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Detecting Relevant Interactions in High Dimensional Data Analysis

So, Mike K. P. - 2014

In high dimensional data, relevant interactions can be difficult to identify due to the extremely large number of possible interactions among variables. Conventional methods use a screening stage to vastly reduce the dimension of the variable space before examining the interaction effect....

Persistent link: https://www.econbiz.de/10013045217

Optimal Instruments in Time Series : A Survey

Anatolyev, Stanislav - 2006

This article surveys estimation in stationary time series models using the approach of optimal instrumentation. We review tools that allow construction and implementation of optimal instrumental variables estimators in various circumstances - in single- and multi-period models, in the absence...

Persistent link: https://www.econbiz.de/10014056578

Valid Edgeworth Expansions for the Whittle Maximum Likelihood Estimator for Stationary Long-Memory Gaussian Time Series

Andrews, Donald W. K.; Lieberman, Offer - 2003

In this paper, we prove the validity of an Edgeworth expansion to the distribution of the Whittle maximum likelihood estimator for stationary long-memory Gaussian models with unknown parameter theta in Theta subset R^{d_theta) . The error of the (s-2)-order expansion is shown to be...

Persistent link: https://www.econbiz.de/10014116712

Identification and frequency domain quasi-maximum likelihood estimation of linearized dynamic stochastic general equilibrium models

Qu, Zhongjun; Tkachenko, Denis - In: Quantitative economics : QE ; journal of the … 3 (2012) 1, pp. 95-132

This paper considers issues related to identification, inference, and computation in linearized dynamic stochastic general equilibrium (DSGE) models. We first provide a necessary and sufficient condition for the local identification of the structural parameters based on the (first and) second...

Persistent link: https://www.econbiz.de/10011756473

Testing for Reverse Causation and Omitted Variable Bias in Regressions

Marvell, Thomas B. - 2020

or missing variable bias), an important and intractable problem in many disciplines. The test is simple: one selects a …

Persistent link: https://www.econbiz.de/10012848483

Testing for Reverse Causation and Omitted Variable Bias in Regressions

Marvell, Thomas B. - 2022

regressors. This paper shows that this often does not occur if the regression suffers from simultaneity or omitted variable bias … test for the presence of simultaneity or omitted variable bias, important and intractable problems in many disciplines. The …. Simultaneity or omitted variable bias is indicated if t-ratios and coefficients undergo these trends with more collinearity. The …

Persistent link: https://www.econbiz.de/10013308808

Testing of the mean reversion parameter in continuous time models

Iglesias, Emma M. - In: Economics letters 122 (2014) 2, pp. 187-189

Persistent link: https://www.econbiz.de/10010395196

On the Choice of the Unit Period in Time Series Models

Fuleky, Peter - University of Hawai'i Economic Research Organization … - 2011

When estimating the parameters of a process, researchers can choose the reference unit of time (unit period) for their study. Frequently, they set the unit period equal to the observation interval. However, I show that decoupling the unit period from the observation interval facilitates the...

Persistent link: https://www.econbiz.de/10010933408

On the Choice of the Unit Period in Time Series Models

Fuleky, Peter - Department of Economics, University of Hawaii-Manoa - 2011

Persistent link: https://www.econbiz.de/10009321240

Theoretical and empirical differences between diagonal and full Bekk for risk management

Allen, David E.; McAleer, Michael - 2017

BEKK. The results of non-parametric tests suggest evidence of considerable bias in the Full BEKK estimates. The results of …

Persistent link: https://www.econbiz.de/10011699474