Testing Parametric Conditional Distributions of Dynamic Models

By Jushan Bai. Review of Economics and Statistics, 2003

263 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/5b41892fe0df92c300ff96634fd922f3b72633ca

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Citations in the corpus

Distribution free specification tests of conditional models (2008, methodology): “The empirical process ̂n (1; ) has also been considered by Bai (2003) for testing _ H0 : E FY jX; 0 (yjX) = FY (y) for some 0 2 ; with FY denoting the marginal d.”
SV mixture models with application to S&P 500 index returns ☆ (2007, unknown): “Papers include Bontemps and Meddahi (2005), Duan (2003), Bai (2003), Hong and Li (2002), and Diebold, Gunther, and Tay (1998).”
Quantile Regression Under Misspecification, with an Application to the U.S. Wage Structure (2006, unknown): “2τ = Y −Qτ (Y |X), (5) with conditional density f2τ (e|X) at 2τ = e.”
Testing functional inequalities (2011, methodology): “Exceptions are tests that use an innovation martingale approach (see, e.g., Khmaladze (1993), Stute, Thies and Zhu (1998), Bai (2003), and Khmaladze and Koul (2004)) or some tests of independence (or conditional independence) among random variables (see, e.g., Blum, Kiefer, and Rosenblatt (1961),…”
Combining inflation density forecasts (2010, methodology): “These tests require the assumption of correct specification of the density forecast under the null hypothesis using all the relevant information (e.g. Diebold, Gunther and Tay, 1998; Bai, 2003) or conditional”
Predictive density and conditional confidence interval accuracy tests (2006, methodology): “Some of the important recent papers in this area include Diebold, Gunther and Tay (DGT: 1998), Christoffersen (1998), Bai (2003), Diebold, Hahn and Tay (1999), Hong (2001) and Christoffersen, Hahn and Inoue (2001), and Giacomini (2002).(1) This paper has two primary objectives.”
Bootstrap Conditional Distribution Tests In the Presence of Dynamic Misspecification (2006, unknown): “To overcome this problem, Bai (2003) uses a novel approach based on a martingalization argument to construct a modified Kolmogorov test which has a nuisance parameter free limiting distribution.”
Alternative tests for correct specification of conditional predictive densities (2019, unknown): “There are several existing approaches for testing the correct specification of a parametric density in-sample (e.g. Bai, 2003, Hong and Li, 2005, Corradi and Swanson, 2006a).”
A consistent test for conditional symmetry in time series models (2001, methodology): “(9) and is proved in Bai (2000).”
Modeling and forecasting expected shortfall with the generalized asymmetric Student-t and asymmetric exponential power distributions (2011, methodology): “When β is replaced with a consistent estimate β̂, for all Ck to be nonsingular, we use the statistic T ∗n = [n/ (n− l)] 1/2 sup1≤j≤n−l ∣∣∣Ŵn(υj)∣∣∣ for a small number l > 0 (see Theorem 4 of Bai (2003)).”
Instrumental quantile regression inference for structural and treatment effect models (2006, methodology): “3See e.g. Durbin (1973), Bai (1997), and Koenker and Xiao (2002) for related discussions.”
Testing Distributional Assumptions: A GMM Approach (2007, methodology): “Interestingly, by using a Khmaladze (1981)’s transform to get a robust test against parameter uncertainty, Bai (2003) did the conditional approach of Wooldridge (in an infinite dimensional space).”
Tests for Skewness, Kurtosis, and Normality for Time Series Data (2005, methodology): “…use the block bootstrap © 2005 American Statistical Association Journal of Business & Economic Statistics January 2005, Vol. 23, No. 1 DOI 10.1198/073500104000000271 49 method to obtain the critical values, or use martingale transformation methods (as in Bai 2003) to obtain distribution-free tests.”
Comparing Density Forecasts via Weighted Likelihood Ratio Tests (2007, unknown): “(1998) adopted mainly qualitative tools for testing the iid U(0,1) behavior of the transformed data, formal tests of the same hypothesis were suggested by Berkowitz (2001), Hong and White (2005), and Hong (2000). Tests that account for parameter estimation uncertainty were proposed by Hong and Li (2”