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Session 6 a discussion of aten paper in session 6 a
- 1. Regional Price Parities & Real Regional Income for the US: 2008-2012 Bettina Aten and Eric Figueroa, authors Marshall Reinsdorf, discussant IARIW 33rd General Conference, Rotterdam Session 6A August 28 The views expressed herein are those of the author and should not necessarily be attributed to the IMF, its Executive Board, or its management 8/29/2014 1 IMF Statistics Department The views expressed are those of the authors and should not be attributed to the IMF, its Executive Board or its management, nor to the US Department of Commerce
- 2. IMF Statistics Department 8/29/2014 Background 2 The Bureau of Economic Analysis (BEA) has a project to estimate relative real income of states and metropolitan areas in the US Estimates have been published for about 3 years The deflators are based on Regional Price Parities (RPPs) that measure differences in price levels across regions, Adjustment of RPPs from different years for national level inflation is based on the national personal consumption expenditure (PCE) price index
- 3. IMF Statistics Department 8/29/2014 Price Data for Constructing RPPs Data on prices (except rent) come from the CPI program > 1 million price quotes/year from 38 areas classified into 200+ item strata and ca. 8000 ELI-area cells CPI tries to hold the sample composition constant over time but not over space Data on rents come from the ACS (American Community Survey), which has a huge sample and global coverage To deal with heterogeneity in the cross section, hedonic regression techniques are used 3
- 4. IMF Statistics Department 8/29/2014 Forming Price Aggregates 4 Hedonic regressions give ELI relative price levels Weighted country-product dummy method used to aggregate ELIs into item strata indexes Both steps undergo outlier detection and filtering using Quaranta tables similar to those used for the ICP and by OECD Item strata indexes are aggregated into 16 expenditure classes using the Geary technique Expenditure classes aggregated to all-items level again using the Geary technique Counties aggregated into states and metro areas also using Geary
- 5. IMF Statistics Department 8/29/2014 Geary inter-area price index 5 퐶 = 푃퐺푒푎푟푦 푁 푝푞 푛퐶 푛=1 푁 휋푛푞푛 푛=1 퐶 휋푛 = 푀 푝푞 푛퐶 퐶=1 퐶 푑=1 푃퐺푒푎푟푦 푑 푀 푞푛 pn is the relative price of the item stratum πn is the national average price of the item stratum qn is the notional quantity equal to (pq)/p c and d are regions, which take a value of 1 through M n is the item stratum
- 6. IMF Statistics Department 8/29/2014 Indexes for counties as building blocks All counties that are included in a CPI area are assumed to share the same price level for an item Expenditure weights for the CPI are allocated to counties based on household income from the ACS Rent weight used in the CPI is replaced with rent weight calculated from rents in the ACS Owner-occupied rents imputed for weighting purposes National shares of expenditure classes are forced to equal those of Personal Consumption Expenditures (PCE) in GDP 6
- 7. IMF Statistics Department 8/29/2014 CPI vs. National Accounts Weights 7
- 8. IMF Statistics Department 8/29/2014 Adjustment to base year price level Price level differences measured by the RPPs are specific to one point in time RPPs from different years rescaled to reflect change in national price level since the base year of 2008 The implicit regional inflation is: (Pi,t / Pi, t-1) = (RPPi,t / RPPi,t-1) * (PUS,t / PUS, t-1) where the US price change is measured by the national PCE price index. 8
- 9. IMF Statistics Department 8/29/2014 Comparing 2012 to 2011 Regional price growth ranged from 0.7% in Nevada to 3.2% in North Dakota and 3.6% in South Dakota Real personal income growth ranged from -1.2% in South Dakota to 15.1% in North Dakota Excluding the Dakotas, Maine had the lowest real income growth (0.3%) and Indiana and Montana the highest (3.7%) 9
- 10. IMF Statistics Department 8/29/2014 State Total Real Personal Income and Implicit Price Growth, 2012 10 Was SD imputed with ND prices?
- 11. IMF Statistics Department 8/29/2014 RPPs for co-vary with rents 11 RPPs* Tercile All Items Goods Rents Other Services 1 – Top 107.4 102.3 122.9 105.1 2 – Middle 95.9 98.2 89.5 96.8 3 – Bottom 89.3 95.2 71.6 92.3 United States 100.0 99.4 101.2 100.0
- 12. IMF Statistics Department 8/29/2014 Income and Prices in the cross section 12 Units of slope of 4.4?
- 13. IMF Statistics Department 8/29/2014 13
- 14. IMF Statistics Department 8/29/2014 Per-capita incomes, real & nominal 14 RPP Per Capita Personal Income Dollars 2011 2012 Percent growth Real Per Capita Personal Income Chained (2008) Dollars 2011 2012 Percent growth 2012 Highest Per Capita Personal Income Midland, TX 77,495 83,049 7.2 76,841 80,504 4.8 97.9 Bridgeport-Stamford-Norwalk, CT 79,099 81,068 2.5 62,559 63,336 1.2 121.5 San Francisco-Oakland- Hayward, CA 62,954 66,591 5.8 51,279 52,105 1.6 121.3 San Jose-Sunnyvale-Santa Clara, CA 61,831 65,679 6.2 50,322 51,095 1.5 122.0 Washington-Arlington- Alexandria, DC-VA-MD-WV 60,834 61,743 1.5 49,804 48,645 -2.3 120.4 Lowest Per Capita Personal Income Lake Havasu City-Kingman, AZ 26,524 27,220 2.6 27,170 27,546 1.4 93.8 Yuma, AZ 27,385 26,995 -1.4 27,712 27,447 -1.0 93.3 Laredo, TX 25,612 26,120 2.0 26,949 27,871 3.4 88.9 Brownsville-Harlingen, TX 23,405 23,909 2.2 25,814 26,661 3.3 85.1 McAllen-Edinburg-Mission, TX 22,127 22,400 1.2 24,399 25,008 2.5 85.0 United States nonmetropolitan portion 34,018 35,324 3.8 36,911 38,125 3.3 87.9 United States 42,298 43,735 3.4 40,663 41,282 1.5 100.0
- 15. IMF Statistics Department 8/29/2014 Future research Augmenting CPI price observations by web-scraping and using third-party sources of information RPPs that reflect investment and government Improve reconciliation of the Personal Consumption Expenditure weights in the national accounts with the weights in the Consumer Expenditure (CE) survey Better home value estimates for imputing owner-occupied rents Models for improving prices and weights of rural areas 15
- 16. IMF Statistics Department 8/29/2014 Comments Very ambitious project with really interesting results Mention & discuss 5-year averaging of RPPs Assumption of within-area homogeneity is unrealistic Which states/metro areas are completely or largely based on imputed prices? 16