Program Overview

Applied Econometrics and Data Analysis Undergraduate Certificate

Overview

Those with economics degrees are in high demand in a large number of occupations, whether in business or government; students with advanced econometrics skills who understand how to apply these techniques in real-world settings are in even higher demand. This Certificate in Applied Econometrics and Data Analysis is designed to provide the education needed for employment in analysis positions in business or government. The Certificate is a valuable credential for economics majors with a quantitative focus, (applied) math majors, and selected students from other social sciences.

Certificate Requirements

The Certificate consists of 6 courses met through 3 required courses and 3 electives which must be selected from the list below. At least 4 of these courses must be completed in residency at UMSL.

• Required Courses:
  • ECON 4100: Introduction to Econometrics (4 credits)
  • ECON 4110: Applied Econometrics (4 credits)
  • ECON 4120: Time Series Econometrics for Economics and Finance (4 credits) or ECON 4130: Business and Economic Forecasting
• Electives: The remaining 3 electives must come from the following list:
  • ECON 4040: Booms and Busts in the Economy: Data and Theory
  • ECON 4120: Time Series Econometrics for Economics and Finance (if course not used above)
  • ECON 4130: Business and Economic Forecasting (if course not used above)
  • ECON 4160: Geospatial Analysis in the Social Sciences
  • MATH 4200: Mathematical Statistics I
  • MATH 4210: Mathematical Statistics II
  • POL SCI 4040: Survey Research Practicum in Political Science
  • PSYCH 4365: Psychological Testing and Assessment
  • SOC 4040: Survey Research Practicum for Sociology
  • SOC 3221: Qualitative Methods in Social Research
  • SOC 4312: Sociology of Wealth and Poverty

Learning Outcomes

Upon completion of the program, certificate earners will be able to:

• Use statistical software to estimate, analyze, and interpret economic relationships applying regression analysis techniques to data.
• Develop appropriate econometric models using real-world data to make management or policy recommendations in a variety of professional settings.
• Apply key concepts of estimation and forecasting in a time series context.