Characterizing a Time Series Using SAS Software

Attempts to quantify the economic and financial relationships between variables with the help of econometric techniques extend back to the founding of the Econometric Society in 1930.1 Over the past 20 years, the breadth of applications of time series analysis has expanded, with analysts relying extensively on real-world data and statistical software. These applications have extended far beyond the limited realm of traditional macroeconomics, and analysts who employ such methods extend far beyond the academic world. Much of the core economic and financial data utilized in applied econometric analysis is now available online and, in some cases, for a small cost. Furthermore, data often is available for use in a statistical analysis in a user-friendly format, such as Excel. Over the years, data collection methods have improved, increasing the scope of the data available.

Software that incorporates key econometric techniques has become an essential element of modern-day quantitative analysis. Such software produces statistical results in a few minutes, rather than hours, for routine techniques such as regression analysis. Until the late 1980s, it usually took researchers several days to estimate a regression. Researchers had to manually collect the data, format it to fit the needs of the statistical model, and finally calculate the results. While today's data processing is much quicker and relatively inexpensive, the risk is ...

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