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thorek1 authored Nov 20, 2023
2 parents 1fc4fd0 + 65556e6 commit 4d3547c
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8 changes: 3 additions & 5 deletions docs/src/how-to/loops.md
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Expand Up @@ -141,11 +141,9 @@ Making use of this and continuing the example of the Backus, Kehoe and Kydland (

```@repl howto_loops
@parameters Backus_Kehoe_Kydland_1992 begin
F_H_ratio = .9
K{F}[ss] / K{H}[ss] = F_H_ratio | beta{F}
K{H}[ss] = 11 | beta{H}
beta = 0.99
K_ss = 11
K[ss] = K_ss | beta
mu = 0.34
gamma = -1.0
alpha = 1
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6 changes: 3 additions & 3 deletions docs/src/how-to/obc.md
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Expand Up @@ -27,7 +27,7 @@ using MacroModelling
@model Gali_2015_chapter_3_obc begin
W_real[0] = C[0] ^ σ * N[0] ^ φ
[0] = β * (C[1] / C[0]) ^ (-σ) * Z[1] / Z[0] / Pi[1]
Q[0] = β * (C[1] / C[0]) ^ (-σ) * Z[1] / Z[0] / Pi[1]
R[0] = 1 / Q[0]
Expand Down Expand Up @@ -316,13 +316,13 @@ Statistics.std(sims(:Y,:,:))
Compare this to the theoretical mean of the model without the occasionally binding constraint:

```@repl howto_obc
get_mean(borrowing_constraint)
get_mean(Gali_2015_chapter_3_obc)
```

and the theoretical standard deviation:

```@repl howto_obc
get_std(borrowing_constraint)
get_std(Gali_2015_chapter_3_obc)
```

The mean of output is lower in the model with effective lower bound compared to the model without and the standard deviation is higher.
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1 change: 1 addition & 0 deletions docs/src/unfinished_docs/todo.md
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Expand Up @@ -4,6 +4,7 @@

- [ ] add technical details about SS solver, obc solver, and other algorithms
- [ ] rm obc vars from get_SS
- [ ] fix SS solver (failed for backus in guide)
- [ ] functions to reverse state_update (input: previous shock and current state, output previous state), find shocks corresponding to bringing one state to the next
- [ ] cover nested case: min(50,a+b+max(c,10))
- [ ] nonlinear estimation using unscented kalman filter / inversion filter (minimization problem: find shocks to match states with data)
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