CoG_SUPPORTINGSTATEMENTB_032921

Department of Commerce

U.S. Census Bureau

OMB Information Collection Request

State and Local Government Finance and Public Employment and Payroll Forms

OMB Control No. 0607-0585

Part B. Collection of Information Employing Statistical Methods

1. Universe and Respondent Selection

For the 2021 and 2023 Annual Surveys of State and Local Government Finances and the Annual Survey of Public Employment and Payroll (ASPEP), the estimated sample distribution will be as given in Table 5 supplemented with samples of births each year.

The 2022 Census of Governments: Finance and Employment will canvass the entire universe of approximate 90,000 governments. For the Annual Surveys of State and Local Government Finances and Annual Survey of Public Employment and Payroll, we use an estimated sample size of about 11,000 state local governments selected with probability proportional to size in order to estimate data for governments other than school districts for the Finance component ¹.

Table 5. Sample and Universe Counts Governments
Government Type	2022 Census of Governments (Universe)	Finance Surveys Estimated Sample (For Fiscal Year 2020 Survey)	ASPEP Estimated Sample (For Fiscal Year 2021 Survey)
States	50	50	50
Counties	3,031	1,711	1,561
Municipalities	19,495	3,879	2,927
Townships	16,253	755	543
Special Districts	38,542	4,537	3,045
School Districts	12,754	-	3,389
Total	90,125	10,882	11,515

Samples for the annual surveys are selected every five years with new samples beginning in years ending in ‘4’ and ‘9’.

Table 6. Estimated Sample and Universe Counts of Public Employee-Pension Systems
System Type	2022 Census of Governments (Universe)	Estimated Sample (For Fiscal Year 2021 Survey)
State Systems	297	294
Local Systems	5,232	1,678
Total	5,529	1,918

This sample is supplemented each year with a sample of births.

The unit response rates for the most recent completed survey were:

Survey	Unit Response Rate
2018 Annual Survey of Local Government Finances	88.1%
2019 Annual Survey of State Government Finances	100%
2019 Annual Survey of Public Employment & Payroll	71.3%
2019 Annual Survey of Public Pensions	61.5%

2. Procedures for Collecting Information

1. Surveys of State and Local Government Finances

Sampling

The Annual Survey of Local Government Finances for the 2021 and2023 surveys will use a state-by-type of government stratified probability proportional to size sample drawn with Census of Governments data.

The certainty criteria for the 2021 and 2023 sample, similar to the 2020 sample are as follows:

1) All local governments in the District of Columbia and Hawaii;

2) All county governments with a 2017 population of 500,000 or more;

3) All cities with a 2017 population of 200,000 or more.

The Annual Survey of Public Pensions (ASPP) for 2021 and 2023will use a state area by level (state-local) sample drawn from Census of Governments (CoG) data. The 2021 and 2023sample, similar to the 2020 sample will be a redesign based on the 2017 CoG. The certainty criteria for the 2021 and 2023sample, similar to the 2020 sample are as follows:

1) All state government pension systems;

2) Local systems with total holdings and investments of $500 million or more;

3) All Local pension systems in states with 20 or fewer state and local pension systems.

Non-certainty units are selected as follows:

For the Annual Survey of Local Government Finance a size variable is defined for the sample selection. The size variable for the finance survey is the maximum of total expenditures and a ratio-adjusted second variable, which depends on the local government type. For county governments, the total taxes is used; for cities and townships, the total revenues is used; and for special districts, the total long-term debt is used. Excluding all certainties, we group remaining government units by the unit size variable. If the size variable is zero, then they belong to the “no activity” stratum. Otherwise, they belong to the stratified probability proportional (πPS) universe. A πPS sample is conducted by state and government types. For some townships and special districts, we further apply a modified cut-off sample methodology, where subsampling is performed to reduce the number of non-contributory sub-counties and special districts in the sample.

 

Between sample redesigns, we supplement the sample with births and remove disincorporation, or deaths from the sample. We take all general purpose governments and add them as births to the sample. In years with a large numbers of special district births, we apply a systematic sample method by function code and state and then add the selected births to the sample; otherwise, all special district births are added to the sample.

 

The total holdings and investments is defined as the size variable whenever it is available. Local governments with this variable are selected for the sample based on a probability proportional-to-size design without replacement (πPS) for each state and government type. For units that are missing total investment and holdings, the ratio of a proxy variable to the total employees is used to construct strata using the cumulative square root of the frequency method.

Estimation Procedure

 

The survey calculations will employ a model adaptive method to estimate aggregated level such as general sales, selective sales, liquor stores revenue, current operation, capital outlay, education, health, highways, and so on, and then apply an indirect synthetic estimation method to project the total for detailed viewable and downloadable variables. Pension Survey estimates are developed using a simple design-based unbiased estimator, the Horvitz-Thompson.

Degree of Accuracy

 

State Area Estimates of Local Government Totals. For state area estimates of only local government totals, the finance sample is designed to produce totals with a relative standard error of three percent or less or five percent or less on the following 11 major financial items:

Three percent or less:

• Long-term debt outstanding

 

• Total revenue

 

• Total expenditure

 

• Criminal justice expenditure

Five percent or less:

 

• Education expenditure

 

• Highways expenditure

 

• Health expenditure

 

• Housing expenditure

 

• Total capital outlay expenditure

 

• Utilities expenditure

 

• Welfare expenditure

State Area Estimates of State and Local Government Totals. With the addition of state government data to the local government information, the finance sample for survey generally yields state area estimates with a relative standard error of one percent or less on total revenue and total expenditures and under two percent for long-term debt outstanding.

 

State Area Estimates of State and Local Pension Systems. For state area estimates of state and local pension systems, the sample is designed to produce totals with a relative standard error of three percent or less on total cash and security holdings of public employee pension systems.

2. Survey of Public Employment & Payroll

The sample is designed and selected to include governments that comprise the majority of the employment and payroll activity. All 50 state governments as well as all units in the District of Columbia and Hawaii are selected with certainty. A two-stage sample was designed to produce state-by-type of government estimates with a relative standard error of three percent or less for FTE employees and total payroll at the national level. In the first stage, the sample design is stratified probability proportional to size (PPS) of the local governments. In the second stage, a modified cut-off sample method was used to reduce the number of small townships and special districts included in the final sample.

The Census Bureau will prepare estimates by state for local government employment and payrolls (total full-time employment, total full-time payroll, total full-time equivalent employment, total part-time employment, and total part-time payrolls) and by state and government function in sample years. Hybrid estimate methods will be used to determine state-by-type of governmental totals. There are three methods in the hybrid approach. First, the Horvitz-Thompson (HT) estimator is a weighted sum of the sample data. Second, the Empirical Best Linear Unbiased Prediction (EBLUP) estimator is used with a robust estimation approach that includes 2017 data as covariates. Third, the synthetic estimator is based on a Decision-Based estimator of the state total and the assumption that employment in the sample year is proportional to employment in the 2017 Census year for the same state and function.

3. Methods to Maximize Response

The Census Bureau area consults with, and presents to, various public and professional groups that use the data. We use several methods and resources to maximize response in the collection of government finance data, including: follow-up mailings; telephone follow-up to non-respondents; central data collection arrangements; electronic files, administrative records; and Internet data collection.

4. Tests of Procedures or Methods

The Census Bureau continually reviews record keeping practice studies and conducts cognitive testing to examine the financial and employment activity of state and local governments, and public employee pension systems and incorporated into survey questionnaires where feasible. The Census Bureau conducted cognitive testing in 2020 of the Quarterly Summary of State and Local Government Tax Revenue to determine the feasibility of collecting new data items, which will also be collected through the Annual Survey of State Tax Collections. The new data items are readily available to respondents with no added burden, thus the results of QTAX Cognitive Interviews Final Report are applicable.

The Census Bureau will continue to test survey questionnaires as needed when planning questionnaire changes.

5. Contacts for Statistical Aspects and Data Collection

Questions relating to the statistical aspects of the surveys:

Bac Tran (301-763-1937) Chief, Public Sector Sample Design and Estimation Branch

Questions relating to the collection and analysis of the data:

Randy Moore (301-763-7231), Chief, Local Finance Statistics Branch

Kristina Frates (301-763-5034), Chief, State Finance and Tax Statistics Branch

Phil Vidal (301-763-1749), Chief, Pensions Statistics Branch

Paul Villena (301-763-7286), Chief, Employment Statistics Branch

Attachments

1. Finance Surveys Initial Request, Due Date Reminder and Follow-Up Letters

2. Forms F-5 Spreadsheet, F-11, F-12, F-13, F-28, F-29, F-32 and electronic reporting instrument login screen and burden statement for local finance and public pensions.

3. Forms E-1 through E-10, electronic reporting instrument login screen and burden statement for employment

4. ASPEP Initial Request, Due Date Reminder and Follow-Up Letters and Elected Officials Flyer

5. Letter of Support from BEA

6. QTAX Cognitive Interviews F&R Final Report

1¹ Elementary and secondary school system finance data are collected under authority of a separate submission; see OMB clearance 0607-0700, expiration date 1/31/2024 through a joint undertaking between the National Center for Education Statistics and the Census Bureau. For the 2022 Census of Governments, we will use the universe data and for the annual surveys in 2021and 2023, we will use the universe for independent school systems and only the dependent school systems included in those government units chosen in the non-school local government sample..

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