When Money Feels Tight: Subjective Financial Strain and Depression Among Older Americans

HRS Wave 15 Replication Package Description This repository contains the complete replication package for analyzing the relationship between subjective financial well-being and depressive symptoms among older adults using Health and Retirement Study (HRS) Wave 15 data. Files Included financial_wellbeing_analysis.ipynb - Complete Jupyter notebook with data processing, analysis, and visualization code README.md - Detailed instructions and variable descriptions requirements.txt - Python package dependencies How to Use in Google Colab Step 1: Upload to Google Colab Go to Google Colab Click "File" → "Upload notebook" Upload the financial_wellbeing_analysis.ipynb file from this repository Step 2: Install Dependencies Run this code cell first to install required packages: python !pip install pandas numpy scipy statsmodels matplotlib seaborn Step 3: Access HRS Data The notebook uses publicly available HRS data. You have two options: Option A: Download HRS data directly Register at HRS website Download Wave 15 RAND longitudinal file Upload the .dta file to your Colab session Option B: Use the provided sample dataset (if included) The notebook will automatically load a sample dataset for demonstration purposes. Step 4: Run the Analysis Execute cells in order: Data Import & Cleaning - Loads and preprocesses HRS variables Descriptive Statistics - Summary statistics and data exploration Regression Analysis - OLS models predicting depression scores Results & Visualization - Tables and plots of key findings Variables Used Dependent Variable: CES-D depression score (0-8 scale) Independent Variables: Financial strain (self-reported financial problems) Financial satisfaction (satisfaction with financial situation) Difficulty making ends meet (difficulty paying bills) Income adequacy (perceived adequacy of income) Expected Runtime Full analysis: 2-3 minutes in Google Colab Sample size: ~4,371 observations after listwise deletion Output The notebook generates: Descriptive statistics tables OLS regression results (R² ≈ 0.143) Coefficient plots showing effect sizes Diagnostic plots for model assumptions Anon. (2025). Financial Well-being and Depression Analysis: HRS Wave 15 Replication Package [Data set]. Zenodo. https://doi.org/[your-doi] Requirements Python 3.7+ pandas, numpy, scipy, statsmodels, matplotlib, seaborn Google Colab account (free) HRS data access (free registration required)