WP3. Indicator Development

Building on the rich data collected in Work Packages 1 and 2, Work Package 3 aims to develop three different sets of indicators covering (a) transparency; (b) corruption risks; and (c) administrative quality. It will run for 18 months starting in March 2016 and is led by the Department of Sociology at the University of Cambridge where the Lead Investigator, Dr Mihály Fazekas, is based. Other contributing Consortium Members are the University of Cambridge Computer Laboratory, Hertie School of Governance, the Corruption Research Center Budapest and Università Cattolica del Sacro Cuore.

The new indicators to be developed will have to live up to stringent requirements. They will have to be:

  • specific: measuring a well-defined phenomenon and only that;
  • “objective”: based on data describing actor behaviour rather than perceptions;
  • actionable: able to guide citizens’ and governments’ actions;
  • real-time: shortly after an action takes place, the indicators will reflect it; and
  • comparable: scores are commensurate over time, within countries and cross-nationally.

The indicators will thus contribute towards increased transparency of public spending, fight against corruption, and improve public spending efficiency. They will represent a key DIGIWHIST output which will be disseminated on web portals and through a piece of software for public authorities to assess risks.

The three key documents describing the outputs of the Work Package are set out below. Development of each of the three indicator sets requires, at a minimum, a conceptual description, computer codes implementing them in our databases, and the results of validation tests.

Methods paper on fiscal transparency indicators: the proposed indicators of fiscal transparency or access to information on government spending measure the degree to which ordinary citizens can get information on government spending (i.e. direct or effective transparency) whether at a national level, at the level of individual organisations, or at the level of particular spending items such as contracts. The indicators will thus relate to individual countries, organisations and procurement tenders. As fiscal transparency is a matter of actual active access to information which, nevertheless, is defined by legal provisions, we propose de jure as well as de facto indicators with the difference between the two types of indicators pointing at implementation gaps.

Methods paper on corruption risk indicators: corruption risk indicators capture the degree of government favouritism through public procurement and represent the most novel aspect of the project as currently there is a pronounced void in the field in terms of objective, hard measures. Our approach is distinct in that we use data and text mining techniques for identifying irregular patterns which can be associated with favouritistic behaviour. Our understanding of government favouritism is also closely associated with the lack of market openness and unfair competition. The proposed indicators will allow for identifying risks of favouritism in conjunction with unfair competition and limitations on market access. By implication, the proposed indicators will also directly contribute towards improving the efficiency of the single market across Europe.

Methods paper on administrative quality indicators: administrative quality denotes the capacity of public administrations and state-owned enterprises to pursue essential public goals set out by elected leaders. One of the most elementary and universal of these goals is reliable, timely and precise account giving and record keeping as it has a crucial role to play in transparency and spending efficiency. A significant number of errors in such records implies that a public organisation is less capable of administering public procurement procedures and announcements. Using the rich datasets assembled in Work Packages 1 and 2, we will develop direct indicators of administrative quality on country and organisation levels.

Lead Researcher

Dr Mihaly Fazekas

Lead Institution

Start Date Mar 2016End Date Aug 2017