Weak Identification of Long Memory with Implications for Inference

Jia Li (), Peter Phillips, Shuping Shi and Jun Yu
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Jia Li: Singapore Management University

No 8-2022, Economics and Statistics Working Papers from Singapore Management University, School of Economics

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 (search for similar items in EconPapers)
JEL-codes: C12 C13 C58 (search for similar items in EconPapers)
Pages: 49 pages
Date: 2022-06-18
New Economics Papers: this item is included in nep-sea
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Citations: View citations in EconPapers (1)

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