Economic Statistical Analysis

Economic statistical analysis helps researchers explain economic events and support theories.

Statistical methods and techniques comprise important tools by which economists analyze economic data and forecast the economy's future direction. Within the field of economics, statistical analysis has become a specialty of its own known as econometrics. Economic statistical analysis enables researchers to scientifically study economic phenomena, and provide empirical evidence for economic theories and government policies.

Identification

Econometrics, or economic measurement, applies mathematical and statistical methods to the study of economic phenomena. Economists and econometricians use complex equations (known as models) and statistical analysis software, such as SAS and SPSS, to analyze extensive economic data from government agencies, financial institutions and other sources. Through these techniques of economic statistical analysis, econometricians and others strive to find empirical evidence to explain economic phenomena and lend support to theories.

Features

Regression analysis is a favored technique of economic statistical analysis. This procedure analyzes the impact of one or more predictors (known as independent variables) on a particular outcome, or dependent variable. For example, an economist studying U.S. teacher salaries might examine how such predictors as experience, geographic location, type of degree and other predictors might influence salary levels. Regression analysis, in short, tries to predict or estimate the values of a dependent variable based on the known values of a series of independent variables.

Types

Three main types of regression analysis include cross-sectional, time series and pooled regression, named after the types of data on which the analyses are conducted. Data collected at a single point in time are cross-sectional. Examples include public opinion polls by the Gallup organization and others, as well as the U.S. Census, taken every 10 years. Time series data are collected on the same variables at regular intervals, such as weekly, monthly or quarterly. Examples include monthly unemployment figures, the monthly Consumer Price Index or the quarterly Gross Domestic Product. Pooled data combine cross-sectional and time series elements. Damodar Gujarati, author of "Basic Econometrics," a popular textbook in graduate and undergraduate econometrics classes, cites the U.S. Commerce Department's housing census, which interviews the same households periodically to trace changes in living conditions, as an example of pooled data.

Benefits

Econometric analysis lends empirical support to economic theories, which are generally qualitative statements. For example, economic theory holds that the price of a product or service will increase as the demand for it rises. Economic statistical analysis provides numerical evidence for gauging how much the price will increase in response to higher demand (or lower supply). Statistical analysis also helps economists and other researchers examine the impacts--intended and unintended--of public policies, as well as provides important research findings that could inform future policies aimed at issues related to economic policy, health care, education and other public issues. For example, statistical analysis of a policy boosting the minimum wage could find that the higher wages increased living standards for low-income workers; however, it also could reveal higher unemployment among low-skilled people as an unintended consequence.

Considerations

Because economic researchers analyze statistical data collected from the real world of economic activity, rather than in a controlled laboratory experiment, they must be aware of possible measurement errors. Econometrics includes a series of analytical methods used by statistical analysts to identify and deal with measurement errors in the data.

References

• "Basic Econometrics, 3rd ed."; Damodar N. Gujarati; 1995
• "Guide to Econometrics, 3rd ed."; Peter Kennedy; 1993

Resources

• Econometrics.org
• State University of New York at Oswego: Econometric Resources on the Internet