Compositional Time Series: Past and Present
AbstractThis survey reviews diverse academic production on compositional dynamic series analysis. Although time dimension of compositional series has been little investigated, this kind of data structure is widely available and utilized in social sciences research. This way, a review of the state-of-the-art on this topic is required for scientist to understand the available options. The review comprehends the analysis of several techniques like autoregresive integrate moving average (ARIMA) analysis, compositional vector autoregression systems (CVAR) and state space techniques but most of these are developed under Bayesian frameworks. As conclusion, this branch of the compositional statistical analysis still requires a lot of advances and updates and, for this same reason, is a fertile field for future research. Social scientists should pay attention to future developments due to the extensive availability of this kind of data structures in socioeconomic databases.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 0510002.
Length: 9 pages
Date of creation: 13 Oct 2005
Date of revision:
Note: Type of Document - pdf; pages: 9
Contact details of provider:
Web page: http://18.104.22.168
compositional data analysis; time series;
Find related papers by JEL classification:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
- C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-10-15 (All new papers)
- NEP-ECM-2005-10-15 (Econometrics)
- NEP-ETS-2005-10-15 (Econometric Time Series)
- NEP-FOR-2005-10-15 (Forecasting)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Arellano, Manuel & Bond, Stephen, 1991.
"Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations,"
Review of Economic Studies,
Wiley Blackwell, vol. 58(2), pages 277-97, April.
- Tom Doan, . "RATS program to replicate Arellano-Bond 1991 dynamic panel," Statistical Software Components RTZ00169, Boston College Department of Economics.
- Dale, Poirier J & Tobias, Justin, 2006. "Bayesian Econometrics," Staff General Research Papers 12428, Iowa State University, Department of Economics.
- Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA).
If references are entirely missing, you can add them using this form.