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Sequential regression : a neodescriptive approach to multicollinearity

Fickel, Norman - 2001

Classical regression analysis uses partial coefficients to measure the influences of some variables (regressors) on another variable (regressand). However, a descriptive point of view shows that these coefficients are very bad measures of influence. Their interpretation as an average change of...

Persistent link: https://www.econbiz.de/10011511033

Bayesian measures of explained variance and pooling in multilevel (hierarchical) models

Gelman, Andrew; Pardoe, Iain - 2004

Explained variance (R^2) is a familiar summary of the fit of a linear regression and has been generalized in various ways to multilevel (hierarchical) models. The multilevel models we consider in this paper are characterized by hierarchical data structures in which individuals are grouped into...

Persistent link: https://www.econbiz.de/10011513072

The maximum number of parameters for the Hausman test when the estimators are from different Sets of equations

Nawata, Kazumitsu; McAleer, Michael - 2013

Hausman (1978) developed a widely-used model specification test that has passed the test of time. The test is based on two estimators, one being consistent under the null hypothesis but inconsistent under the alternative, and the other being consistent under both the null and alternative...

Persistent link: https://www.econbiz.de/10010226558

Set identification of generalized linear predictors in the presence of non-classical measurement errors

Wüthrich, Kaspar - 2013

This paper studies the identification of coefficients in generalized linear predictors where the outcome variable suffers from non-classical measurement errors. Combining a mixture model of data errors with the bounding procedure proposed by Stoye (2007), I derive bounds on the coefficient...

Persistent link: https://www.econbiz.de/10009787993

An econometric perspective on algorithmic subsampling

Lee, Sokbae; Ng, Serena - 2020

Datasets that are terabytes in size are increasingly common, but computer bottlenecks often frustrate a complete analysis of the data. While more data are better than less, diminishing returns suggest that we may not need terabytes of data to estimate a parameter or test a hypothesis. But which...

Persistent link: https://www.econbiz.de/10012216998

Improvements in maximum likelihood estimators of truncated normal samples with prior knowledge of σ : a simulation based study with application to historical height samples

A'Hearn, Brian; Komlos, John - 2003

Researchers analyzing historical data on human stature have long sought an estimator that performs well in truncated-normal samples. This paper reviews that search, focusing on two currently widespread procedures: truncated least squares (TLS) and truncated maximum likelihood (TML). The first...

Persistent link: https://www.econbiz.de/10010440937

Finite sample results of range-based integrated volatility estimation

Rossi, Eduardo; Spazzini, Filippo - 2009

Persistent link: https://www.econbiz.de/10003899120

The dynamic Skellam model with applications

Koopman, Siem Jan; Lit, Rutger; Lucas, André - 2014

extension of numerically accelerated importance sampling techniques. We illustrate the new model by two empirical studies and …

Persistent link: https://www.econbiz.de/10010253460

Exogenous drivers of cryptocurrency volatility : a mixed data sampling approach to forecasting

Walther, Thomas; Klein, Tony - 2018

We apply the GARCH-MIDAS framework to forecast the daily, weekly, and monthly volatility of five highly capitalized … quality, we determine the most important exogenous drivers of volatility in Cryptocurrency markets. We find that the Global … Global Real Economic Activity provides superior volatility predictions for both, bull and bear markets. In addition, the …

Persistent link: https://www.econbiz.de/10011906495

On importance sampling for state space models

Jungbacker, Borus; Koopman, Siem Jan - 2005

We consider likelihood inference and state estimation by means of importance sampling for state space models with a … are presented that lead to a more effective implementation of importance sampling for state space models. An illustration … is given for the stochastic volatility model with leverage. …

Persistent link: https://www.econbiz.de/10011348357