VARs are often estimated with Bayesian techniques to cope with model dimensionality. The posterior means define a class of shrinkage estimators, indexed by hyperparameters that determine the relative weight on maximum likelihood estimates and prior means. In a Bayesian setting, it is natural to...

This paper focuses on the specification and stability of a dynamic, stochastic, general equilibrium model of the American business cycle with sticky prices. Maximum likelihood estimates reveal that the data prefer a version of the model in which adjustment costs apply to the price level but not...

We consider competition between firms that design and use algorithms to target consumers. Firms first choose the design of a supervised learning algorithm in terms of the complexity of the model or the number of variables to accommodate. Each firm then appoints a data analyst to estimate demand...

Time-varying coefficient models have been widely used to model changing relationships of economic and financial variables. The existing literature usually specifies the time-varying coefficient vector as a stochastic stationary process, a deterministic function of time, or a unit root process....