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

Autor:	Jinyong Hahn, Maurizio Mazzocco, Guido M. Kuersteiner
Rok vydání:	2020
Předmět:	Economics and Econometrics Series (mathematics) Conditional independence Autocorrelation Applied mathematics Estimator Sample (statistics) Limit (mathematics) Time series Social Sciences (miscellaneous) Complement (set theory) Mathematics
Zdroj:	Econometric Theory. 38:942-958
ISSN:	1469-4360 0266-4666
DOI:	10.1017/s0266466620000316
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::71a941e072b1f213828e66218f3fd8de https://doi.org/10.1017/s0266466620000316 Zobrazit plný text záznamu