We propose a new sequential procedure for estimating a dynamic joint distribution of a group of assets. The procedure is motivated by the theory of composite likelihood and by the theory of copula functions. It recovers m-variate distributions by coupling univariate distributions with...

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...

This note proposes an econometric framework for studying electoral returns using aggregate voting and socioeconomic panel data. Along with usual covariates, the model includes electoral unit effects, electoral subunit effects and time effects, and features nested groupings and...

This paper studies the asymptotic validity of the Anderson–Rubin (<italic>AR</italic>) test and the <italic>J</italic> test for overidentifying restrictions in linear models with many instruments. When the number of instruments increases at the same rate as the sample size, we establish that the conventional <italic>AR</italic> and <italic>J</italic> tests are...

This essay covers the principles and methodology of nonparametric estimation of a mean regression. The emphasis is put on kernel smoothing, but non-kernel methods are also reviewed.

We consider a standard instrumental variables model contaminated by the presence of a large number of exogenous regressors. In an asymptotic framework where this number is proportional to the sample size, we study the impact of their ratio on the validity of existing estimators and tests. When...