Comment

This article tests the hypothesis of perfect competition in the consumer nondurables sector of the U.K. economy. First, it uses household-level data to estimate time-varying price elasticities of demand for disaggregated commodity groups. U.S. product prices are used as instruments for U.K. prices in the demand equation. Then it matches the product definitions to the Standard Industry Classification and uses firm-level data, combined with the estimated elasticities, to estimate a price model of firms operating in different industries. Household characteristics are used as instruments for the demand effects in the firms' supply equation. The results reject perfect competition and appear to be consistent with the argument that less competition increases profits through collusion.     

Comment

The article provides detailed and accurate illustrations of Bayesian analysis of DSGE models that are likely to be used increasingly in support of central bank policy making. These comments identify a dozen aspects of these methods, discussing how their application and improvement can contribute to effective support of policy.     

Comment

A vector autoregression is a reduced-form representation and therefore would be expected to change when any structural equation in the system changes, regardless of whether economic decisions are forward-looking. Even so, a dynamic simulation of a model with unit roots will exhibit large cumulative errors, making it difficult to detect whether a structural change has indeed occurred.     

Comment

Some considerations relating to the post–data selection of models are discussed. These include some difficulties with orthodox theory, implementation of the likelihood principle, and Bayesian tests of hypotheses.     

Comment

We propose a sequential test for predictive ability for recursively assessing whether some economic variables have explanatory content for another variable. In the forecasting literature it is common to assess predictive ability by using “one-shot” tests at each estimation period. We show that this practice leads to size distortions, selects overfitted models and provides spurious evidence of in-sample predictive ability, and may lower the forecast accuracy of the model selected by the test. The usefulness of the proposed test is shown in well-known empirical applications to the real-time predictive content of money for output and the selection between linear and nonlinear models.