Peter van de Ven Head of National Accounts, OECD The value added of official statistics: an overview of possible methods for Monetisation CESS-conference, October 20 - 21, 2016 Session A3 Peter van de Ven Head of National Accounts, OECD

Starting point UNECE Task Force on the Value of Statistics Preliminary report discussed at the 2016 meeting of the Conference of European Statisticians More fundamental remark: further expand the report to include (im)possibilities to monetise official statistics A draft report has recently been finalised, for consultation among members of the Task Force Five different approaches described, with pros and cons

Five approaches Cost-based approach Market (equivalent) pricing Stated preference methods Revealed preference methods Impact assessments Short discussion of the first three methods, Thilo Klein will present some examples of the latter two methods Shortly address the main pros and cons of each of the methods

Cost-based approach (1) Monetary value = operational costs to produce statistics (compensation of employees, intermediate consumption and depreciation of fixed assets) Method similar to national accounts Represents the willingness to pay for statistics by the society at large Some measurement issues: Coverage of official statistics: including costs of all statistical authorities; including/excluding costs incurred by respondents, database providers and users? Treatment of one-off budgets (census, investment for improving statistics, etc.)

Cost-based approach (2) However …, this valuation does not truly represent the output value of statistics So, what’s the value added? Showing the relatively low costs (per capita, as % of GDP) Monitoring of developments of inputs over time, also allowing for comparisons with some output indicators Comparisons across countries, but … Comparisons with the monetary values derived from the other methods (returns on expenditures related to statistics)

Market (equivalent) pricing Various private companies exploit statistics commercially: CPI: Premise and Pricestats Business data: Bureau van Dijk Macro-economic statistics: CEIC and Haver Analytics General: Statista.com Use the market prices charged to monetise official statistics However … The relevant companies exploit certain commercial niches They may also provide additional services Limited to specific areas of statistics Underemphasising the use for policy and research But … it may be a useful approach for certain areas

Stated preference method Basically, asking users of statistics directly, via surveys, what they would be “willing to pay” for or “willing to accept” in return for official statistics Main advantages: Flexible and straightforward Potential to arrive at a relatively complete coverage Most widely accepted method Main disadvantages: Willingness to pay can differ substantially from what people would be willing to pay in practice Survey can be expensive and time-consuming

Revealed preference method and impact assessments Examples, see presentation by Thilo Klein Main difference between stated preference and revealed preference: instead of asking people about their willingness to pay, inferring their preferences from actual choices Main advantages: Very compelling stories Standardised methodology (advertisement method) Main disadvantages: Coverage issues: only focused on general public (advertisement method), problematic to generalise the methodology, difficult to replicate (school choice) Other factors impacting on the analysis (school choice)

Overall conclusions For reasons of coverage and ease of application, the cost-based approach, the stated preference method and the revealed preference method (advertisements) are to be preferred, Although … stated preference method may be quite expensive and time-consuming, also lacking external validation However … revealed preference method (school choice) and impact assessment are able to provide very compelling stories on the value added of statistics More experience needed, encourage countries to apply certain methods, to be put in a repository

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