Teaching Mathematics for Economists

Fuente: arXiv
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Main Author: Hillebrand, Eric
Format: Preprint
Published: 2025
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author Hillebrand, Eric
author_facet Hillebrand, Eric
contents In this chapter, I discuss teaching mathematical tools specifically tailored for economics students. A typical one-semester course in this area seeks to blend a range of topics: from foundational elements of subjects such as linear algebra and multivariate calculus to intermediate areas like real and convex analysis and further into advanced topics such as dynamic optimization in both continuous and discrete time. This breadth of coverage corresponds to material usually spread across multiple years in traditional mathematics programs. Given the comprehensive nature of these courses, careful selection of topics is essential, balancing numerous trade-offs. I discuss potential course sequences and instructional design choices. I then focus on conceptualizing and explaining mathematical modeling in economics. I reflect on three years of teaching an advanced undergraduate course in mathematical methods online. The latter part of the chapter offers examples and visualizations I have found particularly beneficial for imparting intuition to economics students. They cover a range of topics at different degrees of difficulty and are meant as a resource for instructors in Mathematics for Economists. Among these, I use the Ramsey model as a recurring example, especially relevant when designing a mathematical tools course with an orientation towards preparing students for macroeconomic analysis.
format Preprint
id arxiv_https___arxiv_org_abs_2505_22671
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Teaching Mathematics for Economists
Hillebrand, Eric
History and Overview
In this chapter, I discuss teaching mathematical tools specifically tailored for economics students. A typical one-semester course in this area seeks to blend a range of topics: from foundational elements of subjects such as linear algebra and multivariate calculus to intermediate areas like real and convex analysis and further into advanced topics such as dynamic optimization in both continuous and discrete time. This breadth of coverage corresponds to material usually spread across multiple years in traditional mathematics programs. Given the comprehensive nature of these courses, careful selection of topics is essential, balancing numerous trade-offs. I discuss potential course sequences and instructional design choices. I then focus on conceptualizing and explaining mathematical modeling in economics. I reflect on three years of teaching an advanced undergraduate course in mathematical methods online. The latter part of the chapter offers examples and visualizations I have found particularly beneficial for imparting intuition to economics students. They cover a range of topics at different degrees of difficulty and are meant as a resource for instructors in Mathematics for Economists. Among these, I use the Ramsey model as a recurring example, especially relevant when designing a mathematical tools course with an orientation towards preparing students for macroeconomic analysis.
title Teaching Mathematics for Economists
topic History and Overview
url https://arxiv.org/abs/2505.22671