Panel data econometrics : common factor analysis for empirical researchers / Donggyu Sul

By:

Sul, Donggyu, 1965- [VerfasserIn]

Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Publisher: London ; New York : Routledge, 2019Description: 1 Online-RessourceISBN:

9780429423765

Subject(s):

Additional physical formats: 9781138389663. | 9781138389670. | Erscheint auch als: Panel data econometrics. Druck-Ausgabe London and New York : Routledge, 2019. xiii, 150 SeitenRVK: RVK: QH 330LOC classification:

H61.26

Online resources:

Zugang im Netz des KIT

Summary: 2.4.2 Hierarchical factor model3 Factor number identification; 3.1 A step-by-step procedure for determining the factor number; 3.2 Information criteria and alternative methods; 3.3 Standardization and prewhitening; 3.4 Practice: factor number estimation; 3.4.1 STATA practice with crime rates; 3.4.2 STATA practice with price indices; 3.4.3 Practice with GAUSS; 3.4.4 Practice with MATLAB; 4 Decomposition of panel: estimation of common and idiosyncratic components; 4.1 Measurement of accuracy: order in probability; 4.2 Estimation of the common factorsSummary: 4.2.1 Cross-sectional average (CSA) approach4.2.2 Principal component estimator; 4.2.3 Comparison between two estimators for the common factors; 4.3 Estimation of the idiosyncratic components; 4.4 Variance decomposition; 4.5 Cross-sectional dependence and level of aggregation; 4.5.1 General static factor structure; 4.5.2 Hierarchical factor structure; 4.6 Practice: common factors estimation; 4.6.1 GAUSS practice I: principal component estimation; 4.6.2 GAUSS practice II: standardization and estimation of PC factors; 4.6.3 MATLAB practice; 4.6.4 STATA practiceSummary: 5 Identification of Common Factors5.1 Difference between statistical and latent factors; 5.2 Asymptotically weak factors approach; 5.2.1 Single-factor case; 5.2.2 Multi-factor case; 5.2.3 Some tips to identify latent factors; 5.2.4 Application: testing homogeneity of factor loadings; 5.3 Residual-based approach; 5.4 Empirical example: exchange rates; 5.5 Practice: identifying common factors; 5.5.1 MATLAB practice I: leadership model; 5.5.2 MATLAB practice II: multiple variables as single factor; 5.5.3 Practice with GAUSS; 5.5.4 Practice with STATA; 6 Static and dynamic relationshipsSummary: 6.1 Static and dynamic relationship under cross-sectional independence6.1.1 Spurious cross-sectional regression; 6.1.2 Spurious pooled OLS estimator; 6.1.3 Time series and panel-fixed effect regressions; 6.1.4 Between-group estimator; 6.2 Static and dynamic relationship under cross-sectional dependence; 6.2.1 Homogeneous factor loadings; 6.2.2 Heterogeneous factor loadings: factor-augmented panel regression; 6.2.3 Cross-sectional regressions with nonstationary common factors; 6.3 Practice: factor-augmented and aggregation regressions; 6.3.1 Practice with GAUSS I: common-dynamic relationshipSummary: Cover; Half Title; Title; Copyright; CONTENTS; List of figures; List of tables; Preface; 1 Basic structure of panel data; 1.1 Meaning of fixed effect; 1.1.1 Fixed effects with non-trended data; 1.1.2 Fixed effects with trended panel data; 1.2 Meaning of common components; 1.2.1 Aggregation or macro factor; 1.2.2 Source of cross-sectional dependence; 1.2.3 Central location parameter; 1.3 Meaning of idiosyncratic components; 2 Statistical models for cross-sectional dependence; 2.1 Spatial dependence; 2.2 Gravity model; 2.3 Common factor approach; 2.4 Other variations; 2.4.1 Dynamic factor modelPPN: PPN: 1685652794Package identifier: Produktsigel: BSZ-4-NLEBK-FROGFH | BSZ-4-NLEBK-KAUB | ZDB-4-NLEBK

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