We still know very little about whether and to what extent the experimental results established in the lab carry over to field situations. An investigation of the relationship between lab-based experimental measures and field outcomes is required if we are to rely on the experimental method to make inferences about the real world. Unfortunately, research has so far mainly focused on lab experiments with very small and nonrepresentative samples of students or other citizens, raising important concerns about external validity (see Henrich et al., 2001, for a comparison of social preferences across small-scale societies). This issue is all the more problematic since these samples are generally drawn from university students in Western countries. In the field of psychology, Arnett (2008) found that 96% of subjects in studies published in top journals were from “WEIRD” (Western, educated, industrialized, rich, and democratic) backgrounds. Researchers—often implicitly—assume that either there is little variation in experimental results across populations, or that these WEIRD subjects are as representative of the human species as any other population. This is not the case: WEIRD subjects are “among the least representative populations one could find for generalizing about humans,” and there is substantial variability of results across countries (Heinrich et al., 2001).
Due to its lack of external validity, experimental economics leaves important questions unanswered. What is the heterogeneity of social preferences across populations, organizations, or countries, based on real and comparable behaviors? How does this heterogeneity explain economic and institutional development? How is this heterogeneity explained by economic and institutional factors? How well do behaviors exhibited in experimental games (which are often conducted in somewhat artificial environments) match behavior in the real world?
Karlan (2005) uses the trust game to obtain individual-level measures of taste for reciprocity, and shows that it can be used to predict loan repayment among participants, up to one year later, in a Peruvian microcredit program. De Oliveira, Croson, and Eckel (2014) elicit subjects’ taste for cooperation in the lab using a traditional public goods game. They show that the results are correlated with subjects’ contributions to local charities in a donation experiment, and with whether they self-report contributing time and/or money to local charitable causes. Similarly, Laury and Taylor (2008) and Benz and Meier (2008) use public goods games to elicit participants’ taste for cooperation and show that it is associated with the probability to contribute to a public good in the field through a charitable donation. Algan et al. (2015) also show that trust is a good predictor of contributions in online economics communities. In particular, the emergence of large organizations based on cooperation and nonmonetary incentives, such as Wikipedia and open software, provides a perfect experiment to test the relationship between experimental measures and field behaviors.
The main concern with experimental measures of trust is related to the limited and nonrepresentative samples for the lab experiments. Survey questions, on the other hand, have representative samples if collected by National Statistical Offices, but they measure individual beliefs (about others and themselves) rather than how much people actually engage in trusting behavior.
Combining Experimental and Survey Data
Survey-based questions on trust are good predictors of macro-economic outcomes, but by themselves cannot disentangle the underlying mechanisms involved. Experimental measures of trust can do so, but they cannot be conducted on a wide scale. Experiments carried out on representative samples could shed light on the exact nature of social attitudes and on the extent of bilateral cooperation between individuals in the larger population, not only WEIRD subjects. In addition, with a few exceptions, identical experiments are not repeated in different countries, so it is difficult to understand if there is cross-country variation in the underlying mechanisms of trust. The TrustLab project has the potential to overcome these limitations. For the first time, researchers, civil society, and government can compare social preferences drawn from an identical experimental setup based on representative samples for different countries.
What Can We Say Based on Available Evidence?
International surveys have yielded evidence of large differences in trust levels across countries. In Norway, the country with the highest level of trust in the sample, more than 68% of the population are trusting others (Figure 10.4). At the opposite end of the ranking lies Trinidad and Tobago, where only 4% of the population report high levels of inter-personal trust. In general, Northern European countries lead the ranking with high-average levels of inter-personal trust, while populations in African and South American countries seem not to trust others very much. The United States ranks in the top quarter of countries, with an average trust level of more than 40%. The extent to which people trust others, however, varies not only across countries, but also across regions in the same country. Algan and Cahuc (2014) show that trust levels vary remarkably between regions across Europe, the United States, and in several other countries.
Figure 10.4. Average Trust in Others Across 109 Countries, 2014
Source: Algan, Y. and P. Cahuc (2014), “Trust, growth and well-being: New evidence and policy implications,” in Aghion, P. and S. Durlauf (eds.), Handbook of Economic Growth, Vol. 2, Elsevier, North-Holland, Amsterdam, pp. 49–120. StatLink 2 http://dx.doi.org/10.1787/888933840095.
In addition to better understanding the distribution of trust across countries, researchers have expanded the evidence base on the three observed relationships that justify interest in trust: its relationship with economic activity and GDP growth, with people’s subjective well-being, and with governance and public policy. Research on each of these relations is described later on.
Trust Matters for Economic Activity and Growth
Trust in others is the only statistically significant predictor for the cross-country variation in income per capita and GDP growth after controlling for education, ethnic fractionalization (number, size, socio-economic, and geographical location of distinct cultural groups), legal origins, and political institutions (Algan and Cahuc, 2014). One concern has been that this correlation, first noted by Knack and Keefer (1997), could go the other way around, i.e., from income to trust. Alternatively, the trust variable could be picking up the deeper influence of time-invariant features such as legal origins, the quality of institutions, initial education, the extent of ethnic segmentation, and geography.
More light on this issue is provided by Algan and Cahuc (2010), who established a steady causal relationship going from trust to income by controlling for confounding factors and reverse causality. Algan and Cahuc used time variation in inherited trust of children of immigrants to the United States to explain GDP growth in the countries of their forebears—since children inherit some of their trusting nature from their parents, one can work backward to estimate their immigrant forebears’ trust, and use this to estimate the level of trust in the origin country at the time the forebears left. Since the forebears left their home country at different times, one can estimate the level of trust in the home country at different times, obtaining a data set that traces changes in trust over time in different countries.2 This structure of data—a panel data set—allows for the estimation of the impact of changes in generalized trust on income per capita in the countries of origin. By focusing on the inherited component of trust, the authors avoid reverse causality. By providing a time-varying measure of trust over long periods, they can control for both omitted time-invariant factors and other observed time-varying factors such as changes in the economic, political, cultural, and social environments.
Algan and Cahuc find a significant impact. Income per capita in 2000 would have been 546% higher in Africa if, all else being equal, the level of inherited trust had been the same as inherited trust from Sweden. Inherited trust also has a nonnegligible impact on GDP per capita in eastern European countries and Mexico. Income per capita would have increased by 69% in the Russian Federation, 59% in Mexico, 30% in Yugoslavia, 29% in the C
zech Republic, and 9% in Hungary had these countries inherited the same level of inter-personal trust as Sweden. The effect, though less important, is also sizable in more developed countries. Income per capita would have been 17% higher in Italy, 11% in France, 7% in Germany, and 6% in the United Kingdom if these countries had had the same level of inherited trust as Sweden. The authors also compare the effect of trust on income per capita and of time-invariant factors such as geography and institutions. For countries in Africa or Latin America, initial economic development and invariant factors have a large impact on income per capita. In contrast, change in income per capita in developed countries is overwhelmingly explained by inherited trust.
Progress has been made not only in understanding the role of trust at a macro-economic level, but also at a micro-economic level. Trust in others shapes the capacity to achieve common goals through pooling of resources, reduced transaction costs and coordination failures during economic exchanges, and more generally the way people live together (OECD, 2015). Therefore, innovation, investment, and the functioning of financial and labor markets are contingent on trust (Algan and Cahuc, 2009). Algan and Cahuc (2014) show different channels through which generalized trust can affect economic growth. Trust plays a preponderant role for economic activities—investment and especially innovation—that are affected by uncertainty on account of moral hazard and the difficulties of contract enforcement. The effect of trust also acts through the organization of firms and the functioning of the labor market. By facilitating cooperation among anonymous persons, trust favors the emergence and growth of private and public organizations (Fukuyama, 1995; La Porta et al., 1997; Bertrand and Schoar, 2006). Trust favors the decentralization of decisions within organizations, allowing them to adapt better to alterations in the environment (Bloom, Sadun, and Van Reenen, 2012). Trust likewise influences the functioning of the labor market through several channels. For example, countries with higher generalized trust have higher levels of cooperative relations between labor and management (Aghion, Algan, and Cahuc, 2011); in turn, the quality of employer-employee relations is associated with an array of factors that favor GDP growth and well-being.
Trust Matters for Subjective Well-Being
Trust and subjective well-being are positively correlated, and there is growing evidence for this in the literature. For example, Helliwell and Wang (2011) show that trust can mitigate the impact of bad shocks on individuals and is associated with lower suicide rates. Helliwell and Putnam (2004) and Helliwell and Wang (2011) provide cross-country micro-evidence on the positive relationship between trust and subjective well-being, and estimate how much this relationship is “worth” in terms of the effects on income. From the 2006 wave of the Gallup World Poll, they use the “lost wallet” trust question for 86 countries. Individuals are asked what is the likelihood of the respondent’s lost wallet (with clear identification and $200 cash) being returned if found by a neighbor, a police officer, or a stranger. Helliwell and Wang estimate that an increase in income by two-thirds is necessary to compensate the welfare loss associated with thinking that no one will bring back your wallet and your documents. For example, to live in a country like Norway (highest mean expected wallet return of 80%) rather than in Tanzania (lowest mean expected wallet return of 27%) is equivalent to a 40% increase in household income. Boarini et al. (2012) take this analysis further, and show that average levels of inter-personal trust at the country level are strongly correlated with the life satisfaction of individuals living in these countries, independently of the individual’s own trust, and after controlling for demographic and economic variables. A more general study on the country’s endowment of relational capital, proxied by the share of the cooperative sector, finds that more cooperativeness is associated with more happiness, after controlling for countries’ Human Development Index and other variables (Bruni and Ferri, 2016).
All these studies focus on cross-country correlations. But the same type of evidence holds within a given community, and changes in trust over time are associated with changes in subjective well-being over time. Helliwell et al. (2009) show that the same result holds in the workplace. Using micro-data from Canada (the 2003 wave of the Equality, Security and Community Survey) and the United States (the 2000 wave of the Social Capital Benchmark Survey), the authors find that the climate of trust in the workplace, in particular workers’ trust in their managers, is strongly related to the subjective well-being of workers. On a 1–10 scale, an increase by one point of workers’ trust in managers has the same effect on their life satisfaction as an increase in household income by 30%.
There is also evidence to suggest that generalized trust correlates positively with better health outcomes for individuals (Boreham, Samurçay, and Fischer, 2002; Arber and Ginn, 2004). For example, Hamano et al. (2010) studied around 200 neighborhoods in Japan and found that high levels of generalized trust (along with high levels of membership in associations) were linked with better mental health after controlling for age, sex, household income, and educational attainment. A study of Chicago neighborhoods showed that high levels of reciprocity, generalized trust, and civic participation were associated with lower death rates and rates of heart disease, after controlling for neighborhood material deprivation (Lochner et al., 2003).
However, the causal pathways between trust in others and well-being are still unclear. One possible explanation of the associations described above is that less-trusting individuals may have a tendency toward social isolation, thereby depriving themselves of many of the positive health benefits of supportive social networks (Glass and Balfour, 2003). Another possible explanation is that people living in higher-trust communities have lower levels of social anxiety, and thus lower levels of chronic stress (Wilkinson, 2000).
To get more causal evidence, recent research has looked at the physiological reaction and brain images of participants depending on their degree of cooperation in a trust game. Zack, Kursban, and Matzner (2004) show that when people cooperate with others in trust games, they increase production of oxytocin. The authors also tested a variant in which the receiver receives a monetary transfer not from a real person but from a lottery. In this variant, the level of oxytocin does not rise with the money received. This result illustrates that it is trust that is associated with sentiments of happiness, and not the mere fact of receiving money. These results have been confirmed by brain images: as soon as individuals do not cooperate in trust games, the insular cortex activates (Sanfey et al., 2003). This area of the brain is known for being active in states of pain and disgust. The main conclusion from this research is that the nonmonetary dimension of having trusting behavior with others affects happiness by more than the monetary gains derived from cooperation. All in all, these results suggest that trust affects many dimensions of social progress, including both economic development and life evaluations, and is a key component of human development at large.
Trust in Institutions and Social and Economic Progress
There is also good evidence of a positive relationship between institutional trust and citizen support for government policy (OECD, 2016). In one of the earliest studies on this subject, Knack and Keefer (1997) analyzed responses to World Values Surveys across about 30 countries, finding a positive correlation between measures of citizens’ confidence in government and objective indicators of bureaucratic efficiency. In a cross-country analysis, Zhao and Kim (2011) highlight a positive correlation between institutional trust and levels of foreign direct investment. Murphy, Tyler, and Curtis (2009) find a strong positive relationship between trust in regulators and voluntary compliance in the area regulated, while Daude, Gutiérrez, and Melguizo (2012) find a strong relationship between institutional trust and willingness to pay taxes. There is also a robust cross-country correlation between people’s trust in institutions and their perceptions of corruption (OECD, 2013). These studies, based on the correlation between citizen support for government and trust in institutions, need to be understood in a conte
xt where there is almost certainly reverse causality, i.e., people are less likely to trust inept or corrupt institutions (highlighting the issue of interpretation of the institutional trust measure discussed above). It should be stressed though that most of these studies are based on correlations and the research still needs to make progress in establishing a causal link between trust in institutions and economic progress.
Trust in institutions is also necessary to maintain democratic systems. The recent trust crisis in Europe is a good illustration of the risks. Algan et al. (2017) show that the financial crisis and Great Recession that followed it, and the inability of European institutions to cope, led to a sharp decline in trust in European and national parliaments, associated with a rise in extreme votes and populism. Algan et al. find a strong relationship between increases in unemployment and voting for nonmainstream, especially populist parties, and a decline in trust in national and European political institutions. In an effort to advance on causation, the authors extract the component of increases in unemployment stemming from the pre-crisis structure of the economy, and in particular the share of construction in regional GDP, which is strongly related both to the build-up and outbreak of the crisis. Crisis-driven economic insecurity is a substantial driver of populism and political distrust. An important policy implication from the European economic crisis is that national governments and the European Union should focus not only on structural reforms, but also on protecting the trust of their citizens from economic insecurity.
Trust in institutions is also directly related to subjective well-being. Figure 10.5 shows positive correlations between life satisfaction and trust in the judicial system (Panel A) and in the government (Panel B). This relationship can be explained if trusted institutions function better, and are therefore associated with better outcomes that raise people’s life satisfaction. The causality can also go in the other direction though, with people trusting institutions that function better. But there is also evidence of a direct impact of trust in institutions on people’s subjective well-being. Frey, Benz, and Stutzer (2004) and Frey and Stutzer (2005, 2006) show the importance of “procedural utility” (i.e., the process through which people are involved in making important collective decisions) for people’s subjective well-being, independently of the actual outcome of the decision. In this perspective, although a policy decision might increase total income, the welfare effect could be reduced due to the losses resulting from a decision process perceived by people as unfair or nondemocratic. This literature may be important to understand the current rise in populism in much of the world.
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