often not provided. If confidence intervals are given they are often based on bootstrap methods with poor theoretical …

Using Monte Carlo experiments, we examine the performance of indirect inference tests of DSGE models in small samples …, using various models in widespread use. We compare these with tests based on direct inference (using the Likelihood Ratio … power of the indirect inference test is by far the greater, necessitating re-estimation to ensure that the model is tested …

We extend the method of indirect inference testing to data that is not filtered and so may be non-stationary. We apply …

Using Monte Carlo experiments, we examine the performance of Indirect Inference tests of DSGE models, usually versions … of the Smets-Wouters New Keynesian model of the US postwar period. We compare these with tests based on direct inference … substantial so that a false model will tend to be rejected by all three; but that the power of the indirect inference tests are by …

functions. This requires joint inference about sets of structural impulse responses, allowing for dependencies across time as … well as across response functions. Such joint inference is complicated by the fact that the joint distribution of …, which can be approximated by the bootstrap, allowing the construction of asymptotically valid joint confidence sets for any …

indirect inference; the resulting model passes the Wald test on output, inflation and interest rates. We then extract the model …

its asymptotic distribution, and we show how this distribution can be approximated by bootstrap methods. Our methods of … inference remain asymptotically valid when the order condition is satisfied, regardless of whether the usual rank condition for … to ensure the asymptotic validity of Bayesian methods of inference. A simulation study suggests that the frequentist and …

statistical inference. Here we examine a new and inexpensive recursive bootstrap procedure that allows forecasters to account … explicitly for these dependencies. The procedure allows forecasters to merge empirical evidence and draw inference in the light …