Blathering managers harm their company If a senior executive refuses to give information to professional investors, the...
Productivity: More with Less by Better Available resources are scarce. To sustain our...
IWH FDI Micro Database
IWH FDI Micro Database The IWH FDI Micro Database (FDI = Foreign Direct...
The CompNet Competitiveness Database The Competitiveness Research Network (CompNet)...
IWH-CompNet Discussion Papers
IWH-CompNet Discussion Papers The IWH-CompNet Discussion Paper series presents research...
Deposit Competition and Securitization
IWH Discussion Papers,
We provide novel evidence that deposit competition incentivizes banks to securitize loans. Exploiting the state-specific removal of deposit market caps across the U.S. as an exogenous source of competition, we document a 7.1 percentage point increase in the probability that banks securitize their assets. This result is driven by an 11 basis point increase in costs of deposits and a corresponding decrease in banks’ deposit growth. Our results are strongest among small and single state incumbent banks that rely more on deposit funding. These findings highlight an unintended regulatory cause that motivates banks to adopt the originate-to-distribute model.
Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information
This paper makes the following original contributions to the literature. (i) We develop a simpler analytical characterization and numerical algorithm for Bayesian inference in structural vector autoregressions (VARs) that can be used for models that are overidentified, just‐identified, or underidentified. (ii) We analyze the asymptotic properties of Bayesian inference and show that in the underidentified case, the asymptotic posterior distribution of contemporaneous coefficients in an n‐variable VAR is confined to the set of values that orthogonalize the population variance–covariance matrix of ordinary least squares residuals, with the height of the posterior proportional to the height of the prior at any point within that set. For example, in a bivariate VAR for supply and demand identified solely by sign restrictions, if the population correlation between the VAR residuals is positive, then even if one has available an infinite sample of data, any inference about the demand elasticity is coming exclusively from the prior distribution. (iii) We provide analytical characterizations of the informative prior distributions for impulse‐response functions that are implicit in the traditional sign‐restriction approach to VARs, and we note, as a special case of result (ii), that the influence of these priors does not vanish asymptotically. (iv) We illustrate how Bayesian inference with informative priors can be both a strict generalization and an unambiguous improvement over frequentist inference in just‐identified models. (v) We propose that researchers need to explicitly acknowledge and defend the role of prior beliefs in influencing structural conclusions and we illustrate how this could be done using a simple model of the U.S. labor market.