## Higher Frequency Indicators for Liechtenstein

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**Canonical URL:** [Higher Frequency Indicators for Liechtenstein](https://www.imf.org/-/media/files/publications/selected-issues-papers/2025/english/sipea2025044.pdf)

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### A. Introduction
- Purpose: Compile a high-frequency indicator of growth for timely monitoring of real sector activity in Liechtenstein and as an interim step toward quarterly GDP estimates.
- Rationale:
  - The Liechtenstein Office of Statistics (OS) publishes annual GDP by economic activity in current prices with a lag of 23 months.
  - High-frequency indicators measure domestic production rather than expenditure, making them well suited for monitoring Liechtenstein’s export-oriented economy.
- Key recommendations:
  - Develop a High-Frequency Indicator of Economic Growth (HFIEG) as a less burdensome interim solution that requires only economic growth trends rather than detailed tabulations of real value of economic production.
  - Use the HFIEG as an input to GDP nowcasting exercises.
  - Complement the existing quarterly composite business cycle indicator with an HFIEG that draws more heavily on quantitative transactions data.

### B. KonSens (existing composite indicator)
- Structure:
  - KonSens is a concurrent quarterly composite business cycle indicator based on systematic aggregation of 16 indicators grouped into:
    - Quantitative measures of economic activity: goods exports, goods imports, employees, commuters, unemployed, vacancies, share prices of companies, electricity consumption, overnight stays, and new vehicle registrations.
    - Qualitative measures of business sentiment and perception: Liechtenstein economic survey (assesses general situation, plant utilization, incoming orders, and earnings on a scale of good, satisfactory, or poor).
    - Qualitative measures of consumer sentiment in Switzerland and Austria.
- Methodology:
  - Each indicator is standardized to ensure comparability.
  - Principal component analysis is used to identify underlying patterns and extract a composite score.
- Interpretation:
  - KonSens operates on a continuous scale where values indicate the state of the economy in relation to its long-term average, newly calculated each quarter.
  - Positive values indicate growth above the long-term average since 1998; negative values indicate growth below the long-term average.
  - A KonSens value above 0 is interpreted as seasonally adjusted quarterly growth above average for the period beginning in the second quarter of 1998.
  - Axes are set so that a KonSens value of 0 is aligned with the average annual growth in real GDP – 1999–2023 (2.06 percent).
- Limitations:
  - Direct quantitative comparisons cannot be made between index values at different points in time (e.g., a decline from 2 to 1 indicates slowing but not a 50 percent slowdown).
  - KonSens cannot be decomposed to determine economic conditions by activity (e.g., manufacturing versus financial services).
- Empirical note:
  - Figure 1 compares the annual average of KonSens quarterly figures with changes in GDP in constant prices and demonstrates KonSens as a strong predictor of changes in the business cycle since inception.

### C. High-Frequency Indicator of Economic Growth (HFIEG) — design characteristics
- Core characteristics (Stanger 2020b):
  - Bottom-up approach: total economic activity is an aggregation of estimates of changes in production for major activity sectors (e.g., manufacturing, trade, financial services, professional services, public administration).
  - National accounting framework: activity value-added weights consistent with annual national accounts; updates use the most recent annual national accounts.
  - Transaction-data focus: relies heavily on transaction data tied to specific economic output in Liechtenstein from a statistically representative panel of domestic producers (observed quantities and sales values), sourced from administrative tax filings such as VAT records and/or targeted surveys of large companies. Business sentiment indicators are not used.
  - Constant-dollar estimation: excludes price effects; where production values are used they are deflated with relevant price indices (likely detailed Swiss PPIs for manufacturing examples).
  - Provides growth rates allowing direct quantitative comparisons of the value of economic activity over time.
- Implementation sequencing:
  - While many countries compile monthly indicators (MIEG), a quarterly indicator is recommended as a first step for Liechtenstein.
  - Examples cited: Mongolia (monthly indicator compiled by National Statistical Office), Canada, Mexico, Argentina, Chile, Uganda.

### D. Key steps to establish an HFIEG
- Step 1 — Analyze economic structure:
  - List production activities by value-added in descending order to determine most important productive activities.
  - Table of largest activities uses preliminary 2022 national accounts compiled by OS.
- Step 2 — Identify source data for values or quantities of output:
  - Assess availability and frequency of VAT data. Current status: the Fiscal Authority provides OS with a broad indicator of changes in VAT receipts for large enterprises every six months.
  - Recommendation: Expand data sharing with the Fiscal Authority to higher frequency, expanded enterprise coverage, and mapping to NACE classification used by OS.
- Step 3 — Supplement VAT with other administrative and survey sources:
  - Monthly merchandise trade exports (reported quarterly by large Liechtenstein enterprises to the Swiss National Bank (SNB) as part of the Swiss current account survey) could be obtained regularly from SNB.
  - Expand the quarterly Liechtenstein economic survey to include quantitative data on sales, production, inventories, expenses, and services exports.
  - Use non-tax administrative records where appropriate: employment and wage data, FMA financial reports, public health authority data.
- Step 4 — Estimation approach:
  - For some activities, direct estimation of production volumes (instead of deflation of production values) may be more realistic as a first step.
  - Interim estimates based on preliminary sources or modeled estimates may be used until preferred data sources are developed.
  - Fill data gaps using interpolation/estimation as needed.
- Step 5 — Aggregation and adjustment:
  - Calculate activity-specific volume indices and aggregate to an economy-wide HFIEG.
  - Recommend Laspeyres formulation using value-added activity weights from most recently compiled annual national accounts for timely compilation.
  - Apply seasonal and calendar adjustment methods adapted from KonSens.
- Step 6 — Dissemination and product design:
  - Disseminate HFIEG by OS on a regular, pre-announced schedule.
  - While detailed volume indices for the entire NACE classification may not be feasible, provide summary sub-indices for manufacturing, financial services, and other activities.
  - Use timely constant-price growth estimates for specific activities to support faster preliminary estimates of annual real GDP, creating synergies with improving timeliness of annual constant-price GDP.

### E. Key statistics — Gross Value Added by NACE Activity (2022, nominal, Million CHF; Share; Cumulative Share)
- 28 Manufacture of machinery and equipment n.e.c. — 1359.02 — 20.01%
- 69 Legal and accounting services — 638.99 — 9.41% — 29.42%
- 45-47 Wholesale and retail trade; motor vehicle repair — 628.89 — 9.26% — 38.68%
- 64-66 Financial service activities, insurance, and related services — 533.37 — 7.85% — 46.54%
- 68 Real estate services — 461.86 — 6.80% — 53.34%
- 84 Public administration and defence; compulsory social security — 407.05 — 5.99% — 59.33%
- 31-33 Manufacture of all other products n.e.c; machinery and equipment repair — 301.74 — 4.44% — 63.78%
- 41-43 Construction — 273.84 — 4.03% — 67.81%
- 29-30 Manufacture of motor vehicles and other transport equipment — 225.13 — 3.32% — 71.13%
- 62-63 Computer programming, data processing, hosting, and related services — 207.03 — 3.05% — 74.17%
- 70 Activities of head offices and management consultancy — 201.12 — 2.96% — 77.14%
- 10-12 Manufacture of food, beverage, and tobacco products — 186.12 — 2.74% — 79.88%
- 24-25 Manufacture of basic metals and fabricated metal products — 170.32 — 2.51% — 82.38%
- 26 Manufacture of computer, electronic and optical products — 159.42 — 2.35% — 84.73%
- 77-82 Rental and leasing; business support activities n.e.c. — 145.72 — 2.15% — 86.88%
- 86 Human health activities — 117.81 — 1.73% — 88.61%
- 71 Architectural and engineering activities; technical testing and analysis — 108.71 — 1.60% — 90.21%

### F. Potential data sources for estimating real output and prices by NACE activity (selected)
- Manufacturing:
  - Potential sources to estimate change in value of production: Merchandise exports reported to the SNB, company surveys.
  - Potential source to estimate change in prices: Swiss PPIs for manufacturing.
- Construction:
  - Potential sources to estimate change in value of production: Building permits, government investment, supply of construction inputs, private investment reports of large projects, records of public tenders.
  - Potential source to estimate change in prices: Direct volume estimation (no deflation).
- Wholesale and retail trade:
  - Potential source to estimate change in value of production: Value-added tax data.
  - Potential source to estimate change in prices: Swiss CPIs.
- Financial service activities, insurance, and related services:
  - Potential sources to estimate change in value of production: Assets under management, premiums and claims for insurance, stocks of deposits and loans and interest flows for banking, FMA statistics.
  - Potential source to estimate change in prices: Direct volume estimation (no deflation).
- Real estate services:
  - Potential sources to estimate change in value of production: Employment, register of realtors, number of transactions.
  - Potential source to estimate change in prices: Direct volume estimation (no deflation).
- Non-financial services activities:
  - Potential sources to estimate change in value of production: Employment, hours worked.
  - Potential source to estimate change in prices: Direct volume estimation (no deflation).
- Public administration:
  - Potential sources to estimate change in value of production: Employment, hours worked.
  - Potential source to estimate change in prices: Direct volume estimation (no deflation).
- Human health activities:
  - Potential sources to estimate change in value of production: Use of services by type of care, usage of hospital beds.
  - Potential source to estimate change in prices: Direct volume estimation (no deflation).

*Source: IMF Selected Issues Paper SIP/2025/044, “Higher Frequency Indicators for Liechtenstein,” prepared by Andrew Baer (completed March 5, 2025).*

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_Source: https://www.imf.org/-/media/files/publications/selected-issues-papers/2025/english/sipea2025044.pdf_