Data/hora: 03/06/2024 16:18:01

Provedor de dados: 	Ciência Rural	
País: 	Brazil	
Título: 	Persistence effect determination of variability in forecasting of agricultural and road machinery national production	
Autores: 	Martins,Tailon; Barreto,Alisson Castro; Coronel,Daniel Arruda; Jacobi,Luciane Flores; Lirio,Valentina Wolff; Souza,Adriano Mendonça.	
Data: 	2020-01-01	
Ano: 	2020	
Palavras-chave: 	Time series; Prediction; Volatility; Agricultural machinery; Road machinery.	
Resumo: 	ABSTRACT: The objective of this research was to forecast the Brazilian national production of agricultural and road machinery in the short term by BOX &amp; JENKINS methodology and determine the persistence effect. Data were obtained at National Association of Automotive Vehicle Manufacturers (ANFAVEA) from January 1960 to October 2019, totaling 718 monthly observations. The Autoregressive Integrated Moving Average (ARIMA) and Autoregressive Conditional Heteroscedasticity (ARCH) methodology were used. The ARIMA (2,1,1)-ARCH (2) model was fitted and persistence of 0.60 was determined, showing that the instability in the series will be for a long period of time.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782020000600351	
Editor: 	Universidade Federal de Santa Maria	
Relação: 	10.1590/0103-8478cr20190631	
Formato: 	text/html	
Fonte: 	Ciência Rural  v.50 n.6 2020	
Fonte: 	info:eu-repo/semantics/openAccess