We propose a new sequential procedure for estimating multivariate distributions in cases when conventional maximum likelihood has too many parameters and is therefore inaccurate or non-operational. The procedure constructs a multivariate distribution and its pseudo-likelihood sequentially, in...

Optimal GMM is known to dominate Gaussian QMLE in terms of asymptotic efficiency [Chamberlain, G., 1984. Panel data. In: Griliches, Z., Intriligator, M.D. (Eds.), Handbook of Econometrics, vol. II, pp. 1248-1313]. I derive a new condition under which QMLE is as efficient as GMM for a general...

For covariance structure models, the QMLE second-order bias is derived and compared with EL and GMM. Surprisingly, QMLE and EL have the same second-order bias if QMLE and GMM(EL) are equally first-order efficient. Other examples favoring QMLE are given.

We propose a simple kernel estimator for semiparametric partial linear models with endogeneity in the nonparametric function. Compared to the existing backfitting estimator, our estimator is notationally simpler and relatively easier to implement. We also discuss data-driven bandwidth selection...

This note examines the robustness that two modes exist in the world's density of per capita income. Our results suggest that this bimodal feature is robust and are arrived at using recently developed nonparametric deconvolution techniques.

A simple graphical approach to presenting results from nonlinear regression models is described. In the face of multiple covariates, ‘partial mean’ plots may be unattractive. The approach here is portable to a variety of settings and can be tailored to the specific application at hand. A...

This note explores clustering in cross country GDP per capita using recently developed model based clustering methods for panel data. Previous research characterizing the components of the overall distribution of output either use ad hoc methods, or methods which ignore/subvert the panel nature...