Migration correlation: Definition and efficient estimation |
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| Affiliation: | 1. Institute of Finance, University of Lugano, Via Buffi 13, 6900 Lugano, Switzerland;2. Laboratoire Finance-Assurance, CREST, 15 Bd Gabriel Péri, 92245 Malakoff Cedex, France;3. Department of Economics, University of Toronto, 150 St. George Str., Toronto, Ontario M5S3G7, Canada;1. International Monetary Fund, 700 19th St., NW, Washington, DC 20431, USA;2. Monash University, Faculty of Business and Economics, Clayton Campus, VIC 3800, Australia;3. Bank of England, Threadneedle St., London EC2R 8AH, United Kingdom;1. College of Information and Communication Engineering, Sungkyunkwan University, Republic of Korea;2. Laboratory of Discrete Optimization in Operations Research, Sobolev Institute of Mathematics, Russia;3. School of Engineering and Technology, Indiana University-Purdue University Indianapolis, USA;1. Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Xueyuan Avenue, Shenzhen 51805, China;2. North Dakota State University, Fargo 58108-6050, USA;3. Technological Institute of Lamia, Lamia 35100, Greece;4. University of Thessaly, Volos 38221, Greece;5. Wayne State University, Detroit 48202, USA;1. Department of Mechanical Engineering, Stanford University, Stanford, CA 94305-4040, USA;2. Centro de Investigación en Ecosistemas de la Patagonia (CIEP), Conicyt Regional/CIEP R10C1003, Universidad Austral de Chile, Ignacio Serrrano 509, Coyhaique, Chile |
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| Abstract: | The aim of this paper is to explain why cross-sectional estimated migration correlations displayed in the academic and professional literature can be either not consistent, or inefficient, and to discuss alternative approaches. The analysis relies on a model with stochastic migration in which the parameters of interest, that are migration correlations, are precisely defined. The impossibility of estimating consistently the migration correlations from cross-sectional data only is emphasized. We explain how to handle with individual rating histories, how to weight appropriately the cross-sectional estimators and how to estimate efficiently the joint migration probabilities at longer horizons. |
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