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Social Indicators Research

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01.12.2013

Correcting for Scale Perception Bias in Measuring Corruption: an Application to Chile and Spain

verfasst von: Carmelo J. León, Jorge E. Araña, Javier de León

Erschienen in: Social Indicators Research | Ausgabe 3/2013

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Abstract

Corruption perceptions are commonly utilized as essential information to measure corruption across countries and regions. In this paper we consider the hypothesis that respondents to corruption perception questions utilize different response scales in their answers, i.e. for identical levels of corruption practices, subjects from one country could answer a different level of corruption perception than subjects from another country, based on socioeconomic characteristics. This hypothesis is investigated by utilizing the technique of anchoring vignettes with a sample of citizens in Spain and Chile. The results show that response scales are used differently across individuals in both countries, suggesting that the use of uncorrected measures of corruption perceptions could mislead some conclusions about the comparisons of the corruption levels between countries.

Vorheriger Artikel How Cognitive Interviewing can Provide Validity Evidence of the Response Processes to Scale Items

Nächster Artikel Multidimensional Wellbeing: An Index of Quality of Life in a Developing Economy

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See Mauro (1995), Tanzi and Davoodi (2001), Kauffman et al. (1999, 2000), Wei (1997), Ades and Di Tella (1997), Knack and Keefer (1995), LaPorta et al. (1999), Treisman (2000) and Idemudia et al. (2010). The World Bank has estimated that more than 10⁹ million dollars are lost each year due to corruption, which represents 5 % of the global GDP. The African Union estimates that because of corruption, the African continent loses 25 % of GDP (Podobnik et al. 2008).

Olken (2009) argues that corruption imposes a tax on private production and public services.

Empirical studies have shown that corruption reduces GDP per capita (Mauro 1995; Lambsdorff 1999; Welsch 2008) and affects a wide range of economic indicators, such as public expenditure, total investment, capital inflows and foreign direct investment, international trade and foreign aid.

Recent applications of the estimation of corruption perception indexes can be found in Song and Cheng (2011), Rose-Ackerman (2004), Sah (2007), Connolly (2007), Welsch (2008), Anderson and Heywood (2009), Fan et al. (2009), Melgar et al. (2010), Di Tella and Schargrodsky (2003), Reinikka and Svensson (2004), Fisman and Wei (2004), Yang (2004), Hsieh and Moretti (2006) and Olken (2006). For example, Song and Cheng (2011) analyze corruption at local levels, Melgar et al. (2010) study individual characteristics and macroeconomic performance indicators that shape perceptions of corruption, Reinikka and Svensson (2004) examine corruption in educational expenditures, Fisman and Wei (2004) and Yang (2004) examine corruption in international trade, Di Tella and Schargrodsky (2003) examine corruption in hospital procurement, and Olken (2006) examines theft from a government redistribution program.

Transparency International combines assessments responses from asking (1) experts residing in the country and abroad, and (2) local business leaders. The World Bank governance indicators combine surveys of companies and individuals, the assessments of risk rating agency companies, NGO´s, and a number of multilateral aid agencies and other public sector organizations.

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The full questionnaire utilized for this study is available from the authors upon request.

The institutions are the African Development Bank, the Asian Development Bank, the Bertelsmann Foundation, the Economist Intelligence Unit, Freedom House, Global Insight, Political Risk Services, World Justice Project and the World Bank. It also utilizes four sources that reflect the views of business leaders about the countries where they reside: IMD, Political and Economic Risk Consultancy, Transparency International Bribe Payers Survey and the World Economic Forum. The World Bank governance indicators combine surveys of companies and individuals, the assessments of risk rating agency companies, NGO´s, and a number of multilateral aid agencies and other public sector organizations.

Results for the other domains of corruption perception analyzed in this study (tax efficacy and public employment) were similar to those presented in this paper and are available from the authors on request. Thus, throughout this paper we focus on modeling the domain of bribing practices of corruption utilizing both non-parametric and parametric approaches. This is actually the domain that can be considered that best represents corruption practices in both Spain and Chile.

The simulated levels of corruption perception are obtained by using HOPIT parameter estimations (eg first column of Table 5) and the average values of the corresponding explanatory covariates for each country (eg proportion of females, age, income, …). The HOPIT model presented in Table 5 includes dummy variables, which allow us to account for the possibility that the impact of explanatory covariates may be different among countries. That is, when calculating the perceived corruption level for each country, the bottom sections of Table 5 (eg Chile dummy interactions) are only employed for simulating Chile’s index (since the dummy takes value 0 for Spain).

Following King et al. (2004) recommendations, the few inconsistencies in the ordinal ranking found in the data set were treated as ties. The inefficiencies in this method come from the information lost due to this ties and ranking inconsistencies.

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Titel: Correcting for Scale Perception Bias in Measuring Corruption: an Application to Chile and Spain
verfasst von: Carmelo J. León
Jorge E. Araña
Javier de León
Publikationsdatum: 01.12.2013
Verlag: Springer Netherlands
Erschienen in: Social Indicators Research / Ausgabe 3/2013
Print ISSN: 0303-8300
Elektronische ISSN: 1573-0921
DOI: https://doi.org/10.1007/s11205-012-0185-7

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