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Home > Academics > Undergraduate > Economics >
Economics
Course Description

EXPANDED
Economics 164
Econometrics and Business Forecasting

Description
Researchers in virtually every scientific discipline use regression analysis to quantify the relationships among variables. Many variables of interest to economists exhibit patterns not typically seen in the data collected by, say, biologists or physicists. To handle analytical problems specific to economic data, economists have developed a panoply of specialized statistical methods. “Econometrics” is not as narrowly specialized a subject as the name suggests, however. It encompasses not only those methods favored almost exclusively by economists, but also the standard regression techniques used in many disciplines. This introductory course in econometrics covers only the core concepts of classical regression analysis, and nearly everything you will learn is applicable in any quantitative discipline.

The twin goals of the course are for you (1) to understand the basic theory of regression analysis, and (2) to know how to carry out your own regression analysis using standard regression software. Once you understand some of the theory and some of the practical issues that lie behind regression estimates, you will be a more discriminating consumer of the numerical estimates that you encounter almost daily. Regression models underlie, for example, estimates of the male/female wage gap, of racial discrimination in mortgage lending, of the effectiveness of a new drug, of the impact of executive compensation on share price, of the impact of air pollution on child health, of the effect of congressional term limits on political fundraising, of the relative riskiness of two financial assets, of the number of deaths attributable to tobacco, of the impact of carbon taxes on CO2 emissions, of the bridge toll needed to reduce bridge traffic by 20 percent, of house buyers’ willingness to pay for school districts with higher test scores, of an FDIC-insured bank’s insolvency risk, of the harm done to economic development by corruption, or of the default risk of a VISA cardholder.

After this course, you will be able to interpret standard regression results reported in journal articles, and you will have the intellectual foundation needed for continued study in statistical modeling methods. You will also know how to organize real data in a regression-friendly format, how to use statistical software to estimate a variety of linear regression models, how to decide which model is best suited to your question, and how to report your findings.

Textbook: Using Econometrics: A Practical Guide (6th edition), by Studenmund.



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Go to: Graduate Economics

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P: 510.430.2194
E: economics@mills.edu

Last Updated: 6/22/17