SAIPE Data Source Reference

Census Bureau Small Area Income and Poverty Estimates (SAIPE) — annual model-based poverty estimates for school districts (Portal mirror; county and state data not in Portal). Use when district-level poverty is needed for Title I allocation interpretation, annual poverty trend analysis, or school-age children in poverty estimates. Estimates have ~18-month lag and no race/ethnicity disaggregation at district level — use ACS 5-year for race-disaggregated poverty.

Reference for understanding Census Bureau poverty estimates for school districts, counties, and states. SAIPE is the only annual, district-level poverty source and the legally mandated basis for Title I education funding allocations.

CRITICAL: Value Encoding

This document describes Education Data Portal integer encodings, which differ from Census Bureau raw file formats. The Portal uses integers for FIPS codes and standard missing data conventions.

Context	FIPS Alabama	FIPS California	Missing	Suppressed
Portal (integers)	1	6	-1	-3
Census raw files	01 (string)	06 (string)	varies	varies

Key difference: Portal FIPS codes are integers (no leading zeros), while Census files use 2-character strings.

See

./references/variable-definitions.md

for complete encoding tables.

What is SAIPE?

SAIPE is the Census Bureau's program for producing model-based estimates of income and poverty:

• Primary purpose: Provide annual poverty estimates for Title I education funding allocations
• Collector: U.S. Census Bureau
• Coverage: All 50 states, 3,100+ counties, 13,000+ school districts
• Key measure: Related children ages 5-17 in families in poverty
• Update frequency: Annual (released each December, ~18-month lag)
• Available years: 1995-2023 (gaps at 1996, 1998; annual from 1999)
• Primary identifier: FIPS code + LEAID (district ID)
• Methodology: Model-based — combines ACS survey data with administrative records (IRS tax returns, SNAP data) using regression models with "shrinkage" techniques; school district estimates are allocated from county totals using within-county shares; all estimates contain uncertainty and confidence intervals are essential
• Available through: Education Data Portal mirrors (district-level only; state and county SAIPE are not in Portal mirrors — see Data Access section)

Reference File Structure

estimation-methodology.md

school-district-estimates.md

variable-definitions.md

data-quality.md

historical-changes.md

comparison-other-sources.md

Decision Trees

What do I need to understand?

Understanding SAIPE?
├─ How are estimates created?
│   ├─ State/county models → ./references/estimation-methodology.md
│   └─ School district shares → ./references/school-district-estimates.md
├─ What variables are available?
│   └─ Variable definitions → ./references/variable-definitions.md
├─ How reliable are estimates?
│   ├─ Confidence intervals → ./references/data-quality.md
│   └─ Small district uncertainty → ./references/data-quality.md
├─ Comparing data sources?
│   ├─ SAIPE vs FRPL → ./references/comparison-other-sources.md
│   ├─ SAIPE vs ACS → ./references/comparison-other-sources.md
│   └─ Why estimates differ → ./references/comparison-other-sources.md
└─ Year-to-year changes?
    ├─ Methodology breaks → ./references/historical-changes.md
    └─ Safe comparisons → ./references/historical-changes.md

Common research questions

Research question?
├─ District poverty rate for Title I
│   ├─ Use SAIPE (official source for Title I)
│   └─ Note: rates use different numerator/denominator universes
├─ Compare district poverty over time
│   ├─ Check methodology breaks → ./references/historical-changes.md
│   └─ Cannot compare school districts pre/post 2010
├─ Why doesn't SAIPE match FRPL?
│   └─ Different income thresholds → ./references/comparison-other-sources.md
├─ Poverty by race/ethnicity in districts
│   └─ SAIPE does NOT provide race breakdowns for districts
│       Use ACS 5-year estimates instead
└─ Very small district reliability
    └─ Check CV by population size → ./references/data-quality.md

Quick Reference: SAIPE Variables

CRITICAL: Field Name Prefix

All SAIPE estimate columns in the Education Data Portal use the

est_

population_total

est_population_total

population_5_17

est_population_5_17

population_5_17_poverty

est_population_5_17_poverty

population_5_17_poverty_pct

est_population_5_17_poverty_pct

Key Identifiers

fips

6

leaid

0100005

year

2022

School District Estimates

est_population_total

est_population_5_17

est_population_5_17_poverty

est_population_5_17_poverty_pct

State/County Estimates (additional)

Not available in Portal mirrors. The datasets below describe variables in SAIPE state and county files published by the Census Bureau. Only the district-level dataset (

saipe/districts_saipe

) is available in the Education Data Portal mirrors. These variables are listed for context only — they cannot be fetched via

fetch_from_mirrors()

.

population_0_4_poverty

population_0_17_poverty

population_poverty

median_household_income

Missing Data Codes

Empirical observation (2025): The

districts_saipe

parquet file uses

null

for all missing/unavailable values. No negative integer codes (-1, -2, -3) were observed in any column. Verify against the live codebook if this changes in future releases.

null

When to Use SAIPE vs Alternatives

Confidence Intervals

State and county estimates include 90% confidence intervals. Interpretation:

Estimate: 5,000 children in poverty
90% CI: 4,200 - 5,800

Interpretation: We are 90% confident the true value falls
between 4,200 and 5,800.

School district estimates do NOT have published confidence intervals - use CV guidance:

Data Access

Datasets for SAIPE are available via the Education Data Portal mirror system. See

datasets-reference.md

mirrors.yaml

fetch-patterns.md

saipe/districts_saipe

saipe/codebook_districts_saipe

Only district-level SAIPE data is available in the Portal mirrors. State and county SAIPE estimates are published by the Census Bureau but are not included in the Education Data Portal mirror system.

Codebooks are

.xls

get_codebook_url()

fetch-patterns.md

url = get_codebook_url("saipe/codebook_districts_saipe")

Truth Hierarchy: When interpreting variable values, apply this priority:

1. Actual data file (what you observe in the parquet/CSV) — this IS the truth
2. Live codebook (.xls in mirror) — authoritative documentation, may lag
3. This skill documentation — convenient summary, may drift from codebook

If this documentation contradicts the codebook, trust the codebook. If the codebook contradicts observed data, trust the data and investigate.

Filtering

# Filter to a specific state and year
df_state = df.filter(
    (pl.col("fips") == 6) & (pl.col("year") == 2022)
)

# Exclude null poverty estimates
df_valid = df.filter(
    pl.col("est_population_5_17_poverty").is_not_null()
)

# High-poverty districts (above 20%)
df_high = df.filter(
    pl.col("est_population_5_17_poverty_pct").is_not_null()
    & (pl.col("est_population_5_17_poverty_pct") >= 20)
)

Common Pitfalls

./references/historical-changes.md

est_

est_

est_

Poverty Definition

SAIPE uses the official Census Bureau poverty definition:

• Poverty threshold based on family size and composition
• Cash income only (excludes non-cash benefits like SNAP)
• Pre-tax income
• 2023 threshold example: $30,900 for family of 4 with 2 children

"Related children" = persons ages 5-17 related to householder by birth, marriage, or adoption who live in families (excludes foster children, group quarters residents).

Related Data Sources

education-data-source-meps

education-data-source-ccd

education-data-source-nhgis

education-data-explorer

education-data-query

Topic Index

./references/estimation-methodology.md

./references/estimation-methodology.md

./references/estimation-methodology.md

./references/estimation-methodology.md

./references/school-district-estimates.md

./references/school-district-estimates.md

./references/school-district-estimates.md

./references/school-district-estimates.md

./references/variable-definitions.md

./references/variable-definitions.md

./references/variable-definitions.md

./references/data-quality.md

./references/data-quality.md

./references/data-quality.md

./references/data-quality.md

./references/historical-changes.md

./references/historical-changes.md

./references/historical-changes.md

./references/comparison-other-sources.md

./references/comparison-other-sources.md

./references/comparison-other-sources.md