Real Personal Consumption Expenditures and Personal Income by State, 2020
Today, the U.S Bureau of Economic Analysis (BEA) released official statistics of real state personal consumption expenditures (PCE) for the first time. The new statistics cover the period from 2008 to 2020. Real PCE decreased 3.8 percent in 2020 for the nation after increasing 2.2 percent in 2019. Across states, the percent change ranged from 2.2 percent in Utah to –7.0 percent in Hawaii, Maryland, and New York; the percent change was –8.9 percent in the District of Columbia (table 1).
In 2020, real PCE decreased in 47 states and the District of Columbia and increased in only three states: Utah (2.2 percent), Idaho (2.0 percent), and Montana (1.0 percent). Real state PCE is a state's current-dollar PCE adjusted by the state's regional price parity and the national PCE price index.
- In Utah, Idaho, and Montana current-dollar PCE increased while their implicit regional price deflators decreased 1.0 percent, 0.7 percent, and 0.6 percent respectively (table2).
- New York, Maryland, and Hawaii had the largest decrease in real PCE. In all three states, current-dollar PCE decreased while their implicit regional price deflators increased 1.9 percent, 2.8 percent, and 1.8 percent respectively.
Coronavirus (COVID-19) Impact on 2020 Real PCE and Personal Income by State Estimates
The 2020 estimates of real PCE and personal income by state were impacted by the response to the spread of COVID-19, as governments issued and lifted "stay-at-home" orders and government pandemic assistance payments were distributed to households and businesses. The full economic effects of the COVID-19 pandemic cannot be quantified in the real PCE and personal income by state estimates because the impacts are generally embedded in source data and cannot be separately identified. For more information, see Federal Recovery Programs and BEA Statistics.
Real Personal Income
Real state personal income increased 5.3 percent in 2020 for the nation after increasing 2.6 percent in 2019. Across states, the percent change in real personal income ranged from 9.8 percent in Idaho to 1.6 percent in Alaska (table 1).
In 2020, real personal income increased in all 50 states and the District of Columbia.
- Idaho (9.8 percent) and Utah (9.0 percent) had the largest increases in real personal income. In both states, the implicit regional price deflator decreased.
- Alaska (1.6 percent) and Oklahoma had the smallest increases in real personal income. Their implicit regional price deflators increased 1.0 percent and 2.2 percent respectively.
Regional Price Parities
Regional price parities (RPPs) measure the differences in price levels across states for a given year and are expressed as a percentage of the overall national price level.
The all items RPP covers all consumption goods and services including housing rents. Areas with high/low RPPs typically correspond to areas with high/low price levels for rents.
- States with the highest RPPs were Hawaii (112.0), New Jersey (111.2), and California (110.4); the RPP in the District of Columbia was 111.5 (table 2).
- States with the lowest RPPs were Mississippi (87.8), West Virginia (88.0), and Arkansas (89.2).
- Across states, California had the highest RPP for housing rents (160.2) and Mississippi had the lowest (56.1); the RPP for housing rents in the District of Columbia was 168.9.
Updates to Real Personal Income by State and Metropolitan Area
The estimates for 2020 incorporate the results of BEA's annual update of real personal income for states and metropolitan areas that was also released today. The annual estimates of state and metropolitan area real personal income for 2008 to 2019 were revised. The update incorporates revised source data that are more complete and more detailed than previously available. The update includes the results of the July 2021 annual update of the National Income and Product Accounts, the September 2021 annual update of the state personal income statistics, and the November 2021 annual update of local area personal income statistics. The update also includes changes to RPP estimation methods. For a summary, see Regional Price Parity Methodology Revisions. A complete description of the source data and the methodology will be published in an upcoming Survey of Current Business article.
BEA state real per capita PCE statistics and real per capita personal income statistics for states and metropolitan areas are calculated using U.S. Census Bureau midyear population estimates. These annual midyear estimates are based on the 2010 census. BEA will incorporate the Census Bureau midyear population estimates based on the 2020 census results when they become available.
Real Personal Consumption Expenditures by State and Real Personal Income by State and Metropolitan Area, 2021
Technical Notes on Regional Price Parities and Implicit Regional Price Deflators
Price indexes commonly measure price changes over time. The BEA PCE price index and the Bureau of Labor Statistics Consumer Price Index (CPI) are two examples. Spatial price indexes measure price level differences across regions for one period. An example of these types of indexes are purchasing power parities, which measure differences in price levels across countries for a given period and can be used to convert estimates of per capita gross domestic product into comparable levels in a common currency. The RPP BEA has developed compares regions within the United States, without the need for currency conversion. An implicit regional price deflator (IRPD) can be derived by combining the RPPs and the U.S. PCE price index.
Regional price parities. The RPPs are calculated using price quotes for a wide array of items from the CPI covering apparel, education, food, housing, medical, recreation, transportation, and other goods and services.1 Data on housing rents are obtained separately from the Census Bureau American Community Survey (ACS). The expenditure weights for each category are constructed using BEA PCE and Census ACS housing rents expenditures.2
The CPI price levels and the ACS housing rents are combined with the expenditure weights using a multilateral aggregation method that expresses a region's price level relative to that of the United States.3
For example, if the RPP for area A is 120 and for area B is 90, then on average, price levels are 20 percent higher and 10 percent lower than the U.S. average for A and B, respectively. If the personal income for area A is $12,000 and for area B is $9,000, then RPP-adjusted incomes are $10,000 (or $12,000/1.20) and $10,000 (or $9,000/0.90), respectively. In other words, the purchasing power of the two incomes is equivalent when adjusted by their respective RPPs.
For a summary of changes to RPP estimation methods, see Regional Price Parity Methodology Revisions.
Implicit regional price deflator. The IRPD is a regional price index derived as the product of two terms—the regional price parity and the U.S. PCE price index.
The IRPD will equal current-dollar PCE divided by real PCE in constant dollars. The growth rate or year-to-year change in the IRPDs is a measure of regional inflation.4
1 The BEA RPP statistics are based in part on restricted access CPI data from the Bureau of Labor Statistics (BLS). The BEA statistics presented herein are products of BEA and not BLS.
2 To estimate RPPs, annual average CPI price quotes and ACS housing rents are quality adjusted. The rents data are from the ACS Public Use Microdata Sample, and results incorporate BEA's new method for estimating housing services across the regional and national accounts (for more information, see the May 2021 issue of the Survey of Current Business).
3 The multilateral system that is used is the Geary additive method. Any region or combination of regions may be used as the base or reference region without loss of consistency.
4 The growth rate of the IRPDs will not necessarily equal the region or metropolitan area price deflators published by BLS. This is because the CPI deflators are calculated directly, while the IRPDs are indirect estimates based on CPI and ACS price levels and PCE expenditure weights.