Appendix A

List of Conclusions and Recommendations

*Indicates inclusion in Summary

*Conclusion 2-1: Conceptual definitions of household income, consumption, and wealth are most useful when they are constructed to satisfy the budget identity, C = I – S. The components of income (I) and saving (S) should be consistent with a sources-and-uses framework for consumption (C). Such a framework accounts for all the value coming in and going out of the household (via savings and transfers), with the residual being the amount consumed. A fundamental principle in specifying an integrated data system is that decisions about what to count as income have direct implications for what to count as consumption and wealth.

Conclusion 2-2: For the purpose of addressing distributional questions, a complete description of the budget identity (and, in particular, an accurate portrayal of consumption) requires the calculation and investigation of discrepancies therein.

*Conclusion 2-3: Multiple definitions of household income, consumption, and wealth (ICW) are needed to examine different policy and research questions ranging from the impacts of fiscal policies to distributional analyses. To aid users of ICW statistics in selecting appropriate measurement constructs, each definition requires specification of accompanying purpose(s) and a transparent guide to its construction.

*Conclusion 2-4: Definitions embedded in systems of national accounts provide a well-established starting point for the variety of income, consumption, and wealth concepts envisioned for the dataset recommended in this report. These definitions include an income measure comparable to the national accounts, a measure of adjusted disposable income comparable to the Organisation for Economic Co-operation and Development measure (including retirement distributions and in-kind transfers), a measure of consumption similar to personal consumption expenditures, and a measure of wealth consistent with the financial accounts, which is similar to the definition used in the regular publication for the Survey of Consumer Finances but which also adds the value of defined benefit pension wealth.

Conclusion 2-5: Definitions of income that do not completely satisfy the budget identity or aggregate to the national accounts may still be useful for some statistical and policy purposes. An example is after-tax- and-transfers income as defined by the Congressional Budget Office (see Table 2-1) but that includes both realized and unrealized capital gains.

*Conclusion 2-6: Just as there are tailored definitions of income, consumption, and wealth to serve various research and policy purposes, the construction of conceptually complicated components, such as retirement income, health insurance benefits, capital gains, corporate profits, and the value of homeownership, will also entail tailored definitions.

Conclusion 2-7: An additional definition of consumption that would be useful for distributional and other analyses is one that would include rental equivalence (for home owners) and service flows from vehicles and add health and education spending but exclude time use. The measure proposed by the Bureau of Labor Statistics in its initiative to develop a comprehensive consumption measure would go part of the way by adding (to the Consumer Expenditure Survey) estimates of imputed rental income and the consumption component of education (but not investment components, of which tuition is one), but also including time use and excluding expenditures on health insurance.

Conclusion 2-8: A useful definition of wealth for assessing the ability of households to finance current and future consumption is that used for the Bulletin publication for the Survey of Consumer Finances, which includes both debts and net assets.

*Conclusion 3-1: The initiatives by the Bureau of Economic Analysis, the Bureau of Labor Statistics, the Census Bureau, the Congressional Budget Office, and the Division of Research and Statistics of the Federal Reserve Board to develop new and improved estimates of the distribution of household income, consumption, expenditures, and wealth, are laudable. An example is the Census Bureau’s National Experimental Well-being Statistics initiative to improve its household income estimates. These initiatives deserve support to become established series as soon as practicable.

Conclusion 3-2: Established definitions of household consumption, income, and wealth often match well with definitions in the System of National Accounts (as used by Organisation for Economic Cooperation and Development). Such definitions include those by the Bureau of Economic Analysis for household personal consumption expenditures and personal income; by the Bureau of Labor Statistics for consumer unit consumption; and by the Federal Reserve Board for household wealth.

*Recommendation 3-1: In the next 3-5 years, statistical agencies should build on their current initiatives publish improved statistics of household income, consumption, expenditures, and wealth. Specifically:

• The Bureau of Economic Analysis (BEA), the Bureau of Labor Statistics (BLS), and the Census Bureau should move as quickly as possible, consistent with time and resources to assess quality, to compile distributional estimates for household personal income (PI), personal consumption expenditures, BLS comprehensive consumption, and income based on the Census Bureau’s National Experimental Wellbeing Statistics (NEWS). These statistics should be published at least annually and within a year of the time the underlying data are collected.
• BEA should make its distributional household PI estimates more useful by adding estimates for: (1) disposable (after-tax) PI that excludes nonprofit institutions serving households (NPISH); (2) disposable PI (excluding NPISH) that adds retirement distributions and excludes retirement contributions (as in the System of National Accounts definition); and (3) adjusted disposable income (similar to Organisation for Economic Co-operation and Development).
• The Census Bureau’s household income estimates should include pre- and post-tax-and-transfer series, where transfers include in-kind benefits. NEWS should follow suit. The Census Bureau should

• publish money income estimates in appendixes to its reports for use by relevant programs.
• BLS, in cooperation with other economic statistical agencies, should expand and accelerate its program to publish annual estimates of household consumption that are definitionally consistent with previous recommendations.

*Recommendation 3-2: Relevant statistical agencies (Bureau of Economic Analysis, Bureau of Labor Statistics, Census Bureau, Statistics of Income of the Internal Revenue Service, and the Federal Reserve Board) should collaboratively publish a major report every three years that compares levels and trends among the household income, consumption, expenditure, and wealth statistical series using the improved measures as specified in Recommendation 3-1. In addition, their annual reports should compare their estimates to those from other agencies and, to the extent possible, identify the factors, including differences in definitions, that contribute to differences in estimates.

Conclusion 3-3: A priority goal, requiring longer-term research and development, for relevant statistical agencies and coordinating mechanisms is to develop an integrated system of household income, consumption, and wealth data. The system needs to support improved estimates—to be the established estimates of the future—for each of these three dimensions of household economic wellbeing and joint distributions of all three dimensions for the same households. Differences in economic resources and living standards among households cannot be fully understood without considering at the same time and conjointly their income, their consumption, and their wealth.

Conclusion 3-4: Because household members typically pool some, or all, of their income and wealth and consume certain types of goods (mainly housing and food) and services collectively, it is sensible to use the household—defined as all people living in the same housing unit—as the main unit of analysis for official statistics on income, consumption, and wealth. It is also useful to compile results for families, treating cohabitors and their children as family units, and for other groups of people who pool income for basic expenses, and to assess how to make units equivalent by applying appropriate equivalence scales.

Conclusion 3-5: Statistical agencies’ estimates of household income, consumption, expenditures, and wealth would be more helpful to users if presented in both inflation-adjusted and nominal terms. Agencies can

usefully collaborate on periodic reports that compare series adjusted for inflation using the personal consumption expenditure deflator, the chained Consumer Price Index, and the Consumer Price Index Research Series or other inflation series.

*Conclusion 3-6: To summarize levels and trends in household economic wellbeing, agencies that publish improved estimates of household income, consumption, expenditures, and wealth need to display them with categories that illuminate the entire distribution. At a minimum, it would be useful to provide levels for decile groups (tenths), as well as for the top 5% and 1% and the bottom 5% of households. The relevant statistical agencies could also collaborate on publishing a comparable set of inequality measures along with distributional breakdowns by socio-demographic groups.

*Recommendation 3-3: To provide additional geographic detail for new and improved estimates of household income, consumption, and wealth, relevant statistical agencies should conduct research and development and move to implementation, as appropriate, as follows:

• The Census Bureau should conduct research to produce subnational estimates (e.g., states, counties, cities) for the recommended household income definitions (for example, using the American Community Survey in conjunction with the Current Population Survey and National Experimental Wellbeing Statistics data).
• The Bureau of Economic Analysis should expand its research producing state-level distributions for personal income and extend these estimates to metropolitan areas and counties for the recommended household income definitions.
• Other agencies should conduct research on subnational estimates for consumption and wealth (e.g., using alternative data or modeling techniques).

Conclusion 3-7: Agencies that publish improved estimates of household income, consumption, expenditures, and wealth need to display them for socio-demographic groups that are of policy interest and that provide insights into differences in levels and trends. Groups of interest include those defined by such characteristics (for the household reference person or individuals in households) as age, gender, race/ethnicity, education level, disability status, employment status, family type and size, and housing tenure (own/rent). The relevant statistical agencies could collaborate on publishing comparable categories for these and other characteristics of interest.

Conclusion 3-8: Expanding on the recent efforts by the U.S. Office of Management and Budget on Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity (Statistical Policy Directive No. 15) and the efforts of the U.S. Census Bureau to capture more information on people’s race and ethnic identities, critical analysis of these delineations of race and ethnicity, the definitions of the categories, and the data sources that could be used to measure race and ethnicity would have great value.

Conclusion 4-1: Current federal household survey datasets that include income, consumption, and wealth data suffer from multiple data quality issues, including unit and item nonresponse, coverage error, and reporting error (mostly underreporting). Use of administrative records can provide additional data to address these errors.

Recommendation 4-1: The relevant statistical agencies should ensure that the integrated household-level data on income, consumption, and wealth are representative of the national population; cover individual, family, and household units of analysis; have key components of income, consumption, and wealth that bear on economic wellbeing; and can be used to construct estimates that are consistent with published macro aggregates.

*Recommendation 4-2: Statistical agencies should develop estimates of error when producing estimates for households of income, consumption, and wealth using integrated multiple data sources. The estimates of error should account for linkage errors in addition to other errors such as those arising from sampling, lack of coverage, and misreporting. Agencies should regularly publish measures of the different kinds of error, and both agencies and data users should document the methods used to account for them.

Conclusion 4-2: It is important that statistical agencies producing estimates of income, consumption, and wealth using multiple data sources maintain high quality of the data and estimates while maintaining low burden on survey respondents and containing costs to the extent feasible.

*Recommendation 4-3: Statistical agencies that produce estimates for households about income, consumption and wealth should regularly consult with expert groups and agency advisory committees and evaluate their datasets (whether based on a single data source or multiple sources) to assess whether the datasets and estimates derived from

them meet quality criteria—namely, relevance, accuracy, timeliness and punctuality, accessibility and clarity, and comparability and coherence.

Conclusion 4-3: International experience shows that the most comprehensive integrated data infrastructures (IDIs) to date are “owned” by a national statistical agency—that is, there is a single organization with IDI oversight, coordinating powers, and responsibility. The IDI may use data from multiple agencies and sources, and such an agency needs to be well resourced. Establishment of an IDI needs legal structures that enable the collection, sharing, and use of linked data while respecting considerations of relevance, quality, privacy, and confidentiality. These legal structures are themselves conditional on social consent and trust for IDIs. Having a single personal identification number that uniquely identifies every individual in the target population underpins the most successful national register-based data infrastructures to date.

*Recommendation 5-1: The Chief Statistician and the National Secure Data Service should work together to create a coordinating entity to solve administrative, legal, and technical challenges to integrate data from multiple federal entities (e.g., Bureau of Economic Analysis, Census Bureau, Bureau of Labor Statistics, Statistics of Income) as well as private businesses that collect microdata on individual and household income, consumption, and wealth. In the near term, the coordinating entity will codify agreements and protocols that enable data acquisition, integration, exchange, and access, and support the publication of privacy-protected statistics.

*Recommendation 5-2: In the near term, the coordinating entity working with the relevant agencies should expand on current efforts and coordinate new pilot studies to blend multiple datasets that have the key components of income, consumption, and wealth; develop and refine modeling methods appropriate for estimating household income, consumption, and wealth (including an income capitalization option); perform statistical matching to combine information from multiple data sources; fill missing population groups using synthetic records; and impute missing information using relationships estimated in ancillary datasets.

Recommendation 5-3: In the near term, the coordinating entity should work with the relevant statistical agencies to ensure that they publish comparisons of linked income, consumption, and wealth (ICW) data relative to the conceptual framework and budget identity relationships between ICW, in conjunction with their release of ICW data and

estimates. Doing so will gauge the internal consistency between ICW, and wealth/wealth change at the micro level.

*Recommendation 5-4: In the initial phase, the coordinating entity, in collaboration with the relevant statistical agencies, should explore statistical matching and other methods to combine relevant publicly accessible datasets (e.g., Survey of Consumer Finances, Annual Social and Economic Supplement to the Current Population Survey, Consumer Expenditure Survey, American Community Survey, Survey of Income and Program Participation) to serve as a bridge to a comprehensive integrated dataset. The work undertaken in the initial phase should also include documenting questionnaire concepts and shortcomings across these datasets to ensure coherence and summarizing the best question wording to capture income, consumption, and wealth as described in the Conceptual Framework.

Recommendation 5-5: In the initial phase, the coordinating entity, in collaboration with the relevant statistical agencies, should assess the costs and benefits of constructing a new panel dataset based on a survey, and via consent, links to administrative data and commercial data.

*Recommendation 5-6: Relevant statistical agencies should investigate updating their data collection methods, blending other available data, and using modeling procedures to improve the timeliness of data on household income, consumption, and wealth—for example, using techniques developed for the Realtime Inequality project at the University of California, Berkeley (and the aggregate methods used in the Distributional Financial Accounts).

Recommendation 5-7: Relevant statistical agencies, working with the coordinating entity, should ensure that the integrated dataset eventually made available to researchers includes geographic identifiers to aid the construction of small-area statistics. The agencies should explore options to use alternative data to produce small-area statistics on income, consumption, and wealth, possibly by socio-demographic groups.

Conclusion 6-1: Expanding access to the data infrastructure for household income, consumption, and wealth will require building a tiered access system that relies on open data (statistical series that are regularly published) and a set of public data products such as tables, public-use files, and/or synthetic data as well as restricted access to microdata for approved projects and users who work in secure enclaves, in Trusted Execution Environments, or using secure query servers.

*Recommendation 6-1: In the initial phase of building the proposed income, consumption, and wealth data infrastructure, the coordinating entity, in collaboration with relevant statistical agencies, should jointly develop a risk-utility framework and a combination of traditional disclosure limitation strategies and privacy-enhancing technologies to support the agencies’ publication of summary statistics of household income, consumption, and wealth.

*Recommendation 6.2: The coordinating entity, in collaboration with relevant statistical agencies, should propose options for a National Secure Data Service pilot to be created through which approved researchers would be allowed to access linked microdata consistent with standard definitions of income, consumption, and wealth through the National Secure Data Service.

Conclusion 6.2: The success in using multi-source data and data integration in other countries that operate with a single centralized statistical agency can provide guidance to improve the collaboration within and integration of the current U.S. statistical system.

*Recommendation 6-3: The Office of Management and Budget’s Chief Statistician, in collaboration with the Interagency Council on Statistical Policy, should establish an income, consumption, and wealth technical steering committee that includes academic researchers, leadership from statistical agencies, and government researchers. The steering committee’s functions could include determining value propositions and risks; making recommendations about improvements to estimation methods; ensuring that the relevant statistical agencies cooperate to implement the panel’s recommended production of statistics; coordinating the release and communication of the new estimates; and working with the coordinating entity to develop an acquisition and collaboration system for sharing survey, commercial, and administrative data.

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