Science Score: 54.0%

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  • CITATION.cff file
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  • codemeta.json file
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    Links to: zenodo.org
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    Low similarity (6.7%) to scientific vocabulary
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Repository

Basic Info
  • Host: GitHub
  • Owner: llorracc
  • License: apache-2.0
  • Language: TeX
  • Default Branch: master
  • Size: 25 MB
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  • Stars: 0
  • Watchers: 1
  • Forks: 6
  • Open Issues: 2
  • Releases: 0
Created over 7 years ago · Last pushed about 2 years ago
Metadata Files
Readme License Citation

README.md

Liquidity Constraints and Precautionary Saving

DOI

The LiqConstr directory contains code to reproduce the figures of the paper Liquidity Constraints and Precautionary Saving by Carroll, Holm, and Kimball, and the LaTeX source to produce the paper once the figures have been created.

Code

Figures can be produced either:

Live in your browser using MyBinder: Binder

Locally by running an ipython program on your computer:

  1. Install the necessary tools on your computer
  2. Download this repository using git clone https://github.com/econ-ark/LiqConstr or a zip folder using this link.
  3. Change to the LiqConstr directory and execute ipython LiqConstr.py from the command line.

In a local interactive jupyter notebook

  1. Install the jupyter notebook tool per Installation.md
  2. Download this repository using git clone https://github.com/econ-ark/LiqConstr or a zip folder using this link.
  3. Type jupyter lab at the command line
  4. Click on LiqConstr.ipynb

Reproduce the figures and compile the paper locally using nbreproduce

  1. Install nbreproduce
  2. Download this repository using git clone https://github.com/econ-ark/LiqConstr or a zip folder using this link.
  3. Execute nbreproduce from the command line.

Paper

The paper can be generated by compiling the LaTeX file LiqConstr.tex using a standard distribution of LaTeX like TeXLive or Overleaf.

Owner

  • Name: Christopher Llorracc Carroll
  • Login: llorracc
  • Kind: user

Citation (CITATION.cff)

cff-version: "1.2.0"
message: "This paper shows that liquidity constraints and precautionary saving are closely related to each other, since both can be thought of is \"counterclockwise concavifications\" of the consumption function.; all results are paired with illustrative numerical solutions."
authors:
  - family-names: "Carroll"
    given-names: "Christopher D."
    orcid: "https://orcid.org/0000-0003-3732-9312"
  - family-names: "Kimball"
    given-names: "Miles S."
  - family-names: "Holm"
    given-names: "Martin B."
title: "Liquidity Constraints and Precautionary Saving"
abstract: "We provide the analytical explanation of strong interactions between precautionary sav- ing and liquidity constraints that are regularly observed in numerical solutions to consump- tion/saving models. The effects of constraints and of uncertainty spring from the same cause: concavification of the consumption function, which can be induced either by constraints or by uncertainty. Concavification propagates back to consumption functions in prior periods. But, surprisingly, once a linear consumption function has been concavified by the presence of either risks or constraints, the introduction of additional concavifiers in a given period can reduce the precautionary motive in earlier periods at some levels of wealth."
date-released: 2020-09-14

references:
  - type: article
    authors:
      - family-names: "Carroll"
        given-names: "Christopher D."
        orcid: "https://orcid.org/0000-0003-3732-9312"
      - family-names: "Kimball"
        given-names: "Miles S."
      - family-names: "Holm"
        given-names: "Martin B."
    title: "Liquidity Constraints and Precautionary Savings"
    doi: "10.1016/j.jet.2021.105276"
    date-released: 2021-07-01
    publisher:
        name: "Journal of Economic Theory"

repository-code: https://github.com/econ-ark/LiqConstr

keywords: # optional
  - liquidity constraints
  - uncertainty
  - precautionary saving

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Dependencies

binder/requirements.txt pypi
  • econ-ark ==0.10.7
  • ipywidgets ==7.5.1
  • matplotlib ==3.3.2
  • numpy ==1.19.2
  • voila ==0.2.2
reproduce/Dockerfile docker
  • $BASE_CONTAINER latest build
binder/environment.yml conda
  • pip
  • python 3.7.*