JOINT TIME-SERIES AND CROSS-SECTION LIMIT THEORY UNDER MIXINGALE ASSUMPTIONS

Jinyong Hahn, Guido Kuersteiner and Maurizio Mazzocco

Econometric Theory, 2022, vol. 38, issue 5, 942-958

Abstract: In this paper, we complement joint time-series and cross-section convergence results derived in a companion paper Hahn, Kuersteiner, and Mazzocco (2016, Central Limit Theory for Combined Cross-Section and Time Series) by allowing for serial correlation in the time-series sample. The implications of our analysis are limiting distributions that have a well-known form of long-run variances for the time-series limit. We obtain these results at the cost of imposing strict stationarity for the time-series model and conditional independence between the time-series and cross-section samples. Our results can be applied to estimators that combine time-series and cross-section data in the presence of aggregate uncertainty in models with rationally forward-looking agents.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:cup:etheor:v:38:y:2022:i:5:p:942-958_5

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