Saturday, September 3, 2022

Long memory and weak ID

I've thus far never been a big fan of the weak ID literature.  Always seemed to me that if you wind up with weak ID, it's time to think harder about the underlying economics rather than fancier econometrics.  But this opened my eyes and changed my mind.  Totally cool.  

 Weak Identification of Long Memory with Implications for Inference

By:Jia Li (Singapore Management University); Peter C. B. Phillips (Cowles Foundation, Yale University, University of Auckland, Singapore Management University, University of Southampton); Shuping Shi (Macquarie University); Jun Yu (Singapore Management University)
Abstract:This paper explores weak identification issues arising in commonly used models of economic and financial time series. Two highly popular configurations are shown to be asymptotically observationally equivalent: one with long memory and weak autoregressive dynamics, the other with antipersistent shocks and a near-unit autoregressive root. We develop a data-driven semiparametric and identification-robust approach to inference that reveals such ambiguities and documents the prevalence of weak identification in many realized volatility and trading volume series. The identification-robust empirical evidence generally favors long memory dynamics in volatility and volume, a conclusion that is corroborated using social-media news flow data.
Keywords:Realized volatility; Weak identification; Disjoint confidence sets, Trading volume, Long memory
JEL:C12 C13 C58

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