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ABSTRACT - Assessment of Manual vs Automated Survey Editing and Imputation. Sean Rhodes (U.S. Department of Agriculture National Agricultural Statistics Service)

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English

1

UNITED NATIONS ECONOMIC COMMISSION FOR EUROPE CONFERENCE OF EUROPEAN STATISTICIANS Expert Meeting on Statistical Data Editing 7-9 October 2024, Vienna Austria

12 July 2024

Assessment of Manual vs Automated Survey Editing and Imputation

Sean Rhodes, Megan Lipke, Jennifer Maiwurm, Darcy Miller, Denise A. Abreu, Linda J. Young (U.S. Department of Agriculture National Agricultural Statistics Service, United States of America) [email protected] Abstract The United States (U.S.) Department of Agriculture’s National Agricultural Statistics Service (NASS) conducts hundreds of surveys each year to estimate nearly every facet of agriculture in the U.S. One of these surveys is the Crops Acreage, Production, and Stocks (APS) Survey. Crops APS is conducted quarterly in the months of June, September, December, and March. The September Crops APS collects data on acres planted, acres harvested, yield or production for small grains, and grain stored. Once data have been collected, responses are then reviewed and edited by NASS’s regional field offices for outliers, edit failures, and item imputation. The current review process and item-level imputations are done though a manual, interactive process, which can be time consuming and costly for the Agency. NASS has taken steps to develop a generalized system called IDEAL (Imputation, Deterministic Edits, Automation and Logic) to automate the imputation and error correction occurring after data collection but before the outlier review process. This automated imputation and error correction was applied to historical data to evaluate the imputation methodology, efficiency, and data quality. This paper presents the results from testing on historical data which compares the data quality and efficiency of the manual process to the data quality and efficiency of the automated process using the historical data. These testing results are critical to implementing the new automatic editing system in the production environment for September Crops APS 2024.

  • Assessment of Manual vs Automated Survey Editing and Imputation

MWW2024_S6_USA_Gillman

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English

UNITED NATIONS ECONOMIC COMMISSION FOR EUROPE

CONFERENCE OF EUROPEAN STATISTICIANS

ModernStats World Workshop

21-22 October 2024, Geneva

Capabilities and Metadata Standards

Speaker: Daniel Gillman, US Bureau of Labor Statistics

Author(s):

Abstract

Over time as the needs and desires for modernizing the production and dissemination of statistical data have

increased, several capabilities have been identified as necessary for making the improvements possible. These

include findability, accessibility, interoperability, reusability, and transparency.

As many will recognize, the first 4 of these are the capabilities that comprise the FAIR principles. As

documentation on FAIR makes clear, metadata is a big part of what makes FAIR work. Transparency could be

interpreted as the result of the combination of all of FAIR. The conclusion is all these capabilities depend on

metadata.

It turns out that we can make this more precise. The FAIR principles are presented in a generic sort of way, and

what might actually be required is glossed over. But the same ideas that make interoperability dependent on

conformance to metadata schemas, as included in the report on Data Governance under the UNECE, can be

applied to similar arguments about the other capabilities.

Metadata and metadata standards play central roles. This understanding elevates the work of the Supporting

Standards Group and ties it in with the broader framework being developed outside the UNECE, especially

FAIR.

Some of these ideas have been presented in UNECE workshops before, but the generality of the approach is a

new discovery, and it meshes nicely with the aims of the workshop.

Measuring Emigration from the United States: Past, Present, and Future Approaches (United States)

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English

Measuring Emigration from the United States: Past, Present, and Future Approaches

Esther R. Miller U.S. Census Bureau

This presentation is released to inform interested parties of ongoing research and to encourage discussion of work in progress. Any opinions and conclusions expressed herein are those of the author(s) and do not reflect the views of the U.S. Census Bureau. The Census Bureau's Disclosure Review Board has reviewed this data product for unauthorized disclosure of confidential information and have approved the disclosure avoidance practices applied to this release. DRB Approval Number: CBDRB-FY2022-CES010-011.

Demographic Balancing Equation for Population Estimates

2

Population Base Births Deaths Migration

Net Domestic Migration

Net International

Migration

Population Estimate

3

Components of Net International Migration

Net International

Migration

Non-U.S.-born immigration (ins)

Non-U.S.-born emigration (outs)

Net migration between U.S. and Puerto Rico

Net movement of the Armed Forces

Net U.S.-born migration

Approaches to Estimate Emigration of the Non-U.S.-born Population

Past Residual: Census Data

Present Residual: Annual Household Surveys

Future Link Longitudinal Administrative Records

Approaches to Estimate Emigration of the non-U.S.-born Population

Past Residual: Census

6

• Rates held constant for V2000 and V2010

• Pattern expected given stability of responses to American Community Survey (ACS)

Estimates of Non-U.S.-born Emigration Using 10-Year Residuals: 1990 - 2020

V2000 (Census-to-Census) V2010 (Census-to-ACS)

V2020 (ACS-to-ACS)

U.S. Census Bureau, Population Division, Internal Simulations

Explanation of Residual Emigration Estimates

7

Observed cohort

(T1)

Survival rates from life

tables

Expected cohort (T2)

Expected cohort

(T2)

Observed cohort

(T2)

Emigration estimate for the cohort (T1-T2)

X =

-- =

8

Before 2015

2015-present

ACS Questionnaire Changes Affect Estimate of Immigration

• Questionnaire changes led to higher numbers of recent immigrants measured in Time 2

• Increase in recent immigrants will increase emigration rates/estimates

9

Data Quality Measures in the ACS Survey: 2005-2021

• Increases in non- response, refusal, and imputation rates lead to lower quality data

• Lower quality of data affects estimates of the population and immigration

• Ultimately affects estimates of emigration (residual)

Source: U.S. Census Bureau, American Community Survey - Sample Size and Data Quality. https://www.census.gov/acs/www/methodology/sample-size-and-data-quality/

10

Estimates of Non-U.S.-born Emigration: 1990-2020

• Estimate tripled between V2014 and V2016

• Due to declines in data quality and questionnaire changes in 2015 ACS

Source: U.S. Census Bureau, Population Division, Internal Simulations

V2000 (Census-to-Census) V2010 (Census-to-ACS)

V2014 (ACS-to-ACS)

11

Estimates of Non-U.S.-born Emigration Using Shortened Residual Periods: 2010-2020

• Estimates of emigration rise dramatically in recent years from one vintage to the next

• Ultimately, produces negative net-migration

Source: U.S. Census Bureau, Population Division, Internal Simulations

(ACS-to-ACS)

(ACS-to-ACS)

V2000 (Census-to-Census) V2010 (Census-to-ACS)

Present Residual:

Annual Household Surveys

Hold Rates Constant: Average of Three Rates Calculated in Beginning of Decade

• Solution: Hold residual rate constant across decade using average of early-decade residuals

• Net-migration will be positive (or zero)

Source: U.S. Census Bureau, Population Division, Internal Simulations

V2000 (Census-to-Census) V2010 (Census-to-ACS

(ACS-to-ACS)

(ACS-to-ACS)

Approaches to Estimate Emigration of the non-U.S.-born Population

Past Compute Residual

with Population Components

Present Hold Average Residual Constant

Future Link Longitudinal

Administrative Records

“Signs of Life” Emigration Framework

Link individual records using

Protected Identification Keys

(PIKs)

Construct starting population

estimate

Track resident non-U.S.-born

population over time

Look for evidence non-U.S.-born

person exited the U.S. (Confirmed

Emigrant)

15

Linked Administrative Records Datasets

16

• Tax Identifier ID • TIN (SSN) • ITIN (Assigned by IRS – no link to Numident)

• Address • Domestic • Abroad

Tax Forms (IRS)

• Social Security Number (SSN)

• Place of Birth • Citizenship status Native Born Naturalized Citizen Non-citizen

• Year SSN assigned

NUMIDENT

Derive Starting Population of Non-U.S. Born from Two Consecutive Years of IRS Data

----------- (T1 -1) ----------- ----------- (T1) -----------

Identify non- U.S.-born PIKs

in Tax Year T1-1

Identify non- U.S.-born PIKs in Tax Year T1

Resident non- U.S.-born T1 population

----------- (P1) -----------

Universe = Linked PIKs (with domestic address)

Starting Population Derived from Administrative Records: Tax Years 2010 - 2018

(in millions)

18

38.9 40.3 42.6 43.1 43.9 44.6 45.2 45.8 45.9

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

2010 2011 2012 2013 2014 2015 2016 2017 2018

Source: U.S. Census Bureau, IRS 1040/1099 (Tax Years 2009-2020) and Numident (2022). DRB Approval Number: CBDRB-FY24-CES025-003.

• Linking two consecutive years of files is stable across time

• Eight years later, increase of 6 million people

Track Individuals Over Time to Look for “Signs of Life”

T1 Annual starting

non-U.S.- born

population estimate

T2

Add to Signs of Life

Emigrant Counts

Add to Possible

Emigrant

T2 address abroad?

YES

Reside in US Not counted as emigrant

NO

T1 and T2 Linked?

YES NO

T3

Add to Signs of Life

Emigrant Counts

Add to Possible

Emigrant

T3 address abroad?

YES

Reside in US Not counted as emigrant

NO

T1 and T3 Linked?

YES NO

Non-U.S.-born Emigration Rates: 2010-2019

20

Source: U.S. Census Bureau, ACS-ACS unadjusted residual estimates; Linked IRS 1040/1099 (Tax Years 2009-2020) and Numident (2022). DRB Approval Numbers: CBDRB-FY22-CES010-011, CBDRB-FY22-CES010-028, and CBDRB-FY23-CES014-025.

0.00

0.50

1.00

1.50

2.00

2.50

Em ig

ra tio

n Ra

te (p

er 1

00 N

on -U

.S .-b

or n)

Emigration Interval (Calendar Year)

Benchmark Confirmed Emigrants Residual Emigrants Confirmed + Residual EmigrantsPossible Emigrants Confirmed Emigrants + Possible Emigrants

Summary

• Survey data are affected by declining quality and changes to questionnaire

• Mirror statistics do not support past residual computations

Residual

• “Signs of Life” framework produces consistent emigration rates

• Possible migrants difficult to determine • Under-coverage, especially children • Geographic assignment may be difficult • Other

Linking administrative

Records

21

Conclusion

“Signs of Life” Method is Promising

and as always, Needs Further Research

22

Contact Information

Esther Miller Population Division U.S. Census Bureau

[email protected]

  • �Measuring Emigration from the United States: Past, Present, and Future Approaches
  • Demographic Balancing Equation �for Population Estimates
  • Slide Number 3
  • Approaches to Estimate Emigration of the�Non-U.S.-born Population
  • Approaches to Estimate Emigration of the� non-U.S.-born Population
  • Explanation of Residual Emigration Estimates
  • Slide Number 8
  • Slide Number 9
  • Slide Number 10
  • Slide Number 11
  • Slide Number 12
  • Hold Rates Constant: Average of Three Rates Calculated in Beginning of Decade
  • Approaches to Estimate Emigration of the� non-U.S.-born Population
  • “Signs of Life” Emigration Framework
  • Linked Administrative Records Datasets
  • Derive Starting Population of Non-U.S. Born from Two Consecutive Years of IRS Data
  • Starting Population Derived from Administrative Records:� Tax Years 2010 - 2018�(in millions)
  • Track Individuals Over Time to Look for “Signs of Life”
  • Non-U.S.-born Emigration Rates: 2010-2019
  • Summary
  • Slide Number 22
  • Contact Information

Main revisions and benchmarking – policy and practice: Perspectives from the U.S.

Languages and translations
English

Main revisions and benchmarking – policy and practice: Perspectives from the U.S.

Bob Kornfeld Meeting of the Group of Experts on National Accounts

Geneva, Switzerland, 25-27 April 2024

Outline

1. Highlights from 2023 Comprehensive Update

2. Challenges posed by current approach

3. Alternatives to our current approach

2023 Comprehensive Update of the National Economic Accounts Released Thursday, September 28, 2023

Integration’s final step Benchmark Supply-Use Table

based on 2017 Economic Census

Improved methods, presentations

Reference year updated to 2017

BEA’s 16th Comprehensive

Update

2023 Comprehensive Update of the National Economic Accounts

Harmonizing BEA’s Statistics

Annual I-O and GDP by

Industry

2004

Accelerated Annual I-O

and GDP by Industry

2005

Quarterly GDP by Industry

2014

Current Quarterly Estimates of

National, Regional, and Industry GDP

Statistics

2020

Annual Updates of National,

Regional, and Industry GDP

Statistics

2022

Comprehensive Updates of National,

Regional, and Industry GDP

Statistics

2023

42023 Comprehensive Update of the National Economic Accounts Released Thursday, September 28, 2023

Concurrent Release of Integrated Statistics

National Accounts Directorate

Expanded & Improved Industry Statistics

Industry Economics Directorate

2019: Organizational Alignment

Benefits of Integration

2023 Comprehensive Update of the National Economic Accounts Released Thursday, September 28, 2023

Integration

Balanced Supply-Use framework

Three approaches to

GDP inform each other More

information for users

Gross Domestic Product

Real GDP, Percent Change, Revised

Real GDP, Percent Change, Previously Published

GDP, Revised

GDP, Previously Published

2023 Comprehensive Update of the National Economic Accounts Released Thursday, September 28, 2023

-40,0

-30,0

-20,0

-10,0

0,0

10,0

20,0

30,0

40,0

18,5

19,5

20,5

21,5

22,5

23,5

24,5

25,5

26,5

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

2017 2018 2019 2020 2021 2022

Re al

G DP

p er

ce nt

c ha

ng e

Tr ill

io ns

o f d

ol la

rs

Change in real GDP

Previously Published (lighter shade) Revised (darker shade)

2023 Comprehensive Update of the National Economic Accounts Released Thursday, September 28, 2023

2,2

2,9 2,3

-2,8

5,9

2,1 2,5

3,0 2,5

-2,2

5,8

1,9

-4,0

-3,0

-2,0

-1,0

0,0

1,0

2,0

3,0

4,0

5,0

6,0

7,0

2017 2018 2019 2020 2021 2022

Pe rc

en t

New and revised source data

• Quarterly Census of Employment and Wages

• Occupational Employment Statistics

• Producer Price Index • Consumer Price

Index

• Benchmark supply-use tables

• International transactions accounts

• 2017 Economic Census • American Community Survey • Annual Capital Expenditures Survey • Annual Retail Trade Survey • Annual Survey of Manufactures • Annual Survey of State and Local Government

Finances • Annual Wholesale Trade Survey • Value of Construction Put in Place Survey • Service Annual Survey • Quarterly Services Survey

• Office of Management and Budget: Federal budget

• Internal Revenue Service: Tax returns for corporations, sole proprietorships, and partnerships

• Federal Reserve Board: FAUS • Department of Agriculture: Farm statistics

2023 Comprehensive Update of the National Economic Accounts Released Thursday, September 28, 2023

Improvements

• Improved treatment of regulated investment companies (RICs) and real estate investment trusts (REITs)

• Improved price measures

• Improved measures of industries’ use of FISIM

• Improved measures of investment in own-account software

• Presentational improvements o More detailed presentation of household spending and prices

2023 Comprehensive Update of the National Economic Accounts Released Thursday, September 28, 2023

External communication

• See https://www.bea.gov/information-updates-national-economic-accounts

• Preview articles highlighting main features of the comprehensive update

• Table changes announced in advance

• Schedule for release of data announced in advance

• After the release • Briefing slides, article summarizing major changes and revisions, tables summarizing revisions • Updates as more data becomes available

4/11/2024

11

Challenges

4/11/2024

12

The 5-year economic census is the pillar of BEA’s benchmark CU estimates

• The economic census (EC) provides our most detailed statistics on o intermediate inputs, expenses, and outputs for supply and use tables, revealing any major changes in

production processes o product line sales by industry

• The EC provides the only opportunity for producing “true” production-based measures of GDP • For nonbenchmark years, final demand-based GDP estimates are extrapolated based on relationships

established in the benchmark year.

• CUs provide an opportunity for major improvements (updated classifications, capitalizing new assets etc.)

• The rich detail of the EC enables BEA to produce a balanced SUT at a very detailed level (402 industries and commodities)

• Annual updates in other years are based on less detailed annual surveys o Typically measures of sales/receipts by industry o Limited/minimal data on intermediate inputs and outputs, product line and expense detail

4/11/2024

13

Challenges posed by the current 5-year benchmarking

• Benchmark results are not timely o 2023 CU, released September 29th, 2023, benchmarked to the 2017 Economic Census  At best, “brand new” results are benchmarked to values 5 years old!

 At worst, estimates are benchmarked to values 10-11 years old! (GDP published August 2023 were benchmarked to the 2012 Economic Census.)

 Detailed product-line compositions are dated and present compositional challenges (e.g., 2017 is pre-COVID and surely consumer preferences differed over the pandemic and continue to differ today)

• Independent production-based measures of GDP can only be produced in the benchmark year o Doing something only every 5-years is inherently challenging

4/11/2024

14

Challenges posed by the current 5-year benchmarking

• The EC is extremely costly to produce and poses notable response burden o Doing something only every 5-years is inherently challenging o Large spikes in staff workload, challenges from staff turnover, IT systems issues

• Balancing detailed benchmark SUTs can be especially time consuming

• Maintain consistent time series all the way back to 1929

4/11/2024

15

Alternatives

4/11/2024

16

Committee on National Statistics (CNSTAT) Panel on Reengineering the Census Bureau’s Annual Economic Surveys • The panel recommended the development of an “Annual Business Survey System” to replace the current

suite of largely separate annual economic surveys o Currently, separate annual surveys cover retail trade, wholesale trade, manufacturing, services etc

• The new survey system should… o administer a core set of questions to all respondents, with appropriate industry customization, plus modules containing

industry-specific and topical questions; o use a rotating panel sample drawn from a redesigned comprehensive Business Register; o use standardized data collection, processing, and estimation methods for all industries in the sample; o develop a single application programming interface for access to data for single and multiple industries; o use administrative records to the maximum extent possible for greater efficiency and accuracy of data and reduced

respondent burden; and o incorporate small-area models to produce subnational geographic estimates with sufficient accuracy for users’ needs

• In response, the Census Bureau is currently developing the Annual Integrated Economic Survey (AIES) o a re-engineered survey designed to integrate and replace seven existing annual business surveys into a single survey. o also exploring greater use of administrative data, private data, machine learning, other approaches

• The AIES could eventually provide some of the detailed data currently obtained from the 5-year EC 17

• National Academy of Sciences (NAS) recommended changes to our annual economic programs

• Main drivers of this effort include:

18

Census Bureau AIES

Alternative approaches

• Strive to harmonize process for non-benchmark and benchmark years

o Harmonize non-benchmark and benchmark years level of detail (e.g. less detail for benchmark year, more detail for standard annual year)

o Maintain practice of benchmarking to a full census but produce statistics at same level of detail

o Produce “true” independent production-based measures of GDP

• Explore with data collection partners alternative ways to obtain up-to-date, detailed data on intermediate inputs, product line sales by industry, etc.

o Embrace machine-learning / modeling techniques to fill in missing data

o Make more use of administrative records data 20

Alternative approaches and questions

• Produce/balance benchmark SUTs at a less detailed level

• Carefully analyze pros and cons. Impacts on:

• Thematic accounts

• Global value chains and TiVA

• Dispense with Economic Census?

• How important is it to maintain full time series (all the way back 1929 for the U.S.)

21

  • Main revisions and benchmarking – policy and practice: Perspectives from the U.S.
  • Outline
  • Slide Number 3
  • �Harmonizing BEA’s Statistics�
  • Benefits of Integration
  • Gross Domestic Product
  • Change in real GDP
  • New and revised source data
  • Improvements
  • External communication
  • Slide Number 12
  • The 5-year economic census is the pillar of BEA’s benchmark CU estimates
  • Challenges posed by the current 5-year benchmarking
  • Challenges posed by the current 5-year benchmarking
  • Slide Number 16
  • Committee on National Statistics (CNSTAT) Panel on Reengineering the Census Bureau’s Annual Economic Surveys
  • Slide Number 18
  • Alternative approaches
  • Alternative approaches and questions

Recording Data Assets in the U.S. National Accounts, United States

Languages and translations
English

Recording Data Assets in the U.S. National Accounts

Bob Kornfeld Meeting of the Group of Experts on National Accounts

Geneva, Switzerland, 25-27 April 2024

Prepared by JB Santiago Calderón and Rachel Soloveichik, Research Economists, BEA

Overview

• Capitalization of data a high-priority proposal for the upcoming SNA update

• Since 2018 BEA has worked on various efforts including the development of a proposed methodology and estimates including investment, prices, and net-stock

• Focus has been on own account data assets with some work on purchased data as well as cross country flows to a lesser extent

• BEA has participated in the Advisory Expert Group (AEG) endorsed recommendation put forth by the Digitalization Task Team as well as participating in a current IMF-EuroStat task force for a compilation manual

4/11/2024

2

Definition of Data as an Asset

3

Data is defined as “information content that is produced by accessing and observing phenomena; and recording, organizing and storing information elements from these phenomena in a digital format, which provide an economic benefit when used in productive activities.”

BEA Work on Capitalizing Data

4

• BEA publishes first working paper on “Treatment of Data in National Accounts” (2019). It lays out preliminary thoughts and considerations for the inclusion of data stocks and flows in a national accounts standard.

• Opting for a sum of cost approach, BEA develops a novel methodology to discover and estimate of time-use factors by occupations (2021).

• Experimental methodology and estimates for business sector published in (2022) as a working paper. • Uses novel time-use factors to implement a sum of cost approach • Adjustments needed to avoid double-counting with other IPPs.

Sum of Cost Approach

5

𝐶𝐶𝑖𝑖𝑖𝑖 = 𝛼𝛼𝑖𝑖𝑖𝑖𝜏𝜏𝜔𝜔𝑊𝑊𝜔𝜔𝑖𝑖𝑖𝑖𝐻𝐻𝜔𝜔𝑖𝑖𝑖𝑖

The production cost in industry (i) at time (y) is a function of:

• Wages (W) and employment number (H) for occupation (𝜔𝜔), where 𝜏𝜏𝜔𝜔 is the portion of the employee time-effort allocated to activities within scope.

• Markup 𝛼𝛼𝑖𝑖𝑖𝑖 reflects the ratio of total production costs to the payroll in that industry and year (e.g., total employee compensation, capital services, etc.)

Methodology for Sum of Costs Approach

6

Item Strategy / Progress

Time-use factors Identify data-relevant skills to proxy tasks and to estimate time-use factors using O*NET occupational information and online job ads text.

Adjustment Time use factors for certain occupations are adjusted to avoid multiple counting with other IPPs

Payroll Using BLS data, construct a time series of wages and number of employees for each relevant occupation.

Markup Apply ratio of gross output per industry-year to the wages to transform wages to total production costs.

Prices Input-cost index consisting of wages, overhead costs and capital services.

Net-stock Perpetual inventory method. Researching appropriate service life for the depreciation rates.

Nominal Investment by Industry

7

Share of data investment by occupation (1999-2022)

8

Occupation Share (%)

Accountants and Auditors 13.6

Computer Systems Analysts 9.0

Financial Managers 8.0

Management Analysts 7.9

Data Entry Keyers 5.8

Registered Nurses 5.3

Database Administrators 5.1

Construction and Building Inspectors 4.9

Computer and Information Systems Managers 4.6

Network and Computer Systems Administrators 3.7

Market Research Analysts and Marketing Specialists 3.0

Key Issues

9

• Current guidance favored to include only active surveillance and primary roles in production of the asset. For example, using and analyzing data is not included in the production costs.

• The international measurement community, including BEA, focus is on own account data assets although purchased data is currently likely captured as embedded (e.g., software, databases, R&D, marketing).

• Continued research on appropriate depreciation profiles, including applying techniques we currently use for depreciating R+D (industry-specific depreciation profiles).

• Open questions include capitalization ratios (i.e., intermediate consumption vs assets). Current approach uses a 50% ratio.

• Cross country considerations have not yet been a major focus.

Impact on Accounts

10

• Capitalizing data as an asset for the year 2022 would increase GDP level by ≈1.5% and IPP investment level by ≈28%.

• Capitalizing data assets from 2003-2022 represented a real growth increase in IPP. Only software grew faster than data within IPPs.

• Average annual growth for GDP increases by about 0.04 percentage point.

Conclusion

11

• SNA 2025 will recommend treating data as a produced intangible asset

• National accounting impact of tracking data • GDP ↑ with newly recognized business investment in data assets • GDP ↑ with newly recognized government depreciation on data assets

• Data’s impact on GDP depends on the definition • Lower bound definition: data are only complex digital files that are created and used by data

specialists (About $400 billion in 2022)

  • Recording Data Assets in the U.S. National Accounts��Bob Kornfeld�Meeting of the Group of Experts on National Accounts�Geneva, Switzerland, 25-27 April 2024����
  • Overview
  • Definition of Data as an Asset
  • BEA Work on Capitalizing Data
  • Sum of Cost Approach
  • Methodology for Sum of Costs Approach
  • Nominal Investment by Industry
  • Share of data investment by occupation (1999-2022)
  • Key Issues
  • Impact on Accounts
  • Conclusion

Global Supply Chains: Current Progress and the Path Forward, United States

Languages and translations
English

Global Supply Chains: Current Progress and the Path Forward

Bob Kornfeld

Meeting of the Group of Experts on National Accounts

Geneva, Switzerland, 25-27 April 2024

BEA Input-Output Products

•Annual IO Products (1997-2022) – Sector-level detail (15 industries) – Summary-level detail (71 industries) – Benchmark detail (402 industries) – available for 2007, 2012, 2017

• IO Products Include: – Supply-use tables – Make-use tables – Total requirements and tables, domestic requirements tables

•Historical tables – 1947-1962 – 46 industries – 1963-1996 – 65 industries

4/11/2024

2

BEA Global Supply Chain Strategy

4/11/2024

3

Existing International

Trade and MNE Statistics

SUT Framework

TiVA Statistics

New BEA Survey Data,

Data Links, and Data Purchases

Complementary Supply Chain

Statistics

Data from Census and Other Sources

Why do global supply chains matter?

4/11/2024

4

Past and Current Initiatives

•Support for international Trade in Value Added (TiVA) initiatives –OECD-WTO –Asia Pacific Economic Cooperation (APEC) –North America TiVA Working Group

•Current research efforts: –Development of national TiVA statistics (in collaboration with the

National Science Foundation) –Collaboration with Statistics Canada on a US-Canada regional supply-

use table –Research on extended supply-use tables (investigating the role of

multinational corporations)

4/11/2024

5

National TiVA Statistics (initial release)

• In collaboration with the National Science Foundation (NSF), BEA released prototype National TiVA statistics in December 2021 – Relies primarily on U.S. supply and use tables – Expands the domestic requirements framework to include bilateral trade relationships – No direct use of a multi-country supply-use table

• Statistics include: – Gross Exports by Exporting Industry and Destination Region – Value Added Exports by Producing Industry and Destination Region – Domestic Value Added and Imported Content

• Industry Detail: 81 Industries

• Regional Breakout: Canada, China, Europe, Mexico, and Rest-of-World

• Period: 2007-2020 6

National TiVA Statistics (updates)

•BEA released updated prototype national TiVA statistics in March 2023 and March 2024

•Statistics expanded, starting with 2023 update: – From 81 to 138 industries – From five to seven countries/regions:

• Canada, China, Japan, Rest of Asia and Pacific, Europe, Mexico, and Rest of the World)

•2024 update reflects 2023 comprehensive update of the national accounts

•Period now available: 2017-2022 (2007-2016 soon!) • Improved presentation (enhanced user interface)

7

TiVA Highlights

TiVA Highlights (cont’d)

TiVA Highlights (cont’d)

$308 billion

TiVA Highlights (cont’d)

US-Canada Regional SUT

• Collaboration with U.S. International Trade Administration and Statistics Canada

• Develop regional SUT to go beyond national TiVA tables to examine – share of US exports and final demand that reflect third-party imports to the U.S. via

Canada (and share of Canadian exports and final demand that reflect third-party imports to Canada via the U.S.)

– share of US exports and final demand that reflect Canadian value added and vice versa.

• Relies on detailed SUTs, import and export data from U.S. and Canada

• Preliminary results expected by Spring 2024

• Part of a larger effort to move toward multi-lateral TiVA – Hoping to incorporate SUTs and trade data from other economies

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Extended Supply-Use Tables

•Relies on “bottom up” microdata approach: –merging establishment-level records from the Census Bureau’s economic

census and BEA’s company-level records of surveys of multinational enterprises (MNEs)

•Disaggregates SUTs into transactions for 1) domestic-owned MNEs, 2) foreign-owned MNEs, and 3) entirely domestic business

•Comparison between “bottom up” microdata approach and “top down” aggregate approach based on published data

•Make /supply table results expected later this year

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Collaboration with IMF Multi-Analytical Regional Input-Output (IMF-MARIO) Database

• IMF-Mario intends to provide an analytical tool and a source of harmonized granular data to better understand the inter-relationships between economies, their impact on climate change and the environment, and their economic and social development.

• Linking domestic input-output tables together in a consistent multi-regional model will help improve data consistency within and across economies.

• MARIO’s development will take advantage of already available official statistics.

• MARIO will cover the years from 1990 to 2022 and 209 economies (including all IMF members), 178 products and 144 industries, providing sufficient granularity to perform detailed analysis on themes related to climate change and the environment

• See this paper for more information 4/11/2024

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Future Plans: Increased Timeliness

• Accelerate production of quarterly Gross Output by Industry statistics to be released concurrently with the second estimate of GDP – Release at 60 days after the end of the reference period (versus current 90 days) – A prerequisite for a similar acceleration of GDP by Industry statistics

• Begin publication of quarterly supply-use tables – Unpublished tables used in production of GDP by industry statistics – Additional resources needed for methodology and system improvements and regular pre-

release review – Foundation for quarterly TiVA statistics

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Future Plans: Increased Granularity

• Expanded industry detail – Expand annual 140-industry tables to include full suite of input-output products – Produce annual 400-industry input-output products (including TiVA) – New 400-industry tables set stage for possibility of GDP by industry statistics at this level of

detail

• Expanded country detail – Expand TiVA statistics beyond the seven regions currently covered (Canada, China, Europe,

Japan, Mexico, Rest of Asia and Pacific, Rest of World)

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Future Plans: Special Projects

• Integrate the supply-use framework with the industry level production account (ILPA) – Decomposition of value added into capital and labor services – Decomposition of capital services by type of asset

• Constant-price supply-use tables – Provides a foundation for constant-price TiVA statistics

• Hybrid TiVA model – Expand regional SUT beyond US and Canada – Incorporate data from OECD-WTO TiVA database

• Begin producing separate prices for imported intermediate inputs and domestically produced intermediate inputs

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  • Global Supply Chains: �Current Progress and the Path Forward
  • BEA Input-Output Products
  • BEA Global Supply Chain Strategy
  • Why do global supply chains matter?
  • Past and Current Initiatives
  • National TiVA Statistics (initial release)
  • National TiVA Statistics (updates)
  • TiVA Highlights
  • TiVA Highlights (cont’d)
  • TiVA Highlights (cont’d)
  • TiVA Highlights (cont’d)
  • US-Canada Regional SUT
  • Extended Supply-Use Tables
  • Collaboration with IMF Multi-Analytical Regional Input-Output (IMF-MARIO) Database
  • Future Plans: Increased Timeliness
  • Future Plans: Increased Granularity
  • Future Plans: Special Projects

Do statistical ethics apply equally to all – NSOs and other official statistics producers, whether regional/international or other national statistical authorities? Andreas Georgiou (Amherst College)

Languages and translations
English

Do statistical ethics apply equally to all – NSOs and other official statistics producers, whether regional/international or other national statistical authorities?

ANDREAS V GEORGIOU , AMHERST COLLEGE, USA WORKSHOP ON ETHICS IN MODERN STATISTICAL ORGANISATIONS 26 MARCH 2024, GENEVA, SWITZERLAND CONFERENCE OF EUROPEAN STATISTICIANS

The Greek historian Herodotus relates in his Histories (c. 430 BCE): ”When Darius was king, he summoned the Greeks who were with him and asked them for what price they would eat their fathers' dead bodies. They answered that there was no price for which they would do it. Then Darius summoned those Indians who are called Callatiae, who eat their parents, and asked them (the Greeks being present and understanding through interpreters what was said) what would make them willing to burn their fathers at death. The Indians cried aloud, that he should not speak of so horrid an act.”

Loeb Classical Library

Paraphrasing Herodotus, consider the following not-so- theoretical thought experiment: “If you ask some official statistics producers to show the official statistics to the minister/governor/commissioner before publishing them, they will be appalled. If you ask some other official statistics producers to publish the official statistics without showing them to the minister/governor/commissioner, they in turn will be appalled.”

 The above thought experiment provides a valid sociological view as to whether there is today diversity in ethics of official statistics as implemented/practiced by various official statistics producers (and users and sources)

 It actually does not provide an answer as to whether there is some universal ethics of official statistics

 It also does not answer as to whether there is a point in identifying ethics of official statistics that everyone around the world ought to implement

What do we mean by ethics of official statistics?

 Ethics of official statistics are normative and applied ethics systems that are also organizational and institutional ethics how one ought to act how to apply ethics to practical problems how to act in one’s capacity as member of an

organization or institution  Ethics of official statistics concern producers, users,

and sources of official statistics

Do statistical ethics apply equally to all - to NSOs and to other official statistics producers, whether regional/international or other national statistical authorities?

This question could be approached from three angles: I. Are there global ethics of official statistics? II. Should the ethics of official statistics have

multiple and/or varying foundational objectives?

III. Can differing ethics (rules and practices) of official statistics consistently produce the same result in terms of reliability and quality of official statistics?

Where are ethics of official statistics located?

 Need to distinguish between ethics of official statistics  (A) the sought-after universal, eternal and true object of

knowledge that should guide practices at the level of the individual and of institutions in matters related to or affecting official statistics

 (B) existing supranational codifications of ethics (UNFP, European Statistics Code of Practice, African Charter on Statistics (ACS), IMF DQAF etc.)

 (C)local ethics, revealed in national laws and rules or just in practices considered legitimate within a given country, jurisdiction or institution; they must be considered locally a template of “how things are done here” - the “local statistical culture”

I. Are there global ethics of official statistics? “The central issue around which all of Western ethics has revolved can be traced to the debate between the Sophists, who claimed that goodness and justice are relative to the customs of each society—or, worse still, that they are merely a disguise for the interest of the stronger—and the Platonists, who maintained the possibility of knowledge of an objective Form of the Good.”

Britannica on Ethics

“The safest general characterization of the European philosophical tradition is that it consists of a series of footnotes to Plato.”

Alfred North Whitehead, Process and Reality

Socrates Plato Photo sources: Britannica and Science Photo Library

A Socratic/Platonic philosophical perspective on ethics of official statistics

o A— the sought-after object of knowledge of ethics that should guide practices in official statistics—exists objectively and can in principle be known with inquiry and examination

o The empirical/actual supranational codifications of ethics of official statistics (B) are efforts to approximate A

o Efforts to have B approximate A can be successful to varying degrees, but intentionally or unintentionally may not depict in all their parts the universal truth on what is ’good’ in official statistics

o Local ethics of official statistics (C), tend to be weak approximations of A and usually further away than B

Protagoras Gorgias Photo sources: Ancient Greece Reloaded and World History Encyclopedia

A Sophist philosophical perspective on ethics of official statistics

o The universal and objectively existing object of knowledge of ethics that should guide practices in official statistics (A) does not exist, is not relevant or is not knowable

o What is ethical, i.e., good, in official statistics is what is useful and expedient in a local social setting (C)

o It is not possible to ‘rank’ different local ethics of official statistics (C) or characterize them as closer or less close to something universally and objectively good; they are purely social constructs determined historically at any given instance by social circumstances

o The choice of ethics principles of official statistics (the C) is left to tradition, persuasion (thus the emphasis on rhetoric) and existing authority of the powers that be

o Supranational codifications of ethics (B) are also purely historically specific social constructs determined by the interplay of power relations at the international level. They should have built-in adaptability and ‘flexibility’ to accommodate local circumstances in their application across countries/jurisdictions/institutions

I. Are there global ethics of official statistics?

 If one sees validity in the Socratic/Platonic (or the Kantian or, to some extent, a universalist Consequentialist) philosophical approach of ethics then the true universal/global ethics of official statistics exist objectively and must be approximated as closely as possible and applied to all the same way

 If one sees validity in the Sophist (or a modern Relativist or a narrow Consequentialist) philosophical approach of ethics, then universal/global ethics of official statistics do not exist (or are unknowable) and there are only local ethics that are just unrankable “conversations” of ethics. No uniform ethics of official statistics can and should apply to all. Different statistical producers can and should be subject to ethics adapted to their specificities

II. Should the ethics of official statistics have multiple and/or varying foundational objectives?

Ethics of official statistics as a specific field of applied ethics, always has an explicit or implicit goal, or an array of coexisting goals, around which specific ethics principles can be identified, formulated, articulated and organized: a “foundational objective of ethics” or an array of them

II. Should the ethics of official statistics have multiple and/or varying foundational objectives?

Unique universalist foundational objective  solely the production of internationally (globally) comparable statistics as a global

public good that helps provide as accurate a picture of reality as possible given current scientific developments and their embodiment (ideally) in international compilation standards and conventions

Or a mixture of the above and below foundational objectives  responsibility to “ensure effective implementation of [a political leader’s] political

guidelines”  serving “the national interest”  serving “the planning operations of the state”  ensuring “loyalty between political supervisors and official statisticians”  promoting “the progress of socialist modernization”  “retaining of the [religious] code as a priority”  “obligation to co-operate mutually with other [government] services”  Etc.

II. Should the ethics of official statistics have multiple and/or varying foundational objectives?

If one supports a unique, universalist foundational objective (such as the one above), ethics of official statistics should be unique and should apply to all with no adaptation to ‘local specificities’

If one supports alternative or additional foundational objectives, local ethics (tailored to a statistical producer’s circumstances) are appropriate and desirable and any supranational codifications of ethics should be basically permissive and flexibly interpreted

Conflicts of interest?

III. Can differing ethics (rules and practices) of official statistics consistently produce the same result in terms of reliability and quality of official statistics?

Potentially differing ethics rules and practices (examples) Recruitment procedures of head of statistical producer Dismissal/transfer procedures of head of statistical producer Responsibilities of head in the statistical producer/production Responsibilities of head beyond the statistical producer/production Existence of prerelease access to statistical releases Existence of clearance of statistical releases Institutional independence/dependence of statistical producer:

part of policy body part of policy implementation hierarchical subordination to policy side financial management dependence on policy side administrative/HR dependence on policy side etc.

III. Can differing ethics (rules and practices) of official statistics consistently produce the same result in terms of reliability and quality of official statistics?

For example:  Some would accept the following ethics rules and practices for heads of

NSOs:  procedures for recruitment ought to involve open competition and

transparency and be based on clear professional criteria, among which the major ones should be statistical reputation and a high level of competence in statistical matters

 dismissals of heads or their transfer to other positions ought to be made in a transparent manner and for reasons that do not compromise their professional independence

 But would not accept the above ethics rules and practices for:  the heads of regional or international statistical producers  the heads of other national authorities (other than NSOs) that are producers

of official statistics and are part of non-statistical (policy) institutions

III. Can differing ethics (rules and practices) of official statistics consistently produce the same result in terms of reliability and quality of official statistics? If one is of the view that different ethics rules and practices cannot consistently produce the same quality and reliability in official statistics, then ethics of official statistics should be unique and should apply to all with no adaptation to ‘local specificities’ => same ethics rules and practices for all official statistics producers

If one is of the view that different ethics rules and practices can consistently produce the same quality and reliability in official statistics, ‘local’ ethics are appropriate and desirable and any supranational codifications of ethics should be basically permissive and flexibly interpreted => different ethics rules and practices for different official statistics producers

Do statistical ethics apply equally to all - to NSOs and to other official statistics producers, whether regional/international or other national statistical authorities?

This question was approached from three angles: I. Are there global ethics of official statistics? II. Should the ethics of official statistics have multiple and/or varying

foundational objectives? III. Can differing ethics (rules and practices) of official statistics

consistently produce the same result in terms of reliability and quality of official statistics?

In the view of this author: ethics of official statistics apply equally to all

Thank you

  • Do statistical ethics apply equally to all –�NSOs and other official statistics producers, whether regional/international or other national statistical authorities?�
  • Slide Number 2
  • Slide Number 3
  • Slide Number 4
  • What do we mean by ethics of official statistics? �
  • Do statistical ethics apply equally to all - to NSOs and to other official statistics producers, whether regional/international or other national statistical authorities?�
  • Where are ethics of official statistics located? �
  • I. Are there global ethics of official statistics?�
  • Slide Number 9
  • A Socratic/Platonic philosophical perspective on ethics of official statistics
  • Slide Number 11
  • A Sophist philosophical perspective on ethics of official statistics
  • I. Are there global ethics of official statistics?�
  • II. Should the ethics of official statistics have multiple and/or varying foundational objectives?
  • II. Should the ethics of official statistics have multiple and/or varying foundational objectives?
  • II. Should the ethics of official statistics have multiple and/or varying foundational objectives?
  • III. Can differing ethics (rules and practices) of official statistics consistently produce the same result in terms of reliability and quality of official statistics? �
  • III. Can differing ethics (rules and practices) of official statistics consistently produce the same result in terms of reliability and quality of official statistics?
  • III. Can differing ethics (rules and practices) of official statistics consistently produce the same result in terms of reliability and quality of official statistics?
  • Do statistical ethics apply equally to all - to NSOs and to other official statistics producers, whether regional/international or other national statistical authorities?�
  • Slide Number 21

S3b_5_Hass-UNECE-OECD-CC Expenditure Definition-v3

Languages and translations
English

Climate Change Mitigation and Adaptation Expenditures in the Economy: Towards an Operational Definition

2024 OECD-UNECE SEEA Implementation Geneva, Switzerland

March 18-20, 2024

Julie L. Hass and Scott Wentland

Disclaimer: The opinions are those of the authors and do not necessarily reflect the official position of the Bureau of Economics Analysis, Department of Commerce, or United States Government.

Thematic accounts / “Special Topics”

• Thematic Accounts • “These supplementary statistics

allow in-depth analysis of special topics that aren’t easily seen within BEA’s core statistics… provide a deeper understanding of the U.S. economy.”

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2https://www.bea.gov/data/special-topics

Digital Economy

Small Business

Space Economy

Thematic accounts

• Primarily developed based on expert inputs, data availability, often established based on policy demand for these special topics.

• Difficult to put them into relation with one another since they are built in isolation.

• No definitive guidelines for how to decide what to include or exclude. • For example: There are overlaps between BEA’s

– “Outdoor Recreation” and the “Marine Economy” accounts;

– “Outdoor Recreation” and “Travel and Tourism” accounts

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How do we develop CC Expenditure Accounts?

Two ways forward: A. Based on the established criteria

for the SEEA-CF’s Environmental Protection Expenditure (EPE) and Resource Management(RM) Accounts and broaden to CCEA

B. Thematic/Special Topic – Based on experts and without consideration to the established criteria for the SEEA-CF EPE and RM accounts

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Is there a starting point in the SEEA-CF? Yes! Have EPE on mitigation Greenhouse gases

• Example from Statistics Norway Environmental Protection Expenditure, Reduce Greenhouse gas emissions, NACE B- E36: Mining, Manufacturing, Electricity and Water supply (NOK 1 000), 2019-2022.

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2019 2020 2021 2022

Environmental current expenditure 495 377 422 339 468 038 539 021

EP ancilliary ouput 384 478 283 022 253 200 234 052

Intermediate consumption of EP services 110 899 139 317 214 838 304 969

Investments 1 231 404 2 674 927 4 626 501 1 452 526

Source: https://www.ssb.no/en/statbank/table/13062/

Is there a starting point in the SEEA-CF? Yes! Research Agenda of SEEA-CF (Annex II)

Accounts and statistics relating to the minimization of natural hazards and the effects of climate change: • “A2.19 The SEEA Central Framework limits the scope of

economic activities considered to be environmental to environmental protection and resource management activity. However, it is recognized that there are a number of other economic activities that are related to the environment which may be of particular interest for policy and analytical purposes (see sect. 4.2). A specific set of activities encompasses efforts to minimize the impact of natural hazards (such as floods, cyclones and bush fires) and efforts to mitigate, or adapt to, the effects of climate change.”

(SEEA-CF, Annex II, pages 307-308, emphases added) 3/15/2024

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Is there a starting point thematic/Special Topic Accounts? Work related to Climate Change Expenditures

• UNECE: CES CC related statistics – Indicators but no definitions

• Eurostat: EPE/RM statistics + CC statistics

– Mitigation in EPE & expanded definition of mitigation but no data

– Ongoing project to delineate CC mitigation & adaptation activities – produce EU estimates

• OECD: CC Budget Tagging – Focus on projects and policy. Definitions no

more specific than “principal objective” and descriptions of expected results

• EU: Green Budgeting – Budgetary policymaking to achieve climate

goals

• EU: Taxonomy for Sustainable Activities – Unit of analysis is ‘projects’ – Currently only Mitigation Economic Activities are

described • IADB: Government CC Spending

– Proposes both main purpose and secondary tags which have no CC intent stated but have a measurable impact or are responses to CC impacts

– Proposes classification & methodology • Austrian project: Federal Government current

costs for CC Adaptation – Budget analysis & expert interviews – Provides some figures for 2014

• IMF Data Gaps Initiative 3: Recommendation 7 – Working definitions focus on impacts, adaptation

and resilience

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See London Group Paper for more detailed information and descriptions of these studies: https://seea.un.org/sites/seea.un.org/files/measuring_climate_mitigation_and_adaptation_exp enditures_in_the_economy_-_hass_and_wentland_u.s._bureau_of_economic_analysis_bea.pdf

Climate Change Mitigation & Adaptation Expenditures

• Are there internationally agreed upon definitions of Climate Change Mitigation and Adaptation Expenditures?

• Do we know what is included/excluded?

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IMF Data Gaps Initiative 3: Recommendation 7

• Climate Change Expenditure Accounts – CCEA • Claim: ‘Consistent with SNA, SEEA-CF and GFSM’ (i.e. boundaries)

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• “Working” definition for climate change mitigation expenditure: • Climate change mitigation expenditures are expenditures aimed at making the impacts of climate change less severe by preventing or reducing the emission of greenhouse gases (GHG) into the atmosphere and enhancing sinks of greenhouse gases.

• “Working” definition for climate change adaptation expenditure: • Climate change adaptation expenditures are expenditures aimed at adapting and building resilience of human and ecological systems to the changing climate conditions, reducing vulnerability, and minimizing the negative climate change impacts.

Source: IMF Concept Note for Recommendation 7. January 2024

Note: Emphases in red have been added

SEEA-CF uses ‘primary purpose’ to define EPE/RM

• SEEA-CF 4.15 While some economic activities may be undertaken only for a single purpose, many activities are undertaken for a variety of purposes. Following general principles of classification, activities are deemed to be environmental activities only if the primary purpose of the activity is consistent with the definitions of the two types of environmental activity listed as environmental, i.e., environmental protection and resource management. In practice, the primary purpose must be attributed to particular transactions or groups of transactions as recorded in the accounts.

• Definition of Environmental Protection Expenditure (EPE)

4.12 … Environmental protection activities are those activities whose primary purpose is the prevention, reduction and elimination of pollution and other forms of degradation of the environment.

• Definition of Resource Management Expenditures (RM)

4.13 Resource management activities are those activities whose primary purpose is preserving and maintaining the stock of natural resources and hence safeguarding against depletion.

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Decision criteria – Are NOT the same! SEEA (CEA), SNA (ex. COFOG): Primary Purpose • Primary purpose – used in different

statistical classification systems such as COFOG, SEEA-CF

• Easier to determine • Can make decision criteria

for what is ‘in’ or ‘out’

IMF: Reducing impacts of climate change • Impacts

– implies causality – not known for a long time – how to determine this?

• Further analyses are needed. Estimating net impacts on climate require expertise outside of what national statistical offices typically do.

• Comparability  will this create greater scope for some NSOs to disagree? (one NSO determines a net impact as positive and another determines the same activity as negative?) Will this reduce international comparability?

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IPCC Definition of Climate Change

• Mitigation A human intervention to reduce emissions or enhance the sinks of greenhouse gases.

• Adaptation In natural systems, the process of adjustment to actual climate and its effects; human intervention may facilitate adjustment to expected climate and its effects.

In human systems, the process of adjustment to actual or expected climate and its effects, in order to moderate harm or exploit beneficial opportunities.

(Source: https://apps.ipcc.ch/glossary/)

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Mitigation expenditures – included in EPE Reduce GHG emissions • Included in CEA 1: Protection of ambient air and climate

– Expenditures for the reduction of GHG emissions (technology, process improvements, etc.)

– Includes expenditures (human interventions) for Carbon Capture & Storage • Technically these should also be included:

– Expenditures on GHG emissions tradeable permits/credits – Expenditures imposed by Carbon taxes – Technically, expenditures on offsets should be included but these are not

always reliable projects – so need to take care when including => but often are not currently included due to data collection challenges

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Mitigation: “enhance the sinks of greenhouse gases”

Currently NOT included in EPE mitigation expenditures definitions

• What does “enhance the sinks” of GHGs include? – GHG sinks: sequester or store carbon

• Resource management expenditures that improve or preserve “GHG sinks” would also be CC mitigation expenditures.

• Examples include expenditures that improve or preserve: - Forested areas - Wetlands - Mangroves - Topsoil – soil carbon - Tropical ecosystems

• These types of RM expenditures would also be CC mitigation expenditures

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Climate Change mitigation and EPE/RM expenditures

• What is new to EPE/RM when GHG reduction focus is broadened to include CC mitigation?

• Human systems – Reducing GHG emissions – Tradeable permits & carbon

taxes – GHG offsets

(carbon/biofuel credits) • Natural Systems

– Enhance natural carbon sinks

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Environmental Protection Expenditure (EPE) Resource Management Expenditures (RM) Classification of Environmental Activities (CEA) Classification of Environmental Activities (CEA)

HUMAN SYSTEMS NATURAL SYSTEMS

CEA 1: Protection of Ambient Air & Climate CEA 10-16

CEA 1 Climate Change Mitigation Activities CC Mitigation Activities include expenditures on: include expenditures on:

1) Reducing GHG emissions Enhancing natural sinks for carbon 2) Carbon Capture & Sequestration 3) Tradeable permits 4) Carbon Taxes 5) Carbon offsets

CC mitigation in human and natural systems + CC Adaptation in natural systems in relation to EPE&RM Expenditures

Environmental Protection Expenditure (EPE) Resource Management Expenditures (RM) Classification of Environmental Activities

(CEA) Classification of Environmental Activities (CEA)

HUMAN SYSTEMS

NATURAL SYSTEMS

CEA 1: Protection of Ambient Air &

Climate CEA 10-16

CEA 1 Climate Change Mitigation Activities CC Mitigation Activities include expenditures on: include expenditures on: 1) Reducing GHG emissions Enhancing natural sinks for carbon 2) Carbon Capture & Sequestration 3) Tradeable

permits

4) Carbon Taxes

Mixed CC Mitigation & Adaptation Activities 5) Carbon offsets

include expenditures on: - Increase natural systems' resiliance for dealing with changes in environmental conditions

CC Adaptation Activities include expenditures on: - Increase natural systems' resiliance for dealing with changes in environmental conditions

16

SEEA EPE&RM Expenditures as starting point for CC Expenditure Accounts

CC mitigation in human and natural systems + CC Adaptation in natural systems + CC Adaptation in Human systems

17

Environmental Protection Expenditure (EPE) Resource Management Expenditures (RM)

Classification of Environmental Activities

(CEA) Classification of Environmental Activities (CEA)

HUMAN SYSTEMS

NATURAL SYSTEMS

CEA 1: Protection of Ambient Air & Climate CEA 10-16 CEA 1 Climate Change Mitigation Activities include expenditures on: CC Mitigation Activities 1) Reducing GHG emissions include expenditures on: 2) Carbon Capture & Sequestration Enhancing natural sinks for carbon

3) Tradeable

permits

4) Carbon Taxes

5) Carbon offsets

Mixed CC Mitigation & Adaptation Activities include expenditures on: - Increase natural systems' resilience for dealing with changes in environmental conditions HUMAN SYSTEMS CC Adaptation Expenditures CC Adaptation Activities Related to human systems include expenditures on: - Increase natural systems' resilience

(NOT part of EPE/RM expenditures) for dealing with changes in environmental

conditions

Climate Change Adaptation

• In natural systems… • The process of adjustment to actual

climate and its effects; human intervention may facilitate adjustment to expected climate and its effects. (IPCC definition)  should find these “human interventions” as part of RM expenditure since it has to do with ‘natural systems’

• In human systems… • In human systems, the process of

adjustment to actual or expected climate and its effects, in order to moderate harm or exploit beneficial opportunities. (IPCC definition) most applicable human systems are outside of EPE and RM expenditures

 need to identify and define what these are

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CC Adaptation – Nature-based solutions included in RM

• “Nature-based solutions” – part of resource management expenditures & ecosystem improvement and resilience

• For example: – In Coastal areas, the planting of mangroves or

other wetland species—can reduce the threat of inundation while also providing a habitat for marine life and improving water quality.

– Climate-smart agriculture, preserving and enhancing topsoil

– Decreasing deforestation – Constructing terraces on hillsides, using

vegetation at critical points to control soil erosion, increase soil moisture, and reduce runoff.

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Human systems: Adaptation / Resilience Examples

• Example: Miami, Florida “Beyond water management strategies, Miami must also develop considerably new or reinforced zoning and building codes. Homes, commercial buildings, and urban infrastructure will bear the brunt of climate effects, and there’s a host of potential solutions…” (Source: https://slate.com/technology/2022/05/miami-climate-change-survival.html)

• “Two Florida communities prove the power of climate adaptation” Punta Gorda: after 2007 storm…updated, climate-resilient building codes. Babcock Ranch: “is a new community designed with climate resilience as an underlying principle. …Strong building codes, floodable streets, native plantings in prolific greenspaces, building outside of the floodplain, undergrounding vulnerable utilities, and providing microgrids and energy independence” (Source: https://www.geiconsultants.com/thought_leadership/power-of-climate-adaptation/)

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Primary Purpose and Baselines?

• Consider a bridge built to higher specifications due to climate change. – The “primary purpose” of the bridge is for

transportation, but should we consider the additional expenditure above and beyond the old (baseline) standards as climate change adaptation?

• The primary purpose of this additional (but not entire) expenditure is climate change related.

– Is it the baseline that matters for primary purpose? • Similarly, we consider electric cars as mitigation-related

because the baseline car (or the standard alternative) is an internal combustion engine running on fossil fuel (emitting GHGs)… But what if the electricity production is from coal fired power plants?

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SEEA-CF Environmental Expenditure Accounts

Two pathways to development…

• SEEA-CF EPE/RM Expenditure accounts can form the foundation for Climate Change Expenditure Accounts (CCEA)

• Better to have CCEA related to the SEEA Environmental Expenditure Accounts than as separate, unrelated thematic accounts – especially since we already find parts of the CC Expenditures in the established SEEA-CF EPE/RM Expenditure accounts Must use same criteria: primary purpose and not impacts.

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Next Steps

• Need to further develop criteria for determining what to include / exclude from the different topics.

• Is “primary / main purpose” a good enough criterion? How should we consider secondary purpose and/or technical aspects?

• “Impacts” of expenditures are not useable for developing expenditure statistics.

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Next steps for USA – Learning by doing

• Develop preliminary criteria for what is in and out of CC expenditures – The Eurostat study may be helpful in this work.

• See how far we can get examining the different statistics and data sources to see what could be useable. – Examine products and services in the SUT internal system – Examine the construction and/or housing cost data – Examine the relevant federal government Agency budgets

For example: FEMA (Federal Emergency Management Agency)

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Thank You!

Additional questions/comments? Julie L. Hass

[email protected] Scott Wentland

[email protected] . .

Some Definitions of CC Mitigation and Adaptation

• Intergovernmental Panel on Climate Change (IPCC) IPCC. 2022. Annex I: Glossary. In: P Shukla, J Skea, R Slade, et al. (eds.). Climate Change 2022: Mitigation of Climate Change.

• OECD-Development Assistance Committee (DAC) OECD DAC Rio Markers for Climate: Handbook

• Multilateral Development Banks (MDBs) MDB-IDFC 2021, Common principles for climate mitigation finance tracking, version 3; MDB-IDFC 2015, Common principles for climate change adaptation finance tracking

• International Development Finance Club (IDFC) IDFC. 2021. IDFC Green Finance Mapping Report 2021

• Climate Policy Initiative (CPI) Buchner et al., 2021. Global Landscape of Climate Finance 2021.

• Climate Bonds Initiative (CBI) CBI 2019. Climate Resilience Principles: A framework for assessing climate resilience investments

• EU Sustainable finance taxonomy EU Commission. 2020. Regulation (EU) 2020/852 of the European Parliament and of the Council of 18 June 2020 on the establishment of a framework to facilitate sustainable investment, and amending Regulation (EU) 2019/2088

3/15/2024

26Source: Table 1. of IMF Concept Note for Recommendation 7. January 2024

EPE/RM + Climate Change + Disaster Expenditures

• Putting all three concepts together show that there are areas overlapping – even though the terminology use can be different.

• Disaster preventive/adaptive activities are relevant for both natural and human systems

• Same for Disaster recovery activities • There are also Non-Climate Change

disasters in both human and natural systems

3/15/2024

27

  • Climate Change Mitigation and Adaptation Expenditures in the Economy: Towards an Operational Definition ��
  • Thematic accounts / “Special Topics”
  • Thematic accounts
  • How do we develop CC Expenditure Accounts?
  • Is there a starting point in the SEEA-CF? �Yes! è Have EPE on mitigation Greenhouse gases
  • Is there a starting point in the SEEA-CF?�Yes! è Research Agenda of SEEA-CF (Annex II)
  • Is there a starting point thematic/Special Topic Accounts?�Work related to Climate Change Expenditures
  • Climate Change Mitigation & Adaptation Expenditures
  • IMF Data Gaps Initiative 3: Recommendation 7
  • SEEA-CF uses ‘primary purpose’ to define EPE/RM
  • Decision criteria – Are NOT the same!
  • IPCC Definition of Climate Change
  • Mitigation expenditures – included in EPE
  • Mitigation: “enhance the sinks of greenhouse gases”
  • Climate Change mitigation and EPE/RM expenditures
  • CC mitigation in human and natural systems + �CC Adaptation in natural systems in relation to EPE&RM Expenditures
  • SEEA EPE&RM Expenditures as starting point for �CC Expenditure Accounts ���CC mitigation in human and natural systems + �CC Adaptation in natural systems + �CC Adaptation in Human systems
  • Climate Change Adaptation
  • CC Adaptation – Nature-based solutions included in RM
  • Human systems: Adaptation / Resilience Examples
  • Primary Purpose and Baselines?
  • SEEA-CF Environmental Expenditure Accounts
  • Next Steps
  • Next steps for USA – Learning by doing
  • Thank You!
  • Some Definitions of CC Mitigation and Adaptation
  • EPE/RM + Climate Change + Disaster Expenditures

The Federal Interagency Forum on Child and Family Statistics: a unique model of collaborative data collection and reporting among federal agencies in the United States, Traci Cook (Centers for Disease Control and Prevention, United States of America)

Languages and translations
English

UNECE Conference, Geneva Switzerland

4 March – 6 March, 2024

The Federal Interagency Forum Model &

America’s Children: Key National Indicators of

Well-Being

TRACI COOK, FORUM STAFF DIRECTOR UNITED STATES UNECE WORKGROUP ON CHILD STATISTICS REPRSENTATIVE

• Mission and Overview

• Model

• Collaboration Process

• Participating Agencies

• America’s Children

- Visuals - Domains and Data Findings

• Forum Social Media

Forum Presentation Summary

The Children’s Forum

To foster coordination, cooperation, and collaboration among Federal agencies and improve federal data

related to children and families.

Founded in 1994 by six Federal member agencies and OMB

Formally established in April

1997 through Executive Order

13045

Currently includes 23 Federal

Agencies and Departments

Mission

Overview

The Forum Model: Federal Interagency Collaboration

July 8, 2015

Memo to Heads of Federal Agencies from Office of Information and Regulatory Affairs

• Establish frameworks for identifying report domains and key indicators

Reaching Consensus

Collaboration extends beyond the science

Standard Operating Procedures

• Establish frameworks for identifying report domains and key indicators

• Establish criteria for evaluating data measures

• Establish technical report guidelines and report parameters

Guiding Principles

• Broaden the scope of the report to extend beyond the usual population

• Modify data measures to reflect changes in methodology or to address more timely and relevant topics

• Engage for agency consensus

Forum Agencies

America’s Children Key National Indicators of Well-Being, 2023

Highlights selected indicators across the following domains:

Health

Family and Social Environment

Economic Circumstances

Physical Environment and

Safety

Behavior Education

Healthcare

Demographic Background

NUMBER OF CHILDREN AGES 0-17 IN THE UNITED STATES, 1950-2022 AND PROJECTED 2023-2050

Source: U.S. Census Bureau, Population Division

Family and Social Environment

NUMBER PERCENTAGE OF CHILDREN AGES 0-17 BY PRESENCE OF PARENTS IN HOUSEHOLD, 2010-2022

Source: U.S. Census Bureau, Current Population Survey, Annual Social and Economic Supplement.

Economic Circumstances

PERCENTAGE OF CHILDREN AGES 0-17 LIVING IN POVERTY BY RACE AND HISPANIC ORIGIN, 2000-2021

Source: U.S. Census Bureau, Current Population Survey, Annual Social and Economic Supplement.

Health Care

PERCENTAGE OF CHILDREN AGES 0-17 BY HEALTH INSURANCE COVERAGE STATUS AT THE TIME OF INTERVIEW, 2011-2021

Source: National Center for Health Statistics, National Health Interview Survey.

Physical Environment and Safety

PERCENTAGE OF CHIDLREN AGES 4-11 WITH SPECIFIED BLOOD COTININE LEVELS, SELECTED YEARS 1988-1994 THROUGH 2017-MARCH 2020

Source: National Center for Health Statistics, National Health and Nutrition Examination Survey

Behavior

NUMBER PERCENTAGE OF 8TH, 10TH, AND 12TH GRADE STUDENTS WHO REPORTED SMOKING CIGARETTES DAILY IN THE PAST 30 DAYS BY GRADE, 2000-2022

Source: National Institute on Drug Abuse, Monitoring the Future Survey.

Education NUMBER PERCENTAGE OF CHILDREN AGES 3-5 WHO WERE READ TO THREE OR MORE TIMES IN THE LAST WEEK BY A FAMILY MEMBER BY

MOTHER’S EDUCATION, SELECTED YEARS 1993-2019

Source: U.S. Department of Education, National Center for Education Statistics, National Household Education Surveys Program.

Health

PERCENTAGE OF INFANTS BORN PRETERM AND PERCENTAGE OF INFANTS BORN WITH LOW BIRTHWEIGHT, 2011-2021

Source: National Center for Health Statistics, National Vital Statistics System.

Outreach

Joint Forum Innovation Workgroup

• Collaborations with Forum Agencies

• America’s Children @childstats

Social Media Staff Director

Federal Interagency Forum on Child and Family Statistics

“The 2020 edition of America’s Children in Brief focuses on differences across indicators of children’s well-being by metropolitan status.”

Access the full report at childstats.gov.

• Charter, Mission & Vision

• Current and prior year reports, special publications and project deliverables

• Up-to-date data tables for each indicator

• Information on Forum members agencies and Forum committees

Closing Thoughts

THANK YOU I look forward to staying connected with you!

+1-301-458-4082

[email protected]

Traci Cook | Forum Staff Director