Annex B. Methodology
Objectives
This methodological annex has three key objectives: 1) to describe the sampling frame used to generate the quantitative evidence collected through the OECD-KDI questionnaire; 2) to display the weights used to construct the composite indicators on institutional and political trust; and 3)present the detailed results of the econometric analyses conducted to generate the results of this case study.
Sampling frame
The OECD-KDI survey examined perceptions of the Korean population regarding their level of trust in government institutions. As defined in the instructions accompanying the survey, the main focus was on administrative agencies of central and local government that develop and execute public policy for education, public health, security, defence, transportation and other areas that provide related public services. The survey was structured around eight different sections.1
As the questions focused primarily on administrative institutions, respondents were asked not to take into account their subjective feelings about political organisations (e.g. the National Assembly, local councils or political parties) or about the president, the prime minister, cabinet ministers, National Assembly members, local government heads, or city council members when giving their responses to the various sections of the survey, except when specifically mentioned.
In total, 3 000 citizens were surveyed from all 17 of Korea’s administrative divisions. The sample is representative of the Korean population and follows the sampling frame of the Korean census. Regarding the geographical distribution, 46.6% of respondents were from urban metropolitan areas, 43.8% from mid- and small-sized cities (suburban), and 9.5% from rural areas. The sample was gender balanced, and age distribution was as follows: 18% in their 20s, 21% in their 30s, 22% in their 40s, 18% in their 50s, and 21% 60 and above. The majority of respondents shared a household with their spouse (74%) and with their children (59 %) (multiple responses possible). The vast majority (71%) of respondents were married, while 26% were single (never married) and only 1.4% were divorced.
The survey asked respondents to state their highest level of education: 2% followed a master or a PhD, 32% had graduated from a four-year university programme, while 31% had graduated from high school and 16% from a vocational college. Almost 40% of respondents were permanent employees (with a contract for more than a year), 20% were full time homemakers, while 14% were self-employed. Around 56% of respondents reported earnings between KRW 12 million and KRW 48 million (EUR 9 000 to 36 000) a year. More than half (54%) described themselves as having no religion, 20% were Buddhist, 20% Protestants, and 7% Catholic. For political views, almost 30% considered themselves progressive, 46% neutral and 24% conservative. See Box A B.1 for the survey sample frame.
Subjects and time period
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Population: all citizens over 20 years old
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Sampling size (number of respondents): 3 000 people
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Time period: 20 January to 22 February 2016.
Sampling design and sampling
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Sampling frame: Korea Census 2010
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Sampling method: stratified random sampling
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Stratification criteria: region, gender, age
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Data collection method: face-to-face interview using a structured questionnaire
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Interviewers’ comments: no specific observations on the survey were reported except for the prolonged length of questionnaire.
Composite indicators on political and institutional trust
The objective of the research is to identify trusting patterns among different population groups and to analyse some of the key drivers of trust in government institutions. The questionnaire’s design was based on the measurement and policy framework developed by the OECD, which in turn is based on a comprehensive literature review of the main drivers of institutional trust.
An important challenge is analysing the wealth of information available in a way that is amenable to policy recommendations; in other words, to construct a robust dependent variable that could be tested against respondents’ individual characteristics; the policy drivers identified by the framework; and exogenous factors that could shape trusting patterns. A first step was to evaluate the variability among observed correlated variables and whether or not they can be synthetised into fewer underlying variables. A common data reduction methodology is factor analysis.
The OECD-KDI includes a set of perception questions about trust in several public institutions. After conducting factor analysis, two different factors were identified that captured common data patterns: Factor 1 on institutional trust, and Factor 2 on political trust or trust in the elected leadership.
After identifying variables that capture the same underlying pattern, the question was how to aggregate them into a single measure (i.e. how to weight and combine them). Based on the results of the factor analysis differentiating between two factors (i.e. political and institutional trust) a neutral solution is to mathematically calculate the weights or scoring coefficients. The scoring coefficient identifies the relative weight of each variable within the selected factor, based on the explanatory power of each variable represented by the factor loading. The larger the value of the coefficient, the more important the corresponding variable in calculating the component. Table A B.2 presents the normalised weights for each of the variables within the factor on institutional trust, derived from the mathematical approach described above. Based on these weights, a composite measure for trust in institutions was constructed at the individual level. This is the main dependent variable in our analysis.
A similar approach was followed to calculate the second factor on political trust. Table A B.3 presents the normalised weights for each of the variables within Factor 2, derived from the mathematical approach described above. Based on these weights a composite measure for trust in political institutions was constructed at the individual level.
Econometric analyses
The econometric analyses conducted as part of this case study took into account three main channels that may influence trust: 1) an individual’s characteristics, including their preferences and expectations; 2) the individual’s socio-economic characteristics; 3) the institutional environment the individual acts in (e.g. policy drivers). Both short and long-term factors, as well as micro and macro-level aspects, are thus comprehensively addressed.
At the individual level, a person’s expectations of other people’s behaviour and the future development of the economy, as well as general socio-economic and demographic characteristics, are connected with trust.
Preferences and expectations
An individual’s beliefs about how secure the future will be in terms of income and job conditions, and how accessible are opportunities for social mobility, are linked to whether government institutions afford these. People who consider themselves most at risk of future financial problems or job loss display low trust in public institutions not able to provide security (Bouckaert et al., 2002; Inglehart and Norris, 2016). In turn, a perceived lack of equality and mobility may be another source of frustration among those who do not reap the benefits of economic growth and feel left behind in increasingly unequal societies (Alesina et al, 2017). In turn, volunteering and civic engagement is positively associated with trust in government, even though the direction of causality is debated (Myong and Seo, 2015).
Socio-economic background
Individual demographic and socio-economic characteristics have been consistently found to be highly correlated with trust, including age, gender, education, income level and labour force status (Alesina and La Ferrara, 2002; Algan and Cahuc, 2013). There is a positive relationship between interpersonal and institutional trust and educational status (and to a weaker degree, income levels) (Stolle et al., 2008; Helliwell and Wang, 2010; Carl and Billari, 2014). People that are better off financially and higher educated are likely to enjoy more opportunities and channels to take part in society (e.g. through volunteering and political participation), helping to develop and maintain larger and more diverse social networks (Helliwell and Putnam, 2007; OECD, 2015b). The cognitive skills gained through education also allow for a better understanding of government functions, translating into higher trust of public institutions (Christensen and Laegreid, 2005).
Personal values
A person’s values about how society should be organised is also connected with trust in other people in that society, as well as with trust in the institutions that guard the organisational rules. For instance, religious observance is a strong correlate of social ties, and this correlation is generally observed across religious affiliations (Schoenfeld, 1978; Traunmüller, 2011). Furthermore, one’s political orientation is likely a mitigating factor when formulating judgements about public institutions: in the United States for instance, trust in government is always higher for members of the party of the sitting President (Pew, 2015).
Institutional determinants
The institutional context or the system of bodies, rules, regulation, policies procedures and processes in which people operate is crucial to foster co-operation as well as inspire trust in the institutions themselves. Both the competence of institutions to carry out their role and the values and intentions that guide government action are key components of the institutional determinants of trust (OECD, 2017; Bouckaert and Van der Walle, 2003; Nooteboom, 2007; Bouckaert, 2012).
Government competence
Government competence encompasses the ability to deliver quality public services, to respond to citizen needs and to effectively manage social, economic and political uncertainty. Trust in government institutions responds to shocks in government performance, as measured by scandals in government agencies (Keele, 2004). Moreover, citizens’ evaluations of government services they encounter regularly have been found to be quite accurate (Van Ryzin, 2007) and feed into the advocacy by the “new public management” literature for greater emphasis on improving customer service to strengthen trust (Aberbach, 2007). Nevertheless, the direction of causality between public service performance and trust is not straightforward, since existing levels of trust in institutions might also impact perceptions of quality of services received (Bouckaert and Walle, 2013).
Government values
The notion of government values revolves around norms of integrity: low corruption and high standards of accountability; openness of the policy process to citizen participation; and fair and equal treatment of all population groups.
People are less likely to trust institutions whose effectiveness is limited by corruption, and there is a robust cross-country correlation between trust in institutions and perceptions of corruption (Anderson and Tverdova, 2003; OECD, 2013). At the same time, low institutional and interpersonal trust are likely to reinforce institutions’ weakness: low institutional trust may hinder government efforts to improve integrity, and a society with weak interpersonal trust and norms of low co-operation is likely to be more tolerant of non-compliance with regulations and laws (Morris and Klesner, 2010; Aghion et al, 2010). When it comes to the connection between fairness and institutional trust, experiences of discrimination have been found to harm perceptions of trustworthiness of government actors (Wang, 2016).
Linear regression results
In order to test the relationship between trust in public institutions, its main drivers and the impact of other contextual variables, the study carried out an analysis based on linear regressions. In all regressions, independent variables are normalised, meaning that the coefficients reported represent the change in the dependent variable as a result of one standard deviation increase in the explanatory variable. Results from linear regressions are presented for trust in government institutions and trust in political institutions.
The policy and contextual drivers of trust in government are presented in Table A B.4, while those of trust in political institutions are presented in Table A B.5. Both trust in government institutions and trusts in political institutions are regressed using the three broad categories presented in the conceptual framework: preferences and expectations (Column I), socioeconomic background (Column II) and government competence and values (Column III). Each of the individual categories is first regressed on the dependent variable, first including the full set of variables, and in the following using a selection determined by a stepwise regression. In the final column (Column IV), all three categories are grouped together, and the significant variables are retained (using the same methodology).
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Note
← 1. The eight sections were: 1) life perceptions, experiences and satisfaction; 2) interpersonal trust; 3) trust in institutions and organisations; 4) trust in government (broad sense); 5) capabilities of central government administrative branches; 6) experience with and opinions about policy communication by central government administrative branches; 7) local governments (city, province, country, and district) and the resident participation system; 8) experiences of public conflicts and opinions about administrative capabilities.