MAINT: remove content blocks for consistency (#339)

* MAINT: remove content blocks for consistency

* remove duplicate target

Author: mmcky

lectures/ar1_processes.md

@@ -18,6 +18,7 @@ kernelspec:
 </div>
 ```
 
+(ar1_processes)=
 # AR1 Processes
 
 ```{admonition} Migrated lecture
@@ -29,10 +30,6 @@ This lecture has moved from our [Intermediate Quantitative Economics with Python
 ```{index} single: Autoregressive processes
 ```
 
-```{contents} Contents
-:depth: 2
-```
-
 ## Overview
 
 In this lecture we are going to study a very simple class of stochastic

lectures/eigen_II.md

@@ -16,10 +16,6 @@ kernelspec:
 ```{index} single: The Perron-Frobenius Theorem
 ```
 
-```{contents} Contents
-:depth: 2
-```
-
 In addition to what's in Anaconda, this lecture will need the following libraries:
 
 ```{code-cell} ipython3

lectures/heavy_tails.md

@@ -14,10 +14,6 @@ kernelspec:
 (heavy_tail)=
 # Heavy-Tailed Distributions
 
-```{contents} Contents
-:depth: 2
-```
-
 In addition to what's in Anaconda, this lecture will need the following libraries:
 
 ```{code-cell} ipython3

lectures/markov_chains_I.md

@@ -17,10 +17,6 @@ kernelspec:
 ```{index} single: Markov Chains: Basic Concepts and Stationarity
 ```
 
-```{contents} Contents
-:depth: 2
-```
-
 In addition to what's in Anaconda, this lecture will need the following libraries:
 
 ```{code-cell} ipython3

lectures/markov_chains_II.md

@@ -16,11 +16,6 @@ kernelspec:
 ```{index} single: Markov Chains: Irreducibility and Ergodicity
 ```
 
-```{contents} Contents
-:depth: 2
-```
-
-
 In addition to what's in Anaconda, this lecture will need the following libraries:
 
 ```{code-cell} ipython3

lectures/prob_dist.md

@@ -17,10 +17,6 @@ kernelspec:
 ```{index} single: Distributions and Probabilities
 ```
 
-```{contents} Contents
-:depth: 2
-```
-
 ## Outline
 
 In this lecture we give a quick introduction to data and probability distributions using Python.

lectures/scalar_dynam.md

@@ -17,11 +17,8 @@ kernelspec:
 </div>
 ```
 
-# {index}`Dynamics in One Dimension <single: Dynamics in One Dimension>`
-
-```{contents} Contents
-:depth: 2
-```
+(scalar_dynam)=
+# Dynamics in One Dimension
 
 ## Overview
 

lectures/schelling.md

@@ -28,10 +28,6 @@ kernelspec:
 ```{index} single: Models; Schelling's Segregation Model
 ```
 
-```{contents} Contents
-:depth: 2
-```
-
 ## Outline
 
 In 1969, Thomas C. Schelling developed a simple but striking model of racial

lectures/short_path.md

@@ -23,10 +23,6 @@ kernelspec:
 ```{index} single: Dynamic Programming; Shortest Paths
 ```
 
-```{contents} Contents
-:depth: 2
-```
-
 ## Overview
 
 The shortest path problem is a [classic problem](https://en.wikipedia.org/wiki/Shortest_path) in mathematics and computer science with applications in

lectures/supply_demand_heterogeneity.md

@@ -14,10 +14,6 @@ kernelspec:
 (supply_demand_heterogeneity)=
 # Market Equilibrium with Heterogeneity
 
-```{contents} Contents
-:depth: 2
-```
-
 ## Overview
 
 In the {doc}`previous lecture

lectures/time_series_with_matrices.md

@@ -20,10 +20,6 @@ kernelspec:
 
 # Univariate Time Series with Matrix Algebra
 
-```{contents} Contents
-:depth: 2
-```
-
 ## Overview
 
 This lecture uses matrices to solve some linear difference equations.

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