Uniform Asymptotic Normality in Stationary and Unit Root Autoregression

• Main Authors: HAN, Chirok, PHILLIPS, Peter C. B., SUL, Donggyu
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2011
• Subjects: Aggregating information; Asymptotic normality; Bias Reduction; Differencing; Efficiency; Full aggregation; Maximum likelihood estimation; Econometrics
• Online Access: https://ink.library.smu.edu.sg/soe_research/1823; https://ink.library.smu.edu.sg/context/soe_research/article/2822/viewcontent/UniformAsymptoticNormality_2010_pp.pdf
• Institution: Singapore Management University

While differencing transformations can eliminate nonstationarity, they typically reduce signal strength and correspondingly reduce rates of convergence in unit root autoregressions. The present paper shows that aggregating moment conditions that are formulated in differences provides an orderly mech...