DICTIONARY
Macroeconometrics and Time Series Analysis
This selection of articles balances important theoretical concerns with key empirical debates to provide an overview of this important theme. These are, of course, just some of the many articles from the Dictionary on this theme.
aggregation (econometrics) by Thomas M. Stoker
ARCH models by Oliver B. Linton
Bayesian methods in macroeconometrics by Frank Schorfheide
Bayesian time series analysis by Mark F. J. Steel
central limit theorems by Werner Ploberger
cointegration by Mark W. Watson
continuous and discrete time models by Christopher A. Sims
data filters by Timothy Cogley
equlibrium-correction models by David F. Hendry
Forecasting by Clive Granger
Fractals by Laurent E. Calvert
functional central limit theorems by Werner Ploberger
generalized method of moments estimation by Lars Peter Hansen
Granger-Sims causality by G. M. Kuersteiner
heteroskedasticity and autocorrelation corrections by Kenneth D. West
impulse response function by Helmut Lütkepohl
Kalman and particle filtering by Jesús Fernández-Villaverde
law(s) of large numbers by Werner Ploberger
long memory models by P. M. Robinson
nonlinear time series analysis by Bruce Mizrach
prediction formulas by Charles H. Whiteman and Kurt F. Lewis
rational expectations by Thomas J. Sargent
regime switching models by James D. Hamilton
seasonal adjustment by Svend Hylleberg
serial correlation and serial dependence by Yongmiao Hong
SNP: nonparametric time series analysis by A. Roland Gallant
spectral analysis by Timothy J. Vogelsang
spline functions by Dale J. Poirier
spurious regressions by Clive W. J. Granger
state space models by Andrew Harvey
stochastic Volatility Models by Neil Shephard
structural change, econometrics of by Pierre Perron
structural vector autoregressions by Jesús Fernández-Villaverde and Juan F. Rubio-Ramírez
threshold models by Timo Teräsvirta
time series analysis by Francis X. Diebold, Lutz Kilian and Marc Nerlove
trend/cycle Decomposition by Charles R. Nelson
unit roots by Peter C. B. Phillips
variance decomposition by Helmut Látkepohl
varying coefficient models by Andros Kourtellos and Thanasis Stegnos
vector autoregressions by Tao Zha
wavelets by James B. Ramsey
