Presentation on theme: "Nicholas Charron, Associate Professor Quality of Government Institute, University of Gothenburg Studying and Measuring Governance within and across EU."— Presentation transcript:
Nicholas Charron, Associate Professor Quality of Government Institute, University of Gothenburg Studying and Measuring Governance within and across EU countries.
Brief Description of QoG Institute Founded by Rothstein & Holmberg 2004, funded by sevral large research grants Ca. 30 full time researchers Leader of ANTICORP project, sponsered by EU Commission Gathered all freely available QoG indicators & correlates into a user-friendly dataset. Created 2 original QoG-data sources: 1.Expert survey on bureaucracies 2.Sub-national data, measuring QoG in ca EU NUTS 1 and 2 regions (European Quality of Government Index – ’EQI’)
Publications on the sub-national data Article: Charron, Nicholas, Lewis Dijkstra & Victor Lapuente (2013): Regional Governance Matters: Quality of Government within European Union Member States, Regional Studies, Link: DOI: / Book: ’Quality of Government and Corruption from a European Perspective’ eds. Charron, Nicholas, Victor Lapuente and Bo Rothstein Edward Elgar Publishing EU Commission Working Paper: ‘Charron, Nicholas, Lewis Dijkstra & Victor Lapuente ’Regional Govrnance Matters: A Study on Regional Variation of Quality of Government in the EU Link: ork/2012_02_governance.pdf ork/2012_02_governance.pdf
Governance & corruption in Europe Not just a problem for ’developing countries’ "The links between corruption and the ongoing financial and fiscal crisis in these countries can no longer be ignored,“ (Finn Heinrich, TI, 2012) “Corruption in Greece Continues Virtually Unchecked” (Der Spiegel, 2012) The European Commission has described corruption as a “disease that destroys a country from within” and that “Greece, Italy, Portugal and Spain – the euro zone’s most financially troubled nations – have deeply rooted problems in their public administration, namely that officials are not accountable for their actions” (Irish Times, 2012)
Measuring QoG in EU Ex. corruption Lots of indicators: 1.CPI 2.WGI 3.ICRG 4.Freedom House 5.Eurobarometer & more… ’cluster analysis shows 5 groups’..
What about below the country level? Inspired by several TI surveys in India, Mexico, etc.. EU is a community of regions (ERDF, REGIO, structural funds, etc.), but no assessment of regional QoG.. Regional difference in development wider than states at times: Ex unemployment rates from Eurostat: IT: Bolzano (2.7%) vs. Sicilia (14.7%) ES: Pais Vasco (10.5%) vs. Andalucia(28%) BE: Flanders (5.1%) vs. Wallonne (11.5%) SK: Bratislava Kraj (6.2%) vs. Východné Slovensko (18.5%) Country ex.: Denmark (7.4%) vs. Bulgaria (10.4%) **So we need to measure QoG at regional level as well..
The EQI Almost all existing corruption/ QoG data (from the mid- 1990s) on national-level We present 1st (and only) mulit-country, sub national data on QoG to date. Funded by EU Commission (REGIO) We created a QoG Composite Index for 172 E.U. regions The study is based on a citizen-survey of respondents in EU 34k respondents in 18 countries (+/- 200 per region). ’consumers’ of QoG. Next round (75k respondents – 400 in each for 210 regions) to be published QoG-focused (all translated into country languages) questions on: –personal experiences & perceptions – Key concepts : Quality, Corruption & Impartiality… –On 3 relevant ’sub-nat.’ public sector services: Education, Health care, and Law Enforcement – Always a trade-off: citizens vs. experts, public vs private sector; hard data at sub-nat level?
Building the Index 1. Aggregation Aggregate respondents by region for each of 16 questions Using PCA, 3 groups (’pillars’) identified: corruption, impartialtiy and quality – 16 indicators aggreated to 3 pillars, arithmetic method due to high internal correlation 3 pillars aggregated to Regional QoG Index 2. Normalization of Data Standardized indicators (z-distribution) 3. Weights Equal Weighting
Regional and National QoG Combine regional data with national level WGI data Set each country’s EQI mean to WGI average of 4 QoG pillars Aggregate regional scores (population weighted), around which regional scores show within-country variation Why? Regional QoG embedded in National Context Include countries with no NUTS 2 regions Can retroactively adjust when new regions/countries added in future
The EQI A composite index based on 16 QoG survey questions from Round 2 happening now
Robustness of Data Extensive sensitivity testing (both WGI data and regional data), data very robust.. Alternative aggregation, weighting, normalization method, exluding certain individual charactoristics by gender, income, education and age. Constructed 95% confidence intervals around each regional estimate
Within country variation
Corruption Pillar of the EQI We combine perceptions and experiences of citizens (as opposed to ’experts’ – less risk of ’feedback loop’) Two types of questions: A.general perceptions questions (0-10, higher = less perceived corruption) B.Experiences with ’petty corruption’ *Let’s look at the aggregated regional scores
13. “Corruption is prevalent in my area’s local public school system” (0-10), higher=less corr.
14. “Corruption is prevalent in the public health care system in my area”
15. “Corruption is prevalent in the police force/ law enforcement in my area”
16. ‘In your opinion, how often do you think other citizens in your area use bribery to obtain public services?’
Cont. B. Direct experience with corruption: 17. ‘In the past 12 months have you or anyone living in your household paid a bribe in any form to: a.Education services?(yes/no) b.Health or medical services? (yes/no) c.Police? (yes/no)’
Some results: Regional level
Results from corruption in health care question
Perception vs. Experience: country & regional level
Who pays bribes? Individual level citizen comparisons In Developing World -Sector(s): law/poice, electricity Individual traits: -education: low -income: low -area: rural -gender: mixed findings -minority groups **bribes a a tax on the poor In EU: NMS, S. Europe -Sector: health care Individual traits (NMS): -education: high -income: higher -area: urban, -gender: male -age: no factor **bribes are a way for the privliged to get around ’red tape’?
Conclusions QoG not just a problem of developing world, EU is also plagued with problems 1st attempt to map-out at sub-national level regions based on a survey 34,000 citizens (perceptions & experiences). 75,000 next round in Go beyond ’hunches’ about regional differences and attemt to scientifically map them out & identify problem areas of regional public sec. Regional differences can be larger than national ones – assigning certain countries ’1 number’ is not realistic... Italy, Beligum, Spain, Romania for ex..
Seminar questions Question 3 : How can methodologies be innovatively designed to capture data on poorly reported governance phenomena such as corruption, transparency, fairness, and meritocracy? Challenge similar to any measuring any abstract concept – ‘democracy’, ‘human rights’, ‘gender equality’ Combine subjective data (follows de facto?) on different levels to avoid ‘feedback’ (experts, citizens, firms) with de jure (hard) data Begin to make distinctions between ‘need/greed’ corruption? Public sector recruitment – degree of patrimonial/political appointments? Tax collection.. Use data as initial ‘road map/starting point’ – for ex. In EU Commission REGIO report, we underwent 10 case studies in extreme EU NUTS regions for further investigation
Seminar questions Question 5: What challenges have you faced in your own work that bears on the broader issue of de facto measurement? 1.Sample issues – who are ’experts’ & how to get them to respond? If collecting ’general public perceptions’, costs of original data collection 2. Getting at ’internal mechanisms’ of the bureacracy, not just outcomes with de facto measures & perceptions (as opposed to de jure, which can also be really misleading...). -ok, so public sec. Is perceived to be impartial or corrupt, but why? Which sectors (health, law, customs, etc.)? 3. Extensive debate, but simply how much ’economic performance’ are we picking up instead of QoG? 4. Explaining the data to researchers & public