Box-Jenkins Model

Box-Jenkins Model

A methodology that makes forecasts of future economic behavior by applying a best fit model to past behavior. In using the model, one applies an autoregressive moving average to past data. In order to do this accurately, one must identify the data being measured and ensure it is independent of other variables, define the parameters of investigation, and check the model. The model is used in econometrics.
References in periodicals archive ?
The world cotton price forecasting by using Box-Jenkins model.
The ARIMA model (Autoregressive Integrated Moving Average), known also as the Box-Jenkins Model, uses only stationary series (mean and variance are constant).
Data obtained through the Box-Jenkins model, which were applied to develop index forecasting for trading volume of options on futures contracts, tend to show a decrease in the value question.
5]; Appendix) was formulated for the Box-Jenkins model developed in step 2.
The Box-Jenkins model resembles the OLS model with a few technical embellishments.
The box-jenkins model includes several major steps.
Several statistical packages can be used for estimating the parameters of a Box-Jenkins model using this method.
Typically, effective fitting of Box-Jenkins models requires at least a moderately long series.
Box and Jenkins (1976) first explained the ARIMA method, and ARIMA models are frequently signified to as Box-Jenkins models.
The control charts applied to the residuals of one-step-ahead forecasts based on the Box-Jenkins models of reported cases of measles exhibited no irregular behaviour.
Still, it's nice to sit down and watch your computer do most of the thinking for you, spitting out solutions to complex Box-Jenkins models every two seconds (if you have a built-in math coprocessor) or every thirty seconds (if you don't).
Pierce and Haugh [1977] have shown that Box-Jenkins models estimated for such working series will preserve the causal relationships that exist between the variables.