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Math and science::Algebra

Markov matrices and their eigenvectors. An NZ-AU immigration example.

What is the population of Australia and New Zealand after 100 years of the following migration pattern? Starting with 1 million people in Australia and no one in New Zealand.

To start things off, the transition is described by:

\[ \begin{bmatrix} \text{Australia}_{t+1} \\ \text{New Zealand}_{t+1} \end{bmatrix} = \begin{bmatrix} 0.8 & 0.3 \\ 0.2 & 0.7 \end{bmatrix} \begin{bmatrix} \text{Australia}_{t} \\ \text{New Zealand}_{t} \end{bmatrix} \]

Continue on the reverse. How does \( XVX^{-1} \) come up?


The answer is the result of the following expression:

\[ \begin{bmatrix} 0.8 & 0.3 \\ 0.2 & 0.7 \end{bmatrix}^{100} \begin{bmatrix} 1,000,000 \\ 0 \end{bmatrix} \]

To calculate the result, use eigenvalues and eigenvectors. The transition matrix has eigenvalues 1.0 and 0.5 corresponding to eigenvectors:

\[ \begin{bmatrix} 0.6 \\ 0.4 \\ \end{bmatrix} \text{ and } \begin{bmatrix} -1 \\ 1 \\ \end{bmatrix} \]

We can express the starting population as a linear combination of the eigenvectors:

\[ \begin{bmatrix} 1,000,000 \\ 0 \end{bmatrix} = \begin{bmatrix} 600,000 \\ 400,000 \end{bmatrix} + \begin{bmatrix} 400,000 \\ -400,000 \end{bmatrix} \]

Then,

\[ \begin{bmatrix} 0.8 & 0.3 \\ 0.2 & 0.7 \end{bmatrix}^{100} \begin{bmatrix} 1,000,000 \\ 0 \end{bmatrix} \]

becomes:

\[ 1.0^{100} \begin{bmatrix} 600,000 \\ 400,000 \end{bmatrix} + 0.5^{100} \begin{bmatrix} 400,000 \\ -400,000 \end{bmatrix} \]

Which is

\[ \begin{bmatrix} 600,000 \\ 400,000 \end{bmatrix} \]

General approach

The above intuitive approach is an application of the somewhat opaque symbolic expression \( XVX^{-1} \). The steps are:

  1. Express the starting population as a linear combination of eigenvectors.
  2. Apply the transition matrix to the eigenvectors.
  3. Express the result as a linear combination of eigenvectors.

Repeat the solution from this perspective, letting \( A \) be the transition matrix, and \( X \) be the matrix of eigenvectors and \( V \) be the diagonal matrix of eigenvalues. We will set \( X \) to be:

\[ \begin{bmatrix} 600,000 & 400,000 \\ 400,000 & -400,000 \end{bmatrix} \]
We are trying to calculate:

\[ \text{result} = A^{100} \begin{bmatrix} 1,000,000 \\ 0 \end{bmatrix} \]

By eigenvector decomposition, we have:

\[ \text{result} = X V^{100} X^{-1} \begin{bmatrix} 1,000,000 \\ 0 \end{bmatrix} \]

First, calculate \( X^{-1} \begin{bmatrix} 1,000,000 \\ 0 \end{bmatrix} \):

\[ X^{-1} \begin{bmatrix} 1,000,000 \\ 0 \end{bmatrix} = \begin{bmatrix} 1 \\ 1 \end{bmatrix} \]

Then multiply by \( V^{100} \):

\[ V^{100} \begin{bmatrix} 1 \\ 1 \end{bmatrix} = \begin{bmatrix} 1.0^{100} \\ 0.5^{100} \end{bmatrix} = \begin{bmatrix} 1 \\ 0 \end{bmatrix} \]

Finally, get back to the original basis:

\[ X \begin{bmatrix} 1 \\ 0 \end{bmatrix} = \begin{bmatrix} 600,000 & 400,000 \\ 400,000 & -400,000 \end{bmatrix} \begin{bmatrix} 1 \\ 0 \end{bmatrix} = \begin{bmatrix} 600,000 \\ 400,000 \end{bmatrix} \]