Abstract Model averaging has become a popular method of estimation, following increasing
evidence that model selection and estimation should be treated as one joint procedure …

This article investigates the relationship between countries' financial sector development
and the loans extended to micro, small, and medium-sized enterprises (MSMEs or small …

Estimating the location and scale parameters is common in statistics, using, for instance, the
well-known sample mean and standard deviation. However, inference can be contaminated …

This paper investigates the systemic risk in the West African Economic and Monetary Union
(WAEMU) stock exchange (Bourse Régionale des Valeurs Mobilières-BRVM). It examines …

The weighted-average least squares (WALS) approach, introduced by Magnus et al.(2010)
in the context of Gaussian linear models, has been shown to enjoy important advantages …

We consider inference for linear regression models estimated by weighted-average least
squares (WALS), a frequentist model averaging approach with a Bayesian flavor. We …

In specifying a regression equation, we need to specify which regressors to include, but also
how these regressors are measured. This gives rise to two levels of uncertainty: concepts …

Markov chain Monte Carlo (MCMC) methods are a popular and widely used means of
drawing from probability distributions that are not easily inverted, that have difficult …

Many statistical and econometric learning methods rely on Bayesian ideas. When applied in
a frequentist setting, their precision is often assessed using the posterior variance. This is …

We investigate the asymptotic behavior of the WALS estimator, a model-averaging estimator
with attractive finite-sample and computational properties. WALS is closely related to the …