Work in progress

• "Simulation-based estimation with many auxiliary statistics applied to long-run dynamic analysis", with Bertille Antoine (R&R, Journal of Econometrics)

The existing asymptotic theory for estimators obtained by simulated minimum distance does not cover situations in which the number of components of the auxiliary statistics (or number of matched moments) is large - typically larger than the sample size. We establish the consistency of the simulated minimum distance estimator in this situation and derive its asymptotic distribution.

Our estimator is easy to implement and allows us to exploit all the informational content of a large number of auxiliary statistics without having to, (i) know these functions explicitly, or (ii) choose a priori which functions are the most informative. This allows us to exploit, among other things, long-run information. We illustrate the implementation of the proposed method through Monte-Carlo simulation experiments based on small- and medium-scale New Keynesian models. These examples illustrate how to exploit information from matching a large number of impulse responses including at long-run horizons.

• "Monte Carlo Test for Markov-switching Autoregressive Models using Higher-order Moments"

This paper proposes tests of the null hypothesis of autoregressive models against ones with Markov-switching autoregressive components. The empirical simulation-based tests allow for unknown distributions and use Monte-Carlo test techniques. The approach is flexible and computationally simple. The designed test statistic allows for a large number of empirical moments and relies on simulations under the null hypothesis which permits the use of higher-order moments. Our simulation experiments demonstrate that more information can be harvested with more moments matched, with evidence of increased empirical power. The Monte-Carlo testing methodology is illustrated with a mean-variance switching model, an autoregressive coefficient switching model, and an application to US output growth modeling.

West Mall Complex, Rm2698

Simon Fraser University

8888 University Drive, Burnaby, BC, Canada V5A 1S6

wenqians@sfu.ca