Finding starting-values for maximum likelihood estimation of vector STAR models
AbstractThis paper focuses on finding starting-values for maximum likelihood estimation of Vector STAR models. Based on a Monte Carlo exercise, different procedures are evaluated. Their performance is assessed w.r.t. model fit and computational effort. I employ i) grid search algorithms, and ii) heuristic optimization procedures, namely, differential evolution, threshold accepting, and simulated annealing. In the equation-by-equation starting-value search approach the procedures achieve equally good results. Unless the errors are cross-correlated, equation-by-equation search followed by a derivative-based algorithm can handle such an optimization problem sufficiently well. This result holds also for higher-dimensional VSTAR models with a slight edge for the heuristic methods. Being faced with more complex Vector STAR models for which a multivariate search approach is required, simulated annealing and differential evolution outperform threshold accepting and the grid with a zoom. --
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Bibliographic InfoPaper provided by ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research in its series ZEW Discussion Papers with number 13-076.
Date of creation: 2013
Date of revision:
Vector STAR model; starting-values; optimization heuristics; grid search; estimation; non-linearieties;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-11-14 (All new papers)
- NEP-CMP-2013-11-14 (Computational Economics)
- NEP-ECM-2013-11-14 (Econometrics)
- NEP-ETS-2013-11-14 (Econometric Time Series)
- NEP-ORE-2013-11-14 (Operations Research)
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- Lyra, M. & Paha, J. & Paterlini, S. & Winker, P., 2010.
"Optimization heuristics for determining internal rating grading scales,"
Computational Statistics & Data Analysis,
Elsevier, vol. 54(11), pages 2693-2706, November.
- Marianna Lyra & Johannes Paha & Sandra Paterlini & Peter Winker, 2008. "Optimization Heuristics for Determining Internal Rating Grading Scales," Working Papers 005, COMISEF.
- Marianna Lyra & Johannes Paha & Sandra Paterlini & Peter Winker, 2008. "Optimization Heuristics for Determining Internal Rating Grading Scales," Center for Economic Research (RECent) 023, University of Modena and Reggio E., Dept. of Economics.
- Marianna Lyra & Johannes Paha & Sandra Paterlini & Peter Winker, 2009. "Optimization Heuristics for Determining Internal Rating Grading Scales," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 09031, Universita di Modena e Reggio Emilia, Facoltà di Economia "Marco Biagi".
- Francesco Battaglia & Mattheos Protopapas, 2009.
"Time-varying Multi-regime Models Fitting by Genetic Algorithms,"
- Francesco Battaglia & Mattheos K. Protopapas, 2011. "Time‐varying multi‐regime models fitting by genetic algorithms," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(3), pages 237-252, 05.
- Peter Winker & Dietmar Maringer, 2009. "The convergence of estimators based on heuristics: theory and application to a GARCH model," Computational Statistics, Springer, vol. 24(3), pages 533-550, August.
- Makram El-Shagi, 2010.
"An Evolutionary Algorithm for the Estimation of Threshold Vector Error Correction Models,"
IWH Discussion Papers
1, Halle Institute for Economic Research.
- Makram El-Shagi, 2011. "An evolutionary algorithm for the estimation of threshold vector error correction models," International Economics and Economic Policy, Springer, vol. 8(4), pages 341-362, December.
- Felix Chan & Michael McAleer, 2002. "Maximum likelihood estimation of STAR and STAR-GARCH models: theory and Monte Carlo evidence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 509-534.
- Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
- Schleer, Frauke & Semmler, Willi, 2014.
"Financial sector-output dynamics in the euro area: Non-linearities reconsidered,"
ZEW Discussion Papers
13-068 [rev.], ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
- Schleer, Frauke & Semmler, Willi, 2013. "Financial sector-output dynamics in the euro area: Non-linearities reconsidered," ZEW Discussion Papers 13-068, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
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