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Complex Reduced Rank Models For Seasonally Cointegrated Time Series
Author(s) -
Cubadda Gianluca
Publication year - 2001
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/1468-0084.00231
Subject(s) - estimator , rank (graph theory) , econometrics , series (stratigraphy) , statistics , monte carlo method , inference , statistical inference , mathematics , cointegration , representation (politics) , sample (material) , regression analysis , regression , computer science , paleontology , combinatorics , chemistry , chromatography , artificial intelligence , politics , political science , law , biology
This paper introduces a new representation for seasonally cointegrated variables, namely the complex error correction model, which allows statistical inference to be performed by reduced rank regression. The suggested estimators and tests statistics are asymptotically equivalent to their maximum likelihood counterparts. The small sample properties are evaluated by a Monte Carlo study and an empirical example is presented to illustrate the concepts and methods.