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Top incomes, heavy tails, and rank-size regressions

Schluter, Christian - In: Econometrics 6 (2018) 1, pp. 1-16

In economics, rank-size regressions provide popular estimators of tail exponents of heavy-tailed distributions. We discuss the properties of this approach when the tail of the distribution is regularly varying rather than strictly Pareto. The estimator then over-estimates the true value in the...

Persistent link: https://www.econbiz.de/10011995211

On Tail Index Estimation for Dependent, Heterogenous Data

Hill, Jonathan B. - EconWPA - 2005

In this paper we analyze the asymptotic properties of the popular distribution tail index estimator by B. Hill (1975) for possibly heavy- tailed, heterogenous, dependent processes. We prove the Hill estimator is weakly consistent for processes with extremes that form mixingale sequences, and...

Persistent link: https://www.econbiz.de/10005556320

Gaussian Tests of "Extremal White Noise" for Dependent, Heterogeneous, Heavy Tailed Time Series with an Application

Hill, Jonathan B. - EconWPA - 2004

We develop asymptotically chi-squared tests of tail specific extremal serial dependence for possibly heavy-tailed time series, including infinite variance and infinite mean processes. Our test statistics have a chi-squared limit distribution under the null of "extremal white-noise" for processes...

Persistent link: https://www.econbiz.de/10005119202

On diagnostic checking of vector ARMA-GARCH models with Gaussian and Student-t innovations

Wang, Yongning; Tsay, Ruey S. - In: Econometrics 1 (2013) 1, pp. 1-31

model checking. A residual-based bootstrap method is provided and demonstrated as an effective way to approximate the …

Persistent link: https://www.econbiz.de/10010421289

Bias-correction in vector autoregressive models: A simulation study

Engsted, Tom; Pedersen, Thomas Q. - In: Econometrics 2 (2014) 1, pp. 45-71

compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models …

Persistent link: https://www.econbiz.de/10010421293

Statistical inference on the Canadian middle class

Davidson, Russell - In: Econometrics 6 (2018) 1, pp. 1-18

normality. Bootstrap inference can be expected to be more reliable, and appropriate bootstrap procedures are proposed. As an … enough for asymptotic and bootstrap inference to be almost identical, but that, in the twenty-first century, the bootstrap …

Persistent link: https://www.econbiz.de/10011995215

Testing for a set of linear restrictions in VARMA models using autoregressive metric: An application to Granger causality test

DiIorio, Francesca; Triacca, Umberto - In: Econometrics 2 (2014) 4, pp. 203-216

In this paper we propose a test for a set of linear restrictions in a Vector Autoregressive Moving Average (VARMA) model. This test is based on the autoregressive metric, a notion of distance between two univariate ARMA models, M0 and M1, introduced by Piccolo in 1990. In particular, we show...

Persistent link: https://www.econbiz.de/10011755267

Asymptotic distribution and finite sample bias correction of QML estimators for spatial error dependence model

Liu, Shew Fan; Yang, Zhenlin - In: Econometrics 3 (2015) 2, pp. 376-411

In studying the asymptotic and finite sample properties of quasi-maximum likelihood (QML) estimators for the spatial linear regression models, much attention has been paid to the spatial lag dependence (SLD) model; little has been given to its companion, the spatial error dependence (SED) model....

Persistent link: https://www.econbiz.de/10011755286

On bootstrap inference for quantile regression panel data: A Monte Carlo study

Galvão Júnior, Antônio Fialho; Montes-Rojas, Gabriel - In: Econometrics 3 (2015) 3, pp. 654-666

This paper evaluates bootstrap inference methods for quantile regression panel data models. We propose to construct … confidence intervals for the parameters of interest using percentile bootstrap with pairwise resampling. We study three different … bootstrapping procedures. First, the bootstrap samples are constructed by resampling only from cross-sectional units with …

Persistent link: https://www.econbiz.de/10011755298

Testing for A Set of Linear Restrictions in VARMA Models Using Autoregressive Metric: An Application to Granger Causality Test

Iorio, Francesca Di; Triacca, Umberto - In: Econometrics 2 (2014) 4, pp. 203-216

In this paper we propose a test for a set of linear restrictions in a Vector Autoregressive Moving Average (VARMA) model. This test is based on the autoregressive metric, a notion of distance between two univariate ARMA models, M0 and M1, introduced by Piccolo in 1990. In particular, we show...

Persistent link: https://www.econbiz.de/10011105155