13th OECD-NBS Workshop on National Accounts Measuring U.S. GDP within the Input-Output Framework Comments on “Interrelationship Between China’s Input-Output Estimation: Production-based GDP and Expenditure-based GDP” Brian C. Moyer 13th OECD-NBS Workshop on National Accounts Haikou, China November 30 – December 4, 2009

U.S. Industry Accounts Benchmark I-O Accounts Annual I-O Accounts Prepared every five years 400 industries/commodities Annual I-O Accounts 12 months after close of year 65 industries/commodities GDP by Industry Statistics 4 months after close of year 22 industry groups

Three ways to measure GDP Expenditure Approach GDP = C + I + G + (X-M) Income Approach GDP = Compensation + Gross operating surplus + Taxes on production Production Approach GDP = Gross output - Intermediate inputs

Data from various sources … Census Bureau annual survey data Monthly/quarterly Census survey data Data from the tax authority Labor Dept. employment and wage data Administrative data Trade association data Data from other government agencies

Balanced I-O framework: Use table -second table in the input-output accounts shows which inputs an industry “uses” in its production process -arranged just a little differently, with the industries across the top and the products down the left side, correspond to the industry and product output values in the make table -So, the make table shows what industries are making, and one purpose of the use table is to show what happens to that output. Here in the center we have the intermediate use section of the use table. This section shows that much of the output that industries produce is consumed by other industries. And by looking at an actual use table we could see how much of each product the different industries were buying from each other. This section to the right, the final use section, captures the portion of output consumed by final users. This includes purchases by consumers (you and me), investment purchases by businesses. Some output is not purchased at all in a given year, but is stored as inventory until a later period. That is captured here. Some output is shipped over seas, and we also see here the portion of output purchased by the government. Now I’ll just point out here that the sum of the cells in the final use section equals total GDP for the economy. This section should look pretty familiar to most of us. These columns capture the basic economic accounting identity that many of us learned in our undergraduate macroeconomics course—Y (or GDP) = C + I + G + NX. This is the expenditure-based approach that is used in preparing the NIPA measure of GDP. Now, moving back to the other side of the table. Recall that the blue section shows how industries depend on each other to produce their output. This section shows the intermediate inputs to an industry’s production process. These intermediate inputs are also sometimes referred to as secondary inputs, implying that there must be some primary inputs as well. The primary inputs to the production process are labor and capital. And this section down at the bottom, the value added section, shows the amount of labor and capital that each industry requires to make its products. I’d like to note here that the cells in the value added section also sum up to GDP. Recall that there are three ways to calculate GDP, one is to some up expenditures as in the final use section, one is to some up incomes as in the value added section, and the last is the production approach—or to take total output less total intermediate inputs. All three of these measures are visible in the use table, and so the use table provides an important framework for understanding differences between the different approaches to measuring GDP.

Results show small differences [Percent changes and percentage-point contributions]   2004 2005 2006 2007 Gross domestic product 3.6 2.9 2.8 2.0 Construction 0.0 -0.2 -0.6 Manufacturing 0.7 0.1 0.3 Other goods-producing industries Trade 0.8 0.4 Transportation Finance 0.6 0.9 Health care 0.2 Other services-producing industries 1.3 1.0 Government Addenda: Not allocated by industry 0.16 -0.24 -0.01 0.06

Building the annual accounts Output by industry and commodity Intermediate purchases and final uses Value added by industry Balancing Quantity and price measures

Industry and commodity output Industry output: most recent benchmark I-O estimates extrapolated with appropriate indicators; consistent with expenditure-based GDP indicators Commodity output: composition of industry output retained from benchmark I-O, except in manufacturing

Intermediate and final uses Initial input estimates prepared in two broad steps Base-year inputs extrapolated with quantity change in output by industry Inputs “reflated” with appropriate input prices Initial final use estimates prepared using commodity-flow method; controlled to expenditure-based GDP categories

Value added by industry Initial estimates based on gross domestic income by industry Compensation and Taxes on production obtained from income-based GDP measures Gross operating surplus extrapolated from “combined” benchmark-year values; company-to-establishment adjustments applied

Balancing Based on RAS procedure—scaling of transactions Outputi = Inputsi + Value addedi Total commodity output = Total industry output Total final uses = total value added = GDP Primarily adjustments to inputs; controls for value added by industry (Gross operating surplus) relaxed, as necessary

Quantity and price measures Outputs and inputs deflated separately Primarily BLS Producer Price Indexes Consistency with expenditure-based GDP Value added quantity and price measures computed using Fisher-Ideal, double-deflation procedure “Not allocated by industry” reflects differences with expenditure-based GDP

Further improvements to consistency “Feedback” between production and expenditure approaches Time-series consistency of benchmark I-O accounts Quarterly GDP by industry

Improving consistency

Feedback Focused on consumer spending Annual I-O accounts: commodity flow method Expenditure-based GDP: Retail control method based on retail sales data Requires evaluating data quality and timing of alternative methods

Example: PCE for shoes