Quantitative Economics

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This course studies quantitative approaches for solving dynamic economic models.

There is a heavy theoretical component: this course provides basic background in dynamic programming techniques (Bellman equation) frequently used in modern economics. We will also study economic theory related to consumption and savings decisions. There is also a heavy computational component: we will study numerical methods (value function iteration, endogenous grid, policy function iteration and similar) and learn to apply them in deterministic and stochastic settings.

We will use Julia, a modern, open source, high productivity language primarily used in technical and scientific computing. No prior knowledge of Julia is needed.

This course is an introduction to quantitative methods used in modern economics. We will focus mostly on tools, techniques and theories used by macroeconomists who study distributional issues. We will analyze consumption-savings problems, income dynamics and wealth inequality in partial and general equilibrium. To confront our models with the data we will solve them on a computer and compare their predictions with empirical regularities.

We will make extensive use of mathematics, numerical methods and computer programming. There is a heavy theoretical component: this course provides basic background in dynamic programming techniques (Bellman equation) frequently used in modern economics. We will also study economic theory related to consumption, savings, wealth and income distributions. There is also a heavy computational component: we will study numerical methods and learn to apply them in deterministic and stochastic settings.

We will use Julia, a modern, open source, high productivity language primarily used in technical and scientific computing. No prior knowledge of Julia is needed as a brief introduction to this language and example code will be provided. Students can also work in a different programming language, such as C, Fortran, Matlab, Python or R, if they are already proficient in it.

Students who do not find such a quantitative, computational approach to economics appealing are strongly advised against taking this course.

We will discuss the following topics:

1. Introduction, programming in Julia.

2. Deterministic consumption-savings problems, value function iteration

3. Stochastic consumption-savings problems, precautionary savings

4. Numerical dynamic programming.

5. Calibration, income processes, wealth distribution model vs data

6. General equilibrium, Bewley, Aiyagari, Huggett models

7. Marginal propensities to consume and two asset model

Lecture notes.

The list of required readings will be posted on Moodle.

Students know basic computational techniques used to study dynamic economic models and know how to implement them in on a computer. Students are familiar with economic theories of consumption, savings, wealth and income distributions.

Grading will be based on:

• Problem sets (x3) 50%

• Final project 40%

• Class participation 10%