Consumer price index and Inflation. Introduction Consumer price index (CPI) Inflation rate Content.
Big Data in the U.S. Consumer Price Index Presentation...Big Data in the U.S. Consumer Price Index:...
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1 — U.S. BUREAU OF LABOR STATISTICS • bls.gov Big Data in the U.S. Consumer Price Index: Experiences & Plans Crystal Konny, Brendan Williams, and David Friedman Federal Economic Statistical Advisory Committee Meeting - June 14, 2019
Transcript of Big Data in the U.S. Consumer Price Index Presentation...Big Data in the U.S. Consumer Price Index:...
1 — U.S. BUREAU OF LABOR STATISTICS • bls.gov
Big Data in the U.S. Consumer Price Index:
Experiences & Plans
Crystal Konny, Brendan Williams, and David Friedman
Federal Economic Statistical Advisory Committee Meeting - June 14, 2019
2 — U.S. BUREAU OF LABOR STATISTICS • bls.gov2 — U.S. BUREAU OF LABOR STATISTICS • bls.gov
Potential Benefits
Transaction prices
Larger sample sizes
Reduced collection costs
Reduced or eliminated respondent burden
Data descriptiveness
Real-time expenditures and weights
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Challenges Methodological
Product life cycle, representativeness, data descriptiveness
Operational
Data lag, continuity, quality verification
Geographic structure
System design
Legal, Policy, and Budgetary
Contracting for data, webscraping agreements, confidentiality concerns
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Alternative Data Data not collected through traditional field
collection procedures by BLS staff
(traditional = in-store/on-phone/manually on website)
Three main categories:
Corporate
Secondary Source
Web/Mobile app scraping data
Decade of explorations & pilot projects –transition into production
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General steps for Alt Data Projects
Determine what to pursue
Evaluate options
Evaluate selected source (definition, coverage, other quality dimensions)
Evaluate data quality over predefined time
Methods to test
Evaluate results
Transition to production?
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Criteria for use in production (to date)
As good or better than current pricing methodology
Does improvement in index justify any additional costs – cost effective?
In general, is it a good fit for CPI?
Use of short-term solution while continuing to research longer-term improvements
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Corporate Data
CorpX
0
20
40
60
80
100
Oct
-14
Jan-1
5
Apr-
15
Jul-15
Oct
-15
Jan-1
6
Apr-
16
Jul-16
Cosmetics Misc. Goods Jewelry
Dishes Misc. Household Men’s suits or blazers
Women's tops, skirts, and suits Women’s outerwear
Impact of Incorporating CorpX
96
98
100
102
104
106
108
Jul-16
Oct
-16
Jan-1
7
Apr-
17
Jul-17
Oct
-17
Jan-1
8
Apr-
18
Jul-18
Oct
-18
Apparel CPI Apparel CPI + Transaction Data
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CorpY
February 2012 refused to initiate new prescription drug sample
March 2015 agreement to supply data corporately
May 2015 first use in index
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CorpYCorpY In-store
Item Selection
Probability Proportional to Size (PPS) over the past year nationally by sales excluding lowest 10% of transactions
PPS based on price of the last 20 prescriptions sold
Geography National Outlet Specific
Price Average price of at least 100 transactions
Single price
Insurance prices Mostly cash prices
National price Outlet specific price
Per pill price Per prescription price
Patent Loss Unit prices averaged across brand and generic
Based on analyst monitoring of patents for an NDC
Data Frequency
Bimonthly odd collection Monthly and bimonthly odd/even collection
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Secondary Source Data
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Hospitals and Physicians’ Services
Relative Importance 4.04%; response rate for Medical Care is 48.1%
4,116 price quotes
Cash price overrepresented
High respondent burden
High collection costs
Difficult collection methodology
Researching use of medical claims datasets
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New Vehicle Observations
0
100,000
200,000
300,000
400,000
500,000
CPI JDPower
Num
ber
of
Obse
rvations/
Month
Model Year Price Indexes
80
85
90
95
100
105
Jan-0
8
Jan-0
9
Jan-1
0
Jan-1
1
Jan-1
2
Jan-1
3
Jan-1
4
Jan-1
5
2009 2010 2011 2012 2013 2014 2015
Experimental Index for New Vehicles
Untaxed)
90
95
100
105
110
115
200712 200812 200912 201012 201112 201212 201312 201412 201512 201612 201712 201812
Exp New Vehicles (Untaxed) Official New Vehicles (Taxed)
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Web/Mobile app scraping data
Crowd Sourced Motor FuelsRegular Unleaded Gasoline
90
95
100
105
110
115
120
Nov-1
7
Dec-
17
Jan-1
8
Feb-1
8
Mar-
18
Apr-
18
May-1
8
Jun-1
8
Jul-18
Aug-1
8
Sep-1
8
Oct
-18
CPI GasBuddy Data
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Plans
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Establishing Priorities Relative importance of the item
Number of quotes replaced
Cost of collection relative to cost of alternative data
Respondent relationship with BLS
Concentration of respondents in the sample
Ease of implementation
Accuracy issues in the current index…
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In the works
Item RI#
quotes concentration issues
priority
Source of data
% sample
Gasoline (all types)4.344 3,778 M L H scrape 100
Other motor fuels0.094 830 M L H scrape 90
New vehicles3.695 1,900 L H H sec 100
Physicians' services1.728 1,993 L H H sec 75
Hospital services2.312 2,123 L H H sec 85
Cable and satellite television service 1.501 1,906 H H H sec 95
Wireless telephone services1.693 1,279 H H H sec 98
Land-line telephone services0.572 874 H H H sec 95
Internet services & electronic info providers 0.780 773 H H H sec 95
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In pursuitRI
# quotes
concentration issues priority
Source of data Experience
% sample
Prescription drugs1.316 4,641 H H H corp some
Limited service meals and snacks 2.542 2,808 M L M corp pursue
Delivery services0.014 231 H L corp pursue
Airline fares0.683 1,745 H L M
scrape, corp research
Used cars and trucks2.329 4,537 H H H sec Prod, seek 100
Postage0.094 230 H L sec prod
Leased cars and trucks 0.655 265 L H M sec research 100
Electricity2.655 1,406 M M H seek
Utility (piped) gas service 0.747 1,404 M M H seek
Rent and OER 31.548 seek
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Conclusions
Significant portion of the CPI based on alternative data within 5 years
Substantial R&D on methodology needed
Alternative data introduced incrementally alongside monthly publication
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Questions for FESAC
Do you have any reactions to the general criteria CPI has used to date for determining fitness for use? Are we missing anything, etc.?
Do our criteria for establishing priorities in moving forward make sense to you?
Any advice for meeting the methodological challenges BLS faces with some of the alternative data sources?
Contact Information
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Brendan Williams
Senior Economist
Branch of Consumer Prices
Crystal Konny
Branch Chief
Branch of Consumer Prices
David Friedman
Associate Commissioner
Prices and Living Conditions
