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Some identification and estimation results for regression models with stochastically varying coefficients

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Cited by:

  1. Nnamdi Chinwendu Nwaeze & Kingsley Ikechukwu Okere & Izuchukwu Ogbodo & Obumneke Bob Muoneke & Ifeoma Nwakaego Sandra Ngini & Samuel Uchezuike Ani, 2023. "Dynamic linkages between tourism, economic growth, trade, energy demand and carbon emission: evidence from EU," Future Business Journal, Springer, vol. 9(1), pages 1-12, December.
  2. de Jong, F.C.J.M. & Kemna, A. & Kloek, T., 1992. "A contribution to event study methodology with an application to the Dutch stock market," Other publications TiSEM 7805a40a-1e85-4621-ac05-0, Tilburg University, School of Economics and Management.
  3. Bušs, Ginters, 2009. "Comparing forecasts of Latvia's GDP using simple seasonal ARIMA models and direct versus indirect approach," MPRA Paper 16684, University Library of Munich, Germany.
  4. Fabian Y.R.P. Bocart & Christian M. Hafner, 2012. "Volatility of price indices for heterogeneous goods," SFB 649 Discussion Papers SFB649DP2012-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  5. McNelis, Paul D. & Schmidt-Hebbel, Klaus, 1991. "Volatility reversal from interest rates to the real exchange rate : financial liberalization in Chile, 1975-82," Policy Research Working Paper Series 697, The World Bank.
  6. Panagiotis Samartzis & Nikitas Pittis & Nikolaos Kourogenis & Phoebe Koundouri, 2013. "Factor Models of Stock Returns: GARCH Errors versus Autoregressive Betas," DEOS Working Papers 1318, Athens University of Economics and Business.
  7. Carlo Grillenzoni, 1997. "Optimized adaptive prediction," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 6(1), pages 37-58, April.
  8. Sonia Sotoca López, 1994. "Una nota sobre la estimación eficiente de modelos con parámetros cambiantes," Documentos de Trabajo del ICAE 9408, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  9. Cheng Hsiao & M. Hashem Pesaran, 2004. "Random Coefficient Panel Data Models," CESifo Working Paper Series 1233, CESifo.
  10. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis & Panagiotis Samartzis, 2016. "Factor Models of Stock Returns: GARCH Errors versus Time‐Varying Betas," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(5), pages 445-461, August.
  11. Tommaso Proietti & Alessandra Luati, 2013. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362, Edward Elgar Publishing.
  12. Alejandra López-Pérez & Manuel Febrero-Bande & Wencesalo González-Manteiga, 2021. "Parametric Estimation of Diffusion Processes: A Review and Comparative Study," Mathematics, MDPI, vol. 9(8), pages 1-27, April.
  13. Andrew Ang & Jean Boivin & Sen Dong & Rudy Loo-Kung, 2011. "Monetary Policy Shifts and the Term Structure," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(2), pages 429-457.
  14. Winston T. Lin, 1999. "Dynamic and Stochastic Instability and the Unbiased Forward Rate Hypothesis: A Variable Mean Response Approach," Multinational Finance Journal, Multinational Finance Journal, vol. 3(3), pages 173-221, September.
  15. Lin, W.L. & Engle, R.F. & Ito, T., 1991. "Do Bulls and Bears Move Across Borders? International Transmission of Stock Returns and Volatility as the World Turns," Working papers 9121, Wisconsin Madison - Social Systems.
  16. Solimano, Andres, 1989. "How private investment reacts to changing macroeconomic conditions : the case of Chile in the 1980s," Policy Research Working Paper Series 212, The World Bank.
  17. Yoonsik Hong & Yanghoon Kim & Jeonghun Kim & Yongmin Choi, 2022. "Index Tracking via Learning to Predict Market Sensitivities," Papers 2209.00780, arXiv.org, revised Dec 2022.
  18. Lu, Xun & Su, Liangjun, 2023. "Uniform inference in linear panel data models with two-dimensional heterogeneity," Journal of Econometrics, Elsevier, vol. 235(2), pages 694-719.
  19. Enrique Sentana & Giorgio Calzolari & Gabriele Fiorentini, 2004. "Indirect Estimation of Conditionally Heteroskedastic Factor Models," Working Papers wp2004_0409, CEMFI.
  20. Lin, Chien-Fu Jeff & Terasvirta, Timo, 1999. "Testing parameter constancy in linear models against stochastic stationary parameters," Journal of Econometrics, Elsevier, vol. 90(2), pages 193-213, June.
  21. Spanos, Aris, 1989. "On Rereading Haavelmo: A Retrospective View of Econometric Modeling," Econometric Theory, Cambridge University Press, vol. 5(3), pages 405-429, December.
  22. Thomas Url, 1997. "Die Kosten des Paktes für Stabilität und Wachstum," WIFO Monatsberichte (monthly reports), WIFO, vol. 70(6), pages 373-383, June.
  23. Dacheng Liu & Tao Lu & Xu-Feng Niu & Hulin Wu, 2011. "Mixed-Effects State-Space Models for Analysis of Longitudinal Dynamic Systems," Biometrics, The International Biometric Society, vol. 67(2), pages 476-485, June.
  24. Carlo Grillenzoni, 2000. "Time-Varying Parameters Prediction," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 52(1), pages 108-122, March.
  25. Mohammed Benmoumen & Imane Salhi, 2023. "The Strong Consistency of Quasi-Maximum Likelihood Estimators for p-order Random Coefficient Autoregressive (RCA) Models," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 617-632, February.
  26. David F. Hendry & Ross Williams, 2000. "Distinguished Fellow of the Economic Society of Australia, 1999: Adrian R. Pagan," The Economic Record, The Economic Society of Australia, vol. 76(233), pages 113-115, June.
  27. Gruen, David & Pagan, Adrian & Thompson, Christopher, 1999. "The Phillips curve in Australia," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 223-258, October.
  28. Guðmundur Guðmundsson, 1998. "A model of inflation with variable time lags," Economics wp02, Department of Economics, Central bank of Iceland.
  29. Mikkelsen, Jakob Guldbæk & Hillebrand, Eric & Urga, Giovanni, 2019. "Consistent estimation of time-varying loadings in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 208(2), pages 535-562.
  30. Timothy Neal, 2016. "Multidimensional Parameter Heterogeneity in Panel Data Models," Discussion Papers 2016-15, School of Economics, The University of New South Wales.
  31. Giuseppe Storti & Cosimo Vitale, 2003. "Likelihood inference in BL-GARCH models," Computational Statistics, Springer, vol. 18(3), pages 387-400, September.
  32. Anil K. Bera & Philip Garcia & Jae-Sun Roh, 1997. "Estimation of Time-Varying Hedge Ratios for Corn and Soybeans: BGARCH and Random Coefficient Approaches," Finance 9712007, University Library of Munich, Germany.
  33. Becker, Janis & Hollstein, Fabian & Prokopczuk, Marcel & Sibbertsen, Philipp, 2019. "The Memory of Beta Factors," Hannover Economic Papers (HEP) dp-661, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  34. Mehmet Balcilar & Riza Demirer & Festus V. Bekun, 2021. "Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
  35. G. Everaert, 2007. "Estimating Long-Run Relationships between Observed Integrated Variables by Unobserved Component Methods," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/452, Ghent University, Faculty of Economics and Business Administration.
  36. Jakob Guldbæk Mikkelsen & Eric Hillebrand & Giovanni Urga, 2015. "Maximum Likelihood Estimation of Time-Varying Loadings in High-Dimensional Factor Models," CREATES Research Papers 2015-61, Department of Economics and Business Economics, Aarhus University.
  37. Tucci, Marco P., 1995. "Time-varying parameters: a critical introduction," Structural Change and Economic Dynamics, Elsevier, vol. 6(2), pages 237-260, June.
  38. Camiel de Koning & Stefan Straetmans, 1997. "Variation in the Slope Coefficient of the Fama Regression for Testing Uncovered Interest Rate Parity: Evidence from Fixed and Time-varying Coefficient Approaches," Tinbergen Institute Discussion Papers 97-014/2, Tinbergen Institute.
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