Of course nobody can really see the future. But modern statistical methods,
econometric models and business intelligence software can help businesses
to make forecasts, and they can also help them to estimate what is going to
happen in the future.
What is Dynamic Regression?
Dynamic Regression is a regression model that includes lagged values of
explanatory variables or of dependent variables or both. The relationship
between the forecast variable and the explanatory variable is modeled using
a transfer function. A dynamic regression model can predict what will happen
if the explanatory variable changes.
The Dynamic Regression model is similar to
Regression Analysis, but it
is believed to produce more realistic results, because it emphasizes the ripple
effects the input variables can have on the dependent variable. For example,
a price change made today might influence sales volumes in a variety of ways
for many future periods.
Book: Jeffrey Wooldridge
- Introductory Econometrics: A Modern Approach -
Book: Russell Davidson,
James G. Mackinnon - Econometric Theory and Methods -
Book: Alan Pankratz
- Forecasting with Dynamic Regression Models -
Dynamic Regression Special Interest Group
Dynamic Regression Education & Events
Compare with: Regression Analysis
| Exponential Smoothing
| ARIMA |
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