@@ -15,7 +15,11 @@ kernelspec:
1515
1616In this lecture we study the overlapping generations (OLG) model.
1717
18- The dynamics of this model are quite similar to Solow-Swan growth model.
18+
19+
20+ ## Overview
21+
22+ The dynamics of the OLG model are quite similar to Solow-Swan growth model.
1923
2024At the same time, the OLG model adds an important new feature: the choice of
2125how much to save is endogenous.
@@ -165,7 +169,7 @@ so the Euler equation can also be expressed as
165169```
166170
167171Suppose that, for each $w_t$ and $R_ {t+1}$, there is exactly one $s_t$ that
168- solves :eq: ` euler_2_olg ` .
172+ solves [ ] ( euler_2_olg ) .
169173
170174Then savings can be written as a fixed function of $w_t$ and $R_ {t+1}$.
171175
@@ -288,6 +292,11 @@ Rearranging [](interest_rate_2) gives the aggregate demand for capital
288292
289293## Equilibrium
290294
295+ In this section we derive equilibrium conditions and investigate an example.
296+
297+
298+ ### Equilibrium Conditions
299+
291300In equilibrium, savings at time $t$ equals investment at time $t$, which
292301equals capital supply at time $t+1$.
293302
@@ -309,7 +318,10 @@ From it and [](aggregate_demand_capital_olg), we can obtain the equilibrium quan
309318When we solve for this equilibrium, time $t$ quantities are already given, so
310319we can treat $w_t$ as a constant.
311320
312- or, equivalently,
321+
322+ ### Example: log utility
323+
324+ In the case of log utility, we can use [ ] ( equilibrium_1 ) and [ ] ( saving_log_2_olg ) to obtain
313325
314326``` {math}
315327:label: equilibrium_2
@@ -324,15 +336,15 @@ Solving for the equilibrium interest rate gives
324336 R_{t+1} =
325337 \alpha
326338 \left (
327- \frac{\beta (1-\alpha)( k_t / \ell ) ^{\alpha}}{1+\beta}
339+ \frac{\beta (1-\alpha)k_t^{\alpha}}{1+\beta}
328340 \right )^{\alpha - 1}
329341```
330342
331343Plugging into either the demand or the supply function gives the equilibrium quantity
332344
333345``` {math}
334346:label: equilibrium_quantity
335- k_{t+1} = \frac{\beta }{1+\beta} (1-\alpha)( k_t / \ell ) ^{\alpha} \ell
347+ k_{t+1} = \frac{\beta }{1+\beta} (1-\alpha)k_t^{\alpha}
336348```
337349
338350``` {code-cell} ipython3
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