62402 Federal Register / Vol. 88, No. 174 / Monday, September 11, 2023 / Notices 

statistical programs, and labor 

management standards. 

This information collection is subject 

to the PRA. A Federal agency generally 

cannot conduct or sponsor a collection 

of information, and the public is 

generally not required to respond to an 

information collection, unless the OMB 

approves it and displays a currently 

valid OMB Control Number. In addition, 

notwithstanding any other provisions of 

law, no person shall generally be subject 

to penalty for failing to comply with a 

collection of information that does not 

display a valid OMB Control Number. 

See 5 CFR 1320.5(a) and 1320.6. 

DOL seeks PRA authorization for this 

information collection for three (3) 

years. OMB authorization for an ICR 

cannot be for more than three (3) years 

without renewal. The DOL notes that 

information collection requirements 

submitted to the OMB for existing ICRs 

receive a month-to-month extension 

while they undergo review. 

Type of Review: Extension. 

Agency: DOL—OASAM. 

Title of Collection: Department of 

Labor Generic Clearance for Outreach 

Activities. 

OMB Number: 1225–0059. 

Affected Public: Individuals and 

Households; Private Sector; not-forprofit institutions; State, Local and 

Tribal Governments. 

Number of Respondents: 800,000. 

Number of Responses: 800,000. 

Annual Burden Hours: 80,000 hours. 

Annual Respondent or Recordkeeper 

Cost: $0. 

(Authority: 44 U.S.C. 3507(a)(1)(D)) 

Nicole Bouchet, 

Acting Departmental Clearance Officer. 

[FR Doc. 2023–19488 Filed 9–8–23; 8:45 am] 

BILLING CODE 4510–04–P 

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: IPP_FRN@bls.gov. 

FOR FURTHER INFORMATION CONTACT: 

Susan Fleck, International Price 

Program, Bureau of Labor Statistics, by 

phone at 202–691–6043 or by email at 

IPP_FRN@bls.gov. 

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: 

• 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: 

Æ 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. 

Æ Application of a matched-model 

approach to administrative trade records 

to create unique product varieties that 

are consistently traded over time by: 

D Applying a rigorous approach to 

define unit values and product varieties 

that mitigates unit value bias. 

D Using coefficient of variation and 

other statistics to evaluate and rank 

homogeneity of product varieties and 

product categories. 

D 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. 

D Filtering outliers that could cause 

large fluctuations in monthly price. 

• Improve representativity of price 

index by accounting for current period 

trade with current period price and 


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quantity from trade transaction records 

for the subset of homogeneous goods. 

• 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. 

• 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. 

• 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 (http://

www.bls.gov/mxp/data/research.htm). 

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 toplevel 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 


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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 midterm 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 


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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 localityspecific 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 HSproduct 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 


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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 monthto-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 http://www.bls.gov/mxp/ 

home.htm. 

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 

NATIONAL FOUNDATION ON THE 

ARTS AND THE HUMANITIES 

National Endowment for the 

Humanities 

Meeting of Humanities Panel 

AGENCY: National Endowment for the 

Humanities; National Foundation on the 

Arts and the Humanities. 

ACTION: Notice of meeting. 

SUMMARY: The National Endowment for 

the Humanities (NEH) will hold 

seventeen meetings, by 

videoconference, of the Humanities 

Panel, a federal advisory committee, 

during October 2023. The purpose of the 

meetings is for panel review, discussion, 

evaluation, and recommendation of 

applications for financial assistance 

under the National Foundation on the 

Arts and the Humanities Act of 1965. 

DATES: See SUPPLEMENTARY INFORMATION

for meeting dates. The meetings will 

open at 8:30 a.m. and will adjourn by 

5:00 p.m. on the dates specified below. 

FOR FURTHER INFORMATION CONTACT: 

Elizabeth Voyatzis, Committee 

Management Officer, 400 7th Street SW, 

Room 4060, Washington, DC 20506; 

(202) 606–8322; evoyatzis@neh.gov. 

SUPPLEMENTARY INFORMATION: Pursuant 

to section 10(a)(2) of the Federal 

Advisory Committee Act (5 U.S.C. 10), 

notice is hereby given of the following 

meetings: 

1. Date: October 4, 2023 

This video meeting will discuss 

applications on the topic of U.S. 

History, for the Humanities Collections 

and Reference Resources grant program, 

submitted to the Division of 

Preservation and Access. 

2. Date: October 11, 2023 

This video meeting will discuss 

applications on the topics of Film and 

Media Studies, for the Humanities 

Collections and Reference Resources 

grant program, submitted to the Division 

of Preservation and Access. 

3. Date: October 12, 2023 

This video meeting will discuss 

applications on the topics of Literary 

and Cultural Studies, for the Humanities 

Collections and Reference Resources 


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