Testing Models of Low‐Frequency Variability

By Ulrich K. Müller, Mark W. Watson. 2006

120 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/0ca3d6fd804ad12a04625ec4e98444321dcfbb11

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Finance

Citations in the corpus

Low-Frequency Econometrics (2015, methodology): “The covariance matrix Σ for each of these models is given in Müller and Watson (2008), and can be approximated using the appropriate choice of Ξ for the finite-sample methods in Section 2: the covariance matrix for the LTUM can be approximated using the autocovariances of a stationary AR(1) process…”
Consideration of Trends in Time Series (2011, background): “A more elaborate recent suggestion by Mueller and Watson (2008) proposed approximating the low frequency component of a series by a number of ltered components.”
A Test Against Spurious Long Memory (2011, background): “This work is also related to that of Müller and Watson (2008), who discussed a general framework for testing for low-frequency variability.”
Testing for long memory in the presence of non-linear deterministic trends with Chebyshev polynomials (2016, unknown): “…of the error term ut, the coefficients in (7) can be estimated by standard ordinary least square/generalized least square (OLS/GLS) methods.5 The same happens in our 3 Alternative formulations of low frequency variability using also cosine transformations can be found in Müller and Watson (2008).”
Measuring Uncertainty about Long-Run Predictions (2016, background): “Müller and Watson (2008, 2012) discuss this issue in detail.”
t-Statistic Based Correlation and Heterogeneity Robust Inference (2010, background): “The rest of the paper is organized as follows: Section 2 reviews the small sample result by Bakirov and Székely (2005), and discusses the large sample validity and consistency of the t-statistic approach.”
The asymptotic size and power of the augmented Dickey–Fuller test for a unit root (2018, background): “Such tests have been considered by Breitung (2002), Müller and Watson (2008), and Nielsen (2009).”