Firms with good management practices optimize and synthesize human resources, leadership, and technical and conceptual skills to enhance firm value. In this paper, we examine the role of management practices in merger and acquisition (M&A) decisions. M&A decisions are among the most important...

We address the identification of low-frequency macroeconomic shocks, such as technology, in Structural Vector Autoregressions. Whilst identification issues with long-run restrictions are well documented, we demonstrate that the recent attempt to overcome said issues using the Max-Share approach...

We propose a method for constructing an arbitrage-free multi-asset pricing model which is consistent with a set of observed single- and multi-asset derivative prices. The pricing model is constructed as a random mixture of N reference models, where the distribution of mixture weights is obtained...

We address the identification of low-frequency macroeconomic shocks, such as technology, in Structural Vector Autoregressions. Whilst identification issues with long-run restrictions are well documented, we demonstrate that the recent attempt to overcome said issues using the Max-Share approach...

Time-varying parameter (TVP) models have the potential to be over-parameterized, particularly when the number of variables in the model is large. Global-local priors are increasingly used to induce shrinkage in such models. But the estimates produced by these priors can still have appreciable...

In this paper, we explore the relationship between state-level household income inequality and macroeconomic uncertainty in the United States. Using a novel large-scale macroeconometric model, we shed light on regional disparities of inequality responses to a national uncertainty shock. The...

We compare the finite sample performance of a number of Bayesian and classical procedures for limited information simultaneous equations models with weak instruments by a Monte Carlo study. We consider Bayesian approaches developed by Chao and Phillips, Geweke, Kleibergen and van Dijk, and...

Time-varying parameter (TVP) models have the potential to be over-parameterized, particularly when the number of variables in the model is large. Global-local priors are increasingly used to induce shrinkage in such models. But the estimates produced by these priors can still have appreciable...

We show that the higher order biases of instrumental variable statistics in the strong instrument case indicate the degeneracy of the first order asymptotic distributions of these statistics under weak or many instrument asymptotics. We express the higher order approximations using an estimator...

We construct higher order expressions for Wald and Lagrange multiplier (LM) GMM statistics that are based on 2step and continuous updating estimators (CUE). We show that the sensitivity of the limit distribution to weak and many instruments results from superfluous elements in the higher order...