Institutional quality, trust and savings

An abundant literature demonstrates the importance of formal institutions (i.e. the system of property rights, laws and regulations) for growth and development (Acemoglu et al., Reference Acemoglu, Gallego and Robinson2014; North, Reference North1990). The protection of property rights, in the form of ‘a fair and balanced judicial system, contract enforcement, and effective limits on government's ability to transfer wealth through taxation and regulation’ (Sobel, Reference Sobel2008: 644), is indeed a condition for capital accumulation (Jordan, Reference Jordan2001: 22) and ultimately economic growth. Property rights encourage accumulation because they protect individuals against all forms of expropriation (Demsetz, Reference Demsetz1967). Anything that increases the risk of expropriation (e.g. theft or tax) slows accumulation, investment and ultimately productivity gains and the level of production because agents have no incentive to accumulate and more generally to be more effective (Besley and Ghatak, Reference Besley, Ghatak, Rodrick and Rosenzweig2010: 4,529). Under these conditions, the savings rate in a country should depend on the quality of its formal institutions. To encourage saving, it should be sufficient for the State to protect the property rights of savers.

Such a narrative logically recommends that poor countries should copy the institutions of rich countries to reach their level of accumulation and thus create good conditions for economic growth. Nonetheless, experience shows that institutional copying often fails (Chang, Reference Chang2011; Couyoumdjian, Reference Couyoumdjian2012; Lecce and Ogliari, Reference Lecce and Ogliari2019; Rodrik, Reference Rodrik2008; Seidler, Reference Seidler2018), suggesting that culture is crucial for the effectiveness of an institutional system. Law (formal institutions) and culture (informal institutions) are inseparable (North, Reference North1990: 7; Williamson, Reference Williamson2000: 597). This implies that the question of the institutional determinants of the saving rate must be revisited and this is where the theme of trust enters the discussion, by introducing two extra dimensions into the picture.

First, trust can be thought of as a judgement about the quality of institutions (informal and formal). Institutions are crystallised knowledge (Hayek, Reference Hayek1960: 27). This knowledge is a set of cognitive rules. ‘Cognitive rules are social constructs that convey information that distills and summarizes society's beliefs and experience’ (Greif and Mokyr, Reference Greif and Mokyr2017: 26). The individuals are co-producers of shared beliefs about each type of institutions (Frolov, Reference Frolov2023). They make judgements about the quality of institutions, about the consistency and validity of the set of cognitive rules that justify and legitimize each institutional system. They may or may not trust these rules. They believe in them or not. Trust is a judgement on the quality of these cognitive rules according to which certain actions will lead to certain outcomes (Greif and Mokyr, Reference Greif and Mokyr2017: 27). Trust is the mental model reflecting a common belief system that will translate into a set of institutions (North, Reference North2005: 104). It is the glue of institutions (Gallagher and Petracca, Reference Gallagher and Petracca2022). Savers not only need to know that their savings are formally (de jure) protected by law. They need to believe that this is actually the case. They need to believe that their savings will not be confiscated in the event of a crisis or government need.

The second extra dimension introduced by trust is a consequence of the first. The need to believe is an act of faith. In an uncertain world, no amount of information or objective knowledge can guarantee that savings will not be confiscated. Trust thus complements the theory of institutions with a theory of beliefs that is not based on facts, but on will (James, Reference James1897) and/or un-necessary reasons (Aquinas, Reference Aquinas1265–1274Footnote ¹). (i) When the act of faith finds its origin in the will to believe, savers want to believe that the world can be what they want it to be. Trust, in this perspective, is a personal or cultural attribute (Fukuyama, Reference Fukuyama2000). Individuals' trust in others, in the State or in the market is independent of the reliability of others, the efficiency of public decisions and the performance of market institutions. The prevalence of pro-social behaviours makes formal contract enforcement mechanisms unnecessary (McCannon, Reference McCannon2011). Trust is a substitute for the quality of institutions and becomes essential in countries where the institutions that enforce contracts are weak (Karlan et al., Reference Karlan, Mobius, Rosenblat and Szeidl2009). (ii) When the act of faith finds its origin in un-necessary reasons to believe it, savers are sure, without necessity, because of experience or education. Savers trust market institutions or government because they have rarely been disappointed by these institutions. They have always worked well. Or savers have confidence in the institutions of the market because they have had teachers or listened to journalists who explained to them how the market worked and what were the mechanisms that made it possible to protect their savings. Institutions play a key role as facilitators of trust (Bachmann and Inkpen, Reference Bachmann and Inkpen2011: 287). Trust would thus evolve with the quality of institutions (Farrell, Reference Farrell2005). A positive experience of public institutions or officials increases trust (Edlund, Reference Edlund2006). A positive experience of law and regulations encourages people to be honest (Bohnet and Baytelman, Reference Bohnet and Baytelman2007) and improves social trust (McCannon et al., Reference McCannon, Asaad and Wilson2018: 812).

This will of belief is probably ‘less realistic at least where business relationships are concerned’ (Bachmann and Inkpen, Reference Bachmann and Inkpen2011: 288), but when institutions are highly regulated by government, the trust of savers is not mainly in the quality of business relationship and private contracts, it is in economic institutions which are embedded in political institutions. The saver should not doubt the government's ability to maintain a currency (exchange rate risk) and to be fiscally responsible. It is then a matter of having confidence in the government's ability to manage the complexity of the social order. Because of the impossibility of gathering all the knowledge necessary to ensure this, the willingness to believe that the government is credible, benevolent and omniscient is a cognitive shortcut, a means of reducing the costs of information gathering. In a world organized into a system of territorial States and where States can enforce the law or change it and facilitate or not the production of money, the saver must above all have confidence in the State and in the hierarchy of norms that it imposes. Taking into account the hierarchy of legal norms, with the Constitution at the top and the contract at the bottom (Kelsen, Reference Kelsen1967), creates the conditions for the existence of a hierarchy of trust (Figure 1).

Figure 1.

Pyramids of formal institutions and of corresponding trust related to banking and savings.

This approach leads us to make the hypothesis that trust in the hierarchically highest institutions is a substitute for every lower level of trust down to social trust. Concretely, this means that even though social trust could theoretically matter because institutions are run by individuals, trust in institutions and more particularly in political institutions is probably sufficient to foster savings. One can believe that the banker is incompetent, but that in the event of the bank's failure, the central bank will preserve one's savings. One can believe that the central banker is incompetent, but that government under the democratic process will be obliged to prevent the bankruptcy of households to avoid losing the elections. Trust in political institutions should ultimately be the main determinant of household saving rates. It may operate in the minds of citizens through two channels: directly via regulation since political actors may easily seize or tax citizens' savings and indirectly via fiscal and monetary policy since citizens should be more prone to save if they trust the political actors to provide a reasonably stable economic environment.

There is already empirical evidence of a significant positive relationship between various types of trust and the investment volume of savers at the micro level (using individual data). It concerns social trust (Guiso et al., Reference Guiso, Sapienza and Zingales2004; Hong et al., Reference Hong, Kubik and Stein2004), trust in the bank officer and in the bank (Coupé, Reference Coupé2011; Guiso et al., Reference Guiso, Sapienza and Zingales2008), trust in political institutions and in financial institutions (Baidoo and Akoto, Reference Baidoo and Akoto2019; Balloch et al., Reference Balloch, Anamaria and Philip2015), trust in national currency and in current monetary policies and institutions (Brown and Stix, Reference Brown and Stix2015). Evidence at the macro level, as well as an interpretation in terms of a hierarchy of trust, are however lacking, while it is known that trust in banks and financial institutions differs strongly from one country to another (Agnew et al., Reference Agnew, Szykman, Utkus and Youn2012; Stix, Reference Stix2013). The rest of the paper aims to contribute to fill this gap.

Data and hypotheses

Data on savings and macroeconomic determinants were obtained from Grigoli et al. (Reference Grigoli, Herman and Schmidt-Hebbel2018).Footnote ² They explain the household savings rate by: (i) the GDP per capita in purchasing power parity, (ii) the GDP growth rate, (iii) the public sector savings rate, (iv) age, (v) the share of the population living in cities, (vi) the interest rate, (vii) the inflation rate, (viii) the flow of private sector credit and (ix) the terms of trade. They calculated their own private savings indicator using data mainly from the World Economic Outlook Database (WEO), UN National accounts and several national central banks for missing observations. Data for independent variables and controls were obtained from various sources (World Bank Development Indicators database, IMF World Economic Outlook, etc.; see Grigoli et al., Reference Grigoli, Herman and Schmidt-Hebbel2018). In the following analyses, we use the household savings rate as our explained variable and the nine other variables as control variables. Our explanatory variables of interest are the quality of institutions measured at three levels (political, legal and financial) and trust in institutions measured at four levels (political, legal, financial and social), which we now describe.

Our indicator of institutional quality at the political level is from the ‘Polity5 Project’ Database by Marshall and Gurr, from the Center for Systemic Peace. We use the ‘Polity2’ Index, which subtracts a score measuring the strength of democratic patterns of a country from a score measuring the strength of autocratic patterns. The result is a unified polity scale ranging from +10 (strongly democratic) to −10 (strongly autocratic).

Our indicators of institutional quality at the legal and financial levels are taken from the ‘Economic Freedom of the World Report’ issued each year by the Fraser Institute, which combines data from various sources, mostly based on experts' opinions on their national institutions.Footnote ³ We use the indicator ‘legal system and property rights’ as a measure of the quality of legal institutions. It refers to the respect of the rule of law, the security of property rights, an independent and unbiased judiciary and impartial and effective enforcement of the law. We use the indicator ‘sound money’ as a measure of the quality of financial institutions. It measures the stability of the money growth taking into account inflation, but also the freedom to own foreign currency bank accounts.

We use six indicators of trust. Five of them (two measures of trust in political institutions, two measures of trust in legal institutions and one measure of social trust) are taken from the European Social Survey, which is an academic-quality opinion survey on the values of Europeans conducted by a team of researchers and carried out every 2 years since 2002. Sampling is random and involves around 1,500 people over 15 years of age for each country for each of the survey waves. Data are collected in face-to-face computer-assisted personal interviews. We use the waves from 2002 to 2012. The sixth one (trust in financial institutions) comes from the database ‘Gallup World Poll’.

The indicators of trust in political and legal institutions draw on the work of Sønderskov and Dinesen (Reference Sønderskov and Dinesen2016) and Zmerli and Newton (Reference Zmerli and Newton2008). It measures citizens' confidence in various public institutions by asking the following question: ‘please tell me on a score of 0–10 how much you personally trust each of the institutions I read out. 0 means you do not trust an institution at all, and 10 means you have complete trust’. We use trust in parliament and in politicians as measures of trust in political institutionsFootnote ⁴ and trust in the judicial system and the police as measures of trust in legal institutions.

The indicator of trust in financial institutions is based on Gallup annual World Polls. The question asked was the following: ‘In this country, do you have confidence in each of the following, or not? How about financial institutions or banks?’. The question was asked on samples of approximately 1,000 respondents between 2008 and 2018 on a yearly basis. The indicator gives us the share of respondents in the country who answered ‘Yes’, meaning that they are confident in these institutions.

The indicator of social trust, or trust in others, follows the methodology of Sønderskov and Dinesen (Reference Sønderskov and Dinesen2016). It takes up three questions from the ESS. The first question concerns the trust that people place in strangers outside their family and friends: ‘In general, do you think that you can trust most people, or that you can never be too careful in your dealings with others?’ It is answered on an 11-point scale based on the following two opposite options: ‘you can trust most people’ and ‘you can never be too careful’. To this first question are added two other questions to make the answer more robust. One concerns fairness: ‘Do you think that most people would try to take advantage of you if they had the chance, or would they try to be fair?’ The other relates to the representation that each person has of the other: ‘Would you say that most of the time people try to be helpful, or that they care most about themselves?’ We constructed an additive scale by averaging the three responses for each respondent (it showed a high degree of internal consistency with alpha values ranging from 0.76 and 0.80 from one wave to the next) and then aggregated the individual responses for each wave per country.

Table 1 summarizes the data used in this study. Our key hypothesis is that trust in political institutions is significantly and positively related to the private saving rate. We can also expect institutional quality, trust in legal and financial institutions and social trust to have a positive relationship with savings, but neither of them is necessary in view of our theoretical arguments. Indeed, there are logical reasons that could explain such positive relationships, but they are very likely to be less important than trust in political institutions. As one might expect a relationship between institutional quality and institutional trust, Appendix Table A1 provides a correlation matrix of these variables. Although all the correlations are statistically significant, they are of moderate intensity for political and financial institutions (of the order of 0.3), which supports our approach of studying the specific effect of each variable and not to rule out a priori the idea of substitutability between trust in institutions and institutional quality, the latter being based in part on the willingness to believe.

Table 1.

Descriptive statistics

GPDI, gross personal disposable income.

The expected impact of most control variables lies in debates arising from the opposition between Keynesian and classical macroeconomics. These two models are based on two propositions that could be summed up as follows: more income means more savings (i), and higher interest rates mean more savings (ii). Appendix Table A2 summarizes the results of existing studies for each variable.

Empirical strategy

We estimate the impact of our nine key explanatory variables (three indicators of institutional quality and six indicators of institutional trust) on the private saving rate by introducing them alternatively in a set of regressions relying on the approach of Grigoli et al. (Reference Grigoli, Herman and Schmidt-Hebbel2018). More precisely, for each key explanatory variable, we implement six different specifications, presented in order of increasing complexity, and corresponding to four analysis steps.

In the first step, we estimate the following model:

(1)$$S_{i, t} = \alpha + \beta T_{i, t} + \gamma C_{i, t} + \tau _t + \varepsilon _{i, t}$$

where S _i,t denotes private savings for country i at time t, T _i,t refers to our key explanatory variable, C _i,t refers to the set of covariates described above (see also Table 1), τ _t are time-fixed effects and $\varepsilon _{i, t}$ the error term. We use ordinary least squares (OLS) applied to our pooled panel sample, computing robust standard errors clustered at the country level.

In the second step, we account for the panel structure of the data and control for time-invariant unobserved variables at the country level, using both OLS fixed effects (OLS FE) and OLS first differences (OLS FD) models. These models rely on different assumptions regarding the idiosyncratic error (the FE model is optimal under independent identically distributed idiosyncratic error, while the FD model is optimal under idiosyncratic error following random walk). We consider that they provide plausible bounds for the actual estimates.

In the third step, we estimate the following model:

(2)$$S_{i, t} = \alpha + \delta X_{i, t} + \eta D_{i, t} + \tau _t + \varepsilon _{i, t}$$

where X _i,t refers to the set of strictly exogenous covariates (the log of the term of trade, the old-age dependency ratio and the share of urban population) and D _i,t includes the endogenous covariates (all other explanatory variables). Endogeneity is addressed using the two-stage least squares (2SLS) estimator with the lags of endogenous variables as instruments. As in step 2, both FE and FD models are used to control for time-invariant omitted variables at the country level.

In the fourth step, we turn to a dynamic specification, including the lag of the dependent variable as explanatory variable:

(3)$$S_{i, t} = \alpha + \theta S_{i, t-1} + \delta X_{i, t} + \eta D_{i, t} + c_i + \tau _t + \varepsilon _{i, t}$$

This model, which includes country- and time-fixed effects, is estimated using the two-step system-generalized method of moments (S-GMM) (Blundell and Bond, Reference Blundell and Bond1998), with the finite-sample correction of the two-step covariance matrix derived by Windmeijer (Reference Windmeijer2005).

This last specification is the one preferred by Grigoli et al. (Reference Grigoli, Herman and Schmidt-Hebbel2018), in particular because it partially controls for possible reverse causality. Given the reduced size of our sample, this specification is less appropriate to our data. We report the results for illustrative purposes. In general, our interpretation of the results is mainly driven by the stability of findings across the six different specifications, which constitutes a sign of robustness.