Graduate Program

Graduate Program

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 Master's level course. Master's 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 560: Computational Methods for 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 9 of the required 30 semester hours of approved graduate credits (i.e., no more than 3 of the 10 required courses) may receive grades of "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.

Prerequisites

Recommended Prerequisite Coursework

In addition to fulfilling other admissions requirements, successful applicants to the Economics master's program should have completed courses in single variable and multivariable calculus, linear algebra, and  undergraduate statistical methods. At a minimum, a candidate needs to have taken a single variable calculus course and an undergraduate statistics course. 

However, applicants need not have majored in Economics and those who have majored in mathematics, computer science, physics or engineering are encouraged to apply. It is strongly recommended that applicants have taken Intermediate Microeconomics and Intermediate Macroeconomics.

Courses offered at Rutgers University that would satisfy these requirements are listed below.

Single variable calculus: 01:640:135-136 or 01:640:151-152 or 01:640:191-192
Multiple variable calculus: 01:640:251
Linear Algebra: 01:640:250
Statistics: 01:960:211-212 or 01:960:285 or 01:960:401 or 01:960:484
Intermediate Economics: 01:220:320 (Int. Microeconomics) and 01:220:321 (Int. Macroeconomics)

Example Course Schedule:

 It is expected that the program can be completed in three semesters. Below is a sample schedule for both tracks.

Doctoral Preparation Track

Fall (First Semester)

Spring (Second Semester)

Fall (Third Semester)

Econ 16:220:551 (required)

Econ 16:220:586 (required)

Econ 16:220:600 (required)

Econ 16:220:552 (required)

Econ 16:220:608, 609, or 610 (required)

Econ 16:220:601 (required)

Econ 16:220:585 (required)

1 to 2 electives

Econ 16:220:604 (required)

Econ 01:220:560 (required) 

   

Notes: A total of 1 elective is taken in this track, usually in Spring semester. Additional elective credits can be taken in excess of the 30 degree credits required.

Economic Data Analytics Track

Fall (First Semester)

Spring (Second Semester)

Fall (Third Semester)

Econ 16:220:551 (required)

Econ 16:220:586 (required)

2 to 3 electives

Econ 16:220:552 (required)

Econ 16:220:608, 609, or 610 (required)

 

Econ 16:220:585 (required)

1 to 2 electives

 

Econ 01:220:560 (required) 

   

Notes: A total of four electives are taken in this track. Candidates can take 1 to 2 electives in the Spring semester and 2 to 3 electives in the third (Fall) semester. Courses from outside economics can be substituted for electives with prior approval.

The Master of Arts degree program in Economics at Rutgers–New Brunswick provides training for students wishing to acquire an understanding of economic theory and a facility with associated quantitative methodology. The program's structure is designed to meet diverse career goals by providing students with two tracks for the completion of degree requirements: the doctoral prep option and the economic data analytics option.

Doctoral Program Preparation Option:

Students with an interest in pursuing a Ph.D. in economics will receive a rigorous grounding in micro- and macroeconomic theory, quantitative methods and mathematics that is critical for success in a research oriented doctoral program. This option will also be valuable for those interested in

  •  Learning to apply economic methodology in areas such as law, political science, accounting and marketing.
  •  Acquiring theoretical and empirical skills necessary for economic modeling in the public and private sector.

Economic Data Analytics Option:

The role of analytics and "big data" methods in the modern business environment cannot be overstated. The Rutgers M.A. program in Economics will provide exceptional training in the econometric methodologies crucial for quantitative analysis of economic models using large data sets. Graduates will be prepared to apply these methods in the solution of diverse economic problems arising in

  • Health and environmental policy
  • Government and public policy
  • Macroeconomic analysis and forecasting
  • Insurance and risk management

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Upcoming Workshops

Tue Feb 21 @ 3:00PM - 04:30PM
Macroeconomic Theory
Luis Felipe Céspedes, Universidad de Chile and Central Bank of Chile
Thu Feb 23 @ 4:00PM - 05:30PM
Econometrics
Nese Yildez, University of Rochester
Tue Feb 28 @ 3:00PM - 04:30PM
Macroeconomic Theory
Francesco Bianchi, Johns Hopkins University
Wed Mar 01 @ 3:30PM - 05:00PM
Micro Theory/Experimental Seminar
George Vachadze, CUNY
Fri Mar 03 @ 1:30PM - 03:00PM
Empirical Microeconomics
Rosanne Altshuler, Rutgers University