Many studies have used self-reported dyadic data without exploiting the pattern of discordant answers. In this paper we propose a maximum likelihood estimator that deals with mis-reporting in a systematic way. We illustrate the methodology using dyadic data on inter-household transfers from the...

We propose a numerical method, based on indirect inference, for checking the identification of a DSGE model. Monte Carlo samples are generated from the model's true structural parameters and a VAR approximation to the reduced form estimated for each sample. We then search for a different set of...

Two main approaches are commonly used to empirically evaluate linear factor pricing models: regression and SDF methods, with centred and uncentred versions of the latter. We show that unlike standard two-step or iterated GMM procedures, single-step estimators such as continuously updated GMM...

In the finance literature, cross-sectional dependence in extreme returns of risky assets is often modelled implicitly assuming an asymptotically dependent structure. If the true dependence structure is asymptotically independent then existing finance models will lead to over-estimation of the...

We propose new approaches to test for spanning in the return and stochastic discount factor mean-variance frontiers, which assess if either the centred or uncentred mean and cost representing portfolios are shared by the initial and extended sets of assets. We show that our proposed tests are...

This paper provides a broad empirical examination of the major currencies' roles in international capital markets, with a special emphasis on the first year of the Euro. A contribution is made as to how to measure these roles, both for international financing as well as for international...

Using a data-set that provides unprecedented details on individual investors’ stockholdings, we analyse whether investors take into account corporate governance when they select stocks. After controlling for the supply effect via free float and other firm characteristics, we find that all...

The issue of model uncertainty is central to the empirical study of economic growth. Many recent papers use Bayesian Model Averaging to address model uncertainty, but Ciccone and Jarocinski (2010) have questioned the approach on theoretical and empirical grounds. They argue that a standard...

We provide, for the first time, comparative evidence of the impact of various types of extreme events – natural disasters, terrorism, and violent conflicts – on the perceptions of entrepreneurs concerning some key entrepreneurial issues – such as fear of failure in starting a business...

Structural vector autoregressive (VAR) models were introduced in 1980 as an alternative to traditional large-scale macroeconometric models when the theoretical and empirical support for these models became increasingly doubtful. Initial applications of the structural VAR methodology often were...