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I studied economics at different universities and in different countries, but I never learned much about economic history. We hardly ever discussed the success or failure of different economic policies in history. As a result, I and many of my fellow students had the feeling of being equipped with many tools but not knowing what to use them for.

I think that the combination of the way the MRU teaches ideas, the illustrative and very interesting classes, and the economic history course would be of great value to current and future economists. I can imagine that this course can be the starting point for many future economists to understand why economics is fascinating and encourage them to learn more about economics.

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While statistics has now become an irreplacable component of economic study, mathematical analysis in academic content is growing exponentially. Mathematical modelling is particularly helpful in analysing a number of aspects of economic theory.

Students need to learn mathematical application in economics and MRU is the only platform capable of teaching the same in an engaging manner. Please consider. Would be sharing the academic resources available to me as well.

Proposed syllabus:

Techniques of constrained optimisation.
This is a rigorous treatment of the mathematical techniques used for solving constrained optimisation problems, which are basic tools of economic modelling. Topics include: Definitions of a feasible set and of a solution, sufficient conditions for the existence of a solution, maximum value function, shadow prices, Lagrangian and Kuhn Tucker necessity and sufficiency theorems with applications in economics, for example General Equilibrium theory, Arrow-Debreu securities and arbitrage.

Intertemporal optimisation.
Bellman approach. Euler equations. Stationary infinite horizon problems. Continuous time dynamic optimisation (optimal control). Applications, such as habit formation, Ramsey-Kass-Coopmans model, Tobin’s q, capital taxation in an open economy, are considered.

Tools for optimal control: ordinary differential equations.
These are studied in detail and include linear 2nd order equations, phase portraits, solving linear systems, steady states and their stability.