Notice2023-19486
Comment Request
Primary source
Metadata and text below are from the Federal Register, a public-domain U.S. government work. Always verify the official published version before relying on it for any legal matter.
Published
September 11, 2023
Issuing agencies
Labor DepartmentLabor Statistics Bureau
Abstract
The Department of Labor, through the Bureau of Labor Statistics (BLS) and, specifically, the International Price Program (IPP), is soliciting comments on its plan to improve the Import and Export Price Indexes (MXPI) estimates by using administrative trade data acquired from the U.S. Census Bureau. IPP is responsible for the estimation and publication of the U.S. Principal Federal Economic Indicator of Import and Export Price Indexes (MXPI). The IPP collects data from companies on import and export prices and estimates price indexes for nearly all goods trade and some service trade for the United States. The data are primarily collected with a business survey. After completion of extensive research, and in response to a decline in data collected through traditional survey methods, BLS plans to implement improvements to the quality and quantity of import and export price indexes in fiscal year 2025 by replacing data directly collected from the business survey with administrative trade records for select homogeneous product areas.
Full Text
<html>
<head>
<title>Federal Register, Volume 88 Issue 174 (Monday, September 11, 2023)</title>
</head>
<body><pre>
[Federal Register Volume 88, Number 174 (Monday, September 11, 2023)]
[Notices]
[Pages 62402-62406]
From the Federal Register Online via the Government Publishing Office [<a href="http://www.gpo.gov">www.gpo.gov</a>]
[FR Doc No: 2023-19486]
-----------------------------------------------------------------------
DEPARTMENT OF LABOR
Bureau of Labor Statistics
Comment Request
AGENCY: Bureau of Labor Statistics, Department of Labor.
ACTION: Request for comments on proposed action.
-----------------------------------------------------------------------
SUMMARY: The Department of Labor, through the Bureau of Labor
Statistics (BLS) and, specifically, the International Price Program
(IPP), is soliciting comments on its plan to improve the Import and
Export Price Indexes (MXPI) estimates by using administrative trade
data acquired from the U.S. Census Bureau. IPP is responsible for the
estimation and publication of the U.S. Principal Federal Economic
Indicator of Import and Export Price Indexes (MXPI). The IPP collects
data from companies on import and export prices and estimates price
indexes for nearly all goods trade and some service trade for the
United States. The data are primarily collected with a business survey.
After completion of extensive research, and in response to a decline in
data collected through traditional survey methods, BLS plans to
implement improvements to the quality and quantity of import and export
price indexes in fiscal year 2025 by replacing data directly collected
from the business survey with administrative trade records for select
homogeneous product areas.
DATES: Written comments must be submitted to the office listed in the
Address section of this notice on or before October 26, 2023.
ADDRESSES: Written comments may be submitted by postal mail to Susan E.
Fleck, International Price Program, U.S. Bureau of Labor Statistics,
Room 2150, Postal Square Building, Massachusetts Avenue NE, Washington,
DC 20212, or by email to: <a href="/cdn-cgi/l/email-protection#501900000f16021e10323c237e373f26"><span class="__cf_email__" data-cfemail="dd948d8d829b8f939dbfb1aef3bab2ab">[email protected]</span></a>.
FOR FURTHER INFORMATION CONTACT: Susan Fleck, International Price
Program, Bureau of Labor Statistics, by phone at 202-691-6043 or by
email at <a href="/cdn-cgi/l/email-protection#125b42424d54405c52707e613c757d64"><span class="__cf_email__" data-cfemail="d69f86868990849896b4baa5f8b1b9a0">[email protected]</span></a>.
SUPPLEMENTARY INFORMATION:
I. Introduction
The Department of Labor, through the Bureau of Labor Statistics, is
responsible for the development and publication of Import and Export
Price Index statistics through the International Price Program (IPP).
Currently, monthly estimates of import and export price indexes for
merchandise goods are published for approximately 740 industry and
product classification areas, including the Harmonized System, Bureau
of Economic Analysis (BEA) End Use System, and North American Industry
Classification System (NAICS). Every month, approximately 17,000 prices
for merchandise goods are collected from businesses using the
International Price Survey. The participating businesses are selected
based on a statistically representative sample of import and export
goods trade.
The International Price Program has developed an approach to
maintain and expand the number of publishable price indexes of
merchandise goods for the Import and Export Price Indexes. IPP plans to
replace approximately a third of the sample of merchandise goods trade
with administrative trade transaction records. The improvement is
focused on homogeneous products; monthly prices are calculated from
detailed unit values derived from timely trade transaction records.
These administrative records are reported by companies for regulatory
purposes and are used by the BLS for statistical purposes only. The
administrative records are compiled by the U.S. Census Bureau to
publish official international trade statistics. The Census Bureau is
collaborating with BLS to share the records for use in calculation of
the MXPI. These records have not been used previously to calculate
monthly price indexes. Rather, they have been used by BLS at an
aggregate level on an annual basis to establish the sample frame for
the International Price Survey and to calculate annual trade weight
shares.
This new process is the culmination of a long-standing BLS
objective to mitigate the decline in the number of items whose prices
support the published indexes. In a multi-year, multi-project
initiative that began in FY2018, the following proposed improvements to
import and export price indexes for homogeneous products have been
validated and are scheduled to be implemented:
<bullet> Replace prices collected using the business survey with
unit values of trade transaction records for the subset of homogeneous
merchandise goods. This is accomplished by introducing the following
improvements:
[cir] Revision to sample selection process to replace directly
collected prices from select sampled product areas with current-period
transaction values of administrative trade records for similar goods.
[cir] Application of a matched-model approach to administrative
trade records to create unique product varieties that are consistently
traded over time by:
[ssquf] Applying a rigorous approach to define unit values and
product varieties that mitigates unit value bias.
[ssquf] Using coefficient of variation and other statistics to
evaluate and rank homogeneity of product varieties and product
categories.
[ssquf] Grouping transactions into unique product varieties within
detailed product categories by implementing a product match-adjusted R-
squared method that statistically ranks each combination of descriptors
in transaction records. The best combination results in product
varieties that are continuously traded and prices that are closest to
the mean price of a variety.
[ssquf] Filtering outliers that could cause large fluctuations in
monthly price.
<bullet> Improve representativity of price index by accounting for
current period trade with current period price and
[[Page 62403]]
quantity from trade transaction records for the subset of homogeneous
goods.
<bullet> Reduce bias of price indexes by implementing a superlative
index methodology to calculate lower-level unit value indexes for the
homogeneous product categories, using same-period price and quantity
information. This methodology improves the relevance and quality of
price indexes by accounting for new and disappearing goods. The
methodology also accounts for the seasonality and lumpiness of trade by
calculating a mid-term relative between the current period unit price
and the previous year's average unit price for each product variety.
<bullet> Provide historic time series that allow data users to
independently evaluate the comparability of planned and current
official price indexes using proposed and current data sources.
<bullet> Update the list of publishable import and export price
indexes to expand the coverage from a current 700 to approximately
1,200 detailed product and industry price index series, and
additionally to expand coverage of country-specific price indexes.
To assure data users that this transition to use administrative
data and unit values provides for comparable price index estimates to
the current approach, BLS has provided historical comparisons by
calculating a research data series of the detailed 5-digit BEA End Use
import and export price indexes for 2012 to 2021. BLS will continue to
update the detailed research to current periods and will provide an
overlap of the research data series with the official data series, once
the transition to including administrative trade records occurs in
2025. The research data series is posted to the MXPI research web page
(<a href="http://www.bls.gov/mxp/data/research.htm">http://www.bls.gov/mxp/data/research.htm</a>).
II. Background
The import and export price indexes are calculated with a modified
Laspeyres formula, using current period prices and fixed trade weights
that reflect trade quantities at the time of sampling, and that are
adjusted annually. The target population for coverage of these price
indexes is merchandise trade, excluding military goods, works of art,
used items, charity donations, railroad equipment, items leased for
less than a year, rebuilt and repaired items, and custom-made capital
equipment. The measures are presented at a national level and are
published using three classification systems; by product with the BEA
End Use Classification System and the Harmonized System (HS), and by
industry according to the North American Industry Classification System
(NAICS). The estimates are based on the useable monthly prices of
sampled items provided by company respondents to the International
Price Survey. The data collected are based on a sample drawn from the
frame of administrative trade data provided by importers and exporters
to the U.S. government for regulatory purposes. BLS uses these data
solely for statistical purposes.
The number of companies and prices that support the price indexes
has declined over time. In the 5-year period from 2017 to 2022, there
was a 20-percent decline in the monthly number of prices collected,
from 21,800 to 17,000. While the quality of the top-level price indexes
has been sustained, the reduction in the number of prices has
negatively impacted publishability of detailed price indexes and thus
the relevance of the statistical measure for data users. An initiative
to evaluate the unit prices of administrative trade records to replace
prices reported in the directly collected survey was begun in FY 2018
in response to the decline in prices collected. The research initiative
has successfully shown that unit values from Census administrative
trade records can be used in estimating import and export price indexes
for many homogeneous product categories, because the price indexes
using the new source and method show similar trends to the current
official measures. The new approach also mitigates bias in the indexes
and significantly reduces respondent burden.
III. Differences in Concepts and Methods Using Census Administrative
Trade Data Source for Homogeneous Product Categories
Using the data source of administrative trade transaction records
in a new way to estimate prices requires changes to concepts, design,
and calculation methods for this subset of the target population. This
change in the source introduces a major expansion of coverage of
homogeneous product categories while also reducing respondent burden.
Because unit value price concepts are used for administrative trade
data, the focus of the improvement is on homogeneous product
categories. The changes to concepts and methods introduced by the
change in source data are consistent with internationally recognized
approaches to calculating price indexes, and the concepts and methods
used complement those used for the directly collected business survey.
The changes to concepts are: (1) price concepts, and (2) units and
periodicity of collection. The new concepts are relevant only to the
subset of homogeneous product categories. The change to design affects
the subset of the target population of merchandise goods whose price
source is administrative trade records; these product categories will
no longer be sampled. The changes to methods are relevant only to the
subset of homogeneous product categories; furthermore, these new
methods are only for calculations of the unpublished lower-level price
indexes for 10-digit Harmonized System (HS) product classification
groups. New calculation approaches for the unit value indexes for the
subset of homogeneous products cover (1) calculation of unit value
indexes and aggregation, including treatment of outliers, (2)
substitution procedures, (3) imputation, (4) starting a series, (5)
variance estimates, and (6) sources of error. There are no changes to
the aggregation method of calculating price indexes from the lower
level to the published strata.
Price concepts for administrative trade data source. The current
preferred price concept for directly collected prices is a transaction
price in the currency traded excluding fees, taxes, and duties. The new
price concepts for the administrative trade data source are dependent
on the regulatory requirements for data entry. All prices are border
transaction prices. Prices are reported in U.S. dollars. The reporting
requirements specify that the dollar value of the shipment is to be
recorded, excluding insurance, freight, and duties. This dollar value,
in international commercial (INCO) accounting terms, aligns with the
free on board (f.o.b.) cost basis for imports, and the free alongside
ship (f.a.s.) basis for exports, both of which exclude insurance,
freight, and duties.
In addition, the price definition used for the administrative trade
data is a unit price, and the lower-level index calculated from the
unit price is the unit value index. The unit price is an average price
of a subset of administrative trade transactions grouped by similar
characteristics to create unique matched-model product varieties that
are then able to be consistently priced over time. Grouping
administrative records into product varieties adheres to international
best practices, which establish that unit values should relate to a
single homogenous product whose specifications should remain constant.
The new concept of unit price is based on the data fields reported
in the administrative trade data. Each record reports the product
quantity traded and total trade dollar value for a specific shipment by
a specific company for a
[[Page 62404]]
specific 10-digit HS product category, for a point in time (i.e. the
date of arrival or departure from the U.S. port). The unit price for
each individual shipment is a product's total trade dollar value
divided by the quantity. The shipment records are grouped by data
fields into product varieties. The selection of the data fields to
group records into distinct product varieties uses a match-adjusted R-
squared approach (MARS); data field combinations are ranked based on
the explained variance in product unit prices with product match over
time, using a stratification scheme based on the 10-digit HS product
classifications that include a 5-digit BEA End Use product category.
Product varieties are established as a combination of characteristics
by BEA End Use strata using the MARS analysis. Once the characteristics
are selected, records with the same characteristics are grouped into a
unique product variety to calculate a quantity-weighted average unit
price. The average unit price of each unique product variety is
aggregated into a larger product category by HS classification to
calculate a unit value index. (See New and enhanced methods to
calculate and aggregate unit value indexes.) The unit value index is
equivalent to a directly collected item price for calculation purposes.
The characteristics of product varieties will be reviewed when major
revisions occur in the HS product classification structure. Any change
in HS product classification or product variety will be linked to
continue a time series.
Units and periodicity of collection. The current concept of
periodicity of collection for the directly collected survey is that the
preferred price for items reported by a respondent is the transaction
price for an item traded in the reference month as near as possible to
the first day of the month. The new concept for the subset of
homogeneous products using administrative trade records is to account
for all transactions throughout the reference month and to calculate a
weighted average unit price for each detailed product variety. The
reporting requirements for trade data extend beyond the calendar month,
so that the preliminary estimate of MXPI will not include all trade
during the reference month. Subsequent revisions to the MXPI will
incorporate all transaction records for the reference month that meet
data quality verification criteria.
New and enhanced methods to calculate and aggregate unit value
indexes for homogeneous product MXPI. Unit value indexes are reliably
estimated using an estimation approach that incorporates new methods,
enhancements to current methods, and continuation of other methods
currently in use.
New approach to calculation of unit value indexes. The current
approach to account for those homogeneous product categories that use
an average, spot, or unit price, for homogeneous product types such as
grains, metals, and crude petroleum, is 1) to record the price for the
homogeneous product category as a unit price for an item, and 2) to use
the corresponding trade dollar value for the product category for
aggregation. For crude petroleum imports, specifically, the current
method is more refined; using the administrative data of imported crude
petroleum collected by the U.S. Energy Information Agency, BLS
calculates a weighted average unit price of each unique crude oil
stream, all of which are then aggregated to a single unit value index
for the crude petroleum product category.
This current approach to using unit prices is enhanced for use with
administrative trade data. At the index calculation level of published
strata, the current approach for estimating published strata with
average, spot, or unit prices remains the same. A new method has been
implemented to calculate the unit prices of administrative trade
transactions and to aggregate these transactions into unit value
indexes. The new method accounts for the availability of current period
quantity data in the administrative trade data. The new method results
in a significant quality improvement that mitigates new goods and
substitution bias by using the current period trade weights in a
superlative index formula.
The superlative index formula used for calculating the unit value
indexes is a Tornqvist formula. A Tornqvist price index first
calculates a geometric average of the price relatives of the current to
base period prices. Current period prices are calculated for each of
the 4 months of the revision period. Base period prices are the
arithmetic average of all prices of the previous year. The ratio of
current-period price to previous-year price, also called a mid-term
relative (MTR), is calculated for each month. The Tornqvist calculation
then weights the MTR price relatives of the product varieties by the
arithmetic average of the value shares for the two periods to calculate
the unit value index for each 10-digit HS product classification group.
The index levels in each month are then linked to calculate month-to-
month price changes for each classification group. Using an entire year
for the base period implies that any product variety that was traded
the previous year contributes to the index, even if they were not
traded the previous month. This approach greatly increases the number
of product variety prices used in the unit value index estimation. The
unit value index, once calculated, is then treated as a unique item
price and then aggregated to the publication-level industry or product
import or export price index using the current modified Laspeyres index
method.
New approach to aggregation. The current method to estimate the
published Import and Export Price Indexes uses the monthly prices of
directly collected items to calculate each item's price change, as well
as sample weights and company weights, to aggregate to a 10-digit HS
product classification group. The next step then aggregates the price
change of the 10-digit classification group with annual trade weights
from the calendar year ended 2 years prior to the current calendar year
to calculate a modified Laspeyres price index for each classification
system. The aggregation uses the concordance between the Harmonized
System and the other two classification systems of BEA End Use and
NAICS. With the new data source, aggregation does not require sample or
company weights. Each unit value index is equivalent to an item price
in the calculation of import and export price indexes. Thus the item
prices that are aggregated to the published indexes are composed of
directly collected prices and unit value indexes. Together they form
two non-overlapping subsets of item prices that cover the target
population of merchandise goods trade. The first subset consists of the
monthly prices of directly collected items for product categories that
do not meet the quality criteria for unit value indexes. The second
subset consists of the unit value indexes for product categories that
meet the quality criteria for use. The primary product classification
is the BEA End Use product classification, and the detailed 5-digit BEA
End Use import and export price indexes will be based on either the
survey data or administrative trade data. However, at the higher levels
of aggregation and for other classifications, most other published
indexes will be composed of some combination of the two data sources.
The subset of country-specific NAICS price indexes, called locality
of origin and locality of destination price indexes, are used to
measure U.S. competitiveness with trading partners. The current
sampling approach does not account for locality, but the locality price
indexes are quality-reviewed for
[[Page 62405]]
publication. The revised approach to calculating and publishing
locality price indexes will blend directly collected items with
locality-specific unit value indexes. Product varieties will be grouped
by country and locality before their prices are aggregated to unit
value indexes. Locality-specific unit value indexes are weighted by the
locality-specific dollar value of trade from the transaction to the
unit value index level. Each locality-specific unit value index is
mapped to a classification group and then aggregated to the locality-
specific 6-digit NAICS industry category using the current modified
Laspeyres index method. Some published indexes will be composed of some
combination of the two data sources.
New treatment of outliers. A new approach has been developed to
assure fitness for use of the transactions comprising each 10-digit HS
product category that will replace the directly collected survey data.
This approach eliminates transactions that are not useable and excludes
outliers at the tail ends of the distribution of price and quantity.
Excluding outliers mitigates the occurrence of unit value bias.
Previous research has identified the fitness for use of 10-digit HS
product categories by comparing multiyear trends of price indexes that
are composed of current data sources and administrative trade data,
respectively. When price index trends are shown to be statistically
consistent across years and months, administrative trade data are
selected to replace current data sources. Subsequently, once the
administrative trade data are in place in the official price indexes,
procedures must be in place to evaluate and eliminate those
transactions that are outliers, i.e., that differ greatly from the
average trade transaction that make up a 10-digit HS product category.
The exclusion of outliers will reduce the occurrence of unit value bias
by limiting the variability that contributes to the bias and will
assure the quality of the price indexes.
The administrative trade data are filtered to exclude missing data
and outliers using automated microdata review processes. Regarding
missing data, transactions with null data fields are excluded.
Transactions with a null quantity data field for which the quantity is
imputed are excluded from unit price calculation. However, the dollar-
value weight is included for unit value index calculation. Regarding
trimming outliers, four procedures are implemented progressively to
trim quantities and filter unit prices and price changes to apply the
matched-item approach and mitigate unit value bias. First, unit prices
for each transaction are calculated, after which a set percent of the
quantity is trimmed equally from both tails of the unit price
distribution within the product variety; then the transaction unit
prices are weighted using the trimmed quantities to calculate an
average weighted unit price for the product variety. Thus, the largest
and smallest transaction unit prices will have less impact on the
weighted unit price of a product variety, which mitigates unit value
bias. Second, the coefficient of variation value of the weighted unit
price of each product variety is calculated; for any product variety's
price whose coefficient of variation is over a set threshold, that
product variety displays unit value bias, and thus is excluded from the
unit value index calculation. The exclusion is conditional on the
dollar-value weight of the product variety not exceeding 10 percent of
the trade dollar value of the detailed BEA End Use stratum to which the
variety's corresponding 10-digit HS product classification is mapped.
Thus, this step excludes the product variety prices that show unit
value bias while assuring representativeness. Third, the mid-term
relatives (MTRs) are calculated for each product variety, using the
average unit price in the reference month and the variety's base price
from the previous year. The MTRs of all product varieties that comprise
each 5-digit BEA End Use strata product grouping are sorted by
magnitude, and MTRs on the tails of the distribution are trimmed for
those values that extend beyond a previously established outlier
threshold; the corresponding trade weights are also excluded in the
index aggregation. This step uses historic research data to establish
the outlier threshold. Fourth, in monthly production, automated flags
identify outliers of product variety prices based on established
thresholds relating to larger than average price movements. Individual
product variety prices are compared over time and across varieties to
determine statistical validity. Data values that do not meet
established parameters are excluded.
Enhanced method for substitution. Current substitution procedures
and practices in the survey allow for item substitution, in which a
previously traded item is replaced with a new item from the same
company and within the same commodity classification group. Current
imputation procedures and practices allow for an imputed or estimated
price to be entered when there are missing price data.
The new approach for items comprising HS product classification
groups using administrative trade data does not substitute items.
However, the new approach will immediately account for substitution in
trade. There is no substitution procedure to replace items missing in
trade, because the administrative trade data account for the natural
occurrence of all trade. For unit value indexes, which are mapped to HS
product classification groups, the lack of an observation is not an
indication of missing data, it is rather an indication of no trade in
that period.
Enhanced method for imputation. The current imputation approach is
to impute or estimate a price when there are missing price data and
when starting a series. The new approach for items comprising HS
product classification groups using administrative trade data depends
on the level of calculation. At the level of product varieties,
imputation is not used when a product variety has no unit price,
because the lack of a unit price indicates an absence of trade.
However, imputation is used when starting a series for a new product
variety. A new product variety naturally occurs in trade, which is
characterized by a not-previously defined combination of shared
characteristics for the selected data fields in an HS product
classification category.
Enhanced method for starting a series. The current method for
starting a price series, or initialization, is to impute the first
price of an item based on the value of the index for the weight group.
The enhanced method for starting a price series is to impute the first
price of a product variety from the unit value index that is calculated
from all other product varieties in the same HS-product category. The
mid-term relative (MTR) method is then used to calculate the current
period price relative. The current imputation approach for imputing a
missing price at the classification group level does not change.
Variance estimates for administrative trade data. The current
approach for calculating variance estimates will not be revised;
variance is calculated for price indexes that consist of sampled prices
and are not calculated for price indexes that consist of prices
collected from non-sample sources. For those price indexes that will be
calculated with administrative trade data in place of directly
collected survey data, no variance estimate will be calculated.
Sources of error in administrative trade data. The current sources
of error for survey data are a combination of sampling and nonsampling
error. Sampling error is not relevant to price indexes calculated using
administrative trade data because these are not sample data. With the
new administrative data
[[Page 62406]]
source, there are a few potential sources of error. Processing error is
one source of nonsampling error that is introduced with the use of the
administrative trade data. Among the transaction records processed by
the Census Bureau, some records have incomplete data and are not used
in BLS calculations. Additionally, there is measurement error in
assuming that the characteristics that make up a product variety
adequately explain the month-to-month price change movements.
Furthermore, other records are analyzed and excluded from calculation
because they are at the tails of the distribution of prices or
quantities and are excluded in order to reduce the variability of unit
prices and unit value indexes. The exclusion of transactions with
missing data and estimates at the tails of the distribution may result
in bias or a skewed result if there is a repeatable pattern in either
set of data, such that certain companies have more transactions with
missing data or with widely variable prices. These nonsampling errors
cannot be measured with current methods and there is little actual
research on this topic for administrative data that represents the full
population; however, research has begun and is ongoing to evaluate
sources of error. This research includes methods to adequately explain
mean square error for index estimates that are constructed from the
integration of administrative data and sampled survey data.
Publication of official MXPI. Current publication procedures for
price indexes require an annual review of statistical robustness that
include sample representativeness and that assure the protection of
respondent and company identifiable information. Revised publication
procedures for price indexes calculated with administrative trade data
will be put in place. Current procedures limit publication of indexes
that represent commodity areas with a minimum dollar value of annual
import or export trade value. New procedures for administrative trade
data will not require a minimum dollar value for publication.
Protection of respondent and company identifiable information will
remain in place and thus not all price indexes using administrative
trade data will be published separately.
Modified publication procedures are in place to evaluate the price
indexes selected for inclusion in the aggregation. Up to the date of
publication, a research data series using the new methods will be
calculated to compare monthly and long-term variability and skewness
relative to the official price indexes using current methods to assure
quality and consistency before incorporating the administrative trade
data in the official data release. When a detailed product area is
either under-represented in the sample or difficult to collect, a price
index representing commodity areas with smaller dollar values may use
administrative trade data. This approach increases efficiency and
mitigates respondent burden, even if some bias exists, as long as the
bias does not have an impact on the upper-level indexes.
Publication. Another important improvement is that the methods
allow for an expansion of the number of publishable price indexes. The
enhanced procedure will convert roughly 7 million transaction records
for homogeneous product areas into hundreds of thousands of product
varieties, which subsequently will be used to calculate thousands of
unit value indexes for 10-digit HS product categories. These unit value
indexes are integrated as item prices into the calculation of the MXPI.
There is no change to the method of calculating the monthly estimates
of price indexes. When the transition to using the administrative trade
data occurs, the price indexes currently published will not have a
break in series. Under current procedures, new items brought into the
price indexes replace discontinued items. With the introduction of the
administrative trade data source, new items based on the administrative
trade data will be brought in to completely replace directly collected
survey data within classification groups that have been determined to
meet criteria of homogeneity. Whether a published price index includes
administrative trade data will be determined by the concordance between
HS classification groups and each product and industry classification.
The new approach treats directly collected and administrative data
equally, and no distinction will be made in publication of the data
source. The transition to using administrative trade data in the
official news release will be announced in advance.
This detailed description of the current and redesign approaches
complements the research data series that are available at the BLS MXPI
website <a href="http://www.bls.gov/mxp/home.htm">http://www.bls.gov/mxp/home.htm</a>.
IV. Desired Focus of Comments
This notice is a general solicitation of comments from the public
on the technical approach to this major change in the concepts,
sources, and methods of the Import and Export Price Indexes.
Signed at Washington, DC, this 5th day of September 2023.
Eric Molina,
Acting Chief, Division of Management Systems, Bureau of Labor
Statistics.
[FR Doc. 2023-19486 Filed 9-8-23; 8:45 am]
BILLING CODE 4510-24-P
</pre><script data-cfasync="false" src="/cdn-cgi/scripts/5c5dd728/cloudflare-static/email-decode.min.js"></script></body>
</html>Indexed from Federal Register on September 11, 2023.
This is legal information, not legal advice. Laws vary by jurisdiction and change frequently. Always verify current law with official sources and consult a licensed attorney in your jurisdiction for advice on your specific situation.