@article{5b4bf575b67a4e488fbceff15425c044,
title = "Moving average threshold heterogeneous autoregressive (MAT-HAR) models",
abstract = "We propose moving average threshold heterogeneous autoregressive (MAT-HAR) models as a novel combination of heterogeneous autoregression (HAR) and threshold autoregression (TAR). The MAT-HAR has multiple groups of lags of a target series, and a threshold term can appear in each group. The threshold is a moving average of lagged target series, which guarantees time-varying thresholds and simple estimation via least squares. We show via Monte Carlo simulations that the MAT-HAR has sharp in-sample and out-of-sample performance. An empirical application on the industrial production of Japan suggests that significant threshold effects exist, and the MAT-HAR has a higher forecast accuracy than the HAR.",
keywords = "heterogeneous autoregression (HAR), model selection, out-of-sample forecast, threshold autoregression (TAR), time series analysis",
author = "Kaiji Motegi and Xiaojing Cai and Shigeyuki Hamori and Haifeng Xu",
note = "Funding Information: We thank Marcus Chambers, Eric Ghysels, and conference participants at the 88th Annual Meeting of the Southern Economic Association for helpful comments. The third author is grateful for the financial support of JSPS KAKENHI (Grant No.?(A) 17H00983). The fourth author is grateful for the financial support of the National Natural Science Foundation of China (Grant No.?71801184), Natural Science Foundation of Fujian Province (Grant No.?2018J01114), and the Fundamental Research Funds for the Central Universities (Grant No.?20720171022). Funding Information: We thank Marcus Chambers, Eric Ghysels, and conference participants at the 88th Annual Meeting of the Southern Economic Association for helpful comments. The third author is grateful for the financial support of JSPS KAKENHI (Grant No. (A) 17H00983). The fourth author is grateful for the financial support of the National Natural Science Foundation of China (Grant No. 71801184), Natural Science Foundation of Fujian Province (Grant No. 2018J01114), and the Fundamental Research Funds for the Central Universities (Grant No. 20720171022). Publisher Copyright: {\textcopyright} 2020 John Wiley & Sons, Ltd.",
year = "2020",
month = nov,
day = "1",
doi = "10.1002/for.2671",
language = "English",
volume = "39",
pages = "1035--1042",
journal = "Journal of Forecasting",
issn = "0277-6693",
publisher = "John Wiley and Sons Ltd",
number = "7",
}