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@jstac jstac commented Dec 8, 2025

Summary

This PR adds a new lecture on risk-sensitive preferences in the job search context, positioned as Job Search V (after the fitted VFI lecture).

Changes

New Content

  • mccall_risk.md: New lecture introducing entropic risk-adjusted expectations and their application to the McCall search model
    • Introduction to risk-sensitive preferences via entropic risk measure
    • Examples with Gaussian and Beta distributions
    • Mean-preserving spread analysis
    • Application to McCall job search model with risk aversion parameter θ
    • Analysis showing how reservation wages and unemployment rates vary with risk aversion
    • All code verified to run successfully with JAX

Updated Files

  • _toc.yml: Added mccall_risk after mccall_fitted_vfi in the Search section
  • Lecture renumbering: Updated subsequent Job Search lectures to maintain sequence
    • mccall_persist_trans: V → VI
    • career: VI → VII
    • jv: VII → VIII
    • odu: VIII → IX
    • mccall_q: IX → X

Test Plan

  • All code cells execute successfully without errors
  • MyST formatting verified with standard QuantEcon structure
  • Grammar and spelling checked
  • Figures generate correctly with appropriate styling
  • Lecture numbering sequence verified

Key Results

The lecture demonstrates that more risk-averse agents (more negative θ):

  • Have lower reservation wages
  • Accept a wider range of job offers
  • Experience lower unemployment rates

🤖 Generated with Claude Code

This commit adds a new lecture on risk-sensitive preferences in the job
search context, positioned after the fitted VFI lecture. The lecture
introduces entropic risk-adjusted expectations and applies them to the
McCall search model.

Changes:
- Add mccall_risk.md: New lecture on risk-sensitive preferences
- Update _toc.yml: Insert mccall_risk after mccall_fitted_vfi
- Renumber subsequent lectures (V→VI, VI→VII, VII→VIII, VIII→IX, IX→X)
  - mccall_persist_trans: V → VI
  - career: VI → VII
  - jv: VII → VIII
  - odu: VIII → IX
  - mccall_q: IX → X

Key features of the new lecture:
- Introduction to risk-sensitive preferences via entropic risk measure
- Examples with Gaussian and Beta distributions
- Mean-preserving spread analysis
- Application to McCall job search model with risk aversion
- Analysis of reservation wages and unemployment rates vs risk aversion
- All code verified to run successfully with JAX

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
@jstac
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jstac commented Dec 8, 2025

@mmcky Would you mind to get this building? Then perhaps we can ask someone to review before it's merged.

@mmcky
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mmcky commented Dec 8, 2025

Will do @jstac

/home/runner/_work/lecture-python.myst/lecture-python.myst/lectures/mccall_risk.md:283: ERROR: Directive 'solution-start': 1 argument(s) required, 0 supplied
ERROR: The document (mccall_risk) is missing a solution-start directive
  solution-end at line: 355
  solution-start at line: 652
  solution-end at line: 785
  • @mmcky to review and fix exercise admonitions.

mmcky added 2 commits December 9, 2025 10:57
- Convert first exercise from backtick to MyST curly brace syntax
- Add labels to both exercises (mcr_ex0, mcr_ex1)
- Add exercise references to solution-start directives
- Add dropdown class to solutions for consistency
- Ensure all exercise/solution pairs are properly matched
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mmcky commented Dec 9, 2025

@jstac do you use +++ markdown cell delimiters a lot? I typically remove them for MyST editing in markdown document but if you do lots of editing in ipynb then they might be worth keeping.

@jstac
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jstac commented Dec 9, 2025

Please remove all @mmcky , I never edit in ipynb if I can avoid it!

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github-actions bot commented Dec 9, 2025

📖 Netlify Preview Ready!

Preview URL: https://pr-760--sunny-cactus-210e3e.netlify.app (dd4ac64)

📚 Changed Lecture Pages: career, jv, mccall_persist_trans, mccall_q, mccall_risk, odu

@mmcky
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mmcky commented Dec 9, 2025

Please remove all @mmcky , I never edit in ipynb if I can avoid it!

I will add this to https://github.com/QuantEcon/action-style-guide

@jstac
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jstac commented Dec 9, 2025

 I will add this to https://github.com/QuantEcon/action-style-guide

Thanks @mmcky !

Please add hide output to the pip install. Please also cut

Mean of Beta(2,2): 0.4997 (theoretical: 0.5)
e_theta at theta = -2.0: 0.4504
e_theta at theta = -0.1: 0.4972

as well as θ = -3.00, reservation wage = 0.8824 etc.

- Add :tags: [hide-output] to pip install cell
- Remove print statements from Beta distribution example
- Remove print loops for reservation wage values
- Remove print loops for unemployment rate values
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github-actions bot commented Dec 9, 2025

📖 Netlify Preview Ready!

Preview URL: https://pr-760--sunny-cactus-210e3e.netlify.app (3e3f4f7)

📚 Changed Lecture Pages: career, jv, mccall_persist_trans, mccall_q, mccall_risk, odu

- Add parentheses around MGF abbreviation for clarity
- Fix subject-verb agreement: change 'decrease' to 'decreases'
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mmcky commented Dec 10, 2025

@jstac just some minor changes.

One question, do you indent LaTeX equations as a style preference or is this a hangover from rst days?

$$
    e_\theta = \mu + \frac{\theta\sigma^2}{2}
$$

I think

$$
e_\theta = \mu + \frac{\theta\sigma^2}{2}
$$

is tidier (but maybe you prefer indended). Just keen to set a style guide preference.

@jstac
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jstac commented Dec 10, 2025

Thanks @mmcky . I prefer the former, it's how I indent in my research papers, but I'm happy for you to decide. No strong preference

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📖 Netlify Preview Ready!

Preview URL: https://pr-760--sunny-cactus-210e3e.netlify.app (8fdaf98)

📚 Changed Lecture Pages: career, jv, mccall_persist_trans, mccall_q, mccall_risk, odu

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3 participants