/education-data-source-saipe¶
Source guide to Census Small Area Income and Poverty Estimates for school districts, with the lag, the absence of race breakdowns at district level and when to switch to ACS five-year estimates.
data-handlingLGPL-3.0-or-later (as declared in the README, badge and CITATION.cff; the repo ships the GPL-3.0 text as LICENSE plus COPYING.LESSER)data-acquisition
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) 16-1-3Census 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.mdfor 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: 1995-2024 (gaps at 1996, 1998; annual from 1999). The v2 mirror (build validated 2026-08-06) extends
districts_saipethrough 2024. - 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¶
| File | Purpose | When to Read |
|---|---|---|
estimation-methodology.md |
How state/county models work | Understanding model inputs and outputs |
school-district-estimates.md |
How district estimates are derived | Working with school district data |
variable-definitions.md |
Variables, codes, population universes | Interpreting specific data fields |
data-quality.md |
Uncertainty, CV, limitations | Assessing estimate reliability |
historical-changes.md |
Methodology changes over time | Comparing across years |
comparison-other-sources.md |
SAIPE vs ACS, FRPL, CPS | Choosing between data sources |
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_ prefix:
| Short Name | Portal Column Name |
|---|---|
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¶
| ID | Format | Level | Example | Notes |
|---|---|---|---|---|
fips |
Integer | State | 6 |
State FIPS code (no leading zeros in Portal) |
leaid |
String | District | 0100005 |
NCES district ID; join key to CCD |
year |
Integer | Time | 2022 |
Estimate reference year |
School District Estimates¶
| Variable | Description | Notes |
|---|---|---|
est_population_total |
Total population in district | Not enrollment - residential population |
est_population_5_17 |
Children ages 5-17 | School-age population, all enrollment types |
est_population_5_17_poverty |
Related children 5-17 in families in poverty | Numerator for poverty calculations |
est_population_5_17_poverty_pct |
Percent of children 5-17 in poverty | Not a true rate - see notes |
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 viafetch_from_mirrors().
| Variable | Description |
|---|---|
population_0_4_poverty |
Children under 5 in poverty (states only) |
population_0_17_poverty |
All children under 18 in poverty |
population_poverty |
All ages in poverty |
median_household_income |
Median household income |
Missing Data Codes¶
Empirical observation (2025): The
districts_saipeparquet file usesnullfor 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.
| Code | Meaning | When Used |
|---|---|---|
null |
Missing or unavailable | Estimate not produced for this district/year |
When to Use SAIPE vs Alternatives¶
| Use Case | Best Source | Reason |
|---|---|---|
| Title I allocations | SAIPE | Legally mandated source |
| Annual district poverty | SAIPE | Only annual source for all districts |
| District poverty by race | ACS 5-year | SAIPE has no race breakdown |
| School-level poverty | ACS 5-year or FRPL | SAIPE is district-level only |
| Most current data | ACS 1-year | Lower lag (but fewer districts) |
| 5-year trends | Use caution | Methodology breaks exist |
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:
| District Population | Median CV | Approximate 90% CI Width |
|---|---|---|
| 0-2,500 | 0.67 | +/- 110% |
| 2,500-5,000 | 0.42 | +/- 69% |
| 5,000-10,000 | 0.35 | +/- 58% |
| 10,000-20,000 | 0.28 | +/- 46% |
| 20,000-65,000 | 0.23 | +/- 38% |
| 65,000+ | 0.15 | +/- 25% |
Data Access¶
Datasets for SAIPE are available via the Education Data Portal mirror system. See datasets-reference.md for canonical paths, mirrors.yaml for mirror configuration, and fetch-patterns.md for fetch code patterns.
| Dataset | Type | Years | Path | Codebook |
|---|---|---|---|---|
| District Poverty Estimates | Single | 1995-2024 (gaps: 1996, 1998) | 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 files co-located with data in all mirrors. Use get_codebook_url() from fetch-patterns.md to construct download URLs:
## R equivalent.
## get_codebook_url() is a Python helper; in R, construct the codebook URL from
## the mirror root in mirrors.yaml (codebooks are .xls files co-located with data).
## Mirror failover: see `education-data-query/references/fetch-patterns.md` (R pattern).
config <- yaml::read_yaml("mirrors.yaml")
mirror <- config$mirrors[[1]]
url <- paste0(mirror$root_url, "/", "saipe/codebook_districts_saipe", ".xls")
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)
)
## R equivalent
library(dplyr)
## Filter to a specific state and year
df_state <- df |> filter(fips == 6, year == 2022)
## Exclude null poverty estimates
df_valid <- df |> filter(!is.na(est_population_5_17_poverty))
## High-poverty districts (above 20%)
df_high <- df |> filter(!is.na(est_population_5_17_poverty_pct),
est_population_5_17_poverty_pct >= 20)
Common Pitfalls¶
| Pitfall | Issue | Solution |
|---|---|---|
| Model-based estimates | Not direct counts; contain model uncertainty | Always use confidence intervals; check CV for small districts |
| ~18 month lag | e.g. 2023 estimates released Dec 2024; data never "current" (v2 mirror now reaches 2024) | Accept lag for federal allocations; document vintage |
| No race/ethnicity | School district estimates are not disaggregated by demographics | Use ACS 5-year estimates for racial breakdowns |
| Not enrollment | Population-based (residential), not enrolled students | Different from FRPL counts; do not equate with enrollment |
| Boundary timing | May not reflect very recent district consolidations or splits | Check SDRP update cycle in ./references/historical-changes.md |
| County allocation | Districts inherit county model uncertainty plus allocation uncertainty | Larger CV for small districts; use CV table for reliability |
Missing est_ prefix |
Portal columns use est_ prefix not shown in some documentation |
Always use est_-prefixed column names when working with Portal data |
| Pre/post 2010 comparison | Methodology break at 2010 decennial update invalidates naive trends | Do not compare school district estimates across the 2010 boundary |
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¶
| Source | Relationship | When to Use |
|---|---|---|
education-data-source-meps |
Complementary poverty source (school-level) | School-level poverty estimates (MEPS) vs district-level (SAIPE) |
education-data-source-ccd |
K-12 enrollment and demographics | Join on LEAID for district enrollment alongside poverty |
education-data-source-nhgis |
Census/demographic data | ACS 5-year tables for race-disaggregated poverty |
education-data-explorer |
Parent discovery skill | Routing questions to mirror dataset files and variables |
education-data-query |
Data fetching | Downloading parquet/CSV files from mirrors |
Topic Index¶
| Topic | Reference File |
|---|---|
| Model-based estimation | ./references/estimation-methodology.md |
| Shrinkage estimators | ./references/estimation-methodology.md |
| ACS integration | ./references/estimation-methodology.md |
| Administrative records | ./references/estimation-methodology.md |
| School district methodology | ./references/school-district-estimates.md |
| Within-county shares | ./references/school-district-estimates.md |
| Grade relevance | ./references/school-district-estimates.md |
| Overlapping districts | ./references/school-district-estimates.md |
| Variable definitions | ./references/variable-definitions.md |
| Population universes | ./references/variable-definitions.md |
| Poverty thresholds | ./references/variable-definitions.md |
| Confidence intervals | ./references/data-quality.md |
| Coefficient of variation | ./references/data-quality.md |
| Small area uncertainty | ./references/data-quality.md |
| Geocoding limitations | ./references/data-quality.md |
| 2005 ACS switch | ./references/historical-changes.md |
| 2010 decennial update | ./references/historical-changes.md |
| Methodology breaks | ./references/historical-changes.md |
| SAIPE vs FRPL | ./references/comparison-other-sources.md |
| SAIPE vs ACS | ./references/comparison-other-sources.md |
| Title I requirements | ./references/comparison-other-sources.md |