update sources from lecture-python(9b37b62)

Author: mmcky

lectures/cake_eating_numerical.md

@@ -104,9 +104,7 @@ $$
 1. Take an arbitary intial guess of $v$.
 1. Obtain an update $w$ defined by
 
-   > w(x) = \max_{0\leq c \leq x} \{u(c) + \beta v(x-c)\}
-   > 
-   >
+   w(x) = \max_{0\leq c \leq x} \{u(c) + \beta v(x-c)\}
 1. Stop if $w$ is approximately equal to $v$, otherwise set
    $v=w$ and go back to step 2.
 

lectures/cass_koopmans_2.md

@@ -49,22 +49,19 @@ The present lecture uses  additional  ideas including
   problem and the Hicks-Arrow prices.
 - A **Big** $K$ **, little** $k$ trick widely used in
   macroeconomic dynamics.
-
-* > We shall encounter this trick in [> this lecture](https://lectures.quantecon.org/py/rational_expectations.html#)> 
-  > and also in [> this lecture](https://lectures.quantecon.org/py/dyn_stack.html#)> .
-
+    * We shall encounter this trick in [this lecture](https://lectures.quantecon.org/py/rational_expectations.html#)
+      and also in [this lecture](https://lectures.quantecon.org/py/dyn_stack.html#).
 - A non-stochastic version of a theory of the **term structure of
   interest rates**.
 - An intimate connection between the cases for the optimality of two
   competing visions of good ways to organize an economy, namely:
-
-* **> socialism**>  in which a central planner commands the
-  > allocation of resources, and
-* **> capitalism**>  (also known as **> a  market economy**> ) in
-  > which competitive equilibrium **> prices**>  induce individual
-  > consumers and producers to choose a socially optimal allocation
-  > as an unintended consequence of their selfish
-  > decisions
+    * **socialism** in which a central planner commands the
+      allocation of resources, and
+    * **capitalism** (also known as **a  market economy**) in
+      which competitive equilibrium **prices** induce individual
+      consumers and producers to choose a socially optimal allocation
+      as an unintended consequence of their selfish
+      decisions
 
 Let's start with some standard imports:
 
@@ -581,7 +578,7 @@ which is {eq}`constraint3`.
 Combining {eq}`cond4` and {eq}`eq-price`, we get:
 
 $$
-- \beta^{T+1} \mu_{T+1} \leq 0
+-\beta^{T+1} \mu_{T+1} \leq 0
 $$
 
 Dividing both sides by $\beta^{T+1}$ gives

lectures/exchangeable.md

@@ -181,12 +181,12 @@ $G$ with probability $1 - \tilde \pi$.
 
 Thus, we  assume that the decision maker
 
-- **> knows**>  both $> F$>  and $> G$
-- **> doesnt't know**>  which of these two distributions that nature has drawn
-- > summarizing his ignorance by acting  as if or **> thinking**>  that nature chose distribution $> F$>  with probability $> \tilde \pi \in (0,1)$>  and distribution
-  > $> G$>  with probability $> 1 - \tilde \pi$
-- > at date $> t \geq 0$>  has observed  the partial history $> w_t, w_{t-1}, \ldots, w_0$>  of draws from the appropriate joint
-  > density of the partial history
+- **knows** both $F$ and $G$
+- **doesnt't know** which of these two distributions that nature has drawn
+- summarizing his ignorance by acting  as if or **thinking** that nature chose distribution $F$ with probability $\tilde \pi \in (0,1)$ and distribution
+  $G$ with probability $1 - \tilde \pi$
+- at date $t \geq 0$ has observed  the partial history $w_t, w_{t-1}, \ldots, w_0$ of draws from the appropriate joint
+  density of the partial history
 
 But what do we mean by the *appropriate joint distribution*?
 
@@ -616,7 +616,7 @@ periods when the sequence is truly IID draws from $G$. Again, we set the initial
 π_paths_G = simulate(a=3, b=1.2, T=T, N=1000)
 ```
 
-In  the above graph we observe that now  most paths $\pi_t \rightarrow 0$.
+In the above graph we observe that now  most paths $\pi_t \rightarrow 0$.
 
 ### Rates of convergence