with generalized driving processes should be treated with caution, and that there exists a tradeoff between identification …

inferential problems that persist even in large samples. In the presence of partially identification problems, we show that an … likelihood framework using the 2013 SCF data for the U.S. confirms the results from our identification experiments. …

identification. …

inferential problems that persist even in large samples. In the presence of partially identification problems, we show that an … likelihood framework using the 2013 SCF data for the U.S. confirms the results from our identification experiments. …

In this paper we discuss general identification results for Structural Vector Autoregressions (SVARs) with external … "relevance" and "exogeneity" conditions. We discuss identification results and likelihood-based estimation methods both in the …

In this paper we discuss general identification results for Structural Vector Autoregressions (SVARs) with external … "relevance" and "exogeneity" conditions. We discuss identification results and likelihood-based estimation methods both in the …

observational equivalence, partial and weak identification problems are widespread, that they lead to biased estimates, unreliable t … identification and study how small samples interact with parameters and shock identification. We provide diagnostics and tests to … detect identification failures and apply them to a state-of-the-art model. …

observational equivalence, partial and weak identification problems are widespread, that they lead to biased estimates, unreliable t … identification and study how small samples interact with parameters and shock identification. We provide diagnostics and tests to … detect identification failures and apply them to a state-of-the-art model …