Valuation data from Damodaran

• Part 1 of 4 · Source

• Part 2 of 4 · Timing

Industry and country statistics compiled from Bloomberg, Morningstar, Capital IQ and Compustat for more than 40,000 listed companies, grouped by region: US, Europe, Japan, emerging markets, China, India and global.

Full update in the first two weeks of January, with market data as at 31 December. Equity and country risk premiums are refreshed more often, typically mid-year and sometimes quarterly.

• Part 3 of 4 · Use

• Part 4 of 4 · Limits

How valuers use it

What it is not

As benchmarks and inputs: equity risk premium, country risk premium, unlevered betas, cost of capital, default spreads, margins, reinvestment and multiples, cross-checked against local market evidence.

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.

■ Damodaran data · Getting started

About the datasets

Before using any figure, understand how the data is compiled, what date it reflects and how industry statistics are built. These conventions explain most differences between Damodaran figures and those from a paid data service.

Sources, coverage and timing

Conventions and terms of use

Data sources: the datasets merge raw data from Bloomberg, Morningstar, Capital IQ and Compustat into one consolidated set covering more than 40,000 listed companies, then compute statistics with the author's own definitions. See About the data.

Own definitions: items such as invested capital, EBITDA or reinvestment are defined by the author and may differ from another service. The variable definitions page explains each variable; read it before mixing Damodaran data with other sources.

Regional files: most industry datasets come in eight versions: US, Europe, Japan, Australia/New Zealand/Canada, emerging markets, China, India and global. For an Indonesian subject, the emerging markets file is usually the closest peer group, with the global file as a cross-check.

Industry classification: companies are grouped into roughly 95 industries built by the author from Capital IQ raw data. Check that the industry label really matches the subject's business model before relying on its beta or margin.

Update calendar: a full refresh happens in early January with market data as at 31 December of the prior year. Accounting data lag: the January file uses the latest twelve months available, typically to September or October of the prior year.

Terms of use: the author states there are no strings attached and that acknowledgement is welcome but not required. Valuvix recommends citing the dataset, region and update date in every report so that the input is traceable (IVS 104 para 50.01).

Current and archived data: current files are listed on the Current data page, and earlier years on the Archived data page. Use the archive for retrospective valuation dates so that inputs match what was knowable at the date (IVS 102 para 10.04).

Disputes and policy: the author asks to be left out of legal disputes, notes that methods may change from year to year, and says the data was not built for public policy debates. In litigation work, support key inputs with additional evidence.

Example: a valuation as at 31 March 2025 should normally use the January 2025 industry files and the latest country risk update published before 31 March 2025, not the January 2026 files, even if those are available when the report is written.

Practice tip: save a copy of every file you use, with the download date, in the working papers. Damodaran overwrites files at each update, so a figure you cite today may not be retrievable from the same link next year.

■ Damodaran data · Discount rates

Equity risk premium and historical returns

The equity risk premium (ERP) is the single most influential input in a cost of equity. Damodaran publishes both a forward-looking implied ERP for the US market and long-run historical returns on US stocks, bonds and bills.

Implied ERP

Historical returns

What it is: the implied ERP backs out the premium that equates the S&P 500 index level with expected cash flows to investors (dividends and buybacks) over the next five years and a terminal value. It is forward-looking and moves with market prices.

What it is: annual returns since 1928 on US stocks, 3-month T-bills, 10-year Treasury bonds, Baa corporate bonds, real estate and gold, with arithmetic and geometric averages over several periods.

Where to find it: the annual series since 1960 is on Implied ERP (annual), with a spreadsheet download histimpl.xls. Monthly estimates are published separately on the author's site.

Where to find it: Historical returns with the spreadsheet histretSP.xls.

Mature-market base: Damodaran uses the US implied ERP as the premium for a mature market. Country risk premiums for other markets (next section) are added on top of this base.

How to use it: the historical premium (stocks minus T-bonds) is a cross-check on the implied ERP. Damodaran favours the implied figure because historical averages carry large standard errors and depend heavily on the period chosen.

Example: with an illustrative US implied ERP of 4.3% and a country risk premium for Indonesia of 2.5%, the total equity risk premium for an Indonesian operating business is about 6.8% before any size or company-specific adjustment.

Geometric or arithmetic: for multi-year discounting, geometric averages against T-bonds are generally more consistent with long-term cash flows; arithmetic averages suit one-period estimates. State the choice in the report.

Practice tip: match the ERP date to the valuation date. For a 30 June valuation, use the implied ERP closest to that date, not the January figure, especially after large market moves.

Example: if the 1928–2025 geometric premium of stocks over T-bonds is around 5% while the implied ERP is around 4.3%, a valuer can show both, explain the difference and justify the adopted figure as IVS 103 para A20.33 requires.

■ Damodaran data · Discount rates

Country risk premiums and tax rates

For businesses outside mature markets, the country risk premium (CRP) captures additional sovereign and market risk. The same file also gives default spreads and corporate tax rates by country, which feed cost of debt and after-tax cash flows.

Country risk premiums

Default spreads and tax rates

File: Country default spreads and risk premiums, download ctryprem.xlsx. Updated in January and usually mid-year.

Default spreads: the same file lists sovereign default spreads by rating. Add the country default spread to the risk-free rate when estimating a local-currency cost of debt in USD terms, along with the company's own credit spread.

Method: the CRP starts from the sovereign default spread (based on the Moody's rating, or the CDS spread where available) and scales it by the ratio of equity market volatility to bond market volatility in emerging markets.

Company credit spreads: Ratings, interest coverage and spreads maps interest coverage ratios to synthetic ratings and spreads for large and small firms, useful for unrated Indonesian companies.

Total ERP: the file shows, for each country, the rating, default spread, CRP and total equity risk premium, which is the mature-market ERP plus the CRP.

Corporate tax rates: Marginal tax rates by country draws on a KPMG survey; the author asks users to credit KPMG. Always confirm against current Indonesian law; the statutory corporate rate is 22% with specific reductions for listed and small companies.

Exposure, not domicile: Damodaran suggests weighting CRPs by where a company earns its revenue. An Indonesian exporter earning 60% of revenue in Japan and the EU carries less Indonesian country risk than a domestic retailer.

Currency consistency: Damodaran's figures are in USD terms. To build an IDR discount rate, convert using the inflation differential: (1 + USD rate) × (1 + IDR inflation) / (1 + USD inflation) − 1, rather than adding a currency premium by judgement.

Example: a Jakarta-listed coal producer selling mostly to China and India can be assigned a revenue-weighted CRP across those markets, rather than Indonesia's CRP alone, provided the weighting is documented.

Practice tip: when local market evidence exists, such as the yield on Indonesian government bonds in IDR, reconcile it with the Damodaran-based build-up and explain any gap, as IVS 104 requires maximising observable inputs.

■ Damodaran data · Risk

Betas by industry

Industry betas are the standard way to estimate systematic risk for private or thinly traded companies. Damodaran publishes levered and unlevered betas, and a total beta variant for undiversified owners.

Levered and unlevered betas

Total beta and practical use

File: Levered and unlevered betas by industry, with emerging markets betaemerg.xls and global betaGlobal.xls downloads.

Total beta: Total beta by industry divides the market beta by the correlation with the market, so that it captures total rather than only systematic risk.

Columns: number of firms, average beta, market debt-to-equity, effective tax rate, unlevered beta, cash/firm value, unlevered beta corrected for cash, and the standard deviation of equity and operating income.

When to use total beta: for owner-specific contexts, such as investment value for an undiversified family owner, a small private business sale, or some tax and litigation settings. For market value of a business that diversified buyers would acquire, use the market beta.

Bottom-up approach: take the unlevered beta corrected for cash for the subject's industry, then relever it with the subject's target debt-to-equity ratio and marginal tax rate: βL = βU × (1 + (1 − t) × D/E).

Multi-business companies: weight unlevered betas by the value (or revenue) of each segment before relevering. A conglomerate with palm oil, property and logistics needs a blended beta, not one industry figure.

Why industry averages: averaging many company regression betas reduces the standard error that makes any single company's beta unreliable, especially for small Indonesian listed companies with low trading volume.

Regional choice: emerging-markets betas reflect local market correlations; global betas use a broader peer set. Show both where the subject's industry is thinly represented in the emerging-markets file.

Example: an emerging-markets unlevered beta of 0.80 for food processing, relevered at a target D/E of 40% and a 22% tax rate, gives 0.80 × (1 + 0.78 × 0.40) ≈ 1.05.

Practice tip: record the number of firms behind each beta. An industry with fewer than ten companies gives a fragile average; consider a broader industry or the global file.

■ Damodaran data · Discount rates

Cost of capital by industry

The cost of capital file brings the pieces together: cost of equity, cost of debt, weights and the resulting WACC by industry. It is best used as a benchmark against which a subject-specific WACC is tested.

What the file shows

Using it as a benchmark

File: Costs of capital by industry, with emerging markets waccemerg.xls and global waccGlobal.xls.

Cost of debt cross-check: compare the subject's actual borrowing rate with the industry pre-tax cost of debt and with the synthetic rating spread from the ratings file.

Columns: number of firms, beta, cost of equity, E/(D+E), standard deviation of stock, pre-tax cost of debt, tax rate, after-tax cost of debt, D/(D+E) and cost of capital, all in USD terms.

Capital structure: the D/(D+E) column gives market-value industry leverage, a useful target capital structure under IVS 200 when the subject's own leverage is not typical of a market participant.

Built consistently: the costs of equity use the same risk-free rate and ERP across industries, so the file shows relative risk between industries more reliably than absolute levels for a specific country.

Converting to IDR: translate the USD WACC with the inflation differential method, using consistent long-term inflation expectations for Indonesia and the US.

Regional caveat: the emerging-markets file pools many countries. An Indonesian WACC should be built from the subject's own inputs (CRP, capital structure, tax rate) and compared with the file, not copied from it.

Reconciliation: IVS 103 A20.29–A20.34 expects the discount rate method and significant inputs to be documented and supported. A table showing the build-up, the Damodaran benchmark and local evidence side by side meets this expectation well.

Example: if the file shows a USD WACC of about 9% for an industry in emerging markets and your build-up for an Indonesian peer gives 11.5% in USD terms, the 2.5-point gap should be explained, for example by Indonesia's CRP or a size premium.

Practice tip: never mix a Damodaran WACC with forecasts that already include Indonesian inflation in IDR. Currency and inflation in the rate must match the cash flows (IVS 103 A20.07).

■ Damodaran data · Cash flows

Margins, reinvestment and working capital

Forecast cash flows need sense checks. Damodaran's operating benchmarks show what margins, reinvestment and working capital look like for each industry, helping valuers test management forecasts with professional scepticism.

Profitability and reinvestment

Working capital and other items

Margins: Operating and net margins (emerging marginemerg.xls) gives gross, EBITDA, EBIT (pre- and after-tax), net and R&D-adjusted margins by industry.

Working capital: Working capital ratios (emerging wcdataemerg.xls) gives receivables, inventory and payables as a percentage of sales, and non-cash working capital to sales.

Reinvestment: Capital expenditures and sales-to-capital (emerging capexemerg.xls) reports capex, depreciation, net capex as a percentage of revenue and the sales-to-invested-capital ratio.

R&D: R&D expenditures supports capitalising R&D for technology and pharmaceutical companies, a common adjustment before computing returns on capital.

Sales-to-capital: dividing incremental revenue by this ratio gives the reinvestment needed to support growth, a disciplined way to link growth and cash flow in a DCF.

Goodwill: Goodwill and impairment shows goodwill relative to assets and impairment history by industry, useful context for purchase price allocations and impairment tests.

Example: a forecast showing an EBITDA margin of 35% for an Indonesian retailer, against an emerging-markets retail average near 10%, requires strong evidence such as a unique format or location advantage, otherwise the forecast should be challenged.

Example: for a distribution company, a non-cash working capital of 25% of sales against an industry figure near 15% may indicate slow collections or excess inventory that a buyer would expect to normalise, affecting forecast cash flows.

Practice tip: compare the subject's last three years with the industry median rather than only the mean, because a few outliers can distort averages in small industries.

Practice tip: use benchmarks to question forecasts, not to replace them. IVS 103 A20.13 requires the valuer to evaluate prospective financial information whatever its source; document why the adopted forecast is reasonable.

■ Damodaran data · Growth

Growth and return on capital

Sustainable growth depends on how much a company reinvests and how well it earns on that capital. Damodaran's growth files decompose returns and fundamental growth by industry, a useful check on terminal growth and long-term forecasts.

Returns and fundamental growth

Applying growth benchmarks

Return on equity: ROE decomposition (emerging roeemerg.xls) breaks ROE into margin, turnover and leverage for each industry.

Terminal growth ceiling: long-term nominal growth should not exceed the long-run nominal growth of the economy in the currency of the cash flows. For IDR cash flows this is linked to Indonesian GDP growth and inflation expectations.

Fundamental EBIT growth: Fundamental growth in EBIT (emerging fundgrEBemerg.xls) estimates growth as reinvestment rate × return on capital.

Return on capital convergence: competitive pressure tends to push returns towards the cost of capital over time. Industry return data help decide how far and how fast the subject's excess returns should fade.

Expected growth: the PE file (next section) also reports analysts' expected growth in earnings, a market view that can be compared with fundamental growth.

Consistency with the rate: the risk-free rate, inflation and growth must be in the same currency and nominal or real basis (IVS 103 A20.06).

Example: an industry with a return on capital of 12% and a reinvestment rate of 40% implies sustainable operating growth of about 4.8%; a forecast of 15% annual growth with the same reinvestment is internally inconsistent.

Example: an Indonesian consumer company forecast in IDR may justify terminal growth of 5–6% nominal if long-run inflation is around 3% and real growth around 2–3%, while the same business in USD terms would carry a lower nominal rate.

Practice tip: in the terminal period, set reinvestment = growth ÷ return on capital so that growth is funded. This avoids the common error of a high terminal growth rate with no matching reinvestment.

Practice tip: show terminal growth, reinvestment rate and implied return on capital together in the report so that reviewers can see the economic logic at a glance.

■ Damodaran data · Relative valuation

Multiples by industry and country

Multiples provide market evidence for the market approach and a reasonableness check for DCF results. Damodaran publishes equity and enterprise value multiples by industry and by country, together with the fundamentals that drive them.

Industry multiples

Country multiples and use

Earnings multiples: PE, PEG and expected growth (emerging peemerg.xls).

Country averages: Multiples by country (download countrystats.xls) compares PE, PBV, EV/sales and EV/EBITDA averages across countries, helpful for placing Indonesian valuations in context.

Enterprise value multiples: EV/EBIT and EV/EBITDA (emerging vebitdaemerg.xls).

Aggregate vs average: Damodaran reports aggregate multiples (total market value divided by total earnings) alongside simple averages; aggregates are less distorted by outliers. State which one is used.

Book value multiples: Price and EV to book, with ROE (emerging pbvemerg.xls), particularly relevant for banks and insurers.

Fundamentals matter: each multiples file reports the drivers (growth, margins, ROE). Adjust the multiple when the subject's fundamentals differ from the industry, rather than applying the raw average.

Revenue multiples: Price and EV to sales, with margins (emerging psemerg.xls), useful for early-stage or loss-making companies.

Not a substitute for comparables: industry averages are broad. IVS 103 A10.07 prefers closely comparable transactions or listed companies; use Damodaran multiples to test the range and explain outliers.

Example: an EV/EBITDA of 8x for an emerging-markets industry applied to an Indonesian private company's EBITDA of IDR 50 billion gives IDR 400 billion before adjustments for size, growth, marketability and control under IVS 103 A10.08.

Practice tip: check the date and the denominator (trailing or forward, before or after stock-based compensation) before comparing a Damodaran multiple with a broker's or IDX figure.

■ Damodaran data · Putting it together

Worked example: WACC for an Indonesian company

This illustrative build-up shows how the datasets combine. Figures are hypothetical and rounded; always take current values from the latest files and local market data at the valuation date.

Cost of equity

Cost of debt, WACC and IDR conversion

Step 1, risk-free rate: start from the 10-year US Treasury yield at the valuation date, say 4.2%, because Damodaran's ERP and betas are in USD terms.

Step 5, cost of debt: risk-free rate 4.2% + Indonesia default spread, say 1.8%, + company spread from the synthetic rating table, say 1.6% = 7.6% pre-tax; after 22% tax, about 5.9%.

Step 2, ERP: add the US implied ERP, say 4.3%, plus Indonesia's CRP from the country risk file, say 2.5%, for a total ERP of 6.8%.

Step 6, WACC: with weights of 71% equity and 29% debt (D/E 40%), WACC ≈ 0.71 × 11.3% + 0.29 × 5.9% ≈ 9.7% in USD terms.

Step 3, beta: take the emerging-markets unlevered beta for the subject's industry, say 0.80, and relever at the target D/E of 40% and a 22% tax rate: 1.05.

Step 7, convert to IDR: with expected long-run inflation of 3.0% in Indonesia and 2.2% in the US, IDR WACC ≈ (1.097 × 1.030 / 1.022) − 1 ≈ 10.6%.

Step 4, cost of equity: 4.2% + 1.05 × 6.8% ≈ 11.3% in USD terms, before any size or company-specific premium, which must be separately justified.

Step 8, cross-check: compare with the emerging-markets industry WACC from the cost of capital file and with returns implied by recent Indonesian transactions or listed peers, and explain any difference.

Practice tip: if a company-specific premium is added, explain the risk it captures and confirm it is not already in the forecast cash flows (IVS 103 A20.38).

Example: if a buyer's IRR on a comparable Indonesian acquisition was around 12% in IDR, the 10.6% WACC may be low for a smaller, less liquid subject, supporting a documented size or liquidity adjustment.

■ Damodaran data · Quality control

Common pitfalls when using Damodaran data

Free, well-documented data is easy to misuse. These are the issues reviewers, auditors and tax examiners most often raise when Damodaran inputs appear in a valuation report.

Input errors

Documentation and judgement

Wrong date: using a file published after the valuation date, or a January file for a late-year valuation without checking more recent risk premium updates.

Untraceable inputs: citing 'Damodaran' without the dataset, region, column and update date. IVS 104 para 50.01 requires the source and selection of significant inputs to be explained and documented.

Wrong region: applying US industry betas or margins to an Indonesian company without considering the emerging-markets or global files.

Copying the industry WACC: adopting the file's WACC without building a subject-specific rate. The file is a benchmark, not an answer.

Mixed currencies: combining USD-based ERP and betas with IDR cash flows without an inflation-differential conversion, which usually understates the discount rate.

Ignoring dispersion: relying on an average for an industry with very few firms or a high standard deviation of operating income.

Double counting: adding Indonesia's full CRP to a company whose revenue is mostly earned abroad, or adding a size premium on top of a total beta that already reflects total risk.

Over-precision: reporting a discount rate to two decimals when the inputs carry much wider uncertainty. Round and test sensitivity instead.

Example: a transfer pricing valuation for a 2023 transaction that cites a beta from the January 2025 file invites challenge, because that data was not knowable at the transaction date. The archived January 2023 file avoids the issue.

Practice tip: keep a one-page input register listing each Damodaran figure, file name, region, column, update date and the downloaded copy's location. It answers most review questions in minutes.

✱ Source and attribution

Data by Aswath Damodaran, NYU Stern

All datasets on this page are compiled and published free of charge by Professor Aswath Damodaran on Damodaran Online. Valuvix is not affiliated with him or with NYU Stern, does not reproduce his tables and links to the original files. Figures in the examples are illustrative only: always download the current or archived file that matches your valuation date, and cite the dataset, region and update date in your report.