Evaluation of multiple-imputation procedures for three-mode component models

Ginkel, Joost van; Kroonenberg, Pieter M.

doi:10.1080/00949655.2017.1355368

Cited by 3 publications

(1 citation statement)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The full lists of variables that constitute each financial section are listed in the Appendix 1, Kroonenberg 2017). A relatively more robust interpolation approach will increase the accuracy of each cycle estimated in this study.…”

Section: Data Descriptionmentioning

confidence: 99%

Characterising cycles exhibited by important financial sections in the South African economy

Wet

Botha

2019

Journal of Economic and Financial Sciences

View full text Add to dashboard Cite

Motivation for the study: Financial cycles are complex, making them hard to measure and understand. This, in turn, makes financial cycles and the effect of fluctuations in financial cycles hard to predict and manage.Research design, approach and method: Principal component analyses were used to construct an index for these South African financial sections. The Christiano-Fitzgerald (CF) band-pass filter was used to extract cycles from these South African financial indexes. Finally, spectral density analysis was used to characterise the cyclical duration exhibited by each South African financial section. The time horizon of this study ranges from 01/01/1975 to 01/12/2017, a 42year period. Main findings:The analysis showed that the South African credit cycle has the longest duration among all the South African financial sections and has a duration longer than that of the traditional business cycle. The cycles of other South African financial sections provided no clear evidence of durations longer than the traditional business cycle. Furthermore, South African interest rate conditions and South African economic confidence measures exhibit the largest amplitude. Practical/managerial implications:The findings of this study can be used to enhance the efficiency of policies to manage cyclical fluctuations of important South African financial cycles and help other economic participants to anticipate cyclical fluctuations and thereby manage the potential effects of such fluctuations. Contribution/value-add:The results in this study therefore offer value to both policymakers and other economic participants, such as asset managers, who need to make decisions related to cyclical fluctuations in South African financial conditions.

show abstract

Section: Data Descriptionmentioning

confidence: 99%

Characterising cycles exhibited by important financial sections in the South African economy

Wet

Botha

2019

Journal of Economic and Financial Sciences

View full text Add to dashboard Cite

show abstract

Handling Missing Data in Principal Component Analysis Using Multiple Imputation

Ginkel

2023

Methodology of Educational Measurement and Assessment

View full text Add to dashboard Cite

Principal component analysis (PCA) is a widely used tool for establishing the dimensional structure in questionnaire data. Whenever questionnaire data are incomplete, the missing data need to be treated prior to carrying out a PCA. Several methods exist for handling missing data prior to carrying out a PCA. The current chapter first discusses the most recent developments regarding the treatment of missing data in PCA. Next, of these methods, the method that is most promising both from a theoretical and practical point of view will be discussed in more detail, namely, multiple imputation. Finally, some extensions of multiple imputation to other PCA-related techniques or to statistics within PCA beyond the basics are discussed, and some general recommendations regarding the use of PCA on multiply imputed datasets in different statistical software packages will be given.

show abstract