# #FoodSecurityFridays Week 3 — Reproducibility Files

**"Higher-Income Households Can't Be Food Insecure"**

This folder contains Stata programs to reproduce all statistics in the Week 3 #FoodSecurityFridays infographic.

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## Files Included

| File | Description |
|------|-------------|
| `cpsdec2024.do` | Reads raw CPS-FSS ASCII data and creates Stata dataset |
| `fsf_week3_reproducibility.do` | Reproduces all Week 3 infographic statistics |
| `fsf_week3_README.md` | This documentation file |

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## Requirements

- **Stata** (version 14 or later recommended)
- **December 2024 CPS Food Security Supplement** microdata

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## Data Access

Download the December 2024 CPS Food Security Supplement from the U.S. Census Bureau:

**URL:** [https://www.census.gov/data/datasets/time-series/demo/cps/cps-supp_cps-repwgt/cps-food-security.html](https://www.census.gov/data/datasets/time-series/demo/cps/cps-supp_cps-repwgt/cps-food-security.html)

Download the file `dec24pub.dat` (the raw ASCII data file).

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## Instructions

### Step 1: Prepare the Raw Data

1. Open `cpsdec2024.do` in Stata
2. Update the directory paths at the top of the file:
   ```stata
   * Specify the directory containing the raw data file
   local indir "YOUR_PATH_HERE"
   
   * Specify the directory where the Stata dataset will be saved
   local outdir "YOUR_PATH_HERE"
   ```
3. Run the program to create `cpsdec2024.dta`
4. The program will verify data integrity against Census Bureau tallies

### Step 2: Reproduce Week 3 Statistics

1. Open `fsf_week3_reproducibility.do` in Stata
2. Update the directory paths:
   ```stata
   * Input directory containing raw CPS-FSS data
   local indir  "YOUR_PATH_HERE"
   
   * Output directory for log file
   local outdir "YOUR_PATH_HERE"
   ```
3. Run the program
4. Review the output log (`fsf_week3_reproducibility.log`) to verify statistics

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## Statistics Reproduced

The reproducibility program generates all figures shown in the infographic:

### Headline Statistics
- **6.2 million** households above 185% FPL were food insecure
- **7.9%** food insecurity rate among higher-income households

### Food Insecurity by Income-to-Poverty Ratio
| Income Category | Food Insecurity Rate |
|-----------------|---------------------|
| All households | 13.7% |
| Below poverty | 39.4% |
| 100–129% FPL | 34.6% |
| 130–184% FPL | 25.6% |
| 185–299% FPL | 17.3% |
| 300–399% FPL | 8.9% |
| ≥400% FPL | 3.6% |
| Income unknown | 10.5% |

### Item Endorsement Rates (Among Food-Insecure HHs Above 185% FPL)
| Survey Item | Affirmative Rate |
|-------------|------------------|
| Worried food would run out | 90.6% |
| Couldn't afford balanced meals | 84.8% |
| Food bought didn't last | 83.6% |
| Cut size of or skipped meals | 63.0% |
| Ate less than felt should | 62.3% |
| Hungry but didn't eat | 34.7% |
| Did not eat for a whole day | 11.1% |

### Reference Values
- 2024 poverty threshold (family of 4 with 2 children): **$31,812**
- 185% of threshold: **$58,852**
- Income non-response rate: **~21%**

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## Key Definitions

**Food insecurity:** Households classified as having low or very low food security based on responses to the 18-item U.S. Household Food Security Survey Module.

**Income-to-poverty ratio:** Household income divided by the Census poverty threshold appropriate for the household's size and composition.

**Higher income:** Households with income-to-poverty ratio ≥ 1.85 (185% FPL), which is the upper eligibility limit for most federal nutrition programs including WIC and free school meals.

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## Source

Rabbitt, M.P., Reed-Jones, M., Hales, L.J., Suttles, S., & Burke, M.P. (2025). *Household Food Security in the United States in 2024* (Report No. ERR-358). USDA, Economic Research Service.

[https://www.ers.usda.gov/publications/pub-details?pubid=113622](https://www.ers.usda.gov/publications/pub-details?pubid=113622)

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## Contact

For questions about the methodology or data:

**Matthew P. Rabbitt, PhD**  
Email: matthew.p.rabbitt@gmail.com  
LinkedIn: [linkedin.com/in/matthew-p-rabbitt](https://www.linkedin.com/in/matthew-p-rabbitt/)

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*#FoodSecurityFridays — Measuring What Matters*