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Recent Developments in Modelling Nonstationary Vector Autoregressions
Author(s) -
Mills Terence C.
Publication year - 1998
Publication title -
journal of economic surveys
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.657
H-Index - 92
eISSN - 1467-6419
pISSN - 0950-0804
DOI - 10.1111/1467-6419.00057
Subject(s) - vector autoregression , econometrics , cointegration , impulse response , economics , lag , causality (physics) , error correction model , rank (graph theory) , granger causality , structural vector autoregression , computer science , macroeconomics , mathematics , monetary policy , mathematical analysis , computer network , physics , quantum mechanics , combinatorics
In this paper we review some recent developments in the modelling of nonstationary vector autoregressions (VARs) which we feel have great potential for furthering applied researchers understanding of the relationships linking the variables making up a VAR. The developments surveyed are the use of model determination criteria in selecting lag length, trend order and cointegrating rank, causality testing in vector error correction models, FM‐VAR estimation of levels VARS, common trends and cycles analysis, permanent and transitory decompositions, impulse response asymptotics, and the links between cointegrated VARs and structural models. The techniques are illustrated by applications to the modelling of U.K. equities, dividends and interest rates.