This paper presents estimation methods and asymptotic theory for the analysis of a nonparametrically specified conditional quantile process. Two estimators based on local linear regressions are proposed. The first estimator applies simple inequality constraints while the second uses...

This paper considers issues related to identification, inference and computation in linearized Dynamic Stochastic General Equilibrium (DSGE) models. We first provide a necessary and su¢ cient condition for the local identification of the structural parameters based on the (first and) second...

This paper proposes a test statistic for the null hypothesis that a given time series is a stationary long memory process against the alternative hypothesis that it is a¤ected by regime change or a smoothly varying trend. The proposed test is in the frequency domain and is based on the...

This paper proposes a new family of M tests, building on the work of Kuan and Lee (2006) and Kiefer, Vogelsang and Bunzel (2000). The new test replaces the asymptotic covariance matrix in the conventional M test with an alternative normalization matrix, constructed using moment functions...

The paper considers parameter identification, estimation and inference in medium scale DSGE models from a frequency domain perspective using the framework developed in Qu and Tkachenko (2010). The analysis uses Smets and Wouters (2007) as an illustrative example, motivated by the fact that it...

This paper considers the estimation of multiple structural changes occurring at unknown dates in one or multiple conditional quantile functions. The analysis covers time series models as well as models with repeated cross-sections. We estimate the break dates and other parameters jointly by...

This paper considers inference and model diagnostics for log-linearized DSGE models allow- ing an unknown subset of parameters to be weakly (including un-) identified. The framework allows for latent state variables, measurement errors and also permits analysis using only part of the spectrum,...