Introduction to Dynamic Programming¶

We have studied the theory of dynamic programming in discrete time under certainty. Let's review what we know so far, so that we can start thinking about how to take to the computer.

The Problem¶

We want to find a sequence $\{x_t\}_{t=0}^\infty$ and a function $V^*:X\to\mathbb{R}$ such that

$$V^{\ast}\left(x_{0}\right)=\sup\limits _{\left\{ x_{t}\right\} _{t=0}^{\infty}}\sum\limits _{t=0}^{\infty}\beta^{t}U(x_{t},x_{t+1})$$

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Faster Computations with Numba¶

Some notes mostly for myself¶

Altough Python is fast compared to other high-level languages, it still is noat as fast as C, C++ or Fortran. Luckily, two open source projects Numba and Cython can be used to speed-up computations. Numba is sponsored by the producer of Anaconda, Continuum Analytics more ...

Working with Economic data in Python¶

This notebook will introduce you to working with data in Python. You can use packages like Numpy to work with arrays, matrices, and such, and anipulate data (see my Introduction to Python). But given the needs of economists it is better to use Pandas. Pandas more ...

Introduction to and

Python is a powerful and easy to use programming language. It has a large community of developers and given its open source nature, you can find many solutions, scripts, and help all over the web. It is easy to learn and code, and faster than other high-level programming languages...and did I mention it is free more ...