The aggregation of individual random AR(1) models generally leads to an AR(∞∞) process. We provide two consistent estimators of aggregate dynamics based on either a parametric regression or a minimum distance approach for use when only macro data are available. Notably, both estimators allow...

This paper examines the implications of using VARs in levels under the Max Share identification approach when variables exhibit unit or near-unit roots. We derive the asymptotic distributions of the Max Share estimator, demonstrating that it converges to a random matrix, resulting in...

We show that, in heterogeneous-firm international trade models, common forms of heterogeneity and uncertainty drive a (multiplicative random) wedge between the observable exports distribution and the latent distribution of firm productivity. Even if the latter is exactly Pareto distributed, this...

This paper proposes a joint methodology for the identification and inference of structural vector autoregressive models in the frequency domain. We show that identifying restrictions can be written naturally as an asymptotic least squares problem (Gourieroux, Monfort and Trognon, 1985) in which...

In this paper, we investigate the information content of implied probabilities (Back and Brown, 1993) to improve estimation in unconditional moment conditions models. We propose and evaluate two 3-step euclidian empirical likelihood estimators and their bias-correction versions for weakly...