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lectures/_toc.yml

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- file: linear_equations
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- file: eigen_I
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- file: intro_supply_demand
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- caption: Linear Dynamics
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numbered: true
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chapters:
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- file: pv
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- file: cons_smooth
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- file: cagan_ree
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- file: geom_series
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- caption: Probability and Distributions
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numbered: true
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- file: monte_carlo
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- file: heavy_tails
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- file: schelling
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- caption: Dynamics
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- caption: Nonlinear Dynamics
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numbered: true
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chapters:
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- file: solow
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- file: scalar_dynam
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- file: cobweb
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- file: olg
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- file: commod_price
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- caption: Stochastic Dynamics
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numbered: true
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chapters:
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- file: markov_chains_I
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- file: markov_chains_II
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- file: eigen_II
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- file: pv
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- file: cons_smooth
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- file: cagan_ree
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- file: commod_price
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- caption: Optimization
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numbered: true
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chapters:
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- caption: Modeling in Higher Dimensions
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numbered: true
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chapters:
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- file: eigen_II
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- file: input_output
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- file: lake_model
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- file: asset_pricing
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- file: networks
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- caption: Markets and Competitive Equilibrium
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numbered: true

lectures/asset_pricing.md

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lectures/cagan_ree.md

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We'll use linear algebra first to explain and then do some experiments with a "fiscal theory of the price level".
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According to this model, when the government persistently spends more than it collects in taxes and prints money to finance the shortfall (the "shortfall is called the "government deficit"), it puts upward pressure on the price level and generates
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According to this model, when the government persistently spends more than it collects in taxes and prints money to finance the shortfall (the "shortfall" is called the "government deficit"), it puts upward pressure on the price level and generates
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persistent inflation.
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The "fiscal theory of the price level" asserts that
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To facilitate using linear matrix algebra as our main mathematical tool, we'll use a finite horizon version of the model.
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As in several other lectures, the only linear algebra that we'll be using
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As in the {doc}`present values <pv>` and {doc}`consumption smoothing<cons_smooth>` lectures, the only linear algebra that we'll be using
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are matrix multplication and matrix inversion.
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We reset $m_{T_{1}}$ so that $p_{T_{1}}=\left(m_{T_{1}-1}+\mu_{0}\right)+\alpha\mu_{0}$, with $\pi_{T_{1}}=\mu^{*}$.
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Then,
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$$ m_{T_{1}}=p_{T_{1}}-\alpha\pi_{T_{1}}=\left(m_{T_{1}-1}+\mu_{0}\right)+\alpha\left(\mu_{0}-\mu^{*}\right) $$
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$$
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m_{T_{1}}=p_{T_{1}}-\alpha\pi_{T_{1}}=\left(m_{T_{1}-1}+\mu_{0}\right)+\alpha\left(\mu_{0}-\mu^{*}\right)
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$$
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We then compute for the remaining $T-T_{1}$ periods with $\mu_{s}=\mu^{*},\forall s\geq T_{1}$ and the initial condition $m_{T_{1}}$ from above.
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lectures/cons_smooth.md

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In this notebook, we'll present some useful models of economic dynamics using only linear algebra -- matrix multiplication and matrix inversion.
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**Present value formulas** are at the core of the models.
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{doc}`Present value formulas<pv>` are at the core of the models.
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```{code-cell} ipython3
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import numpy as np

lectures/intro.md

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This lecture series provides an introduction to quantitative economics using Python.
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It was designed and written by [Thomas J. Sargent](http://www.tomsargent.com/), [John Stachurski](http://johnstachurski.net/), and the rest of the QuantEcon team.
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See [About these Lectures](about.md) for background and reading suggestions.
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```{tableofcontents}
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```
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