`/education-data-source-pseo`¶

Source guide to Census Post-Secondary Employment Outcomes, graduate earnings percentiles one, five and ten years out by institution, degree and field from LEHD wage records, with its partial and changing institutional coverage.

Pack: DAAF — Data Analyst Augmentation Framework (Brian Heseung Kim)

Category: data-handling

Field: social-sciences

License:

LGPL-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)

Updated: 2026-08-09

Stages: data-acquisition

↗ view SKILL.md on source · GitHub stars

PSEO Data Source Reference¶

Postsecondary Employment Outcomes (PSEO) — Census Bureau experimental statistics linking college graduates to employment outcomes via UI wage records (LEHD program). Covers earnings (25th/50th/75th percentile, measured 1, 5, and 10 years post-graduation) and employment flows by institution, degree level, and CIP field. Use when comparing graduate earnings across programs or institutions, analyzing industry entry patterns, or studying geographic migration of graduates. Coverage is partner-based and changes by release; Census V4.13.0 (2025Q4) contains 952 institutions and partners in 32 states plus the District of Columbia.

Postsecondary Employment Outcomes (PSEO) is an experimental data product from the U.S. Census Bureau that links college graduate records to national employment data, providing earnings and employment outcomes by institution, degree level, and field of study.

CRITICAL: Value Encoding

This document describes Education Data Portal integer encodings, which differ from Census API string codes. The Portal converts categorical variables to integers for consistency.

Context Baccalaureate Associates Masters Census Division Pacific

Portal (integers) 5 3 7 9

Census API (strings) 05 03 07 9

Key differences: Degree level uses simple integers (1-10), not string codes like "1C", "05". CIP codes are 2-digit integers (11 for Computer Science), not strings like "11.01".

See ./references/variable-definitions.md for complete encoding tables.

What is PSEO?¶

Producer: U.S. Census Bureau, LEHD program (Longitudinal Employer-Household Dynamics)
Coverage: Partner-based and release-specific; V4.13.0 (2025Q4) contains 952 institutions and partners in 32 states plus D.C., including Western Governors University
Content: Links university transcript data with national UI wage records to track graduate employment outcomes
Two data types: Graduate Earnings (percentile earnings) and Employment Flows (industry/geography)
Frequency: Updated periodically; cohorts span 3-year (Bachelor's) or 5-year (all others) windows; verify the latest institution, partner, and version files before reporting coverage
Primary identifiers: unitid (IPEDS Unit ID, integer), opeid (integer in Portal data)
Privacy method: Differential privacy mechanisms protect individual data
Available through: Education Data Portal mirrors (restructured from Census Bureau LEHD format with integer encodings and lowercase variable names)

Reference File Structure¶

File	Purpose	When to Read
`lehd-methodology.md`	How LEHD produces tabulations, data matching process	Understanding data creation
`earnings-data.md`	Percentile earnings, cohort definitions, labor attachment	Analyzing graduate earnings
`geographic-flows.md`	Where graduates work by Census Division	Studying migration patterns
`industry-flows.md`	What industries graduates enter by NAICS sector	Career pathway analysis
`variable-definitions.md`	All variables, codes, and status flags	Building queries or interpreting values
`state-coverage.md`	Participating states, coverage rates, data partners	Understanding limitations

Decision Trees¶

What type of outcome am I researching?¶

Text Only

Graduate outcomes research?
├─ Earnings by program/institution
│   ├─ Median earnings → `p50_earnings` column, filter by `years_after_grad`
│   ├─ Earnings distribution → `p25_earnings`/`p50_earnings`/`p75_earnings`
│   └─ See ./references/earnings-data.md
├─ Where graduates work (geography)
│   ├─ Census Division of employment → `census_division` column
│   ├─ In-state vs out-of-state → `employed_instate_grads_count`
│   └─ See ./references/geographic-flows.md
├─ What industries graduates enter
│   ├─ NAICS sector employment → `industry` column (String)
│   └─ See ./references/industry-flows.md
└─ How many graduates are employed
    ├─ Employment counts → `employed_grads_count_f`
    ├─ Non-employed/marginal → `jobless_m_emp_grads_count`
    └─ See ./references/variable-definitions.md

What degree level am I researching?¶

Text Only

Degree level?
├─ Certificate (<1 year) → degree_level=1
├─ Certificate (1-2 years) → degree_level=2
├─ Certificate (2-4 years) → degree_level=4
├─ Associate's → degree_level=3
├─ Bachelor's → degree_level=5 (default, 3-year cohorts)
├─ Post-Bacc Certificate → degree_level=6
├─ Master's → degree_level=7 (2-digit CIP only)
├─ Post-Masters Certificate → degree_level=8
├─ Doctoral-Research → degree_level=9 (2-digit CIP only)
└─ Doctoral-Professional Practice → degree_level=10

Note: Portal uses integers 1-10. Census Bureau source data uses string codes like "05", "1C" -- these do not appear in Portal data.

Is my institution/state covered?¶

Text Only

Checking data availability?
├─ Current participating partners/institutions → Check Census latest-release files
├─ Release-specific coverage context → ./references/state-coverage.md
├─ Portal-covered institution/cohort rows → Check the mirror data actually used
└─ Why data might be missing
    ├─ Institution not partnered
    ├─ Cell suppressed (count < 30)
    └─ Insufficient labor force attachment

Quick Reference: PSEO Variables¶

Earnings Variables¶

Portal Variable	Description
`p25_earnings`	25th percentile earnings (2022 dollars)
`p50_earnings`	Median earnings (2022 dollars)
`p75_earnings`	75th percentile earnings (2022 dollars)
`years_after_grad`	Years post-graduation: `1`, `5`, or `10`
`employed_grads_count_e`	Graduate count with earnings data
`total_grads_count`	Total IPEDS-reported graduates

Flows Variables¶

Portal Variable	Description
`employed_grads_count_f`	Employed graduates count
`employed_instate_grads_count`	Employed in institution's state
`jobless_m_emp_grads_count`	Non-employed or marginally employed
`industry`	2-digit NAICS sector (String, e.g., `"54"`, `"31-33"`)
`census_division`	Census Division of employment (1-9, 99)

Note: Portal uses restructured schema with years_after_grad column instead of Census API's Y1_*/Y5_*/Y10_* naming. The industry column is String type because some NAICS sectors span ranges (e.g., "31-33" for Manufacturing, "44-45" for Retail Trade).

Key Identifiers¶

ID	Format	Level	Example	Notes
`unitid`	Integer	Institution	`100751`	IPEDS Unit ID (University of Alabama)
`opeid`	Integer	Institution	`105100`	Portal stores as integer (Census uses 8-digit zero-padded string)
`fips`	Integer	State	`48`	State of institution (Texas)
`cipcode`	2-digit integer	Field of study	`11`	Computer Science; Portal uses integers, not "11.01"

Key Filters (Portal Integer Encoding)¶

Parameter	Description	Example
`degree_level`	Degree type integer	`5` (Bachelor's)
`pseo_cohort`	Graduation cohort	`"2016-2020"` or `"2019-2021"` (string format, full year range)
`years_after_grad`	Years post-graduation	`1`, `5`, or `10`

Cohort Definitions¶

Degree Level	Cohort Years	Example Cohorts
Bachelor's	3-year	`"2001-2003"`, `"2004-2006"`, `"2007-2009"`, `"2010-2012"`, `"2013-2015"`, `"2016-2018"`, `"2019-2021"`
All others	5-year	`"2001-2005"`, `"2006-2010"`, `"2011-2015"`, `"2016-2020"`

Missing Data Codes¶

Code	Meaning	When Used
`-1`	Missing/not reported	Primary missing data indicator; very common in earnings and flows columns
`-3`	Suppressed	Cell count < 30 graduates (differential privacy suppression)
`-2`	Not applicable	Item doesn't apply to this entity (Portal convention)

Note: PSEO data has no null values in the parquet files. All missing/suppressed data uses integer codes (-1, -3). Filter with pl.col("p50_earnings") > 0 to get valid earnings, not .is_not_null(). PSEO uses differential privacy rather than traditional suppression. Cells with fewer than 30 graduates are suppressed entirely (coded as -3). Earnings values coded -1 may indicate insufficient labor force attachment.

Data Access¶

Datasets for PSEO 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	Path	Codebook
Earnings and Flows	Yearly (2001-2021)	`pseo/colleges_pseo_{year}`	`pseo/codebook_colleges_pseo`

Codebooks are .xls files co-located with data in all mirrors. Use get_codebook_url() from fetch-patterns.md to construct download URLs.

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.

Fetching PSEO Data¶

Python

import polars as pl

## PSEO is a yearly dataset -- fetch individual years
df = fetch_yearly_from_mirrors(
    path_template="pseo/colleges_pseo_{year}",
    years=[2018, 2019, 2020],
)

## Or fetch a single year
df = fetch_from_mirrors("pseo/colleges_pseo_2020")

S

library(arrow)
library(dplyr)

## fetch_yearly_from_mirrors()/fetch_from_mirrors() are Python helpers; in R,
## build URLs from the mirror root in mirrors.yaml and read directly.
## Mirror failover: see `education-data-query/references/fetch-patterns.md` (R pattern).
config <- yaml::read_yaml("mirrors.yaml")
mirror <- config$mirrors[[1]]

## PSEO is a yearly dataset -- fetch individual years and bind
frames <- list()
## NOTE: illustrative only — mirror parquet files are Polars-written and may
## declare string_view columns, so a plain read can fail under R arrow
## ("cannot handle Array of type <utf8_view>"). Real fetch scripts must use the
## view-safe parquet read from `education-data-query/references/fetch-patterns.md`.
for (y in c(2018, 2019, 2020)) {
  url <- paste0(mirror$root_url, "/", "pseo/colleges_pseo_", y, ".", mirror$format)
  frames[[length(frames) + 1]] <- arrow::read_parquet(url)
}
df <- bind_rows(frames)

## Or fetch a single year
url <- paste0(mirror$root_url, "/", "pseo/colleges_pseo_2020", ".", mirror$format)
df <- arrow::read_parquet(url)

Filtering¶

Python

## Filter by institution
df.filter(pl.col("unitid") == 100751)  # University of Alabama

## Filter by field of study
df.filter(pl.col("cipcode") == 11)  # Computer Science

## Filter by cohort (note: full year range format)
df.filter(pl.col("pseo_cohort") == "2019-2021")

## Earnings rows only (exclude missing/suppressed)
df.filter(pl.col("p50_earnings") > 0)

## Filter by industry (String column, not integer)
df.filter(pl.col("industry") == "54")  # Professional Services

S

## Filter by institution
df |> filter(unitid == 100751)  # University of Alabama

## Filter by field of study
df |> filter(cipcode == 11)  # Computer Science

## Filter by cohort (note: full year range format)
df |> filter(pseo_cohort == "2019-2021")

## Earnings rows only (exclude missing/suppressed)
df |> filter(p50_earnings > 0)

## Filter by industry (String column, not integer)
df |> filter(industry == "54")  # Professional Services

Additional Access Methods (Census Bureau Source)¶

PSEO Explorer: Interactive visualization tool at https://lehd.ces.census.gov/data/pseo_explorer.html
Census bulk download: CSV/XLS files at https://lehd.ces.census.gov/data/pseo/
Census API: https://api.census.gov/data/timeseries/pseo/earnings and .../flows (uses different variable naming and string codes; not used in this system)

Release-Specific Coverage Verification¶

PSEO participation changes between releases. Before reporting a state, partner, or institution count, inspect the current Census release metadata rather than carrying a fixed historical count forward:

Institutions: https://lehd.ces.census.gov/data/pseo/latest_release/all/pseo_all_institutions.csv
Partners: https://lehd.ces.census.gov/data/pseo/latest_release/all/pseo_all_partners.txt
Version: https://lehd.ces.census.gov/data/pseo/latest_release/all/version_pseo.txt

As verified on 2026-07-21, version V4.13.0 (2025Q4) lists 952 institutions and partners in 32 states plus D.C. This release-specific roster does not establish a national percentage of all graduates. The Portal mirror remains a fixed 2001–2021 snapshot; distinguish its observed rows from the current Census release roster.

Common Pitfalls¶

Pitfall	Issue	Solution
Using Census string codes	Portal uses integers (e.g., `5` for Bachelor's), not Census strings (`"05"`)	Always check encoding; see variable-definitions.md
Ignoring suppression	Cells with <30 graduates are suppressed; missing data looks like no program exists	Check `total_grads_count` to confirm cell exists; null earnings may mean suppression
Cross-institution comparison without controlling degree/CIP	Institutions offer different program mixes; aggregate comparison is misleading	Always filter to same `degree_level` and `cipcode` when comparing institutions
Treating PSEO as comprehensive	Participation is voluntary and changes by release; no verified national graduate-coverage percentage is documented here	Report the release/version and partner roster used; acknowledge selection bias and do not generalize to all U.S. graduates
Ignoring labor attachment	Workers need 3+ quarters above minimum wage threshold to appear in earnings data	Some graduates are employed but excluded; note this limitation
Treating Portal opeid as string	Portal stores `opeid` as integer (e.g., `105100`), not Census's 8-digit zero-padded string (`"00105100"`)	Use integer comparison in Portal data; only Census API uses string format
Mixing cohort spans	Bachelor's uses 3-year cohorts; all others use 5-year	Filter by `degree_level` first, then verify cohort format matches
Assuming inflation comparability	All earnings are in 2022 CPI-U dollars	No manual inflation adjustment needed; values are already real dollars

PSEO vs Other Data Sources¶

Feature	PSEO	College Scorecard	State Systems
Coverage	Graduates only	All enrollees	Graduates only
Geographic scope	National (cross-state)	National	In-state only
Sample	All graduates from partners	Federal aid recipients	All graduates
Earnings detail	25th/50th/75th percentile	Median only	Varies
Industry data	Yes (NAICS sector)	No	Varies
Geographic flows	Yes (Census Division)	No	No
Privacy method	Differential privacy	Traditional suppression	Varies

Common Use Cases¶

Use Case	Data Needed	Key Considerations
Compare programs within institution	Earnings by CIPCODE	Check cell counts for suppression
Compare institutions for same program	Earnings by INSTITUTION	Ensure same degree level and CIP
Analyze brain drain/retention	Flows by division + in-state	Only 9 Census Divisions
Career pathway analysis	Flows by NAICS sector	2-digit NAICS only
ROI by degree level	Earnings across DEGREE_LEVEL	Different cohort spans

Important Limitations¶

Experimental status: Not official Census statistics; methodology may change
Partial, changing coverage: Partner and institution participation varies by Census release; V4.13.0 (2025Q4) lists 952 institutions and partners in 32 states plus D.C., but no verified national graduate-coverage percentage is asserted here
Selection bias: Participating states/institutions may differ systematically
Employment coverage: Excludes self-employed, independent contractors, military, some federal
Labor attachment requirement: Workers must have 3+ quarters of earnings above minimum wage threshold
Suppression: Cells with fewer than 30 graduates are suppressed
Earnings inflation-adjusted: All earnings in 2022 dollars (CPI-U)

Source	Relationship	When to Use
`education-data-source-scorecard`	Alternative earnings source (median only, all enrollees)	When PSEO coverage is insufficient or need non-graduate outcomes
`education-data-source-ipeds`	Institution characteristics, enrollment, graduation rates	Contextualizing PSEO institutions; join on `unitid`
`education-data-explorer`	Parent discovery skill	Routing questions to mirror dataset files
`education-data-query`	Data fetching	Downloading parquet/CSV files

Topic Index¶

Topic	Reference File
LEHD program overview	`./references/lehd-methodology.md`
Data matching process	`./references/lehd-methodology.md`
Differential privacy	`./references/lehd-methodology.md`
Percentile earnings	`./references/earnings-data.md`
Labor force attachment	`./references/earnings-data.md`
Cohort definitions	`./references/earnings-data.md`
Census Division employment	`./references/geographic-flows.md`
In-state employment	`./references/geographic-flows.md`
NAICS sector employment	`./references/industry-flows.md`
Industry code reference	`./references/industry-flows.md`
Variable names and codes	`./references/variable-definitions.md`
Status flags	`./references/variable-definitions.md`
State participation	`./references/state-coverage.md`
Coverage rates	`./references/state-coverage.md`
Data partners	`./references/state-coverage.md`
Mirror-based data download	Data Access section above
Bulk data download	Data Access section above

Context	Baccalaureate	Associates	Masters	Census Division Pacific
Portal (integers)	`5`	`3`	`7`	`9`
Census API (strings)	`05`	`03`	`07`	`9`

/education-data-source-pseo¶

PSEO Data Source Reference¶

What is PSEO?¶

Reference File Structure¶

Decision Trees¶

What type of outcome am I researching?¶

What degree level am I researching?¶

Is my institution/state covered?¶

Quick Reference: PSEO Variables¶

Earnings Variables¶

Flows Variables¶

Key Identifiers¶

Key Filters (Portal Integer Encoding)¶

Cohort Definitions¶

Missing Data Codes¶

Data Access¶

Fetching PSEO Data¶

Filtering¶

Additional Access Methods (Census Bureau Source)¶

Release-Specific Coverage Verification¶

Common Pitfalls¶

PSEO vs Other Data Sources¶

Common Use Cases¶

Important Limitations¶

Related Data Sources¶

Topic Index¶

`/education-data-source-pseo`¶