This paper provides a systematic approach to semiparametric identification that is based on statistical information. Identification can be regular or irregular, depending on whether the Fisher information for the parameter is positive or singular, respectively. I first characterize these two...

This article reviews some recent advances in testing for serial correlation, provides Stata code for implementation and illustrates its application to market risk forecast evaluation. The classical and widely used Portamenteau tests and their data-driven versions are the focus of this article....

This paper investigates estimation of linear regression models with strictly exogenous instruments under minimal identifying assumptions. The paper introduces a uniformly (in the data generating process) consistent estimator under nearly minimal identifying assumptions. The proposed estimator,...

Traditional measures of dependence in time series are typically based on correlations or periodograms. These are adequate in many circumstances but, in others, especially when trying to assess market linkages (e.g., financial contagion), might be inappropriate. In the present paper we propose...

This article proposes a new identification strategy and a new estimation method for the hybrid New Keynesian Phillips curve (NKPC). Unlike the predominant Generalized Method of Moments (GMM) approach, which leads to weak identification of the NKPC with U.S. postwar data, our non-parametric...