Open AccessMonte Carlo Test for Stochastic Trend in Space State Models for the Location-Scale Family
Author(s) -
Ivair Ramos Silva,
Dulcidia Carlos Guezimane Ernesto,
Fernando Luiz Pereira de Oliveira,
Reinaldo Marques,
Anderson Castro Soares de Oliveira
Publication year - 2021
Publication title -
brazilian review of econometrics
Language(s) - English
Resource type - Journals
eISSN - 2526-3722
pISSN - 1980-2447
DOI - 10.12660/bre.v40n22020.81082
Subject(s) - monte carlo method , series (stratigraphy) , state space , computer science , scale (ratio) , term (time) , point (geometry) , econometrics , statistical physics , mathematical optimization , mathematics , statistics , paleontology , physics , quantum mechanics , biology , geometry
In space state models for time series, a key point is the decision between modeling the trend of non-stationary processes through a deterministic or a stochastic term. The present paper introduces a Monte Carlo hypothesis test procedure to guide in such a decision. The method works for any time series distribution belonging to the location-scale family. The proposed method provides an alpha-level test for any time series of length greater than 3 and it does not demand assumptions on the distribution of the trend term when it is actually stochastic.