We propose to model endogeneity bias using prior distributions of moment conditions. The estimator can be obtained both as a method-of-moments estimator and in a Ridge penalized regression framework. We show the estimator’s relation to a Bayesian estimator.

We estimate the long rate and its volatility within the Svensson framework. The procedure that best extrapolates the longest observable rate and its volatility is a 2-dimensional grid search conditioned on the ridge regression suggested by Annaert et al. (2013).

In a recent article Bai (2013a) proposes a new factor analytical method (FAM) for the estimation of fixed-effects dynamic panel data models, which has the unique and very useful property that it is asymptotically bias free. In this paper we provide Monte Carlo evidence of the good small-sample...

This paper investigates the Estimating Function method in the context of ACD modelling and appraises the properties of these estimates. A simulation study is conducted to demonstrate that these estimates are more efficient than the corresponding ML and QML estimates.

This note provides explanations for an unexpected result, namely, the estimated parameter of the correlation coefficient of the trend shock and cycle shock in the state–space model is almost always (positive or negative) unity, even when the true variance of the trend shock is zero. It is...

We propose an estimation strategy for two-sided matching models with non-transferable utility based on the characterization using pre-matching that exploits a fixed-point characterization of the set of stable matchings.

There have been numerous applications of partial observability bivariate probit models. These models identify determinants of individual discrete outcomes when all that is observed are collective outcomes and individual characteristics. Numerical difficulties with their likelihood functions are...

A convenient and simple GMM procedure for estimating stochastic frontier models in the presence of endogenous regressors is proposed. Monte Carlo simulations show that the proposed estimator works very well in finite samples. We apply the proposed method to panel data of Norwegian dairy farms to...

This paper investigates the quasi-maximum likelihood (QML) estimation of spatial panel data models where spatial weights matrices can be time varying. We show that QML estimate is consistent and asymptotically normal. We also derive the asymptotic distribution of average impact coefficients...