diff --git a/lectures/aiyagari.md b/lectures/aiyagari.md index 66e3363..9d3f3b3 100644 --- a/lectures/aiyagari.md +++ b/lectures/aiyagari.md @@ -20,10 +20,6 @@ kernelspec: # The Aiyagari Model -```{contents} Contents -:depth: 2 -``` - In addition to what's in Anaconda, this lecture will need the following libraries: ```{code-cell} ipython diff --git a/lectures/arellano.md b/lectures/arellano.md index 4de172f..2e24ed8 100644 --- a/lectures/arellano.md +++ b/lectures/arellano.md @@ -20,10 +20,6 @@ kernelspec: # Default Risk and Income Fluctuations -```{contents} Contents -:depth: 2 -``` - In addition to what's in Anaconda, this lecture will need the following libraries: ```{code-cell} python @@ -80,7 +76,6 @@ import numpy as np import quantecon as qe from numba import njit, prange -%matplotlib inline ``` ## Structure diff --git a/lectures/cass_koopmans_1.md b/lectures/cass_koopmans_1.md index 8386cc0..0deea1f 100644 --- a/lectures/cass_koopmans_1.md +++ b/lectures/cass_koopmans_1.md @@ -20,10 +20,6 @@ kernelspec: # Cass-Koopmans Model -```{contents} Contents -:depth: 2 -``` - ## Overview This lecture and {doc}`Cass-Koopmans Competitive Equilibrium ` describe a model that Tjalling Koopmans {cite}`Koopmans` diff --git a/lectures/cass_koopmans_2.md b/lectures/cass_koopmans_2.md index 9f6e3cb..ff9d6ec 100644 --- a/lectures/cass_koopmans_2.md +++ b/lectures/cass_koopmans_2.md @@ -20,10 +20,6 @@ kernelspec: # Cass-Koopmans Competitive Equilibrium -```{contents} Contents -:depth: 2 -``` - ## Overview This lecture continues our analysis in this lecture diff --git a/lectures/coase.md b/lectures/coase.md index 41fe1c9..44c47e8 100644 --- a/lectures/coase.md +++ b/lectures/coase.md @@ -20,10 +20,6 @@ kernelspec: # {index}`Coase's Theory of the Firm ` -```{contents} Contents -:depth: 2 -``` - In addition to what's in Anaconda, this lecture will need the following libraries: ```{code-cell} ipython @@ -60,7 +56,6 @@ We'll use the following imports: ```{code-cell} ipython import numpy as np import matplotlib.pyplot as plt -%matplotlib inline from scipy.optimize import fminbound from interpolation import interp ``` diff --git a/lectures/knowing_forecasts_of_others.md b/lectures/knowing_forecasts_of_others.md index 5089c3c..d1bc043 100644 --- a/lectures/knowing_forecasts_of_others.md +++ b/lectures/knowing_forecasts_of_others.md @@ -20,10 +20,6 @@ kernelspec: # Knowing the Forecasts of Others -```{contents} Contents -:depth: 2 -``` - In addition to what's in Anaconda, this lecture will need the following libraries: ```{code-cell} ipython diff --git a/lectures/markov_perf.md b/lectures/markov_perf.md index d927efa..3afc45c 100644 --- a/lectures/markov_perf.md +++ b/lectures/markov_perf.md @@ -23,10 +23,6 @@ kernelspec: ```{index} single: Markov Perfect Equilibrium ``` -```{contents} Contents -:depth: 2 -``` - In addition to what's in Anaconda, this lecture will need the following libraries: ```{code-cell} ipython diff --git a/lectures/matsuyama.md b/lectures/matsuyama.md index 681e424..3935b92 100644 --- a/lectures/matsuyama.md +++ b/lectures/matsuyama.md @@ -20,13 +20,9 @@ kernelspec: # Globalization and Cycles -```{contents} Contents -:depth: 2 -``` - ## Overview -In this lecture, we review the paper [Globalization and Synchronization of Innovation Cycles](http://www.centreformacroeconomics.ac.uk/Discussion-Papers/2015/CFMDP2015-27-Paper.pdf) by [Kiminori Matsuyama](http://faculty.wcas.northwestern.edu/~kmatsu/), [Laura Gardini](http://www.mdef.it/index.php?id=32) and [Iryna Sushko](http://irynasushko.altervista.org/). +In this lecture, we review the paper [Globalization and Synchronization of Innovation Cycles](http://www.centreformacroeconomics.ac.uk/Discussion-Papers/2015/CFMDP2015-27-Paper.pdf) by [Kiminori Matsuyama](http://faculty.wcas.northwestern.edu/~kmatsu/), [Laura Gardini](https://en.wikipedia.org/wiki/Laura_Gardini) and [Iryna Sushko](http://irynasushko.altervista.org/). This model helps us understand several interesting stylized facts about the world economy. @@ -45,7 +41,6 @@ Let's start with some imports: ```{code-cell} ipython import numpy as np import matplotlib.pyplot as plt -%matplotlib inline from numba import jit from ipywidgets import interact ``` diff --git a/lectures/rational_expectations.md b/lectures/rational_expectations.md index f04c7f9..4326530 100644 --- a/lectures/rational_expectations.md +++ b/lectures/rational_expectations.md @@ -20,10 +20,6 @@ kernelspec: # {index}`Rational Expectations Equilibrium ` -```{contents} Contents -:depth: 2 -``` - ```{epigraph} "If you're so smart, why aren't you rich?" ``` diff --git a/lectures/re_with_feedback.md b/lectures/re_with_feedback.md index 5df9761..d20f3fa 100644 --- a/lectures/re_with_feedback.md +++ b/lectures/re_with_feedback.md @@ -23,10 +23,6 @@ kernelspec: ```{index} single: Stability in Linear Rational Expectations Models ``` -```{contents} Contents -:depth: 2 -``` - In addition to what's in Anaconda, this lecture deploys the following libraries: ```{code-cell} ipython diff --git a/lectures/troubleshooting.md b/lectures/troubleshooting.md index 60b999a..650b581 100644 --- a/lectures/troubleshooting.md +++ b/lectures/troubleshooting.md @@ -20,10 +20,6 @@ kernelspec: # Troubleshooting -```{contents} Contents -:depth: 2 -``` - This page is for readers experiencing errors when running the code from the lectures. ## Fixing Your Local Environment diff --git a/lectures/uncertainty_traps.md b/lectures/uncertainty_traps.md index 6af9a64..7085a14 100644 --- a/lectures/uncertainty_traps.md +++ b/lectures/uncertainty_traps.md @@ -20,10 +20,6 @@ kernelspec: # Uncertainty Traps -```{contents} Contents -:depth: 2 -``` - ## Overview In this lecture, we study a simplified version of an uncertainty traps model of Fajgelbaum, Schaal and Taschereau-Dumouchel {cite}`fun`.