Program Requirements

Formal credit requirements

Candidates have two options for completion of degree requirements:

      1. The doctoral preparation option
      2. The economic data analytics option

Both options require 30 credits of course work. Satisfactory academic progress will require that students who have attempted 12 or fewer credits have earned a GPA of at least 2.5; those who have attempted 13 or more credits must have earned a GPA of at least 3.0. No more than 9 credits of coursework bearing grades of C or C+ may be used to meet degree requirements. More than one grade of "U" in courses that are graded S/U also constitutes a failure to maintain satisfactory academic progress.

Each course in the program lasts one semester and carries three credits. The required 18 credits of core course work consists of one course in mathematical methods (Introduction to mathematical Economics), two courses in economic theory (Advanced Microeconomic Theory  and Advanced Macroeconomic Theory) and two courses in quantitative economics (Introduction to Econometrics plus either Applied Econometrics for Microeconomics or Applied Econometrics for Macroeconomics).

Three (3) upper level undergraduate courses (with appropriately different workload) can be substituted for a Masters level course. Masters students, at the discretion of the Graduate Program Director, may be allowed to take PhD level courses (course numbers 600 and above).

   Doctoral Program Preparation Option: In addition to the 18 credits of core coursework, this option requires 12 elective credits chosen from the doctoral prep elective offerings, 6 of which must be Economics 600 and Economics 601 (or Economics 603 and Economics 604). In addition, the student must write an expository essay as described in the Economic Data Analytics option below.

  Economic Data Analytics Option: In addition to the 18 credits of core coursework, this option requires 12 elective credits chosen from the data analytics elective offerings. In addition, the student must write an expository essay in a field of economics that was covered in the student's course work. It may be a paper written as part of a course in economics, or it may be based on such a course. No extra credit is given for the preparation of the essay. The essay must be approved by a member of the graduate faculty of economics.

First Semester Required Core Courses:

Economics 551: Introduction to Mathematical Economic

Economics 552: Introduction to Econometrics

            Economics 585: Advanced Microeconomic Theory

            Economics 420: Computational Methods for Research in Economics

 Second Semester:   

            Economics 586:  Advanced Macroeconomic Theory (required)

            Economics 609: Econometrics for Micro OR Economics 610: Econometrics for Macro

Two elective courses

Third Semester

            Doctoral Prep option: Economics 600 and 601 OR Economics 603 and 604.

            Data Analytics option: two elective courses   

Recommended Doctoral Prep elective courses may be chosen from:

            Economics 600: Mathematical Methods for Microeconomics (Fall only)

            Economics 601: Microeconomic Theory 1 (Fall only)

            Economics 603: Mathematical Methods for Macroeconomics (Fall only)

            Economics 604: Macroeconomic Theory I (Fall Only)

            Economics 620: Economics of the Labor Market

            Economics 624: Public Finance 1

            Economics 628: International Economics 1

            Economics 641: Uncertainty and Imperfect Information

            Economics 642: Topics in Game Theory

            Economics 644: Networks and Complexity in Economics

Recommended Data Analytics elective courses may be chosen from:     

            Economics 560: Computational Methods for Economics

            Economics 570: Economic Data Science: Elements of Machine Learning Methods

            Economics 607: Econometrics 1

            Economics 608: Econometrics 2

            Economics 630: Financial Economics 1

            Economics 631: Financial Economics 2

            Economics 716: Seminar in Applied Econometrics

            Economics 571: Economic Forecasting and Big Data

            Economics 422: Advanced Cross-Sectional and Panel Econometrics

            Economics 423: Advanced Time Series and Financial Economics

            Economics 424: Advanced Analytics for Economic Data

            Economics 644: Networks and Complexity in Economics

            Other courses in computational methods in economics and econometrics will be added.

            Other electives from the doctoral prep electives listed below.

Note: In addition to these courses, students may take, with permission, appropriate Masters level courses from computer science and statistics.

Academic Standing

The minimum cumulative grade-point average required for graduation is 3.0 for all courses taken at Rutgers after admission to the MA program. In addition, no more than 6 of the required 30 semester-hours of approved graduate credits, and no more than 2 of the 10 required courses,  may be graded as  "C" or lower. If a student takes a course a second time, both the original grade and the repeated grade contribute to the grade-point average in the standard way (that is a poor course grade cannot be replaced in the calculation of cumulative GPA by a better grade if the course is retaken)

Transfer of Credits

Up to 9 credits of acceptable graduate credits not used to satisfy the requirements of another graduate degree may be permitted to be applied towards meeting the requirements of the Economics Masters degree. This is subject to individual consideration and approval.