The flexible least squares approach to time-varying linear regression
AbstractThis study proposes a Flexible Least Squares (FLS) method for state estimation when the dynamic equations are unknown but the process state evolves only slowly over time. A smoothness prior is introduced in place of an explicit specification for the unknown dynamic equations governing the evolution of the process state. Simulation experiments illustrating the method are presented. Annotated pointers to related work can be accessed here: http://www.econ.iastate.edu/tesfatsi/flshome.htm
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Dynamics and Control.
Volume (Year): 12 (1988)
Issue (Month): 1 (March)
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Web page: http://www.elsevier.com/locate/jedc
Other versions of this item:
- Kalaba, Robert E. & Tesfatsion, Leigh S., 1988. "The Flexible Least Squares Approach to Time-Varying Linear Regression," Staff General Research Papers 11198, Iowa State University, Department of Economics.
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
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- Kalaba, Robert E. & Tesfatsion, Leigh S., 1996.
"A Multicriteria Approach to Model Specification and Estimation,"
Staff General Research Papers
1684, Iowa State University, Department of Economics.
- Kalaba, Robert & Tesfatsion, Leigh, 1996. "A multicriteria approach to model specification and estimation," Computational Statistics & Data Analysis, Elsevier, vol. 21(2), pages 193-214, February.
- Robert Kalaba & Leigh Tesfatsion, 1995. "A Multicriteria Approach to Model Specification and Estimation," Econometrics 9501001, EconWPA.
- He, Ling T., 2005. "Instability and predictability of factor betas of industrial stocks: The Flexible Least Squares solutions," The Quarterly Review of Economics and Finance, Elsevier, vol. 45(4-5), pages 619-640, September.
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"Dynamic modeling of mean-reverting spreads for statistical arbitrage,"
Computational Management Science,
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- Zsolt Darvas & BalÃ¡zs Varga, 2013. "Inflation persistence in Central and Eastern European countries," Working Papers 787, Bruegel.
- Zsolt Darvas & Balázs Varga, 2013. "Inflation Persistence in Central and Eastern European Countries," Working Papers 1302, Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest, revised Jul 2013.
- Pusse, Leo, 1998. "Export als Bestimmungsfaktor der Beschäftigung : ökonomische Analysen auf makroökonomischer Ebene (Export as a determinant of employment : econometric analyses at macroeconomic level)," Mitteilungen aus der Arbeitsmarkt- und Berufsforschung, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 31(1), pages 108-122.
- Ling He & Alan Reichert, 2003. "Time variation paths of factors affecting financial institutions and stock returns," Atlantic Economic Journal, International Atlantic Economic Society, vol. 31(1), pages 71-86, March.
- Kuethe, Todd H. & Foster, Kenneth A. & Florax, Raymond J.G.M., 2008. "A Spatial Hedonic Model with Time-Varying Parameters: A New Method Using Flexible Least Squares," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6306, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
- Zsuzsanna Zsibók & Balázs Varga, 2012. "Inflation Persistence in Hungary: a Spatial Analysis," Working Papers 1203, Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest.
- Zsolt Darvas & Balázs Varga, 2012. "Uncovering Time-Varying Parameters with the Kalman-Filter and the Flexible Least Squares: a Monte Carlo Study," Working Papers 1204, Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest.
- Tucci, Marco P., 1995. "Time-varying parameters: a critical introduction," Structural Change and Economic Dynamics, Elsevier, vol. 6(2), pages 237-260, June.
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