Measuring Poverty Subannually in 

the United States

Ani Rudra Silwal

U.S. Census Bureau

FCSM Conference

October 24, 2023

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This presentation is released to inform interested parties of ongoing research and to encourage discussion. Any views expressed 

are those of the author and not those of the U.S. Census Bureau. The U.S. Census Bureau has reviewed this data product for 

unauthorized disclosure of confidential information and approved the disclosure avoidance practices applied to this release. 

(DMS # D-0000010797, DRB #CBDRB-FY24-SEHSD003-002.)
Why subannual poverty?

• Annual poverty measures used widely to measure monetary well-being.

• Demand for more timely and frequent measures of poverty.

• Subannual: reference period and publication frequency of less than a year.

• Comprehensive data on income are not collected subannually, need to 

exploit existing sources.

• Goal: propose methodology that could be used for a research series by 

the Census Bureau.

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Data and literature

• Current Population Survey (CPS)

• Annual Social and Economic Supplement (CPS ASEC): source of official poverty and 

Supplemental Poverty Measure (SPM) rates.

• Basic monthly CPS: Official source of labor force statistics.

• Literature:

• Orshansky (1963): tension between annual data collection and monthly benefits.

• Ruggles (1990) used SIPP data; Citro and Michael (1995) acknowledged issue.

• Bergmann and Coder (2010) combined CPS ASEC with monthly CPS.

• Response to COVID-19: Han et al. (2020) and Parolin et al. (2020, 2022)

• I generalize and extend Parolin et al. (2020, 2022).

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Methodology at a glance

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CPS ASEC Monthly CPS

Annual resources/thresholds

+ 

Variables associated with poverty

Model of 

poverty status Monthly 

poverty 

statistics

Variables associated 

with poverty
Rules for converting annual resource components to their 

monthly values

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• Group 1: Components that are divided by 12 (e.g., Social Security).

• Group 2: Components that are divided by 12 and then adjusted if an 

individual was unemployed recently (e.g., wage earnings).

• Group 3: Components that are only allocated to a single month (e.g. Earned 

Income Tax Credits).

• Group 4: Components that are allocated equally to all non-summer months 

(e.g., school lunch program).
Core CPS variables used in the imputation model

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Age

Sex

Education

Region of 

residence

Race/

ethnicity

Citizenship 

and origin

Family 

structure

Marital 

Status

Disability 

status

Employment

Unemployment

Interaction 

terms
Multiple imputation

• Combined-sample multiple imputation.

• Outcome variable in CPS ASEC: poverty status. 

• Estimated using linear probability model.

• Imputed variable: probability of someone in monthly CPS being in 

poverty.

• Model specification based on literature.

• Mean of 10 imputations.

• I compute standard error of estimates.

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Monthly OPM and SPM, January 2009 – August 2023

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Source: U.S. Census Bureau, Current Population Survey (CPS) public-use data for January 2009 - August 2023, Annual Social and Economic 

Supplements (CPS ASEC) internal data for survey years 2010-2023. Shaded areas represent 90 percent confidence intervals. 

OPM=Official poverty measure; SPM = Supplemental Poverty Measure
Revising monthly estimates with the release of new 

CPS ASEC data

September

2023

September

2024

Month of 

interest

August

2023

1st estimate published with:

CPS monthly (August 2023)

CPS ASEC (Ref. year 2022)

2nd estimate revised with:

CPS monthly (August 2023)

CPS ASEC (Ref. year 2023)
Will monthly estimates change when new CPS ASEC data are released?

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Each September, estimates for the current and previous calendar years are revised to incorporate the most recent 

release of the CPS ASEC.

Source: U.S. Census Bureau, Current Population Survey (CPS) public-use data for January 2009 - August 2023, Annual Social and Economic 

Supplements (CPS ASEC) internal data for survey years 2010-2023.
Annual revisions of the monthly SPM rate 2019-2023

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Source: U.S. Census Bureau, Current Population Survey (CPS) public-use data for January 2009 - August 2023, Annual Social and Economic 

Supplements (CPS ASEC) internal data for survey years 2010-2023.
Some pandemic-era policies can be modeled by month

12 Notes: EITC = Earned Income Tax Credit; EIP = Economic Impact Payments; CTC = Refundable portion of the Child Tax Credit; CDCC = Child and Dependent Care Credit

Assumptions for modeling refundable tax credits

Month EITC EIP 1 EIP 2 EIP 3 CTC CDCC

Jan-2020

Feb-2020

Mar-2020 X X

Apr-2020 X X (60%) X

May-2020 X (30%)

Jun-2020 X (10%)

Jul-2020

Aug-2020

Sep-2020

Oct-2020

Nov-2020

Dec-2020

Jan-2021 X (80%)

Feb-2021 X (20%)

Mar-2021 X X (80%) X

Apr-2021 X X (20%) X

May-2021

Jun-2021

Jul-2021 X (1/12)

Aug-2021 X (1/12)

Sep-2021 X (1/12)

Oct-2021 X (1/12)

Nov-2021 X (1/12)

Dec-2021 X (1/12)

Refundable tax credits

X (1/2)
EIPs can be allocated to specific months of 2021 and 2022

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EIP = Economic Impact Payments

Monthly SPM rate with and without EIP

Source: U.S. Census Bureau, public-use Current Population Survey (CPS) data for January 2009 - August 2023, Annual Social and Economic 

Supplements (CPS ASEC) for survey years 2010-2023.
Conclusion

• Subannual poverty could be a part of a suite of measures of wellbeing to supplement existing annual measures.

• Next steps: 

• Modify how refundable tax credits are allocated across months.

• Updated working paper with improvements to methodology.

• Tableau dashboard to publish these estimates.

• We are looking for feedback on:

• Are there better ways to model refundable tax credits?

• Should estimates be revised over time (like GDP growth)?

• Anything else we should be considering in these estimates?

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Thank you!