ORIGINAL RESEARCH article
Front. Appl. Math. Stat.
Sec. Statistics and Probability
Volume 11 - 2025 | doi: 10.3389/fams.2025.1673247
This article is part of the Research TopicFrontiers in Information Technology, Electronics, and Management InnovationView all 3 articles
The Smooth Transition Autoregressive Models for the Unemployment Rate of Latvia
Provisionally accepted
- Riga Technical University, Riga, Latvia
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To model potential structural shifts in the data that depend on their historical values, different smooth transition autoregressive models are constructed and compared for the changes in the unemployment rate among 15–75-year-old residents of Latvia, including the popular LSTAR, ESTAR, and LSTAR2 models, as well as the recently introduced ASTAR model with an asymmetric transition function. For their estimation, the special modifications of the only available function in the tsDyn package of R software for the classical logistic smooth transition autoregressive model (LSTAR) are used. The constructed models are also compared with a linear autoregressive model (AR), an autoregressive model with GARCH errors, and a self-exciting threshold model. The first lag of the dependent variable and the inflation rate are used as the threshold variables. LSTAR2 with the first lag as the threshold variable gives the best fit compared to the other constructed models for these data. However, other STAR models may provide a significantly better out-of-sample forecast. Compared by RMSE, the ASTAR out-of-sample forecast performs best among different horizons. Using the inflation rate as the external threshold variable does not improve the model. The study indicates that the new R functions may be useful for economic data analysis.
Keywords: time series, Autoregressive model, Threshold autoregression, smooth transitionautoregressive model, Threshold variable, LSTAR, ESTAR
Received: 29 Jul 2025; Accepted: 14 Oct 2025.
Copyright: © 2025 Pavlenko. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Oksana Pavlenko, oksana.pavlenko@rtu.lv
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