Survey of Current Business
November 2019
Volume 99, Number 11

Updated Summary of NIPA Methodologies

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The Bureau of Economic Analysis (BEA) recently improved its estimates of current-dollar gross domestic product (GDP), current-dollar gross domestic income (GDI), and real GDP as part of the 2019 annual update of the National Income and Product Accounts (NIPAs).1 The sources of data and the methodologies that are now used to prepare the NIPA estimates are summarized in this report.2

Current-dollar estimates of GDP and GDI

The major components and subcomponents of GDP and GDI are listed in table 1. In column 1 of the table, the name of the component is shown along with the current-dollar estimate of that component for 2018. In column 2, information about the sources of data and the methods used to prepare the estimates for the comprehensive benchmark updates and for the annual updates in nonbenchmark years are presented. Major differences between the data and methods used in the benchmark updates and those used in the annual updates are also noted. For example, for “Furnishings and durable household equipment” in personal consumption expenditures (PCE) (the second item in table 1), the table indicates that one methodology (commodity flow) is used to prepare the estimates for benchmark years, and another methodology (retail control) is used to prepare the estimates for all the other years.

In column 3, information about the current quarterly estimates is also presented. For most components, information about the advance quarterly estimates, which are prepared about a month after the end of the quarter, are provided because more attention tends to be focused on this “first look” at GDP for a quarter. Major source data that become available for the “second” or “third” quarterly estimates for some NIPA components are also noted. Only the source data and methods are listed; the number of months of available source data and information about whether the source data will be revised by the source agency are not included.3

Source data

The source data include a variety of economic measures, such as sales or receipts, wages and salaries, unit sales, housing stock, insurance premiums, expenses, interest rates, mortgage debt, and tax collections.

For most components, the estimates are derived from source data that are “value data,” that is, they encompass both the quantity data and the price data required to prepare the current-dollar estimates. For these components, the value data are adjusted to derive estimates that are consistent with NIPA definitions and coverage.

For the estimates that are not derived from value data, the sources of the quantity and price data that are used to prepare value estimates are indicated, and the major adjustments that are needed to derive estimates that are consistent with NIPA definitions and coverage are specified.

For the current-dollar estimates of GDP, a “physical quantity times price” method is used for several components. For example, the annual estimate of expenditures on new autos in a nonbenchmark year is calculated as unit sales times expenditure per auto (the average transactions price that reflects all discounts and customer rebates).

For the current-dollar estimates of GDI, two general methods are used for several components—an “employment times earnings times hours” method and variations of a “stock of assets/liabilities times an effective interest rate” method.

Some quarterly (or monthly) estimates are derived using source data as indicators to interpolate or extrapolate annual estimates. In other cases, extrapolation and interpolation may be based on trends; in those cases, the use of “judgmental trend” is indicated.

International transactions accounts. The source data for the foreign transactions that are reflected in most NIPA components—such as net exports of goods and services, net income receipts, and rest-of-the-world corporate profits—are from the international transactions accounts (ITAs) that are prepared by BEA.4 As noted in table 1, for some NIPA components, the ITA estimates are adjusted to conform to NIPA concepts and definitions. For the annual estimates of these adjustments and their definitions, see NIPA table 4.3B.5

Reconciliation tables. In preparing the annual estimates of several components of GDI, BEA adjusts the source data to conform to NIPA concepts and coverage. For each subcomponent, an annual NIPA table reconciles the value published by the source agency with the NIPA value published by BEA, and the adjustments are listed. Reconciliation tables for the following subcomponents are available on BEA's website: consumption of fixed capital in table 7.13, nonfarm proprietors' income in table 7.14, net farm income in table 7.15, corporate profits in table 7.16, net monetary interest in table 7.17, and wages and salaries in table 7.18.

Estimation methods

For some components, BEA uses one of four methods: the commodity-flow method, the retail-control method, the perpetual-inventory method, and the fiscal year analysis method.

The commodity-flow method involves estimating values based on various measures of output. For example, the estimates of PCE for “Furnishings and durable household equipment” in benchmark years are based on data on manufacturers' shipments from the Census Bureau, and BEA adjusts the data for imports and exports. In general, this method is used to derive estimates of various components of PCE, of equipment investment, and of the commodity detail for state and local government consumption expenditures and gross investment.6 An abbreviated form of this method is used to prepare estimates of equipment investment in nonbenchmark years, and an even more abbreviated form is used to prepare the current quarterly estimates of equipment investment.

The retail-control method uses retail sales data, usually compiled by the Census Bureau, to estimate expenditures.7 It is used to prepare estimates of many subcomponents of PCE for durable and nondurable goods in nonbenchmark years. This method ensures that the growth rate for these subcomponents is the same rate as that of the “retail control” group, a measure based on the total sales of most kinds of businesses selling goods from the Census Bureau's monthly and annual retail trade surveys.

The perpetual-inventory method is used to derive estimates of fixed capital stock, which are used to estimate consumption of fixed capital—the economic depreciation of private and government fixed capital. This method is based on investment flows and a geometric depreciation formula.8

The fiscal year analysis method is used to estimate annual and quarterly estimates of consumption expenditures and gross investment by the federal government. The estimates of expenditures are calculated by program, that is, by activity for a single line item or for a group of line items in the Budget of the U.S. Government. For most programs, BEA adjusts budget outlays so they conform to NIPA concepts and definitions and classifies the expenditures in the appropriate NIPA category, such as current transfer payments or interest payments, with nondefense consumption expenditures and gross investment determined residually. When a fiscal year analysis is completed, the detailed array of NIPA expenditures by program and by type of expenditure provides a set of control totals for the quarterly estimates.9

Estimates of real GDP

BEA uses three methods to estimate real GDP: the deflation method, the quantity extrapolation method, and the direct valuation method. These methods and the source data that are used for estimation are listed in table 2.

The deflation method is used for most components of GDP. A quantity index is derived by dividing the current-dollar index by an appropriate price index that has the base year—currently 2012—equal to 100. The result is then multiplied by 100.

The quantity extrapolation method uses quantity indexes that are obtained by using a quantity indicator to extrapolate from the base-year value of 100.

The direct valuation method uses quantity indexes that are obtained by multiplying the base-year price by actual quantity data for the index period. The result is then expressed as an index with the base year equal to 100.

The subcomponents in table 2 are the same as those shown in table 1, but the detail differs to highlight the alternative methodologies that are used to calculate the real estimates.10

 


  1. The concepts and methodologies that underlie the NIPAs are subject to periodic improvements as part of the comprehensive and annual NIPA updates, and information about these improvements is available on BEA's website. See also “Improved Estimates of the National Income and Product Accounts: Results of the 2019 Annual Update,” Survey of Current Business 99 (August 2019).
  2. For detailed descriptions of the fundamental concepts, definitions, classifications, and accounting framework that underlie the NIPAs and of the general sources and methods that are used to prepare the estimates, see NIPA Handbook: Concepts and Methods of the U.S. National Income and Product Accounts on BEA's website.
  3. For specific information on key monthly source data incorporated in the current quarterly estimates, see “GDP and the Economy” in the Survey.
  4. See U.S. International Economic Accounts: Concepts and Methods on BEA's website. Improvements in methodology are usually introduced as part of annual ITA revisions; see Eric Bryda, C. Omar Kebbeh, and Ted Peck, “Annual Update of the U.S. International Transactions Accounts,” Survey 99 (July 2019).
  5. Quarterly estimates are presented in the NIPA underlying detail table 4.3BU.
  6. For additional information on the commodity-flow method, see “Chapter 4: Estimating Methods” in NIPA Handbook: Concepts and Methods of the U.S. National Income and Product Accounts, pages 4–9.
  7. For additional information, see “Estimating Methods,” pages 4–9, and “What is the retail-control method?
  8. For additional information, see “Estimating Methods,” pages 4–12.
  9. For details, see “Chapter 9: Government Consumption Expenditures and Gross Investment.”
  10. For the real estimates, the distinction between annual and quarterly methodologies is less important than it is for the current-dollar estimates. For the relatively few cases in which the annual and quarterly source data differ, the major differences are noted.