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Testing weak cross-sectional dependence in large panels

Pesaran, M. Hashem - 2012

This paper considers testing the hypothesis that errors in a panel data model are weakly Cross-sectionally dependent (CD), using the exponent of cross-sectional dependence introduced recently in Bailey, Kapetanios and Pesaran (2012). It is shown that the implicit null of the CD test depends on...

Persistent link: https://www.econbiz.de/10009533962

Accuracy and efficiency of various GMM inference techniques in dynamic micro panel data models

Kiviet, J. F.; Pleus, Milan; Poldermans, Rutger - 2015

-Bond GMM estimation techniques for single dynamic panel data models with possibly endogenous regressors and cross …

Persistent link: https://www.econbiz.de/10010476668

General diagnostic tests for cross section dependence in panels

Pesaran, M. Hashem - 2004

This paper proposes simple tests of error cross section dependence which are applicable to a variety of panel data models, including stationary and unit root dynamic heterogeneous panels with short T and large N. The proposed tests are based on average of pair-wise correlation coefficients of...

Persistent link: https://www.econbiz.de/10011449852

Nominal and real wages in the UK, 1750 - 2015 : mean reversion, persistence and structural breaks

Caporale, Guglielmo Maria; Gil-Alaña, Luis A. - 2022

This paper analyses the stochastic properties of UK nominal and real wages over the period 1750-2015 using fractional integration techniques. Both the original series and logged ones are analysed. The results generally suggest that nominal wages exhibit a higher degree of persistence, which...

Persistent link: https://www.econbiz.de/10013417630

Testing with vectors of statistics : revisiting combined hypothesis tests with an application to specification testing

Bjerkander, Lena S.; Dovern, Jonas; Manner, Hans - 2024

the non-parametric estimation of the joint density of all subsidiary test statistics. …

Persistent link: https://www.econbiz.de/10014505804

A multiple testing approach to the regularisation of large sample correlation matrices

Bailey, Natalia; Pesaran, M. Hashem; Smith, L. Vanessa - 2014

This paper proposes a novel regularisation method for the estimation of large covariance matrices, which makes use of …

Persistent link: https://www.econbiz.de/10010361374

Testing for alpha in linear factor pricing podels with a large number of securities

Pesaran, M. Hashem; Yamagata, Takashi - 2017

-Gaussianity and general forms of weakly cross correlated errors. It does not require estimation of an invertible error covariance …

Persistent link: https://www.econbiz.de/10011646274

Natural resources : curse or blessing?

Ploeg, Frederick van der - 2010

Are natural resources a "curse" or a "blessing"? The empirical evidence suggests either outcome is possible. The paper surveys a variety of hypotheses and supporting evidence for why some countries benefit and others lose from the presence of natural resources. These include that a resource...

Persistent link: https://www.econbiz.de/10003986863

Robust standard errors in transformed likelihood estimation of dynamic panel data models

Hayakawa, Kazuhiko; Pesaran, M. Hashem - 2012

This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao … trivial due to the incidental parameters problem that arises, and its implications for estimation and inference. We approach …-sectional heteroskedasticity ; Monte Carlo simulation ; GMM estimation …

Persistent link: https://www.econbiz.de/10009570680

Transformed maximum likelihood estimation of short dynamic panel data models with interactive effects

Hayakawa, Kazuhiko; Pesaran, M. Hashem; Smith, L. Vanessa - 2014

This paper proposes the transformed maximum likelihood estimator for short dynamic panel data models with interactive fixed effects, and provides an extension of Hsiao et al. (2002) that allows for a multifactor error structure. This is an important extension since it retains the advantages of...

Persistent link: https://www.econbiz.de/10010358963

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