About this Course

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This course is an important part of the undergraduate stage in education for future economists. It's also useful for graduate students who would like to gain knowledge and skills in an important part of math. It gives students skills for implementation of the mathematical knowledge and expertise to the problems of economics. Its prerequisites are both the knowledge of the single variable calculus and the foundations of linear algebra including operations on matrices and the general theory of systems of simultaneous equations. Some knowledge of vector spaces would be beneficial for a student. 

The course covers several variable calculus, both constrained and unconstrained optimization. The course is aimed at teaching students to master comparative statics problems, optimization problems using the acquired mathematical tools. 
Home assignments will be provided on a weekly basis.

The objective of the course is to acquire the students’ knowledge in the field of mathematics and to make them ready to analyze simulated as well as real economic situations.

Students learn how to use and apply mathematics by working with concrete examples and exercises. Moreover this course is aimed at showing what constitutes a solid proof. The ability to present proofs can be trained and improved and in that respect the course is helpful. It will be shown that math is not reduced just to “cookbook recipes”. On the contrary  the deep knowledge of math concepts helps to understand real life situations.

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Intermediate Level

Approx. 34 hours to complete

Suggested: 8 weeks of study...

English

Subtitles: English

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 34 hours to complete

Suggested: 8 weeks of study...

English

Subtitles: English

Syllabus - What you will learn from this course

Week

1

4 hours to complete

The basics of the set theory. Functions in Rn

Week 1 of the Course is devoted to the main concepts of the set theory, operation on sets and functions in Rn. Of special attention will be level curves. Also in this week introduced definitions of sequences, bounded and compact sets, domain and limit of the function. Also from this week students will grasp the concept of continuous function.

11 videos (Total 116 min), 1 quiz

11 videos

Promo1m

1.1. Definitions and examples of sets14m

1.2. Operations on sets9m

1.3. Open balls in Rn9m

1.4. Sequences in Rn. Closed sets.10m

1.5. Bounded and compact sets10m

1.6. Functions and level curves in Rn16m

1.7. Domain and limit of a function. Continuous functions.13m

1.8. Continuity of a function. Weierstrass theorem.13m

1.9. Composite function.12m

1.10. Continuity of a composite function3m

Week

2

5 hours to complete

Differentiation. Gradient. Hessian.

Week 2 of the Course is devoted to the main concepts of differentiation, gradient and Hessian. Of special attention is the chain rule. Also students will understand economic applications of the gradient.

13 videos (Total 115 min), 2 quizzes

13 videos

2.1. Differentiation. Partial differentiation.7m

2.2. Example of differentiation. Cobb-Douglas function.9m

2.3. Tangent plane.7m

2.4. Total differential.7m

2.5. Chain rule for multivariate functions.8m

2.6. Gradient of the function.9m

2.7. Economic applications of the gradient.9m

2.8. Equation of a circumference. Smooth curves.13m

2.9. Chain rule for differentiation.10m

2.10. Linear approximation. Example of tangent plane for particular function.10m

2.11. Second-order derivatives.10m

2.12. Young's Theorem.5m

2.13. Hessian matrix.5m

1 practice exercise

Limits. Derivatives. Continuity1h

Week

3

4 hours to complete

Implicit Function Theorems and their applications.

Week 3 of the Course is devoted to implicit function theorems. In this week three different implicit function theorems are explained. This week students will grasp how to apply IFT concept to solve different problems.

12 videos (Total 93 min), 1 quiz

12 videos

3.1. Implicit functions.7m

3.2. Implicit Function Theorem.5m

3.3. Applications of the Implicit Function Theorem (part 1).10m

3.4. Applications of the Implicit Function Theorem (part 2).7m

3.5. Gradient is perpendicular to a level curve of a function.11m

3.6. Implicit function theorem for the function of many variables.6m

3.7. Example of application of the IFT for the function of many variables.8m

3.8. Implicit Function Theorem for the system of implicit functions. Jacobian matrix.10m

3.9. Example of application IFT for the system of implicit functions (part 1).8m

3.10. Example of application IFT for the system of implicit functions (part 2).7m

3.11. Example of application in microeconomics.6m

3.12. Cramer's rule.2m

Week

4

5 hours to complete

Unconstrained and constrained optimization.

Week 4 of the Course is devoted to the problems of constrained and unconstrained optimization. Of special attention are quadratic forms, critical points and their classification.

15 videos (Total 112 min), 2 quizzes

15 videos

4.1. Introduction in optimization.10m

4.2. Global max. Local max. Saddle point.9m

4.3. Unconstrained optimization.9m

4.4. Critical point. Taylor's formula.12m

4.5. Quadratic forms. Positive definiteness. Negative definiteness.7m

4.6. Sylvester's criterion (part 1).7m

4.7. Sylvester's criterion (part 2).5m

4.8. Examples of Hessians (part 1).7m

4.9. Example of Hessians (part 2).4m

4.10. Sufficient condition for a critical point to be a local maximum, a local minimum and neither of both.7m

4.11. Examples of finding and classification of critical points (part 1).6m

4.12. Examples of finding and classification of critical points (part 2).4m

4.13. Constrained optimization.9m

4.14. Lagrangian.5m

4.15. Example of constrained optimization problem.4m

1 practice exercise

Partial derivatives and unconstrained optimization.1h

Week

5

4 hours to complete

Constrained optimization for n-dim space. Bordered Hessian.

Week 5 of the Course is devoted to the extension of the constrained optimization problem to the n-dimensional space. This week students will grasp how to apply bordered Hessian concept to classification of critical points arising in different constrained optimization problems.

13 videos (Total 99 min), 1 quiz

13 videos

5.1. Example of the solution of the constrained optimization.6m

5.2. Weierstrass theorem. Compact sets.7m

5.3. Bordered Hessian.9m

5.4. Constrained optimization in general case (part 1).5m

5.5. Constrained optimization in general case (part 2).6m

5.6. Application of the bordered Hessian in the constrained optimization.7m

5.7. Generalization of the constrained optimization problem for the n variables case.8m

5.8. Example of constrained optimization for the case of more than two variables (part 1).7m

5.9. Example of constrained optimization for the case of more than two variables (part 2).9m

5.10. Example of constrained optimization problem on non-compact set.5m

5.11. Theorem for determining definiteness (positive or negative) or indefiniteness of the bordered matrix.5m

5.12. Example of application bordered Hessian technique for the constrained optimization problem.8m

5.13. Example of violating NDCQ.10m

Week

6

3 hours to complete

Envelope theorems. Concavity and convexity.

Week 6 of the Course is devoted to envelope theorems, concavity and convexity of functions. This week students will understand how to interpret Lagrange multiplier and get to learn the criteria of convexity and concavity of functions in n-dimensional space.

11 videos (Total 85 min), 1 quiz

11 videos

6.1. Envelope Theorem.8m

6.2. Envelope Theorem for constrained optimization.4m

6.3. Examples of the Envelope Theorem application (part 1).7m

6.4. Examples of the Envelope Theorem application (part 2).6m

6.5. Interpretation of the Lagrangian multiplier.10m

6.6. Relaxing assumptions using second order conditions.8m

6.7. Concave and convex functions.7m

6.8. Concave and convex functions in n-dimensional case.7m

6.9. Inequality for concave function in n-dimensional space.9m

6.10. Criteria of concavity and convexity of the function in n-dimensional space.5m

6.11. Properties of concave functions.7m

Week

7

4 hours to complete

Global extrema. Constrained optimization with inequality constraints.

Week 7 of the Course is devoted to identification of global extrema and constrained optimization with inequality constraints. This week students will grasp the concept of binding constraints and complementary slackness conditions.

11 videos (Total 96 min), 1 quiz

11 videos

7.1. How to identify global extrema? (part 1)11m

7.2. How to identify global extrema? (part 2)10m

7.3. How to identify global extrema? (part 3)12m

7.4. How to identify global extrema? (part 4)10m

7.5. Constrained optimization with inequality constraints.8m

7.6. Binding constraints. Complementary slackness conditions.5m

7.7. Constrained optimization problem with inequalities for n-dimensional space.7m

7.8. Constrained optimization problem with inequalities. Theorem.6m

7.9. Example of solving constrained optimization problem with inequalities (part 1).9m

7.10. Example of solving constrained optimization problem with inequalities (part 2).10m

7.11. Example of solving constrained optimization problem with inequalities (part 3).3m

Week

8

4 hours to complete

Kunh-Tucker conditions. Homogeneous functions.

Week 8 of the Course is devoted to Kuhn-Tucker conditions and homogenous functions. This week students will find out how to use Kuhn-Tucker conditions for solving various economic problems.

9 videos (Total 80 min), 2 quizzes

9 videos

8.1. Kuhn-Tucker conditions.7m

8.2. Solving consumer choice problem using Kuhn-Tucker conditions (part 1).9m

8.3. Solving consumer choice problem using Kuhn-Tucker conditions (part 2).11m

8.4. Solving minimization costs problem using Kuhn-Tucker conditions (part 1).9m

8.5. Solving minimization costs problem using Kuhn-Tucker conditions (part 2).7m

8.6. Homogeneous functions.6m

8.7. Homogeneous functions. Two propositions.5m

8.8. Income-consumption curve.10m

8.9. Euler's Theorem.12m

1 practice exercise

Kuhn-Tucker conditions. Concavity, convexity.1h

Instructor

Kirill Bukin

Associate Professor, Candidate of sciences (phys.-math.)

Faculty of Economic Sciences, Department of Theoretical Economics

Frequently Asked Questions

When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?

More questions? Visit the Learner Help Center.

Mathematics for economists

100% online

Flexible deadlines

Intermediate Level

Approx. 34 hours to complete

English

100% online

Flexible deadlines

Intermediate Level

Approx. 34 hours to complete

English

Learners taking this Course are

Syllabus - What you will learn from this course

The basics of the set theory. Functions in Rn

Differentiation. Gradient. Hessian.

Implicit Function Theorems and their applications.

Unconstrained and constrained optimization.

Constrained optimization for n-dim space. Bordered Hessian.

Envelope theorems. Concavity and convexity.

Global extrema. Constrained optimization with inequality constraints.

Kunh-Tucker conditions. Homogeneous functions.

Top reviews from Mathematics for economists

Instructor

Kirill Bukin

About National Research University Higher School of Economics

Frequently Asked Questions