Notes on Time Series Analysis, ARIMA Models and Signal Extraction
AbstractPresent practice in applied time series work, mostly at economic policy or data producing agencies, relies heavily on using moving average filters to estimate unobserved components in time series, such as the seasonally adjusted series, the trend, or the cycle. The purpose of the present paper is to provide an informal introduction to the time series analysis tools and concepts required by the user or analyst to understand the basic methodology behind the application of filters.
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Bibliographic InfoPaper provided by Banco de Espa�a in its series Banco de Espa�a Working Papers with number 0012.
Length: 73 pages
Date of creation: 2000
Date of revision:
time series; economic policy; seasonal fluctuations;
Find related papers by JEL classification:
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
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