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Blockwise empirical entropy tests for time series regressions
Author(s) -
Bravo Francesco
Publication year - 2005
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.2005.00398.x
Subject(s) - mathematics , wald test , series (stratigraphy) , statistics , test statistic , statistic , monte carlo method , parametric statistics , econometrics , statistical hypothesis testing , empirical likelihood , entropy (arrow of time) , time series , estimator , paleontology , physics , quantum mechanics , biology
. This paper shows how the empirical entropy (also known as exponential likelihood or non‐parametric tilting) method can be used to test general parametric hypothesis in time series regressions. To capture the weak dependence of the observations, the paper uses blocking techniques which are also used in the bootstrap literature on time series. Monte Carlo evidence suggests that the proposed test statistics have better finite‐sample properties than conventional test statistics such as the Wald statistic.