diff --git a/lectures/_static/quant-econ.bib b/lectures/_static/quant-econ.bib
index e83d20a9..ad67fe70 100644
--- a/lectures/_static/quant-econ.bib
+++ b/lectures/_static/quant-econ.bib
@@ -2449,7 +2449,7 @@ @Article{Bansal_Yaron_2004
   keywords={},
   doi={},
   abstract={ We model consumption and dividend growth rates as containing (1) a small long-run predictable component, and (2) fluctuating economic uncertainty (consumption volatility). These dynamics, for which we provide empirical support, in conjunction with Epstein and Zin's (1989) preferences, can explain key asset markets phenomena. In our economy, financial markets dislike economic uncertainty and better long-run growth prospects raise equity prices. The model can justify the equity premium, the risk-free rate, and the volatility of the market return, risk-free rate, and the price-dividend ratio. As in the data, dividend yields predict returns and the volatility of returns is time-varying. Copyright 2004 by The American Finance Association.},
-  url={https://ideas.repec.org/a/bla/jfinan/v59y2004i4p1481-1509.html}
+  url={https://doi.org/10.1111/j.1540-6261.2004.00670.x}
 }
 
 @article{hansen2008consumption,
diff --git a/lectures/discrete_dp.md b/lectures/discrete_dp.md
index 845cbaed..5505c219 100644
--- a/lectures/discrete_dp.md
+++ b/lectures/discrete_dp.md
@@ -613,7 +613,7 @@ For larger problems, you might need to write this code more efficiently by vecto
 
 ## Exercises
 
-In the [stochastic optimal growth lecture](https://python-intro.quantecon.org/optgrowth.html) from our introductory lecture series, we solve a benchmark model that has an analytical solution.
+In the [stochastic optimal growth lecture](https://dynamics.quantecon.org/optgrowth.html), we solve a benchmark model that has an analytical solution.
 
 The exercise is to replicate this solution using `DiscreteDP`.
 
@@ -621,7 +621,7 @@ The exercise is to replicate this solution using `DiscreteDP`.
 
 ### Setup
 
-Details of the model can be found in [the lecture on optimal growth](https://python-intro.quantecon.org/optgrowth.html).
+Details of the model can be found in [the lecture on optimal growth](https://dynamics.quantecon.org/optgrowth.html).
 
 We let $f(k) = k^{\alpha}$ with $\alpha = 0.65$, $u(c) =
 \log c$, and $\beta = 0.95$
@@ -907,8 +907,7 @@ plt.show()
 
 #### Dynamics of the capital stock
 
-Finally, let us work on [Exercise
-2](https://python.quantecon.org/optgrowth.html#exercises), where we plot
+Finally, let us plot
 the trajectories of the capital stock for three different discount
 factors, $0.9$, $0.94$, and $0.98$, with initial
 condition $k_0 = 0.1$.