Norman R. Swanson

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This chapter discusses estimation, specification testing, and model selection of predictive density models. In particular, predictive density estimation is briefly discussed, and a variety of different specification and model evaluation tests due to various authors including Christoffersen and Diebold (2000), Diebold, Gunther and Tay (1998), Diebold, Hahn(More)
In this paper, we show the first order validity of the block bootstrap in the context of Kolmogorov type conditional distribution tests when there is dynamic misspecification and parameter estimation error. Our approach differs from the literature to date because we construct a bootstrap statistic that allows for dynamic misspecification under both(More)
Data on monetary aggregates are subject to periodic redefinitions, presumably in part to improve their link to measures of output. Money data are also revised on a regular basis. Taking these data imperfections into account, we reassess the evidence on the marginal predictive content of M1 and M2 for real and nominal output. In particular, by ̄rst using(More)
We take as a starting point the existence of a joint distribution implied by different dynamic stochastic general equilibrium (DSGE) models, all of which are potentially misspecified. Our objective is to compare ‘‘true’’ joint distributions with ones generated by given DSGEs. This is accomplished via comparison of the empirical joint distributions (or(More)
This paper derives the limiting distributions of alternative jackknife IV (JIV ) estimators and gives formulae for accompanying consistent standard errors in the presence of heteroskedasticity and many instruments. The asymptotic framework includes the many instrument sequence of Bekker (1994) and the many weak instrument sequence of Chao and Swanson(More)
It is common practice in econometrics to correct for heteroskedasticity. This paper corrects instrumental variables estimators with many instruments for heteroskedasticity. We give heteroskedasticity robust versions of the limited information maximum likelihood (LIML) and Fuller (1977, FULL) estimators; as well as heteroskedasticity consistent standard(More)
This paper analyzes conditions under which various single-equation estimators are asymptotically normal in a simultaneous equations framework with many weak instruments. In particular, our paper adds to the many instruments asymptotic normality literature, including papers by Morimune (1983), Bekker (1994), Angrist and Krueger (1995), Donald and Newey(More)
We examine the extent to which fluctuations in the money stock anticipate (or Granger cause) fluctuations in real output using a variety of rolling window and increasing window estimation techniques. Various models are considered using simple sum as well as Divisia measures of M1 and M2, income, prices, and both the Tbill rate and the commercial paper rate.(More)
Large aggregation interval asymptotics are used to investigate the relation between Granger causality in disaggregated vector autoregres-sions (VARs) and contemporaneous innovation correlation in aggre-gated systems. This approach allows us to better understand the in-formational content in non-diagonal error covariance matrices, which play an important(More)