Virginia Tech® home

Certificate in Applied Economic Analytics


The Department of Agricultural and Applied Economics, in the College of Agriculture and Life Sciences, is now offering a graduate-level certificate program in econometric, forecasting, and data analytics tools needed to succeed in modern applied economic management and related fields. This program emphasizes foundational methods spanning economic analysis, data analytics, predictive modeling, and data visualization. An emphasis is placed on relevant business and agribusiness applications. The certificate prepares students by allowing them to develop high-level skills that span applied economics, agribusiness management, and data analytics. CIP code: 01.0103

Program features

  • 100 percent online and asynchronous
  • Four 3-credit graduate courses
  • Access to expert faculty
  • Time to complete: In most cases four semesters. 
  1. Degree-seeking students may take courses in conjunction with their regular course load. 
  2. Non-degree seeking, full-time students can complete the certificate in two-to-three semesters. 
  3. Non-degree seeking, part-time students, taking one course per semester, can complete the certificate in four semesters. 

Program goals and outcomes

Students who complete the certificate program will be able to:

  1. Apply statistical properties and probability theory to agribusiness and applied economic data.
  2. Employ advanced computational, statistical, simulation, and data visualization resources using modern statistical computing packages and tools. 
  3. Construct and implement mathematical optimization models relevant to applied economic decision-making.
  4. Estimate statistical and econometric models for applied economic and agribusiness decision-making.
  5. Formulate, specify, and estimate modern forecasting models.
  6. Interpret statistical and econometric results from business, government, and academic research.
  7. Evaluate the statistical integrity of predictive models and the accuracy of alternative forecasting methods.
  8. Apply regression trees and machine learning methods to structured and unstructured data sets.

The curriculum

Mathematical and statistical methods used in applied economic decision-making. Applied mathematical optimization, numerical simulation, data visualization, and linear econometric models applied to economic, agricultural, and environmental data and problems. Extensive application of modern programming platforms used in applied economic analysis. 

Introduction to economic applications of mathematical and statistical techniques: regression, estimators, hypothesis testing, lagged variables, discrete variables, violations of assumptions, simultaneous equations, instrumental variables, and panel data methods. 

  • Susan Chen, Associate Professor and Graduate Director

Forecasting data, with a focus on basic linear and non-linear time series models. Strong emphasis on programming and computational implementation of time series model-selection techniques and practical applications.

Advanced econometric analysis of problems in agricultural and applied economics. Modern techniques in econometrics and data analytics, including multiple regression, classification, instrumental variables, clustering, and regression trees. 

  • Zhenshan Chen, Assistant Professor

Apply and view admissions requirements

Visit the Graduate School website

CIP code: 01.0103


Amy Guerin
Graduate Program Professional Coordinator

Ranked in the top 10%

AAEC is ranked in the top ten percent worldwide of Institutions and Economists in the Field of Agricultural Economics

Award-winning Faculty

Our world-class faculty hold awards for superb teaching and research. 

100+ years in education

Founded in the early 1900s to educate Virginians in agricultural and applied economics. We've been fullfilling that mission ever since.