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A high-dimensional multinomial logit model (replication data)
The number of parameters in a standard multinomial logit model increases linearly with the number of choice alternatives and number of explanatory variables. Since many modern... -
Nonlinearities in macroeconomic tail risk through the lens of big data quanti...
Modeling and predicting extreme movements in GDP is notoriously difficult and the selection of appropriate covariates and/or possible forms of nonlinearities are key in... -
Understanding trend inflation through the lens of the goods and services sect...
We distinguish between the goods and services sectors in an unobserved components model of U.S. inflation. We find that prior to the early 1990s, both sectors contributed to... -
Subspace shrinkage in conjugate Bayesian vector autoregressions (replication ...
For the empirical exercise we use quarterly macroeconomic data for the US, obtained from the FRED-QD database (https://research.stlouisfed.org/econ/mccracken/fred-databases/).... -
A comparison of approaches to select the informativeness of priors in BVARs
Vector autoregressions (VARs) are richly parameterized time series models that can capture complex dynamic interrelationships among macroeconomic variables. However, in small... -
Using a Bayesian Structural Time–Series Model to Infer the Causal Impact on C...
The Bayesian structural time series model, used in conjunction with a state–space model, is a novel means of exploring the causal impact of a policy intervention. It extends the...
