Valuation data from the OECD

• Part 1 of 4 · Source

• Part 2 of 4 · Coverage

Official statistics compiled by the OECD from national agencies and its own economic models, covering 38 member countries, accession candidates and partners such as Indonesia, China and India.

Interest rates, exchange rates, inflation, Economic Outlook projections, national accounts and PPPs, corporate tax statistics, house prices, productivity and labour costs, and patent statistics.

• Part 3 of 4 · Access

• Part 4 of 4 · Limits

How to get the data

What it is not

Browse or search, filter by country and period, view as table or chart, download CSV or Excel, or query the SDMX API. Every dataset shows its last update date.

Not a substitute for subject-specific evidence. Averages hide dispersion, classifications are the author's own, and he asks not to be drawn into legal disputes. Document every input under IVS 104.

■ OECD data · Getting started

About the OECD Data Explorer

Before relying on any OECD series, understand how the platform is organised, how often each dataset is updated and what the reuse terms require. A few minutes here prevents most citation and dating errors in valuation reports.

Navigating the platform

Terms, citation and updates

Entry point: OECD Data Explorer lets you search by keyword or browse topics such as Economy, Finance and investment, Taxation and Science, technology and innovation. Each dataset opens with an overview, metadata and the date of the last update.

Reuse terms: under the OECD Terms and Conditions, data may be extracted, downloaded, copied, adapted and shared for any purpose, including commercial use, as long as appropriate credit is given.

Selecting data: use the filters on the left to choose reference area (for example Indonesia), measure, unit and frequency, then switch between Overview, Table and Chart. The selection is encoded in the page link, so you can save it for the working papers.

Citation format: use the citation shown with the dataset, or the general form 'OECD (year), dataset name, data source, DOI or URL (accessed on date)'. This matches the traceability IVS 104 para 50.01 expects for significant inputs.

Downloading: the Download button exports the current selection or the full dataset as CSV or Excel. Keep the downloaded file and its date, because OECD series are revised as national agencies update their figures.

Third-party data: some series are partly owned by others, such as national statistical offices or data vendors. The terms make it the user's responsibility to check the metadata or source tab and obtain permission where needed.

Developer access: every dataset is also available through the OECD SDMX API, which suits valuers who refresh the same inputs regularly, for example monthly long-term interest rates for several countries.

Revisions and vintages: national accounts, prices and projections are revised. For a retrospective valuation, use the vintage available at the valuation date where possible, for example the Economic Outlook edition published before that date (IVS 102 para 10.04).

Example: for a 30 June 2026 valuation, a valuer filters the financial market dataset for Indonesia, the United States and Japan, monthly frequency, and downloads the June 2026 values with the download date recorded in the input register.

Practice tip: the Data Explorer FAQ explains filters, downloads and API keys. Bookmark the filtered view for each recurring input so that colleagues and reviewers can reproduce exactly the same selection.

■ OECD data · Discount rates

Interest rates, exchange rates and share prices

The financial market dataset gives long-term and short-term interest rates, exchange rates and share price indices by country. For valuers it is a convenient, consistent source for risk-free rates in foreign currencies and for currency conversion.

What the dataset contains

Using it in a valuation

Dataset: Financial market (Short-term economic statistics), monthly, quarterly and annual series by country.

Risk-free rates for cross-border work: when a subject earns cash flows in yen, euro or US dollars, take the matching 10-year government yield at the valuation date rather than mixing currencies.

Long-term interest rates: generally the yield on 10-year government bonds, the standard proxy for a risk-free rate in that currency. Check the metadata for each country's bond definition.

Indonesia coverage: at the time of writing, Indonesia's long-term interest rate series in this dataset ends in December 2024, while exchange rates and short-term rates continue. For IDR yields, use Bank Indonesia, the Ministry of Finance or the PHEI/IBPA yield curve, and cite them.

Short-term rates: 3-month interbank rates and immediate (call money) rates, useful for working capital financing assumptions and short-dated discounting.

Spot versus average: use the end-of-month value on or nearest the valuation date for a point estimate; use averages only when the method calls for them, and say so.

Exchange rates: nominal exchange rates against the US dollar and real effective exchange rates based on consumer prices, useful for converting foreign-currency cash flows and judging currency over- or undervaluation.

Example: a Japanese-owned Indonesian subsidiary licenses technology from its parent in yen. To value the licence in yen, the valuer uses Japan's 10-year yield at the valuation date from this dataset as the base risk-free rate, then adds the relevant risk premiums.

Share prices: national share price indices, a quick check on market movements between a comparable transaction date and the valuation date.

Practice tip: when converting a foreign-currency DCF result into IDR, use the spot exchange rate at the valuation date and document the source, rather than a budget rate supplied by management.

■ OECD data · Inflation

Consumer prices and inflation

Inflation data link nominal and real values, support currency conversion of discount rates and help index rents, costs and historical prices. The OECD provides harmonised consumer price indices and inflation contributions for members and G20 economies including Indonesia.

Datasets

Using inflation data

Consumer price indices: CPIs and HICPs (COICOP 1999), monthly, quarterly and annual, with headline and component indices by country.

Inflation differential: converting a USD discount rate into IDR uses expected inflation in both currencies. Historical CPI shows the track record; forward-looking inputs should come from projections such as the Economic Outlook or Bank Indonesia's target range.

G20 view: G20 consumer price indices, all items gives a compact comparison for Indonesia and its main trading partners.

Real versus nominal: if cash flows are in constant prices, the discount rate must be real; if they include inflation, it must be nominal (IVS 103 para A20.06). CPI data helps check that forecasts and rates are consistent.

Drivers of inflation: Contribution to year-on-year inflation shows which components, such as food, energy or housing, drive headline inflation.

Rent and cost indexation: many Indonesian leases and service contracts index payments to inflation. CPI history supports the assumed escalation in a market rent or income approach valuation.

Measures: index levels, year-on-year growth and period-on-period growth. Check the base year and whether the series is seasonally adjusted before comparing countries.

Example: an IDR forecast assumes 6% annual cost inflation while recent CPI is around 2–3%. Without a specific reason, such as wage agreements or energy prices, the gap should be challenged.

Example: to trend a 2019 equipment purchase price to 2026 when no specific price index is available, a valuer may use the CPI as a last-resort proxy, stating the limitation, since specific cost indices are preferable under IVS 300 para 90.08.

Practice tip: cite the exact series (all items, not seasonally adjusted, index or growth) and the period used. 'Inflation of 3%' without a source and period is not traceable.

■ OECD data · Projections

Economic Outlook projections

The OECD Economic Outlook, published twice a year, gives projections of GDP growth, inflation, interest rates and other macro variables for members and major partners including Indonesia. It is a credible, documented source for forecast-period assumptions.

What the Outlook provides

Using projections

Dataset: Economic Outlook (latest edition), annual and quarterly projections typically extending one to two years beyond the current year.

Forecast reasonableness: compare management's revenue growth with projected real GDP and inflation for Indonesia. Growth well above nominal GDP needs specific support such as market share gains or capacity expansion.

Key variables: real GDP growth, GDP deflator, private consumption deflator, consumer price inflation, short- and long-term interest rates, unemployment, government balance and current account.

Terminal growth: long-run nominal growth in the currency of the cash flows should not exceed the economy's long-run nominal growth. Long-term scenarios and the GDP deflator help anchor this figure.

Long-term scenarios: Economic Outlook long-term scenarios extend potential growth and related variables over several decades, useful context for terminal growth assumptions.

Inflation inputs: projected consumer price inflation for Indonesia and the United States supports the inflation-differential conversion of a USD discount rate into IDR.

Editions: each Outlook is a separate edition published around June and December. Earlier editions remain available, which matters for retrospective valuation dates.

Example: if the Outlook projects Indonesian real GDP growth near 5% and inflation near 3%, nominal growth of about 8% is a sensible upper reference for a mature domestic consumer business during the forecast period, not a floor.

Example: for a valuation at 31 December 2025, the Outlook published in early December 2025 was knowable and can support the 2026–2027 GDP and inflation assumptions; a later edition cannot.

Practice tip: cite the edition number and publication date (for example 'OECD Economic Outlook, Volume 2025 Issue 2') rather than 'OECD forecast'.

■ OECD data · Macro context

National accounts and purchasing power parities

National accounts show the size and growth of economies and sectors; purchasing power parities (PPPs) compare price levels across countries. Both support market analysis, sector benchmarking and cross-border comparisons in valuation reports.

National accounts

PPPs and exchange rates

Annual GDP: Annual GDP and components, growth rates for expenditure-side growth by country.

PPPs and exchange rates: Annual PPPs and exchange rates compares price levels across countries in one table.

Quarterly GDP: Quarterly GDP, real growth and contributions shows recent momentum and which demand components drive it.

Cross-border cost comparisons: PPPs help adjust construction or operating costs from a foreign comparable to Indonesian price levels, for example in a replacement cost estimate based on overseas equipment pricing.

Output by activity: Quarterly GDP by activity (output approach) gives value added by industry, useful for sector growth analysis.

Market size: GDP in PPP terms gives a better comparison of real market size than nominal USD figures, useful when benchmarking an Indonesian business against foreign peers.

Use in valuation: GDP and sector data support the market overview required in many reports and help judge whether a forecast is consistent with the economic environment (IVS 200 para 110.01).

Example: a foreign hotel chain's per-room operating costs are converted using PPPs to estimate what equivalent costs might be in Indonesia, as a cross-check on management's budget.

Example: valuing a cement producer, the valuer compares five-year construction value-added growth with management's volume forecast to test whether projected demand is plausible.

Practice tip: PPP-converted figures are not market exchange rates. Never use a PPP rate to translate actual cash flows; use it only for comparisons of price levels and real volumes.

■ OECD data · Taxation

Corporate tax statistics

The OECD Corporate Tax Statistics database is the most complete international source of statutory and effective corporate tax rates, withholding taxes and tax regimes. It is especially useful for cross-border valuations, intangible asset work and transfer pricing.

Rates

Regimes, rules and CbCR

Statutory rates: Corporate income tax rates gives central, sub-national and combined statutory rates, plus targeted small business rates, by country and year.

IP regimes: Intellectual property regimes lists preferential regimes such as patent boxes, relevant to the tax amortisation benefit and after-tax royalties in IVS 210 valuations.

Effective rates: Effective tax rates shows forward-looking effective marginal and average tax rates, which capture depreciation and incentives.

Interest limitation: Interest limitation rules summarises limits on interest deductibility, which affect the tax shield in WACC and capital structure assumptions.

Withholding taxes: Standard withholding tax rates and treaty-based rates cover dividends, interest and royalties, essential for cross-border royalty and dividend cash flows.

Country-by-country data: CbCR aggregate statistics show profits, taxes and employees of multinational groups by jurisdiction, useful context for transfer pricing and profit-split analysis.

Use in DCF: apply the marginal tax rate that a market participant would face to operating profits, and test whether incentives (tax holidays, super deductions) are transferable or entity-specific (IVS 102 para 30.01(d)).

Example: the statutory corporate rate in Indonesia is 22%, but a listed company meeting the free-float requirements may pay 3 percentage points less. The valuer must decide whether a typical buyer would obtain the reduction before using it.

Example: valuing a trademark owned by a Singapore company and licensed to an Indonesian user, the valuer checks Indonesia's royalty withholding tax under the Indonesia–Singapore treaty before computing after-tax royalty income.

Practice tip: confirm rates against current Indonesian law and regulations at the valuation date; OECD tables are annual snapshots and may not reflect mid-year changes.

■ OECD data · Real estate

House price and housing market indicators

OECD house price indicators compare residential price trends, rents and affordability across countries. Indonesia is not currently covered, so these series serve mainly cross-border work and context, with Bank Indonesia's residential price survey as the domestic source.

Datasets

Using housing data

House price indices: National and regional house price indices, headline for nominal and real price trends.

Market conditions: price trends between a comparable sale and the valuation date support time adjustments in the market approach (IVS 400 para 70.04), especially for cross-border portfolios.

Analytical indicators: Analytical house prices indicators include price-to-rent and price-to-income ratios, useful signals of over- or undervaluation in a housing market.

Rent growth: rent indices help support market rent growth assumptions in DCF valuations of residential investment property.

Coverage: OECD members and selected partners. Indonesia is not included at the time of writing; check the reference area list before relying on it.

Affordability limits: high price-to-income ratios may limit future price growth, a factor to consider in development appraisals under IVS 410.

Domestic alternative: for Indonesia, Bank Indonesia's Survei Harga Properti Residensial and broker research are the usual sources; cite them in the same way.

Example: for a Malaysian or Singaporean residential project financed by an Indonesian bank, OECD data (where the country is covered) or the national agency's index supports the time adjustment of older comparable sales.

Example: an Indonesian investor buying a portfolio of apartments in Australia can use OECD price-to-rent ratios to judge whether the yields assumed in the purchase price are in line with the national market.

Practice tip: national indices hide large regional differences. Use regional series where available and explain why a national trend applies to the subject's location.

■ OECD data · Economy

Productivity, labour costs and leading indicators

Productivity, unit labour costs, wages and business cycle indicators help valuers test cost assumptions and timing. They are especially useful for operating businesses, plant and machinery, and assessments of economic obsolescence.

Productivity and labour

Business cycle indicators

Productivity: Productivity growth rates shows labour and multifactor productivity growth by country.

Composite leading indicators: Composite leading indicators anticipate turning points in the business cycle about six to nine months ahead for covered countries, including major partners of Indonesia.

Unit labour costs: Productivity and unit labour costs indicates how wage growth compares with productivity, a driver of margin pressure.

Business tendency surveys: Business tendency surveys capture managers' views on production, orders and prices.

Minimum wages: Minimum wages in national currency for countries covered; Indonesian provincial minimum wages are set locally and should be taken from regional regulations.

Economic obsolescence: weak demand signals and falling capacity utilisation support external obsolescence adjustments in the cost approach (IVS 103 para A30.21, IVS 300 para 90.01).

Use in valuation: labour cost trends help test operating margin forecasts, particularly for labour-intensive industries such as garments, footwear and hospitality.

Example: a valuer assessing a Cikarang plant serving the automotive sector notes falling leading indicators in its main export markets and supports an economic obsolescence deduction with this evidence and the plant's own utilisation data.

Example: if unit labour costs in a competitor country rise faster than productivity, an Indonesian export manufacturer's relative cost position may improve, supporting a more favourable margin assumption.

Practice tip: indicators are signals, not proofs. Combine them with the subject's own orders, utilisation and pricing data before adjusting value.

■ OECD data · Intangibles

Patents and innovation statistics

Patent statistics show where and how fast technologies are developing. For intangible asset valuers they help assess technological obsolescence, remaining useful life and the competitive landscape around a patent or know-how.

Datasets

Using patent data

Patents by technology: Patents by technology covers applications by technology field, country and filing route.

Competitive landscape: patent counts by country show where competitors are active, informing licensing territory assumptions in relief-from-royalty valuations.

WIPO domains: Patents by WIPO technology domains groups patents into 35 standard technology fields for comparison.

Indonesia context: domestic filings are modest compared with major economies; much technology used in Indonesia is licensed from abroad, so foreign patent trends often matter more for local valuations.

Scope: counts are based on filings at major patent offices and the PCT route; they measure activity, not the value of individual patents.

Royalty context: technology fields with intense patenting often have more licensing activity, which can help identify comparable licences, though royalty rates themselves come from licence databases.

Use in valuation: rising filings in a field signal fast innovation and potentially shorter economic lives for existing technology (IVS 210 para 100.01).

Example: for a transfer pricing valuation of manufacturing know-how licensed to an Indonesian subsidiary, patent trends in the parent's technology field support the assessment of how quickly the know-how will become outdated.

Example: valuing a battery-chemistry patent, the valuer sees filings in the field doubling over five years and shortens the assumed economic life from 15 to 8 years, documenting the evidence.

Practice tip: pair OECD aggregate data with a patent search for the specific family, citations and remaining legal term; aggregate statistics alone cannot value a patent.

■ OECD data · Quality control

Worked example and common pitfalls

This illustrative example shows OECD data in a typical Indonesian engagement, followed by the issues reviewers most often raise. Figures are hypothetical; always use the values available at your valuation date.

Worked example: IDR discount rate

Common pitfalls

Step 1: build a USD cost of capital of, say, 9.7% using a US risk-free rate, equity risk premium, country risk premium and an industry beta.

Wrong vintage: using an Outlook edition or revised data published after the valuation date.

Step 2: from the latest Economic Outlook knowable at the valuation date, take projected consumer price inflation for Indonesia (say 3.0%) and the United States (say 2.2%).

Coverage gaps: assuming a series covers Indonesia when it does not, or when it stops early, as with the long-term interest rate series.

Step 3: convert: (1.097 × 1.030 ÷ 1.022) − 1 ≈ 10.6% IDR discount rate, consistent with IDR cash flows that include Indonesian inflation.

Currency mismatch: mixing PPP rates, real effective exchange rates and market exchange rates when converting cash flows.

Step 4: cross-check against IDR government bond yields from Bank Indonesia or the PHEI/IBPA curve, because the OECD long-term rate series for Indonesia is not current.

Untraceable citations: writing 'source: OECD' without dataset name, edition, filters and access date, which falls short of IVS 104 para 50.01.

Example: cite 'OECD (2025), OECD Economic Outlook, Volume 2025 Issue 2, OECD Data Explorer (accessed on 15 January 2026)' in the input register.

Practice tip: save the filtered Data Explorer link and the downloaded file for each input. If a reviewer asks, you can reproduce the exact figure in seconds.

✱ Source and attribution

Data by the OECD, used under its terms

All datasets on this page are published by the Organisation for Economic Co-operation and Development on the OECD Data Explorer and may be reused with credit under the OECD Terms and Conditions. Valuvix is not affiliated with the OECD and links to the original data. Figures in the examples are illustrative; always use the edition available at your valuation date and check any third-party restrictions.