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Building Scenarios of Multiple Time Series that Take into Account the Effects of an Expected Intervention
Author(s) -
Guerrero Víctor M.,
Silva Eliud,
Gómez Nicolás
Publication year - 2014
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.2271
Subject(s) - series (stratigraphy) , econometrics , autoregressive model , intervention (counseling) , time series , time horizon , computer science , economics , mathematics , statistics , mathematical optimization , psychology , paleontology , psychiatry , biology
We consider a forecasting problem that arises when an intervention is expected to occur on an economic system during the forecast horizon. The time series model employed is seen as a statistical device that serves to capture the empirical regularities of the observed data on the variables of the system without relying on a particular theoretical structure. Either the deterministic or the stochastic structure of a vector autoregressive error correction model of the system is assumed to be affected by the intervention. The information about the intervention effect is just provided by some linear restrictions imposed on the future values of the variables involved. Formulas for restricted forecasts with intervention effects and their mean squared errors are derived as a particular case of Catlin's static updating theorem. An empirical illustration uses Mexican macroeconomic data on five variables and the restricted forecasts consider targets for years 2011–2014. Copyright © 2013 John Wiley & Sons, Ltd.