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The Bias of the Gini Coefficient due to Grouping
Ourti, Tom Van; Clarke, Philip - 2008
We propose a first order bias correction term for the Gini index to reduce the bias due to grouping. The first order … reveals an intuitive formula for the remaining second order bias which is useful in empirical analyses. We analyze the … it reduces a considerable share of the bias due to grouping. …
Persistent link: https://www.econbiz.de/10010325812
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The Bias of the Gini Coefficient Due to Grouping : Revisiting First-Order Corrections
Van Ourti, Tom - 2008
We propose a first order bias correction term for the Gini index to reduce the bias due to grouping. The first order … reveals an intuitive formula for the remaining second order bias which is useful in empirical analyses. We analyze the … it reduces a considerable share of the bias due to grouping …
Persistent link: https://www.econbiz.de/10012722922
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Measurement Error in Education and Growth Regressions
Portela, Miguel; Alessie, Rob; Teulings, Coen N. - 2004
the measurement error. The standard attenuation bias suggests that using these corrected data would lead to a higher …
Persistent link: https://www.econbiz.de/10010325186
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Stationarity and Ergodicity of Univariate Generalized Autoregressive Score Processes
Blasques, Francisco; Koopman, Siem Jan; Lucas, Andre - 2012
We characterize the dynamic properties of Generalized Autoregressive Score (GAS) processes by identifying regions of the parameter space that imply stationarity and ergodicity. We show how these regions are affected by the choice of parameterization and scaling, which are key features of GAS...
Persistent link: https://www.econbiz.de/10010326396
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Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models
Mesters, Geert; Koopman, Siem Jan; Ooms, Marius - 2011
An exact maximum likelihood method is developed for the estimation of parameters in a non-Gaussian nonlinear log-density function that depends on a latent Gaussian dynamic process with long-memory properties. Our method relies on the method of importance sampling and on a linear Gaussian...
Persistent link: https://www.econbiz.de/10010326501
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Asymmetries in Conditional Mean and Variance: Modelling Stock Returns by asMA-asQGARCH
Brännäs, Kurt; de Gooijer, Jan G. - 2000
variancefunctions. In a genuine out-of-sample forecasting experiment theperformance of the best fitted asMA-asQGARCH model is compared …
Persistent link: https://www.econbiz.de/10010324389
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Combined Forecasts from Linear and Nonlinear Time Series Models
Terui, N.; van Dijk, Herman K. - 2000
Combined forecasts from a linear and a nonlinear model areinvestigated for timeseries with possibly nonlinear characteristics. The forecasts arecombined by aconstant coefficient regression method as well as a time varyingmethod. Thetime varying method allows for a locally (non)linear model....
Persistent link: https://www.econbiz.de/10010324396
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The Monetary Exchange Rate Model as a Long-Run Phenomenon
Groen, Jan J.J. - 1998
Pure time series-based tests fail to find empirical support formonetary exchange rate models. In this paper we apply pooled timeseries estimation on a forward-looking monetary model, resulting inparameter estimates which are in compliance with the underlyingtheory. Based on a panel version of...
Persistent link: https://www.econbiz.de/10010324410
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Testing for Integration using Evolving Trend and Seasonals Models: A Bayesian Approach
Koop, Gary; van Dijk, Herman K.; Hoek, Henk - 1997
In this paper, we make use of state space models to investigate the presence of stochastic trends in economic time series. A model is specified where such a trend can enter either in the autoregressive representation or in a separate state equation. Tests based on the former are analogous to...
Persistent link: https://www.econbiz.de/10010324436
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Modelling Economic High-Frequency Time Series
Lundbergh, Stefan; Teräsvirta, Timo - 1999
In this paper we introduce the STAR-STGARCH model that can characterizenonlinear behaviour both in the conditional mean and the conditionalvariance. A modelling cycle for this family of models, consisting ofspecification, estimation, and evaluation stages is constructed.Misspecification tests...
Persistent link: https://www.econbiz.de/10010324484