalized method of moments (GMM). Since th...

Vinod (1997, 1998) discuss the Godambe-Durbin theory of estimating functions (EFs) and its potential in econometrics. Here we consider a popular application of EFs called generalized estimating equations (GEE). It is typically applied to panel data, where the heteroscedasticity is analytically related to , the regression parameter, and where the dependent variable is binary. Geddes (1997) studi...

Fisher’s pivot functions (PFs) continue to dominate statistical inference and bootstrap literature, despite Efron and Hinkley and Royall’s attempts to inject robustness. Vinod uses Godambe’s pivot functions (GPFs) based on Godambe—Durbin estimating functions (EFs) to develop numerically computed GPF roots. Such GPF roots can fill a long-standing need in the bootstrap literature for robust pivot...