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Clarify utility function notation to avoid confusion with unemployment compensation
Changed utility function parameter from 'c' to 'x' to distinguish between: - The consumption argument of the utility function u(x) - The unemployment compensation parameter c This prevents confusion when we write expressions like u(c), where c is the specific value of unemployment compensation being passed to the utility function. Updated in: - Job Search II: def u(c, γ) → def u(x, γ) - Job Search III: def u(c, γ) → def u(x, γ) - Job Search IV: def u(c, γ) → def u(x, γ) - Job Search V: u(c) = ln(c) → u(x) = ln(x) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <[email protected]>
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lectures/mccall_fitted_vfi.md

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We use the same CRRA utility function as in the discrete case:
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```{code-cell} ipython3
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def u(c, γ):
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return (c**(1 - γ) - 1) / (1 - γ)
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def u(x, γ):
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return (x**(1 - γ) - 1) / (1 - γ)
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```
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Here's our model structure using a NamedTuple.

lectures/mccall_model_with_sep_markov.md

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@@ -208,8 +208,8 @@ The optimal policy turns out to be a reservation wage strategy: accept all wages
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The default utility function is a CRRA utility function
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```{code-cell} ipython3
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def u(c, γ):
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return (c**(1 - γ) - 1) / (1 - γ)
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def u(x, γ):
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return (x**(1 - γ) - 1) / (1 - γ)
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```
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Let's set up a `Model` class to store information needed to solve the model.

lectures/mccall_model_with_separation.md

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@@ -239,8 +239,8 @@ Let's now implement a solution method based on the two Bellman equations
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The default utility function is a CRRA utility function
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```{code-cell} ipython3
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def u(c, γ):
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return (c**(1 - γ) - 1) / (1 - γ)
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def u(x, γ):
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return (x**(1 - γ) - 1) / (1 - γ)
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```
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Also, here's a default wage distribution, based around the BetaBinomial

lectures/mccall_persist_trans.md

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\frac{u(w)}{1-\beta} \geq f^*(z)
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$$
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For utility, we take $u(c) = \ln(c)$.
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For utility, we take $u(x) = \ln(x)$.
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The reservation wage is the wage where equality holds in the last expression.
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