On the choice of the unit period in time series models
AbstractWhen estimating the parameters of a process, researchers can choose the reference unit of time (unit period) for their study. Frequently, they set the unit period equal to the observation interval. However, I show that decoupling the unit period from the observation interval facilitates the comparison of parameter estimates across studies with different data sampling frequencies. If the unit period is standardized across these studies, then the parameters will represent the same attributes of the underlying process, and their interpretation will be independent of the sampling frequency.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Economics Letters.
Volume (Year): 19 (2012)
Issue (Month): 12 (August)
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Other versions of this item:
- Peter Fuleky, 2011. "On the Choice of the Unit Period in Time Series Models," Working Papers 201111, University of Hawaii at Manoa, Department of Economics.
- Peter Fuleky, 2011. "On the Choice of the Unit Period in Time Series Models," Working Papers 2011-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
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- Veronika Czellar & G. Andrew Karolyi & Elvezio Ronchetti, 2005.
"Indirect Robust Estimation of the Short-term Interest Rate Process;,"
Research Papers by the Department of Economics, University of Geneva
2005.02, Département des Sciences Économiques, Université de Genève.
- Czellar, Veronika & Karolyi, G. Andrew & Ronchetti, Elvezio, 2007. "Indirect robust estimation of the short-term interest rate process," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 546-563, September.
- Czellar, Veronika & Karolyi, G. Andrew & Ronchetti, Elvezio, 2005. "Indirect Robust Estimation of the Short-term Interest Rate Process," Working Paper Series 2005-4, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
- Veronika Czellar & G. Andrew Karolyi & Elvezio Ronchetti, 2005. "Indirect Robust Estimation of the Short-term interest Rate Process," FAME Research Paper Series rp135, International Center for Financial Asset Management and Engineering.
- Ball, Clifford A. & Torous, Walter N., 1996. "Unit roots and the estimation of interest rate dynamics," Journal of Empirical Finance, Elsevier, vol. 3(2), pages 215-238, June.
- Andrew W. Lo, 1986.
"Maximum Likelihood Estimation of Generalized Ito Processes with Discretely Sampled Data,"
NBER Technical Working Papers
0059, National Bureau of Economic Research, Inc.
- Lo, Andrew W., 1988. "Maximum Likelihood Estimation of Generalized Itô Processes with Discretely Sampled Data," Econometric Theory, Cambridge University Press, vol. 4(02), pages 231-247, August.
- Andrew W. Lo, . "Maximum Likelihood Estimation of Generalized Ito Processes with Discretely Sampled Data," Rodney L. White Center for Financial Research Working Papers 15-86, Wharton School Rodney L. White Center for Financial Research.
- Bergstrom, A. R., 1988. "The History of Continuous-Time Econometric Models," Econometric Theory, Cambridge University Press, vol. 4(03), pages 365-383, December.
- Chan, K C, et al, 1992.
" An Empirical Comparison of Alternative Models of the Short-Term Interest Rate,"
Journal of Finance,
American Finance Association, vol. 47(3), pages 1209-27, July.
- Tom Doan, . "RATS programs to replicate CKLS(1992) estimation of interest rate models," Statistical Software Components RTZ00035, Boston College Department of Economics.
- Millimet, Daniel L. & McDonough, Ian K., 2013. "Dynamic Panel Data Models with Irregular Spacing: With Applications to Early Childhood Development," IZA Discussion Papers 7359, Institute for the Study of Labor (IZA).
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