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Dynamic factor analysis of nonstationary multivariate time series

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  • Peter Molenaar
  • Jan Gooijer
  • Bernhard Schmitz

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  • Peter Molenaar & Jan Gooijer & Bernhard Schmitz, 1992. "Dynamic factor analysis of nonstationary multivariate time series," Psychometrika, Springer;The Psychometric Society, vol. 57(3), pages 333-349, September.
    • Handle: RePEc:spr:psycho:v:57:y:1992:i:3:p:333-349
    DOI: 10.1007/BF02295422
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    References listed on IDEAS

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    1. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
    2. Peter Molenaar, 1985. "A dynamic factor model for the analysis of multivariate time series," Psychometrika, Springer;The Psychometric Society, vol. 50(2), pages 181-202, June.
    3. Hirotugu Akaike, 1987. "Factor analysis and AIC," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 317-332, September.
    4. Bekker, Paul A., 1989. "Identification in restricted factor models and the evaluation of rank conditions," Journal of Econometrics, Elsevier, vol. 41(1), pages 5-16, May.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Fei Gu & Kristopher J. Preacher & Emilio Ferrer, 2014. "A State Space Modeling Approach to Mediation Analysis," Journal of Educational and Behavioral Statistics, , vol. 39(2), pages 117-143, April.
    2. Chang, Lei & Gan, Xiaojun & Mohsin, Muhammad, 2022. "Studying corporate liquidity and regulatory responses for economic recovery in COVID-19 crises," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 211-225.
    3. Lyhagen, Johan, 2005. "The exact covariance matrix of dynamic models with latent variables," Statistics & Probability Letters, Elsevier, vol. 75(2), pages 133-139, November.
    4. Ortega, Jose Antonio & Poncela, Pilar, 2005. "Joint forecasts of Southern European fertility rates with non-stationary dynamic factor models," International Journal of Forecasting, Elsevier, vol. 21(3), pages 539-550.
    5. Carfora, Alfonso & Scandurra, Giuseppe & Thomas, Antonio, 2022. "Forecasting the COVID-19 effects on energy poverty across EU member states," Energy Policy, Elsevier, vol. 161(C).
    6. Peter Molenaar, 1999. "Comment on fitting MA time series by structural equation models," Psychometrika, Springer;The Psychometric Society, vol. 64(1), pages 91-94, March.
    7. Eichler, Michael & Motta, Giovanni & von Sachs, Rainer, 2011. "Fitting dynamic factor models to non-stationary time series," Journal of Econometrics, Elsevier, vol. 163(1), pages 51-70, July.
    8. Stef Buuren, 1997. "Fitting arma time series by structural equation models," Psychometrika, Springer;The Psychometric Society, vol. 62(2), pages 215-236, June.
    9. Xiaochun Jiang & Wei Sun & Peng Su & Ting Wang, 2019. "The Synergy of Financial Volatility between China and the United States and the Risk Conduction Paths," Sustainability, MDPI, vol. 11(15), pages 1-22, August.
    10. Montfort, Kees van & Bijleveld, Catrien, 1997. "Dynamic analysis of multivariate panel data with nonlinear transformations," Serie Research Memoranda 0054, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    11. Nikolaos Zirogiannis & Yorghos Tripodis, 2018. "Dynamic factor analysis for short panels: estimating performance trajectories for water utilities," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(1), pages 131-150, March.
    12. Galeano, Pedro, 2001. "Multivariate analysis in vector time series," DES - Working Papers. Statistics and Econometrics. WS ws012415, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. Peter Molenaar & John Nesselroade, 2001. "Rotation in the dynamic factor modeling of multivariate stationary time series," Psychometrika, Springer;The Psychometric Society, vol. 66(1), pages 99-107, March.

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