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Ex‐post and ex‐ante prediction of unobserved economic time series: a case study
Author(s) -
Nieto Fabio H.
Publication year - 1998
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/(sici)1099-131x(199801)17:1<35::aid-for673>3.0.co;2-3
Subject(s) - econometrics , macro , context (archaeology) , economics , econometric model , series (stratigraphy) , ex ante , variable (mathematics) , macroeconomics , computer science , mathematics , paleontology , mathematical analysis , biology , programming language
In several countries, some macro‐economic variables are not observed frequently (e.g. quarterly) and economic authorities need estimates of these high‐frequency figures to make econometric analyses or to follow closely the country's economic growth. Two problems are involved in this context. The first is to make these estimates after observing low‐frequency values and some related indicators, and the second is to obtain predictions using just the observed indicators, i.e. before observing a new low‐frequency figure. This paper gives a new optimal solution to the first problem, and solves the second using a recursive optimal approach. In the second situation, additionally, statistical tests are developed for detecting structural changes at current periods in the macro‐economic variable involved. © 1998 John Wiley & Sons, Ltd.