Estudo de testes para tendência em séries temporais

Abstract

The time series methodology is an important tool when using data over time. The time series can be composed of the components trend (Tt), seasonality (St) and the random error (at). In this sense, this work aims to study the tests used to analyze the trend component, which were: Pettitt, Run, Mann-Kendall, Cox-Stuart and the unit root tests (Dickey-Fuller, Dickey-Fuller Augmented and Zivot and Andrews), given that there is a discrepancy between the test results found in the literature. The four series analyzed were the maximum temperature in the city of Lavras, the unemployment rate in the Metropolitan Region of São Paulo (RMSP), the Broad Consumer Price Index (IPCA) and the nominal Gross Domestic Product (GDP) of Brazil. It was

found that the unit root tests showed similar results in relation to the presence of the stochas- tic trend for all series. Furthermore, the turning point of the Pettitt test diverged from all the

structural breaks found through the Zivot and Andrews test, except for the GDP series. There- fore, it was found that the trend tests diverged, obtaining similar results only in relation to the unemployment series.