lifecycle-model-of-risk-taking-on-the-job

This model

https://github.com/msanchezromero/lifecycle-model-of-risk-taking-on-the-job

Science Score: 49.0%

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  • DOI references
    Found 5 DOI reference(s) in README
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    Links to: zenodo.org
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    Low similarity (4.6%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

This model

Basic Info
  • Host: GitHub
  • Owner: msanchezromero
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 12.6 MB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 6
Created 8 months ago · Last pushed 7 months ago
Metadata Files
Readme Citation

README.md

Publication: Kerndler, M., Prskawetz, A. & Sánchez-Romero, M. A life-cycle model of risk-taking on the job. J Popul Econ 38, 62 (2025). https://doi.org/10.1007/s00148-025-01118-y

Lifecycle model of risk taking on the job

DOI This model

Program simulations This program generates the economic results for the following set of simulations:

| Number | Column name | Explanation | |:-------|:--------------|:----------------------------------------------------------------------| | 1 | benchmark | Benchmark | | 2 | hretage70 | Retirement age 70 rather than 65 | | 3 | hseprate | Separation rate of 4.5\% rather than 3.4\% | | 4 | hunemben50 | Unemployment benefits replacement rate of 50\% rather than 40\%. | | 5 | hretben50 | Retirement benefits replacement rate of 50\% rather than 40\% | | 6 | sLEhigh | Higher LE | | 7 | sLElow | Lower LE | | 8 | sUmorthigh | 10\% higher conditional mortality in unemployment | | 9 | sUmortlow | 10\% lower conditional mortality in unemployment | | 10 | productivity | Two groups: One with low and another one with high productivity | | 11 | TwoGroups(1) | Two groups: low and high productivity, low and high income profile, | | | | low and high market transitions | | 12 | TwoGroups(2) | Two groups and S2: low and high productivity, low and high income | | | | profile, low and high market transitions | | 13 | TwoGroups(3) | Two groups and S3: low and high productivity, low and high income | | | | profile, low and high market transitions | | 14 | TwoGroups(4) | Two groups and S4: low and high productivity, low and high income | | | | profile, low and high market transitions | | 15 | TwoGroups(5) | Two groups and S5: low and high productivity, low and high income | | | | profile, low and high market transitions | | 16 | TwoGroups(6) | Two groups and S6: low and high productivity, low and high income | | | | profile, low and high market transitions |

Program structure

Use the main Jupyter notebook to generate the simulation results and obtain Figures 4,5,6,7 and Tables 2,3,4,5

text Model/ ├── empirical_analysis/ # R codes for the econometric estimations | ├── 00_Readme.txt # Readme file for the empirical analysis | ├── 01_prepare_CPS.R | ├── 02_prepare_ASEC.R | ├── 03_prepare_CFOI.R | ├── 04_mortality_regression.R | ├── 05_mortality_regression_by_skill.R | ├── data/ | ├── figures/ │ └── raw/ │ ├── notebooks/ # Jupyter notebooks | ├── A_lifecycle_model_of_risk_taking_on_the_job.ipynb # Working notebook │ └── ModelFitting_Results.Rmd # Rmarkdown showing the main results (backup code/not used) │ ├── src/ # Source code │ └── 00_main.jl # Main module │ ├── 01_dictionaries.jl # Defines the dictionaries for all the simulations │ ├── 02a_param_struct.jl # Sets the struct for the parameters │ ├── 02b_parameters.jl # Sets the parameter values │ ├── 02c_parameter_functions.jl # Extra functions necessary for setting the individual parameters │ ├── 03_init_parallel.jl # Parallelization function │ ├── 04_functions_micro.jl # Microeconomic functions │ ├── 05_equilibrium_prices.jl # Computes macroeconomic aggregates and find equilibirum prices │ ├── 06_plots_benchmark.jl # Plots main results of the benchmark simulation │ ├── 07_database.jl # Generates the results database │ ├── 08a_results_dataframe.jl # Compile all dataframes │ └── 08b_results_tables_and_figures.jl # Generates results for Figures 4,5,6,7 and Tables 2,3,4,5 │ ├── results/ # Output datasets (all csv/rds files) │ ├── plots/ # Output plots of the article └── README.txt

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  • Kind: user

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