The Certificate in Quantitative Economics (CQE) is awarded to students who complete the demanding course requirements in economics, statistics, mathematics, and computer science, as well as demonstrating familiarity with important quantitative computer tools. It is open to students in any major, but will be most readily completed by those majoring in economics with a minor or double major in mathematics, statistics, computer science, or mathematical statistics.
Students who have completed the CQE will have developed skills necessary for graduate programs in economics, statistics, business administration, finance, and quantitative finance, among others, as well as for positions in consulting, investment banking, actuarial science, financial operations and more.
The certificate is awarded at the end of the spring semester for graduating students, and is entered on the student’s official transcript. It is also a valuable entry on resumes.
Students wishing to pursue the certificate must have at least a 3.0 overall gpa and must maintain a 3.0 average in the courses required for the certificate. Students should complete the online application form when starting the certificate and meet with the CQE advisor. In their last semester at Rutgers, they will meet with the advisor to certify completion of all requirements.
Note that many of the required courses have prerequisites and thus the program should be started early and students must plan their schedules carefully to satisfy all requirements.
Equivalent transfer courses for any of the requirements, accepted by the appropriate department, will be accepted for the CQE.
In well-justified circumstance, the CQE advisor can allow substitution of comparable courses for up to two of the required courses.
REQUIRED COURSES AND PROFICIENCIES in economics, mathematics, statistics, computer science, and quantitative tools.
ECONOMICS (220) – 6 COURSES
All four of the following:
102 Introduction to Microeconomics
103 Introduction to Macroeconomics
320 Intermediate Microeconomics
And two advanced courses from the following
At least one from:
400 Advanced Time Series and Financial Econometrics*
401 Advanced Cross-sectional and Panel Econometrics*
421 Economic Forecasting and Big Data*
If needed, the other from:
220:409 Computational Research Methods for Economics
220:481 Economics of Uncertainty
220:482 Game Theory
220:483 Economics of Information
220:485 Advanced Microeconomic Theory
640:485 Introduction to Mathematical Finance
MATHEMATICS (640) – 4 courses
151,152 Calculus for Mathematical and Physical Sciences OR 191,192 Honors Calculus or equivalent;
Note: 135 will be accepted in place of 151 but 640:136 does not satisfy the prerequisites for 640:251
640:250 Linear Algebra
640:251 Multivariable Calculus (or 640:291 Honors Multivariable Calculus)
STATISTICS (960 or 640) – 2 courses
960:381 Theory of Probability
960:382 Theory of Statistics
NOTES: Mathematical Theory of Probability (640:477) and Theory of Statistics (640:481) can substitute for 381, 382– students considering a major or minor in math should normally take these courses.
The two-course sequence (960:381-382 or 640:477,481) can substitute for the economics statistics requirement (285)
COMPUTER SCIENCE (198) – 2 courses
111 Introduction to Computer Science
112 Data Structures
To earn the CQE, students must demonstrate advanced proficiency with Excel (pivot tables, macros) and at least basic proficiency in each of the following quantitative application areas (there can be overlaps). This can be demonstrated through a completed course which required use of the tool, through a research project employing the tool, or by other means in consultation with the CQE advisor.
- programming language (python, java, other)
- statistical package (R, SAS, Gauss, Eviews, other)
- graphics or analytics package (tableau, other)
- database (SQL,other)
OTHER COURSES OF INTEREST
198:142 Data 101: Data Literacy R (also offered as 198:143 – hybrid version)
198:170 Computer Application for Business
960:390 Introductory Computing for Statistics (1 credit course teaching SAS)
960:486 Computing and Graphics in Applied Statistics