U. S. Bureau of Labor Statistics Do Poor Pay More, Store by Store? Greg Kurtzon Robert McClelland Preliminary and Incomplete We thank Aylin Kumcu for her assistance with this research. All errors are our own. All views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the U.S. Bureau of Labor Statistics. Do people with different incomes face different prices? The poor pay more because they are less mobile shop at small, independent stores (not chains, not club stores) shop in areas with higher insurance and security costs The poor pay less because they have a lower opportunity cost of time buy lower quality products
shop in areas with lower wages shop in outlets with fewer amenities 2 Real income distributions Some analyses conclude that the distribution of income has been widening The real income distribution may not be as wide, or may be wider, than the nominal distribution suggests 3 Previous literature Caplovitz (1963) The Poor Pay More BLS (1965) independent stores, patronized by low income families, charge more Summary in Sexton (1971) no difference, or poor pay more Summary in in Kaufman, et. Al., (1997) no difference, or poor pay more Hayes (2000)
Aguiar and Hurst (2005) 4 Previous literature Hayes (2000) uses BLS 1998 micro-data for six homogeneous goods, and finds that prices for a set of homogeneous items sold in poor areas are up to 6% lower. Poor is defined by characteristics at the zip code and county level Aguiar and Hurst (2005) use AC Nielsen Homescan data for Denver 1993-5. 85% of purchases come from four chains. They conclude that poor pay about 5% less 5 Data We use the telephone point of purchase survey (TPOPS) to determine how much households with different incomes spend at specific outlets That information, combined with price data is used to construct average prices levels for different incomes We dont have data on the purchasing patterns of different households within an outlet 6
TPOPS Quarterly survey of around 15,000 consumer units, contacted randomly by phone Respondents are asked for recent (recall period varies by good) dollar expenditures on one of 16 POPS groups for each outlet shopped at One POPS group asked for each PSU each quarter Full rotation every 4 years One consumer unit intended to stay in for 4 quarters 7 TPOPS In 2001 only, respondents were asked to place their consumer unit in one of three income groups: 1 Lower less than $8,000 for CUSIZE < 2; less than $18,000 for CUSIZE = 2; less than $18,000 for CUSIZE = 3; less than $24,000 for CUSIZE > 3 2 Middle $8,000-$30,000 for CUSIZE < 2; $18,000-$57,000 for CUSIZE = 2; $18,000-$64,000 for CUSIZE = 3; $24,000-$66,000 for CUSIZE > 3 3 Upper greater than $30,000 for CUSIZE < 2; greater than $57,000 for CUSIZE = 2; greater than $64,000 for CUSIZE = 3; greater than $66,000 for CUSIZE > 3
About 15% group 1, 50% group 2, 35% group 3 8 TPOPS Only first time interviewees were asked the question, with around an 80% response rate Therefore, an income group can be assigned to at least some respondents in quarters 2001 Q1 2002 Q3 The quarter with the most respondents with an assigned income group is 2001 Q4, about 55% The attrition rate is around 17% per quarter, could be a bit high Replacements are not asked income question Outlet income group weights For each outlet in the 2001 Q1 2002 Q3 TPOPS sample, total expenditures for each income group were calculated Many outlets have only one or two consumer units shopping there 9 Weights The probability of selecting a store should be proportional to expenditures in that store (PPS) The probability of selecting an item should be
proportional to the expenditures on that item Expenditures in outlet o by income group I eo, I eo E 1it prt i I eo eo, I o o I 1 0 Weights We create an adjustment factor AoI to reflect expenditures by specific income groups E (i 1it Ao, I pit ) i E (1it )AoI pit eo , I eo i eo o eo , I
o I eo , I o I eo , I pit i eo , I o eo , I pit 1 1 Commodities Prices from Aug 2002 April 2007 Missing prices and weights are deleted Each observation is a price quote for each income group that used that outlet More than one income group can shop at a given outlet 27 food items, plus gasoline 1 2
Estimation strategy We can directly compare average prices paid by low income CUs to middle and high income CUs Equivalently, we can regress log(price) on dummy variables for middle income and high income CUs To account for inflation and interarea variation, we add dummy variables for time period and area 1 3 Two methods to account for quality variation 1. 2. Identify very specific, homogeneous items, then estimate log pit H DH M DM t t Dt a a Da it Create dummy variables for price determining characteristics, then estimate log pit H DH M DM t t Dt a a Da s s Ds it 1 4
Apple Checklist BUREAU OF LABOR STATISTICS U.S. DEPARTMENT OF LABOR CONSUMER PRICE INDEX - ELI CHECKLIST collection outlet quote arranging period: __ __ __ __ number: __ __ __ __ __ __ __ code: __ __ __ code: __ __ __ __ _________________________________________________________________________________________ ELI No./ cluster title FK011 APPLES code 01A item availability: 1-AVAILABLE 2-ELI NOT SOLD 3-INIT INCOMPLETE purpose of checklist: 1-INIT 2-INIT COMPL 3-SPEC CORR
4-SUB 5-REINIT 6-CHECK REV _________________________________________________________________________________________ CURRENT PERIOD | SALES TAX | price: _ _ _ _ _ _ . _ _ _ | included: YES NO | type of price: REG SALE | | quantity: __ __ __ | | size: _ _ _ _ . _ _ _ pair: YES NO | | unit of size: ______________
| | | | | YEAR-ROUND | in-season: JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ____________|____________________________________________________________________________ respondent: location: _________________________________________________________________________________________ field message: _________________________________________________________________________________________ VARIETY A1 Baldwin A2 Ben Davis A3 Delicious ** B1 Red Delicious ** B2 Golden Delicious A4 Fuji A5 Gala A6 Granny Smith A7 Gravenstein A8 Grimes Golden A9 Jonathan A10 McIntosh A11 Rome Beauty (Red Rome)
A12 Stayman A13 Winesap A14 York (York Imperial) A15 Not known A99 Other, ______________________________ ORGANIC CERTIFICATION C1 Not USDA certified organic C2 USDA certified organic C3 Other organic claim ** WEIGHT (See metric sizes, FK011 page 2 of 2) G1 0-10 pounds (0-4.5 Kg) G2 Above 10 pounds (Above 4.5 Kg) ** PACKAGING H1 Loose H2 Multi-pack H3 Single item, individually packaged ** SIZE REPRESENTS I1 Weight labeled I2 Weighed one multi-pack (QUANTITY = # of packages priced) I3 Weighed 2 apples, entered YES for PAIR (QUANTITY = # of apples priced)
** OTHER ITEM IDENTIFIERS J99 ______________________________ K99 ______________________________ OTHER FEATURES D99 _____________________________ E99 _____________________________ ** GRADE F1 U.S. Extra Fancy F2 Other grade/grade not available ZZ99 ________________________________________________________________________________________ BLS 3400B (Rev. February 1995) FK011 page 1 of 2 Revised January 2002 1 5 Examples of homogeneous items
National brand white bread, regular, not buttertop/salt free/dietetic/etc, not frozen, pre-pkged, 24oz National brand, chicken half breasts, skinless, fresh, no seasoning National brand iceberg lettuce, single item package National brand bacon, reg slice, not low salt, not smoked, not maple flavored or brown sugar cured National brand bleached white all-purpose flour 5 lb 1 6 Table 5: Total Number of Significant Coefficients and their Sign, by Regression Medium High + - + -
Homogeneous items 4 7 9 5 Characteristic Vars 10 7 8 6 Outlets/regression All outlets Positive coefficients indicate that CUs in the income group pays more than low income CUs
1 7 Table 5: Total Number of Significant Coefficients and their Sign, by Regression Medium Outlets/regression High + - + - Homogeneous items 4 7
9 5 Characteristic Vars 10 7 8 6 Homogeneous items 5 5 9 2 Characteristic Vars
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