Coursework for the M.A. in Applied Economics is 30 credits. The program structure is designed to be completed in one-year, but also has an option to those who wish to pursue it at a slower pace in 1.5 years.

Program Structure

  • Three 3-credit core courses in economics (Microeconomics, Macroeconomics and Econometrics). 
  • Seven 3-credit elective courses.

In total, students take ten 3-credit courses to complete the 30 credits of the program.

One-year Completion

First Semester 

(Fall or Spring)

Second Semester

 (Spring or Fall)

Summer Semester

Advanced Microeconomics

Elective 2

Elective 6

Advanced Macroeconomics

Elective 3

Elective 7

Econometrics

Elective 4

Elective 1

Elective 5

One-and-a-half year Completion

First Semester 

(Fall or Spring)

Second Semester 

(Fall or Spring)

Third Semester 

(Fall or Spring)

Advanced Microeconomics

Elective 1

Elective 5

Advanced Macroeconomics

Elective 2

Elective 6

Econometrics

Elective 3

Elective 7

Elective 4

  • Elective Courses

    • Experimental Economics    
    • Economic Development    
    • Environment and Economics
    • Energy and the Environment
    • Technology and Economics
    • Urban Economics
    • Sustainable Finance and Impact Investing
    • Big Data for Economics
    • Cryptoeconomics and Blockchain
    • Ethical Challenges of AI
    • Survey Design 
    • Politics and Development
    • Global Agriculture and Food Security 
    • International Organizations and Development
    • Program Management
    • Data analysis
    • Softwares for visualization and data analysis
    • PSY - Psychology of Work (Partnership with Psychology)
    • PSY - Leadership in Organizations (Partnership with Psychology)
    • PSY - Personality Psychology (Partnership with Psychology)
    • DA - Introduction to Data Science and Python (Partnership with Computer Science)
    • DA - Introduction to Machine Learning (Partnership with Computer Science)
    • DA - Data Visualization with Tableau (Partnership with Computer Science)
    • DA  - Business Data Analytics (Partnership with Computer Science)