The Second Order Logistic Smooth Transition Autoregressive Model for Unemployment Rate of Latvia

To account for structural changes in data, the second order logistic smooth transition autoregressive model (LSTAR2) is obtained as the best smooth transition model using popular R software for the differences of the unemployment rate among 15-75 years old residents of Latvia. The specially adjusted...

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Bibliographic Details
Main Authors: Pavlenko, Oksana, Zeltina, Liana
Format: Conference Proceeding
Language:English
Subjects:
autoregressive model
Data models
Economics
Estimation
Forecasting
Information technology
Logistics
Mathematical models
Predictive models
smooth transition autoregressive model
Software
threshold autoregression
time series
Unemployment
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Summary:To account for structural changes in data, the second order logistic smooth transition autoregressive model (LSTAR2) is obtained as the best smooth transition model using popular R software for the differences of the unemployment rate among 15-75 years old residents of Latvia. The specially adjusted R functions for estimation and forecasting of LSTAR2 based on the available in R package tsDyn functions for the first order logistic smooth transition autoregressive model (LSTAR1) are used. The constructed LSTAR2 model also is compared with the best chosen linear autoregressive, multiplicative seasonal autoregressive, self-exciting threshold and LSTAR1 models. LSTAR2 is superior than the compared models for these data, which indicates that the new R functions may be useful for economic data analysis.
ISSN:2771-6937
DOI:10.1109/ITMS64072.2024.10741945