El Tribunal de Garantías Constitucionales en la

Demographic and corruption perception data from the four EB surveys—EB245, 291, 325, 374—is used to evaluate the hypotheses, though the focus of this study is primarily on the 2005-2009 survey data.56 Additional economic variables are created using data from Eurostat, the EU’s primary statistical database.57 Two datasets are assembled to test the hypotheses. The first dataset (Data-1) includes economic variables—Gross Domestic Product (GDP), Gross Domestic Product per capita (GDPpc), unemployment rate, two economic sentiment indicators (Consumer Confidence Indicator (CCI), Retail Trade

Confidence Indicator (RCI)), and GDP growth rate—and 10 corruption perception variables, all obtained from the EB surveys.58

A second dataset is constructed using micro-level data from GESIS Zacat.59 GESIS data includes individual survey responses from each of the EB surveys, providing

approximately 26,000 cases for each year of analysis. This second dataset is primarily created because the quantity of case allows me to disaggregate Spanish responses from the rest of the EU member states. Thus, I am able to test H3 and H3a.

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56 _{The 2011 survey was published in February 2012, during the time of writing. Perceptions of corruption}

remained fairly steady for all EU member states. Given length and time constraints, this study primarily analyzes 2005-2009 data. 2011 data is assessed to provide additional support for H1.

57 _{Available at http://epp.eurostat.ec.europa.eu/portal/page/portal/eurostat/home/}

58_{Data-1 is used to statistically analyze perceptions of corruption based on 2011 data since micro-level data has}

not yet been made public.

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There are 10 dependent variables used in this study—perception of corruption as a major problem, national, regional, and local institutions and politicians, police, judicial, and customs services.60 The primary dependent variables are the perception of corruption as a major problem, national institutions and national politicians. Additional dependent variables are included to test the effect of scandals on corruption perceptions (H2) and to assess the changes in perceived corruption levels in law enforcement services for the Spanish case study (H3). Variables measuring trust in government institutions are also included in the analysis. Trust in national government, political parties, the justice system, the police, and parliament, are obtained from standard EB surveys conducted in the same year as the special corruption surveys.61 The trust variables are included in some of the statistical models as proxies for the effect of political corruption scandals.

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Gender, education, age and occupation are four individual-level variables typically included in social science research, as they have some of the most significant effects

individual perceptions (Mocan 2004; Rose and Mishler 2010; Cabelkova 2007). These four variables are included in Data-2.62 Several economic variables are also included in the analysis to measure the effect of national economic performance on individual perceptions of corruption. GDP and GDPpc are measured in Euros. GDP growth rate is computed as the

60 _{Specific questions are available in the EB reports at: http://zacat.gesis.org/webview/ or}

http://ec.europa.eu/public_opinion/archives/eb_special_en.htm

61 _{Trust in police is used in 2005 and 2007; this was not asked in either 2009 standard EB, so trust in the justice}

system is a proxy for all law enforcement institutions. Trust in parliament is included for the 2009 analysis as another measure of trust in politicians. A complete description of trust questions asked in the EB surveys are available on the Eurobarometer website: http://ec.europa.eu/public_opinion/archives/eb_arch_en.htm

change in the GDP from the previous to current year using a “chain-linked series”.63 Unemployment rate “represents unemployed persons as a percentage of the economically active population” and is based on the EU Labor Force Survey.64 The CCI and RCI are two of the Economic Sentiment Indicators. Answers from the Joint Harmonised EU Programme of Business and Consumer Surveys are aggregated and weighted.65

There are three dependent variables—perceptions of corruption in police, judicial, and customs services—and several independent variables—the four demographic variables and indicators for trust in institutions—are used in the analysis of the final set of hypotheses for the Spanish case study. Four demographic variables are included as well as indicators for trust in institutions. Lastly, to measure citizens’ evaluations of anti-corruption efforts in Spain, I use the question, “are there enough successful prosecutions (country) to deter public officials from the giving and taking of bribes?” Additional anti-corruption questions were added to the 2009 EB survey and are included in the final model.66

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A series of statistical tests are performed including Spearman’s Rho and Pearson’s R (bivariate) correlations and Ordinary Least Squares (OLS) regression. Bivariate correlation and linear regression are performed with the EU-27 data. Spearman’s Rho, “an index of the strength of association between the variables; it ranges from 0 (no association) to +/- 1.00 (perfect association),” is also used.67 This test assesses the relationship between ordinal

63 _{A complete description of is available at; http://epp.eurostat.ec.europa.eu/} 64 _Eurostat.

65 _Eurostat.

66 _{See Appendix for variable description.} 67 _{Healy 2007: 347.}

29

variables such as GDPpc and CPI score, when rank and order are important for the

interpretation of results. Spearman’s Rho is a preliminary statistical analysis used to test H1 and H1a. GDPpc and GDP are ranked (highest to lowest) and tested with both the CPI score and results from corruption as a major problem (EBQ1) question.

OLS regression is the key statistical test used to evaluate the remaining hypotheses. This method enables researchers to determine a dependence relationship between two (or more) variables. Regressions are performed using both datasets; the first to determine dependence relationships between economic variables and perceptions of corruption for the EU-27 and again for Spain.

To test H2, prediction equations are created from linear regression results using 2007 data. For the five member states with above average perceptions of corruption in 2009, the EB argued corruption scandals augmented these scores. To evaluate the validity of this argument and H2, I obtain prediction equations using 2007 EB data (from Data-1). 2009 scores are computed using the 2008-2009 average of the economic indicators for the five “scandal” member states.68 If the computed score does not match the reported EB score, then economic factors do not fully explain changes in perceptions of corruption; corruption

scandals can account for the additional increases in perceived corruption levels.

68 _{For certain government institutions, other variables provided a better explanation of perceptions of}