## wpiea2020013-print-pdf

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---

### I. Introduction — purpose and scope
- Monitoring economic activity is essential for timely policy decision making; traditional partial indicators have become less reliable proxies given structural shifts toward services and commodity price volatility.
- The IMF Data Standards Initiatives: SDDS (and SDDS Plus) prescribes monthly production indexes intended for short-term analysis as early estimates of Quarterly GDP; the e-GDDS recommends monthly indexes.
- Focus: monthly indicators of economic growth (MIEG) — timely, comprehensive monthly measures largely based on quantitative source data and aligned with national accounts statistical framework.
- Primary uses of MIEGs:
  - Provide an up-to-date signal of the economy for policy and business-cycle analysis.
  - Support forecasts because MIEGs are disseminated ahead of more structural measures.
  - Assess effects of prior policy measures and inform budgetary programs.
  - Enable granular contribution analyses if detailed dissemination is available.

### II. MIEGs and related activity indicators — characteristics and contrasts
- Common short-term indicators and coverage:
  - CPI: reported by about 95 percent of IMF member countries.
  - Industrial Production Index (IPI): reported by about 60 percent of IMF member countries.
- MIEG distinct features:
  - Almost exclusively derived from quantitative source data.
  - Largely comply with international methodological standards (SNA).
  - Target concurrent measurement of activity rather than solely anticipating cycles.
  - Broader coverage and comparability across countries; enable contribution analysis.
- For countries with limited statistical systems: develop monthly/quarterly activity indicators for key parts of the economy as intermediate steps before comprehensive QNA; assess predictive power of forward-looking indicators.

### III. Measuring economic activity under the SNA framework — methodology and data processing
- Core methodological points:
  - MIEGs follow SNA methodology and a bottom-up approach: estimate each component (industry or expenditure component) and combine using index-type formulations.
  - Components must be in volume terms (deflated) to measure real growth.
  - Elementary indicators derived from granular source data (surveys, administrative records) are aggregated with weights derived from structural figures (national accounts, surveys, censuses).
  - Statistical procedures for gaps and quality enhancement: time series regressions, principal components, outlier detection, benchmarking.
  - Timeliness of source data is a crucial factor in selecting methods and inputs.
- Index construction specifics:
  - Convert quantities/volumes into index numbers and aggregate using weights; Laspeyres formulation recommended for simplicity and lower data dependency.
  - Weights (w) should be derived from proportions of value added of each activity to total GDP and use annual figures to avoid seasonal distortions.
  - Benchmarking aligns high-frequency indicators with lower-frequency reliable benchmarks.
  - Seasonal and calendar adjustment is integral due to significant monthly calendar effects.

### IV. IMF’s MIEG capacity development — coverage, gaps, and examples
- Coverage and gaps:
  - Most countries that report production indexes to the IMF (about 125) do so monthly, but only a small set compile and disseminate a comprehensive MIEG.
  - About 35 percent of IMF member countries do not have a high-frequency indicator of activity.
  - From the 65 percent that produce at least one high-frequency indicator, most are partial, outdated, lack timelines, or do not necessarily track GDP.
- Typical MIEG inputs:
  - Cover 12 activities (reduced ISIC Rev.4 sections).
- IMF support and activities:
  - STA CD in TA missions and training on MIEG since 2013.
  - Training delivered to more than 75 countries between 2014 and 2019.
  - In 2018 STA started the STA Data for Decisions (D4D) trust fund project including an HFI workstream aligned with MIEG objectives.
  - TA objectives: improve existing indicators, develop experimental additional indicators, compile comprehensive MIEG covering broad activity components (12 activities).
- Country examples:
  - Colombia released a comprehensive MIEG (Economic Tracking Index) for the first time in 2014.
  - Guatemala relaunched a SNA-compliant MIEG by mid-2013; the index is presented to the Central Bank board and disseminated publicly with a lag of about 30 days from the reference month.

### V. Developing a Monthly Indicator of Economic Growth — practical steps and recommendations
- Four main steps:
  1. Comprehensive stocktaking of available source data and timeliness.
  2. Assessment and selection of indicators.
  3. Compilation (index construction, weighting, benchmarking, seasonal/calendar adjustment).
  4. Dissemination (timely, accompanied by metadata and analytical notes).
- A. Stock take of source data — findings and source types:
  - Align classifications using CPC Ver.2.1 and ISIC Rev.4.
  - Distinguish direct data (consistent with target component) and related data (conceptually related).
  - Source types include monthly trade statistics, monthly surveys, administrative/tax records (VAT), monthly labor statistics, big data, IPI, retail trade, agricultural production.
  - CD data findings for low and lower-middle income countries:
    - About ¾ have access to monthly international trade statistics.
    - About ½ have access to VAT data.
    - On average, ¼ compile and disseminate other activity indicators.
    - Many countries have unused data available.
- B. Assessment and selection of indicators:
  - Ensure conceptual consistency; avoid spurious relationships.
  - MIEG is a volume indicator: elementary/component series must exclude price effects; quality changes accounted as volume effects.
  - Prefer direct quantity/volume series; when only value series exist, deflate with appropriate price indices (micro-deflation preferred).
  - Select indicators based on ability to replicate short- and long-term trends of benchmark series (quarterly/annual GDP and components).
- C. Index compilation:
  - Use Laspeyres formulation; derive weights from value-added shares.
  - Benchmark high-frequency indicators to lower-frequency reliable benchmarks.
  - Seasonal and calendar adjustment is crucial.
- D. Index dissemination:
  - Release both unadjusted and seasonally and calendar adjusted series; consider trend-cycle component and revision analysis.
  - Provide descriptive notes on main drivers if disseminating only the headline aggregate.
  - Publish sources, compilation methods, advanced publication calendar, and a consistent revision policy.
  - Timeliness: dissemination should precede quarterly GDP releases.

### VI. Conclusions — role, feasibility, and policy implications
- Monthly high-frequency activity measures are needed for macro policy (e.g., to assess inflation, output gaps, and timely activity assessment).
- Many countries compile monthly price statistics but lack monthly activity measures; central banks develop business cycle indicators as substitutes where statistical agencies lack quality HFI.
- SNA approach is broadly consistent with annual/quarterly GDP compilation; statistical agencies that compile annual and quarterly estimates are well placed to develop MIEGs, typically requiring inter-institutional collaboration.
- MIEG development depends on available source data and national accounts resources; exploiting new sources delivers broader benefits across official statistics (QNA and other HFI).
- Flexibility and ability to use multiple source data make MIEGs suitable for countries across development levels; indicators can be developed experimentally and refined.
- IMF STA will continue assistance to develop and enhance MIEGs for IMF member countries, especially low income countries.

### Appendices — inventory and examples
- Appendix 1: Available indicators by country (sample compiled and disseminated by individual countries includes Australia; Argentina (EMAE); Austria; Armenia (IEA); Bolivia (IMAEB); Brazil (IBC-Br); China (People's Republic of); Belgium; Canada (GDP); Chile (IMACEC); Colombia (ISE); Costa Rica (IMAE); Czech Republic; Denmark; Ecuador (IDEAC); Egypt (IPM); El Salvador (IMAE); France; Germany; Guatemala (IMAE); Greece; Honduras (IMAE); Hungary; India; Ireland; Israel; Italy; Japan; Korea; Mexico (IGAE); Nicaragua (IMAE); Panamá (IMAE); Paraguay (IMAEP); Uganda (MCIEA); U.K.; U.S.
- Appendix 2: Detailed data sources and indicators by type of industry — examples of sources and indicators for 12 activities including Agriculture; Manufacturing and Mining; Electricity, gas, water, and waste management; Construction; Trade, Transportation, Accommodation and food; Information and communication; Financial and insurance activities; Real estate, Professional and supporting services; Public administration and defense; Education; Human health and social work activities; Other service activities.
- Appendix 3: Availability of statistics by geographical area — Index of Industrial Production (IIP) by IMF area department (number of countries and percent):
  - MCD: 13 (40.6%)
  - AFR: 20 (45.5%)
  - APD: 18 (51.4%)
  - WHD: 22 (61.1%)
  - EUR: 40 (87%)
- Appendix 4: Other High Frequency Indicators of Activity — compilers and examples:
  - US Conference Board: Leading, coincident and lagging indicators; Leading indicator component series (9) and Coincident indicator component series (4) listed in source.
  - OECD: Composite Leading Indicators (CLI) for 33 member countries (Iceland excluded), 6 non-member economies and 8 zone aggregates.
  - IMF methodological notes: examples include Matheson (2011), Opoku-Afari and Dixit (2012), Suriname 2013 Article IV, and Eastern Africa RTAC approaches; key point — reliable cycle-tracker indicators require well-established statistical systems and robust benchmarks.

*Source: wpiea2020013-print-pdf*

### Appendix 1: Available indicators by country (to be completed) ............................................ 19

### Appendix 1: Available indicators by country (to be completed) ............................................ 19

### Appendix 1 — Available indicators by country
- Title: Appendix 1: Available indicators by country (to be completed)
- Page reference: 19

### Appendix 2: Detailed data sources and indicators by type of industry ................................... 20

### Appendix 2 — Detailed data sources and indicators by type of industry
- Title: Appendix 2: Detailed data sources and indicators by type of industry
- Page reference: 20

### Appendix 3: Availability of statistics by geographical area ................................................... 22

### Appendix 3 — Availability of statistics by geographical area
- Title: Appendix 3: Availability of statistics by geographical area
- Page reference: 22

### Appendix 4: Other High Frequency Indicators of Activity .................................................... 23

### Appendix 4 — Other High Frequency Indicators of Activity
- Title: Appendix 4: Other High Frequency Indicators of Activity
- Page reference: 23

*Source: wpiea2020013-print-pdf - Appendix 1: Available indicators by country (to be completed) ............................................ 19*

### References .............................................................................................................

### wpiea2020013-print-pdf - References

### I. Introduction — purpose and scope
- Monitoring economic activity is essential for timely policy decision making; traditional partial indicators have become less reliable proxies given structural shifts toward services and commodity price volatility.
- The IMF Data Standards Initiatives: SDDS (and SDDS Plus) prescribes monthly production indexes intended for short-term analysis as early estimates of Quarterly GDP; the e-GDDS recommends monthly indexes.
- This paper focuses on monthly indicators of economic growth (MIEG): timely, comprehensive monthly measures largely based on quantitative source data and aligned with national accounts statistical framework.
- Primary uses of MIEGs:
  - Provide an up-to-date signal of the economy for policy and business-cycle analysis.
  - Support forecasts because MIEGs are disseminated ahead of more structural measures.
  - Assess effects of prior policy measures and inform budgetary programs.
  - Enable granular contribution analyses if detailed dissemination is available.
- Paper organization: description of MIEGs and related indicators; SNA framework for activity measurement; IMF capacity development involvement; guidance on developing a MIEG; conclusions.

### II. MIEGs and related activity indicators — characteristics and contrasts
- Common short-term indicators:
  - CPI: reported by about 95 percent of IMF member countries; widely used for inflation and as GDP deflator.
  - Industrial Production Index (IPI): historically used as proxy for activity but covers a shrinking share of the economy; only about 60 percent of IMF member countries report IPI.
  - Other partial indicators: electricity production, agricultural production, retail sales.
- Business-cycle indicators: combine quantitative and qualitative inputs; can be leading, concurrent, or lagging.
- MIEG distinct features:
  - Almost exclusively derived from quantitative source data.
  - Largely comply with international methodological standards (SNA).
  - Target concurrent measurement of activity rather than solely anticipating cycles.
  - Broader coverage, comparability across countries, enabled contribution analysis.
- For countries with limited statistical systems, the recommended path: develop monthly/quarterly activity indicators for key parts of the economy as intermediate steps before comprehensive QNA; then assess predictive power of forward-looking indicators.

### III. Measuring economic activity under the SNA framework — methodology and data processing
- MIEGs follow SNA methodology and a bottom-up approach: estimate each component (industry or expenditure component) and combine using index-type formulations.
- Key methodological points:
  - Components must be in volume terms (deflated) to measure real growth.
  - Elementary indicators derived from granular source data (surveys, administrative records) are aggregated with weights derived from structural figures (national accounts, surveys, censuses).
  - Statistical procedures (time series regressions, principal components, outlier detection, benchmarking) are needed for data gaps, multiple-source reconciliation, and quality enhancement.
  - Timeliness of source data is a crucial factor in selecting methods and inputs.
- MIEGs provide basis for monthly business-cycle analysis and can be processed to obtain trend-cycle estimates useful as benchmarks for leading indicators.

### IV. IMF’s MIEG capacity development — coverage, gaps, and examples
- Coverage and gaps:
  - Most countries that report production indexes to the IMF (about 125) do so monthly, but only a small set compile and disseminate a comprehensive MIEG.
  - About 35 percent of IMF member countries do not have a high-frequency indicator of activity.
  - From the 65 percent that produce at least one high-frequency indicator, most are partial, outdated, lack timelines, or do not necessarily track GDP.
- Typical inputs to a MIEG cover 12 activities (reduced ISIC Rev.4 sections) with example source data listed (Table 2): agriculture; manufacturing and mining; electricity, gas, water, waste management; construction; trade, transportation, accommodation and food; information and communication; financial and insurance activities; real estate, professional and supporting services; public administration and defense; education; human health and social work activities; other service activities.
- IMF support:
  - STA CD in TA missions and training on MIEG since 2013.
  - Training delivered to more than 75 countries between 2014 and 2019.
  - In 2018 STA started the STA Data for Decisions (D4D) trust fund project including an HFI workstream aligned with MIEG objectives.
  - TA objectives: improve existing indicators, develop experimental additional indicators, compile comprehensive MIEG covering broad activity components (12 activities).
- Country examples:
  - Colombia released a comprehensive MIEG (Economic Tracking Index) for the first time in 2014.
  - Guatemala relaunched a SNA-compliant MIEG by mid-2013; the index is presented to the Central Bank board and disseminated publicly with a lag of about 30 days from the reference month; the updated MIEG aligns better with quarterly GDP (Chart 4 referenced).

### V. Developing a Monthly Indicator of Economic Growth — practical steps and recommendations
- Four main steps:
  1. Comprehensive stocktaking of available source data and timeliness.
  2. Assessment and selection of indicators.
  3. Compilation (index construction, weighting, benchmarking, seasonal/calendar adjustment).
  4. Dissemination (timely, accompanied by metadata and analytical notes).
- A. Stock take of source data:
  - Align classifications across statistical products using CPC Ver.2.1 and ISIC Rev.4.
  - Distinguish direct data (consistent with target component, e.g., value added, output, sales) and related data (conceptually related, e.g., employment).
  - Source types: monthly trade statistics, monthly surveys, administrative/tax records (VAT), monthly labor statistics, big data, IPI, retail trade, agricultural production.
  - CD data findings for low and lower-middle income countries:
    - About ¾ have access to monthly international trade statistics.
    - About ½ have access to VAT data.
    - On average, ¼ compile and disseminate other activity indicators.
    - Many countries have unused data available.
- B. Assessment and selection of indicators:
  - Ensure conceptual consistency between input data and target variable; avoid spurious relationships.
  - MIEG is a volume indicator: all elementary/component series must exclude price effects; quality changes accounted as volume effects.
  - Prefer direct quantity/volume series; when only value series exist, deflate with appropriate price indices (micro-deflation preferred).
  - Select indicators based on ability to replicate short- and long-term trends of benchmark series (quarterly/annual GDP and components).
- C. Index compilation:
  - Convert quantities/volumes into index numbers and aggregate using weights; Laspeyres formulation recommended for simplicity and lower data dependency (and consistency with QNA where applicable).
  - Weights (w) should be derived from proportions of value added of each activity to total GDP and use annual figures to avoid seasonal distortions.
  - Benchmarking aligns high-frequency indicators with lower-frequency reliable benchmarks to integrate short-term dynamics with long-term trends.
  - Seasonal and calendar adjustment is integral and crucial due to significant monthly calendar effects.
- D. Index dissemination:
  - Release both unadjusted and seasonally and calendar adjusted series; consider trend-cycle component and revision analysis.
  - Provide descriptive notes on main drivers if disseminating only the headline aggregate.
  - Publish sources, compilation methods, advanced publication calendar, and a consistent revision policy.
  - Timeliness: dissemination should precede quarterly GDP releases to maximize usefulness.

### VI. Conclusions — role, feasibility, and policy implications
- Monthly high-frequency activity measures are needed for macro policy (e.g., to assess inflation, output gaps, and timely activity assessment).
- Many countries compile monthly price statistics but lack monthly activity measures; central banks develop business cycle indicators as substitutes where statistical agencies lack quality HFI.
- SNA approach is broadly consistent with annual/quarterly GDP compilation; statistical agencies that compile annual and quarterly estimates are well placed to develop MIEGs, typically requiring inter-institutional collaboration.
- MIEG development depends on available source data and national accounts resources; exploiting new sources delivers broader benefits across official statistics (QNA and other HFI).
- Flexibility and ability to use multiple source data make MIEGs suitable for countries across development levels; indicators can be developed experimentally and refined.
- Experience shows MIEGs are relevant macroeconomic indicators and generate dynamic synergies with other macro statistics, driving quality improvements.
- IMF STA will continue assistance to develop and enhance MIEGs for IMF member countries, especially low income countries.

*Source: wpiea2020013-print-pdf - References*

### APPENDIX 1: AVAILABLE INDICATORS BY COUNTRY (TO BE COMPLETED)

### APPENDIX 1: AVAILABLE INDICATORS BY COUNTRY (TO BE COMPLETED)

### Centrally compiled and disseminated
- Conference Board
- OECD

### Compiled and disseminated by individual countries (sample of countries / Accounting Approach)
- Australia: Australia
- Argentina: (EMAE)
- Austria: Austria
- Armenia: (IEA)
- Bolivia: (IMAEB)
- Brazil: Brazil (IBC-Br)
- China: China (People's Republic of)
- Belgium: Belgium
- Canada: Canada (GDP)
- Chile: Chile (IMACEC)
- Colombia: Colombia (ISE)
- Costa Rica: Costa Rica (IMAE)
- Czech Republic: Czech Republic
- Denmark: Denmark
- Ecuador: Ecuador (IDEAC)
- Egypt: Egypt (IPM)
- El Salvador: El Salvador (IMAE)
- France: France
- Germany: Germany
- Guatemala: Guatemala (IMAE)
- Greece: Greece
- Honduras: Honduras (IMAE)
- Hungary: Hungary
- India: India
- Ireland: Ireland
- Israel: Israel
- Italy: Italy
- Japan: Japan
- Korea: Korea
- Mexico: Mexico (IGAE)
- Nicaragua: Nicaragua (IMAE)
- Panamá: Panamá (IMAE)
- Paraguay: Paraguay (IMAEP)
- Uganda: Uganda (MCIEA)
- U.K.: United Kingdom
- U.S.: United States

### Other listed economies (no specific indicator label in source)
- Brazil
- China (People's Republic of)
- India
- Indonesia
- Russia
- South Africa

---

### APPENDIX 2: DETAILED DATA SOURCES AND INDICATORS BY TYPE OF INDUSTRY

### Agriculture, forestry and fishing
- Sources:
  - Ministry of Agriculture
  - Farmer associations
  - Administrative records
  - Customs
- Indicators:
  - Effective sowing
  - Harvest projections
  - Product exports
  - Output of specific products
  - Related activities (sawmills, food processing industries - intermediate consumption)
  - Fishing quotas
  - Imports (specific input products)

### Manufacturing and Mining
- Sources:
  - Statistical office
  - Direct information from large enterprises
  - Business associations
- Indicators:
  - Industrial production index (IPI)
  - Specific product outputs
  - Related activities (suppliers of relevant inputs)
  - Exports

### Electricity, gas, water, and waste management
- Sources:
  - Statistical office
  - Ministry of Finance
  - Direct information from large enterprises
  - Customs
- Indicators:
  - Industrial production index (IPI)
  - Administrative records on electricity, gas and water distribution
  - Administrative record on waste collection (though government charges)

### Construction
- Sources:
  - Ministry of Finance
  - Construction chamber
  - Customs
- Indicators:
  - Building permits
  - Government investment
  - Supply of construction inputs
  - Surveys of construction works put in place
  - Imports of specific inputs
  - Private investment reports of large projects
  - Records of public tenders

### Trade, Transportation, and Accommodation and food
- Sources:
  - Ministry of Transport
  - Ministry of Truism
  - Statistical office
  - Industry associations
  - Customs
  - Commerce chamber
- Indicators:
  - Wholesale and retail trade indexes
  - Tourist arrival and usage of hotels
  - Administrative records on cargo
  - International passenger register
  - Toll records
  - Related industries

### Information and communication
- Sources:
  - Ministry of telecommunications
  - Superintendence of Banks
- Indicators:
  - Postal services records
  - Administrative records on telecommunications (phone usage, land line subscription, internet connections, cable TV subscriptions, etc)
  - Parcel service records (national and international)

### Financial and insurance activities
- Sources:
  - Central Bank
  - Superintendence of Insurance
- Indicators:
  - Loan and deposits by institution
  - Premiums, claims and maturity by type of insurance contract

### Real estate, Professional, and supporting services
- Sources:
  - Statistical office
- Indicators:
  - Employment
  - Register of realtors
  - Administrative records on changes of ownerships
  - Legal cases
  - Register of veterinaries
  - Travel and employment agencies
  - Related industries

### Public administration and defense; compulsory social security
- Sources:
  - Ministry of finance
- Indicators:
  - Wages and salaries
  - Employment by level and public entity
  - Social security contributions

### Education
- Sources:
  - Ministry of Education
- Indicators:
  - Enrolment by type of institution
  - Employment by type of institution
  - Wages and salaries

### Human health and social work activities
- Sources:
  - Ministry of health
- Indicators:
  - Use of services by type of care
  - Usage of hospital beds
  - Health insurance companies
  - Related industries
  - Register of rest-homes (licenses)
  - Direct subsidies

### Other service activities
- Sources:
  - Ministry of finance
  - Statistical office
- Indicators:
  - Employment
  - Direct subsidies (from government, private entities and from abroad)

---

### APPENDIX 3: AVAILABILITY OF STATISTICS BY GEOGRAPHICAL AREA

- Sources: IFS, UNData, DSBB.
- Indicator: Index of Industrial Production (IIP)
  - By IMF area department (number of countries and percent):
    - MCD: 13 (40.6%)
    - AFR: 20 (45.5%)
    - APD: 18 (51.4%)
    - WHD: 22 (61.1%)
    - EUR: 40 (87%)
- Indicator: Forward Looking Indicator (availability shown as Yes/No in source figures)
  - Sample Yes/No counts by region appear in source charts (values presented visually in source).

- Indicator: Production Index (availability shown as Yes/No in source figures)
  - Sample Yes/No counts by region appear in source charts (values presented visually in source).

---

### APPENDIX 4: OTHER HIGH FREQUENCY INDICATORS OF ACTIVITY

### Purpose and compilers
- Business cycle indicators compiled by domestic public or private institutions and third parties support decision making.
- The US Conference Board compiles Leading, concurrent and lagging indicators for member countries and for the Euro Area (indicators currently disseminated for 12 members and the Euro Area).
- The OECD compiles Composite Leading Indicators (CLI) as part of its Main Economic Indicators (MEI) for 33 member countries (Iceland excluded), 6 non-member economies and 8 zone aggregates.

### Examples of component series
- US Conference Board Leading indicator component series (9):
  - Average weekly hours, manufacturing
  - Average weekly initial claims for unemployment insurance
  - Manufacturers' new orders, consumer goods and materials
  - ISM new order index
  - Building permits, new private housing units
  - Stock prices, 500 common stocks
  - Leading Credit Index
  - Interest rate spread, 10-year Treasury bonds less federal funds
  - Average consumer expectations for business and economic conditions
- US Conference Board Coincident indicator component series (4):
  - Employees on nonagricultural payrolls
  - Personal income less transfer payments
  - Industrial production
  - Manufacturing and trade sales
- OECD CLI component series for the US (7):
  - Permits issued: dwellings
  - Net new orders for durable goods
  - Share prices: NYSE composite
  - Consumer sentiment indicator
  - Weekly hours of work: manufacturing
  - Purchasing managers index
  - Spread of interest rates

### IMF use and methodological notes
- The IMF uses the term "high frequency indicators" to describe a range of high frequency statistics (e.g., indicators to assess systemic financial risk; bank stress; inflation targeting).
- Fund staff have developed indicators of economic activity for surveillance, including:
  - Matheson (2011): dynamic factor model to derive indicators for 32 advanced and emerging market economies; dynamic factor models use a large number of time series to produce reliable short-term forecasts of the cycle.
  - Opoku-Afari and Dixit (2012): composite index of economic activities (modified US Conference Board methodology) to interpolate quarterly GDP for selected sub-Saharan countries.
  - Suriname 2013 Article IV Consultation: presents a "parsimonious model including credit and a proxy for global conditions" to derive a monthly indicator of GDP; notes that more complex econometric methods may be infeasible due to data constraints.
  - Eastern Africa Regional Technical Assistance Centers: developing composite indexes of economic activity based broadly on the US Conference Board methodology but emphasizing output figures as inputs.

### Key methodological point
- Deriving monthly activity composite indicators requires a comparative "true" cyclical movement; a well-established statistical system and robust benchmarks are prerequisites for reliable cycle-tracker indicators. Estimated indicators without robust benchmarks are not directly assessable and not reliable in terms of the signals they produce.

*Source: wpiea2020013-print-pdf - APPENDIX 1: AVAILABLE INDICATORS BY COUNTRY (TO BE COMPLETED), and accompanying appendices in the provided PDF content.*

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_Source: https://www.imf.org/-/media/files/publications/wp/2020/english/wpiea2020013-print-pdf.pdf_