The Economic Implications of Trust in Fostering Growth and Convergence

Syed Sibghatullah Shah
Quaid-i-Azam University, Islamabad, Pakistan
Correspondence to: s.sibghats@eco.qau.edu.pk

DOI: https://doi.org/10.70389/PJSS.100006

Additional information

• Ethical approval: N/a
• Consent: N/a
• Funding: No industry funding
• Conflicts of interest: N/a
• Author contribution: Syed Sibghatullah Shah – Conceptualization, Writing – original draft, review and editing
• Guarantor: Syed Sibghatullah Shah
• Provenance and peer-review:
  Commissioned and externally peer-reviewed
• Data availability statement: N/a

Keywords: Trust-based economy, Economic convergence, Transaction costs, Institutional efficiency, Markov process.

Peer Review
Received: 16 October 2024
Revised: 29 October 2024
Accepted: 29 October 2024
Published: 28 November 2024

Introduction

It is necessary to understand the happening of some kind of event happening through defining elements of interaction. Firstly, we need to understand that when there is an interaction, it can be temporary or accidental, or if there are repeated interactions with cooperative outcomes, then formulate a trust. However, information asymmetry is enough to create moral, social, or transaction delays that are filled by trust in most cases. In the literature, Williamson¹ explains some arguments against trust. The first is “opportunism,” which describes a self-interested person considering interaction temporarily and acting selfishly to maximize his gain. The second assumption is concerned with “bounded rationality,” which asserts that agents act in a particular manner due to their restrictive constraints regarding time, information, and ability.² According to Williamson,1 this problem can be resolved through plausible commitment. Therefore, if trust is generated, then an element of opportunism might be omitted. Consequently, Delhey and Newton³ describe trust as the belief that others will not consciously do us damage if they can avoid it and will look after our interests. Therefore, credible commitment can be replaced by the solidifying mechanism of trust. Similarly, Newton and Zmerli⁴ describe three types of trust: one that forms in a complex and small network of individuals like peers or family; second is known as interpersonal trust that formulates among non-family members known as strangers; and finally, there is institutional trust that is our confidence in political systems that comprise government, parliament, and courts.

Currently, an important question is how to measure trust; hence, most studies in the literature use survey response questions like “Generally speaking, would you say that most people can be trusted, or that can be too careful when dealing with strangers” with their answers ranging on various scales. Indeed, the work of Berget al.,⁵ through the dictator game asserts that preferences towards risk aversion, selflessness, and inequality limited the scope of interpersonal trust. Moreover, the questions asked in surveys explain the trustworthiness of individuals in a specific country, region, or society.

In our lives, we have to make several decisions with uncertain outcomes. Once we have two choices among two alternatives that always involve two kinds of risk, in the form of gain or loss of something. Moreover, human choices are influenced by three main factors that impact how we evaluate our decisions. First is loss aversion, which describes that the loss of something hurts twice that of gaining.⁶ The second is diminishing sensitivity, according to which when we acquire a certain thing in a larger quantity, then with more usage, our sensitivity to that thing becomes smaller. Finally, the third is the reference point, as people commonly set some reference point for what people expect. Consequently, results that surpass the setpoint are deemed gains, and those that fall short are deemed losses.⁷ People are incentivized to either create more wealth or stop other people from doing so in certain countries. In addition to social standards and trust between individuals, legal frameworks like contracts and property rights protection” reinforce the comparative outcome of whether there is making or taking of wealth.⁸ Almost every commercial transaction has elements of trust within itself, certainly any transaction conducted over a period.⁹ Whether it’s with close friends and family, larger organizations, or even the government, it can speed up relations and help the economy progress.^10–15 They discovered that trust helps with economic integration by increasing labor productivity and decreasing rent-seeking behavior, and facilitating cooperation, all of which raise economic yield. Less monitoring and transaction costs are also necessary to eliminate anti-social behaviors and practices.

Different researchers have found ways to link trust with macro- or microeconomic integration and growth. Government spending, investment incentives, and economic growth can all flourish when people, organizations, and the government all trust one another.^16,17 Consequently, according to Woolcock,¹⁸ people who are part of a group are more likely to invest in the system as a whole through transactions and exchanges with other important actors, such as other individuals, institutions, or the state, which builds trust, which in turn increases confidence and mutual benefit. Therefore, the government in such a system can focus more on enhancing society and less on rehabilitation, thanks to the trust’s balancing role. The following is a widely held interpretation of trust as proposed by Rotter¹⁹ “generalized expectancy of individual that the word, promise, oral or written statement of another individual or group can be trusted.” Economies where people have trust in each other and also in the state result in public institutions that are more competent and productive.^20,21

Economists are careful about trust because of its connection with economic activity. In this regard, trust is the crucial component in gaining competitive benefit, as buyers are more interested in working with honest and verified sellers. Therefore, trust is an important issue that most researchers neglect while asserting the trade dynamics of countries. According to Fukuyama,²² trust does create value for products and facilitate transactions, and its absence is an obstacle to economic prosperity and integration. For example, if it is possible for us to verify on the spot about product quality (lemon or peach) through a contract or any other mechanism, then we might not require any trust. However, in most cases, we are familiar that contract writing is either costly or people selling products like cars themselves do not want to show their contracts to earn extraordinary profits.²³

Economic historians contend that in the 18th ­century, the oatmeal brand Quaker played an influential role in the economy of Britain because of reliability and trust.²⁴ Therefore, there are two strands of literature explaining the economic significance of trust. The first is based on good type and its importance for seller and buyer. Another is incentives for buying and selling a product relating to rationality and behavior dynamics. According to various sources (Easterly et al.;²⁵ Micallef,²⁶ Ingianni and Žd’árek²⁷) “many developing countries failed in the attainment of convergence in economic outcomes due to deficiency of trust at the individual level” after the transition from state-to-individual industrial reforms and trade liberalization in the 1990s. In addition, due to moral hazard and asymmetric information, it can cause market inefficiency. Protecting transactions via contracts and law enforcement also costs more money, which affects both individuals and the government. Most people in societies with low levels of trust are unable to rely on formal channels for financial transactions because their social networks are too small. Less trust in other people, organizations, and nations leads to smaller trade-related groups, which in turn reduces exports.²⁸

Trust is used to measure social capital, which is instrumental in the formation of a prosperous society through collective and coordinated actions.²⁹ Until now, most studies employed experimental settings to demonstrate the relationship between trust and ­economic integration, and few of them demonstrated individual-level impact. As Fukuyama²² claims, “through interacting daily with each other individuals do create honesty and reliability, thus a society based on Kant’s rational agents will develop social capital over time”. In this regard, Di Cagno and Scuba³⁰ contend that through daily social interactions, people develop skills needed for survival in the economic realm. Similarly, individuals with a higher level of social intelligence are more skilled in quickly understanding relationships and adjusting themselves according to the environment to make more informed judgments.³¹

There are several issues with using cross-national methods to quantify trust in economic outcomes.³² This is because different societies rely on different kinds of trust. A thorough review of the relevant literature has shown that trust significantly correlates positively with economic performance. In the past, methods for evaluating trust’s impact on the economy included trust games, Nash equilibrium, and regression analysis.³³ The research also attempts to use the Markov process to formulate a trust economy. The equilibrium level of economic growth components is determined by a trust-based system that includes individuals, institutions, and the state. We have assumed two separate economies to be part of Group G, according to our work. The work of French³⁴ will serve as the basis for this categorization, which places G_a on a strong foundation of trust and G_b On a weaker one among different stakeholders. One measure of economic health is gross domestic product (GDP). People in our specified system rely heavily on trust in their interactions with one another. The next step is for these people to join groups or institutions that facilitate regular trade and commerce. Institutional interaction with others by dealings of individuals in the form of reciprocity with other organizations. In any form of government, democracy included, the formation of an economic system known as the “Trust Economy,” which is contingent on the honesty and reliability of its citizens. This system benefits society at large by fostering mutual support between citizens and governments, which in turn strengthens the bonds of peace, harmony, and economic integration on a global scale.

Hypothesis

We hypothesize that economies with higher levels of trust among individuals, institutions, and the government will converge to economic equilibrium faster and achieve greater economic efficiency compared to economies with lower levels of trust. This theory is based on the idea that trust lowers transaction costs, boosts cooperation, and makes institutions more efficient, all of which speed up economic growth and convergence. The purpose of this paper is to investigate the importance of trust in determining factors like institutional efficiency, economic growth, and social welfare. Few things are as important as trust when it comes to lowering transaction costs, improving cooperation, and encouraging long-term economic growth. Trust is an important but frequently ignored formal variable in economic models, despite its importance. This research aims to fill that knowledge vacuum by creating a trust-based economic model that analyzes the effects of different trust levels on economic results and integration rates. To gain a better understanding of how trust affects institutional strength, long-term growth, and the efficiency of economic processes, we will use a Markov process to compare economies with high and low trust. Prior research has established a connection between social capital, institutional trust, and economic performance; this study intends to build on that knowledge by measuring the impact of trust on economic integration and convergence.

Theoretical Foundation: Trust Dynamics and Economic Convergence

There is a gap in the trust-economics regression analysis regarding the cooperative production of connectivity among different components of an economic system as a result of increased trust. This is an effort to broaden the understanding of a trust-based economy so that it can be seen as a variable that influences economic integration and growth. A trust-based economy differs from conventional wisdom in several important respects. Several personal qualities, such as honesty, hard work, and frugality, can be enhanced by it. Trust is the key component in the process of achieving production equilibrium while maintaining ideal consumption and saving levels, which can enhance investment. Labor participation and production efficiency both rise in a community where people trust one another and are motivated to work hard.

Individual relationships, transaction costs, and company performance can all benefit from trust, which is seen as an independent variable. Because it leads to the elimination of trade barriers and the coordination of fiscal and monetary policies, it is also the most crucial component for two nations in terms of international trade.³⁵ Thus, those who exhibit these traits actively engage in political organization within their groups and contribute to the strengthening of government institutions. Through the networks of a humanitarian and charitable organization, this type of involvement broadens the social network of society and contributes to the eradication of poverty and inequality. The poor can maximize their utility through consumption because of these socially connected associations, which allow them to get an education and money.

Institutions are bolstered when trustworthy individuals join the system, whether it’s private or public, and continue to produce and nurture individual-level relations and traits. At the end of the day, this procedure yields a government that guides the economy towards stability by enhancing GDP components. These encompass prudent spending, saving, and investment; increased tax revenue to fund government programs; and a trade surplus in international commerce. Being a trust-based economy has all these advantages. Two economies denoted as (G_a) and (G_b) are being ­compared in the study. We go a step further by looking at how future economic convergence might be influenced by the degree to which trust is present or absent. When studying random phenomena for which the precise result is unknown, the Markov process is useful for making predictions. Through using the Markov Process, Shah et al.³⁶ investigate the role of trust and economic development in establishing the equilibrium stage. They argue that economic activity is more akin to a state-initiated system than to that of an individual, group, or community.

Construction of Theoretical Model

When individuals within a community trust one another, it breeds trust among all members. The first society we will look at has ‘n’ people living in it. The probability of a less trustworthy population is (1−m), while the trustworthy population is represented by (m). Being in the (m) phase has many advantages, such as increased education, job security, consumption, savings, investment, psychological and physical health, and overall well-being, all else being equal. On the flip side, a country’s economy might decline if people do not trust each other or if trust is low. The consumption of an individual’s trust Tt and Bi and the benefits (Bi) that come with having or being in the trust phase are the sources of individual utility during time t. Afterwards, we assume that Bi = 1 if the person in question is trustworthy, and Bi = 0 if they are not. Therefore, one of the most telling traits of the world’s rich is their propensity to save money and then invest that money. Spending money on reliable people can help a company save time and money by cutting down on information and transaction costs. The trust economy was structured like a chain, with links that went all the way from individuals to states. A more sustainable level of individual benefits Bi, will be observed in the future.

All of our system’s transactions and trades rely on trust, which is its foundation. As a function of a trust economy, we define economic growth (Y).

y = f(T) where 0 ≤ T ≤ 1

Growth is defined in terms of GDP having components, consumption, investment, government spending, and net exports as, GDP (y) = C + I + G + (X−M).

y = f (T)          (1)

A trust-based economy is represented by Equation (1).

Convergence

We have assumed two possible states in an economy: one with high levels of trustworthiness (T ht  ) and one with low levels of trustworthiness T lt. The former is represented by Ph, while the latter is (1 −  ph) =   pL.

BT ht  = (1 + E)T ht 

When trust is sustained and both the quantity and quality of trust increase, as shown by (1 + E), then trust is beneficial. Strong institutions, at the individual, community, and state levels, will aid the government in enforcing laws and regulations and increasing tax revenue. Individuals and the government incur various expenses, denoted as ∂ = (1 − $)., due to the loss of leisure and revenue.

• BT ht   > ∂T ht 
• (1 + E) T ht   > (1 − $) T ht 
• ∂ ≤ T ht  ≤ T ht   *         (a)

The proportion of trustworthy individuals is higher in society, so, according to the majority voter theorem, the benefits (1+ E)T ht  exceed the minimized costs, resulting in rapid convergence. Because of trust dynamics, all revenues are possible, benefiting society collectively. Cooperative norms are generated, and individual utility is maximized at this level through reduced social spending and increased tax collection. Rehabilitation of deviant behavior, such as crime, is also prioritized. To promote unity and nonviolence, residents of this state are highly likely to become members of various clubs, associations, and nonprofits. On top of that, the government will be in a better position to facilitate greater economic integration. In high-trust societies, such as the Nordic countries (e.g., Sweden, Norway, Denmark), there is a clear relationship between trust and economic outcomes.³⁷ These nations consistently rank among the top in terms of GDP per capita, social cohesion, and overall well-being. The high trust levels among individuals and institutions help to minimize the costs of economic and social transactions, as evidenced by their low crime rates, robust welfare systems, and efficient government spending.

As an example, low rates of tax evasion and high levels of civic engagement are outcomes of the high degree to which people in these nations trust their government and its institutions.³⁸ Taxes are raised due to this shared belief in the government’s ability to provide essential services like healthcare, education, and public services, which in turn boost economic output. All of the model’s predicted advantages, like well-established institutions and increased tax revenue, are present in these countries.³⁹ Additionally, their welfare programs experience reduced transaction costs as a result of less fraud and a reduced need for extensive enforcement mechanisms. These features are particularly important in societies where trust is low. The way trade and business are done in places where trust is high supports the idea that trust can keep institutions working and help economies work together. Scandinavian countries have fewer trade barriers and more economic openness because they trust each other more, which means they don’t need as many complicated legal contracts or third-party enforcement. Both governments and businesses are very sure that each other can keep their promises and deliver products that are up to par, which is why ­international trade is booming. In line with the model’s claim that trustworthy institutions lower the costs of transactions and enforcement, this also makes frameworks work better overall.

The model also says that trust has social benefits along with economic ones. For example, it leads to less crime and more community involvement. Switzerland has some of the highest levels of trust between people in the world, so many people are involved in their communities and local governments on their own time.⁴⁰ When people are actively involved in their government, the government doesn’t have to spend as much on expensive law enforcement and rehabilitation programs for bad behaviors like crime.⁴¹ This helps keep the political system stable and open to everyone. When there is no corruption and people are willing to work together, the government can better use its money to make long-term investments in things like infrastructure and new ideas.

If we want to see how trust affects economic convergence, China is another good example. The government has made it a priority to implement policies that increase transparency and decrease corruption to improve institutional trust in recent years.⁴² With its contentious goals of rewarding honest actions and discouraging dishonest ones, the social credit system seeks to foster confidence. China has improved domestic productivity, attracted foreign investment, and fostered faster global economic integration by increasing institutional trust.⁴³ The model’s premise that institutional trust is critical to economic performance is valid; China’s fast convergence with developed economies is evidence of this, even though the country’s trust dynamics are complicated and not entirely bottom-up.

Delayed Convergence

In the scenario of delayed convergence, where the economy or society experiences low trust, represented as T lt , the probability pl of individuals being in a low-trust state is significantly high. This reflects a societal condition where trust is scarce among individuals, institutions, and the government. As trust diminishes, the negative impact on the entire economic system becomes pronounced, leading to several adverse outcomes that compound over time. These conditions align with the model’s findings that weak trust exacerbates inefficiencies, causing costs to rise while reducing the economic and social benefits derived from interactions.

Implications of Weak Trust for Economic and Social Costs

In societies where trust is weak, denoted by the ­expression, BT lt  = 1 + (E − ε)T lt  The term ε represents significant disruptions or factors that erode trust. These factors could include political corruption, lack of transparency, inefficient legal systems, or widespread inequality. As a result, short-term trust may exist in small, closed networks, but this limited trust cannot sustain broader societal and economic ­functions. This is common in countries where familial or tribal ­loyalties are prioritized over general societal trust, leading to fragmented societies with isolated pockets of cooperation but no widespread economic trust.⁴⁴

One prominent outcome in this scenario is the emergence of corrupt institutions, as the weakened trust between individuals and their government fosters an environment where self-interest and opportunism thrive. Political elites in these systems may exacerbate inequality and encourage rent-seeking by enacting policies that benefit the rich at the expense of everyone else. This is in line with opportunism, according to Williamson’s theory, in which people put their interests ahead of the greater good in the short term.⁴⁵ Since the trust deficit is getting bigger, the government needs to move a lot of money from other programs to ones that focus on crime prevention, law enforcement, and rehabilitation. Because crime, tax avoidance, and corruption are more common in low-trust societies, it costs more to keep an eye on people and make sure they follow the rules. An important part of the budgets of many Latin American countries, like Brazil, goes to keeping the peace because of widespread violence and lack of trust in the government.⁴⁶ Long-term economic growth is slowed down because there are fewer resources for investments that pay off, like building schools and roads.

Not only do problems in the country itself matter in economies with low trust, but trade with other countries also suffers. These governments have stricter trade rules because they are concerned about the safety of transactions that happen across borders. Protectionist policies, such as quotas and high tariffs, may be used to keep home industries safe from what they see as unfair competition from other countries. For example, countries like Zimbabwe and Venezuela, which have had unstable governments in the past, often have trade policies that make it hard to do business.⁴⁷ This makes the economy less open, attracts less foreign direct investment, and makes it harder to export. So, these countries miss out on the opportunities that come with globalization, while economies with high trust enjoy the benefits of free trade and working together with other countries. Differentiating and specializing economies have less room to do so, which slows integration down even more. If people do not trust a country, depending on basic goods or having a small industrial base can make it harder for it to build a more complex economy. This is the same as what the model said would happen, where the equation BT lt  < ∂T lt proven that in low-trust environments, the economic costs exceed the benefits, leading to a negative net outcome for the economy.

1 + (E − ε) T lt   < (1−$) T lt         (b)

Impact on Government Revenues and Policy Outcomes

Government revenues are reduced due to a lack of trust, as is evident in many developing economies where tax evasion is common.⁴⁸ People in societies where trust is low are less inclined to willingly pay their taxes because they have doubts about how the government will put their money to good use. This sets in motion a self-perpetuating loop: less trust means less money for the government to spend on necessities, which means less trust again. Reduced trust results in fewer benefits and greater costs for society and the government. The country in question is a great example of how widespread tax evasion made Greece’s budget problems worse during the economic crisis of 2008–2015.⁴⁹ Tax evasion made the government’s financial problems worse and slowed down the economy’s recovery because people did not trust government institutions and thought they were corrupt. The fact that Greece has not been able to catch up with other European Union (EU) economies on time, which is partly due to a lack of trust in institutions, backs up the model’s prediction that these economies will not reach convergence on time.⁵⁰

Low-trust societies also tend to have a policy climate that puts short-term populist solutions ahead of investing in public goods.⁵¹ Short-term political gain policies include things like subsidies and cash transfers. Governments may use these instead of investing in long-term growth drivers like infrastructure, innovation, and education. These populist policies influence the economy even more because they do not create long-term benefits and often depend on borrowing more money or lowering reserves. This makes economies more vulnerable to shocks from outside sources. In countries where people do not trust each other, more money may be spent on welfare and public services, but the returns on investment are usually lower because of waste.⁵² There is a lot of social inequality, and people do not trust the government in South Africa and other low-trust economies.⁵³ This means that even big welfare programs do not help break down poverty or bring people together. Corruption and waste of resources in welfare programs are common because people do not trust institutions, which makes inequality worse. The model shows that the social and economic costs of staying in a low-trust state can make things stay the same for a long time. Venezuela is a great example of this dynamic at work. The country’s hyperinflation, economic collapse, and large-scale migration are all caused by widespread distrust of the government, as well as bad economic management and corruption.⁵⁴ When trust is low for a long time, it gets passed down from one generation to the next, creating a weak economy with few chances to move up. The model predicts that low-trust economies will not be able to break out of their underperformance cycle for many years, if not decades. These wide-ranging effects are in line with that prediction.

Statement

This research uses the Markov process to explore two economies, one with a lot of trust and the other with little trust. The idea behind this is that trust affects ­economic growth. An economy is said to be close to equilibrium when it takes a certain number of cycles to reach a steady state. People see convergence in fewer iterations as an important and positive sign of economic progress and efficiency. More stable institutions, lower transaction costs, economic integration, and better social welfare are all signs of faster convergence. Delays in convergence, on the other hand, show that economies that do not trust each other are less efficient, have higher costs, and grow less quickly. This study shows how trust is important for deciding how an economy grows and how likely it is to keep growing over the long term.

Methodology

We used a Markov process to model and compare two different economies: a high-trust economy (Ga) and a low-trust economy (Gb). Our goal was to find out how trust affects economic growth and convergence. We were able to simulate how trust levels change over time in each economy and see how these changes affect things like the rate of convergence to equilibrium and economic efficiency. According to the mathematician Andrey Markov, a Markov process is a way to model systems that change from one state to another based on chance. The most important thing about a Markov process is its memorylessness, which means that the system’s future state depends only on its present state and not on the events that came before it. Because of this, the Markov process is perfect for modeling random processes where the past state doesn’t help with predicting the future state. The Markov process works well for our study because it shows how trust changes over time in an economy. People’s trust in each other, institutions, and the government can change based on their current interactions and experiences. The Markov process takes into account the fact that these changes in trust are uncertain and random. In addition, it gives us mathematical tools, like transition matrices and eigenvalues, to look at how the economy changes over time and how it converges.

Description of Variables

To effectively model the economies using the Markov process, we defined several key variables and parameters. Table 1 provides an overview of the variables used in the study along with their descriptions and roles in the model.

Table 1: Variables Used in the Study
Symbol	Description	Role in the Model
C	Set of trust states: C = {c0, c1, c2, . . . ,cn}	Represents the discrete levels of trust within the economy, capturing variations in interpersonal, institutional, and governmental trust
ci	Trust state i	A specific level of trust in the economy; each ci is a state in the Markov chain
mi(t)	Probability of being in trust state ciat time t.	Indicates the likelihood that the economy is in trust state ciat time t; components of the state probability vector
m(t)	State probability vector at time ttt: m(t)=[m0(t),m1(t),…,mn(t)]	Represents the distribution of trust levels across all states at time ttt; evolves over time according to the transition matrix
P	Transition matrix P= [Pij ]	A stochastic matrix containing transition probabilities between states; governs the evolution of trust levels over time
Pij	Transition probability from state cito state cj: P{ij } = P{cj }
π*	Steady-state (stationary) distribution: π * = [π *0, π *1, … ,π *n ]	Represents the long-term stable probabilities of being in each trust state; satisfies               π * = π * P
λI	Eigenvalues of the transition matrix PPP	Used to analyze the convergence properties of the Markov chain; λ1 = 1 is the largest eigenvalue.
δ	Spectral gap: (1 – | λ2 Ú |)
t	Time step (iteration)	Discrete time periods over which the Markov process evolves
n	Number of trust states	Determines the dimensionality of the transition matrix and state probability vectors

Modeling Trust in Economies

We showed each economy as a separate set of trust states, which we called C = {c_o,c₁,c₂, . . . , c_n }. Where each state ci represents a different level of trust in the economy. These levels cover different aspects of trust: In everyday life, people trust each other, which is called interpersonal trust. There is institutional trust, which means trust in businesses and financial institutions. Trust in the government means having faith in its actions, policies, and public institutions. The economy is in one of these trust states all the time. The chance that the economy will be in state ci at time t is shown by m_i (t). The probability vector m(0) = [m₀(0), m₁(0), . . . , m_n(0)] shows how the trust ­levels are spread out across the states at the start. Moreover, m_i(0) shows the chance of being in trust state ci at the start. Before any changes happened, this vector shows how trust levels were in the economy at the start. The way trust levels change over time is controlled by transition probabilities, which are shown in a transition matrix P. Each row and column of this matrix, P_ij, shows the chance of changing from state c_i at time t to state j at time t + 1:

State at
P_ij = P(State at t + 1 = c_j | State at t = c_i),   where,   ” i, jÎC

The matrix P is stochastic which means all elements P_ij ≥ 0 and the sum of the probabilities in each row is 1.

∑  P_ij = 1, for all ij

This makes sure that the total probability of all possible future states stays the same and that the model correctly shows how state transitions are based on chance. We made two different transition matrices that show how trust works in a high-trust and low-trust economy so that we could model them. People, institutions, and the government all trust each other a lot in a high-trust economy (Ga). There is a higher chance of keeping or growing trust levels in the transition matrix. This shows that trust leads to more trust in this environment. For instance, there is a good chance of going from a medium level of trust to a high level of trust. This shows that strong institutions and positive interactions lead to higher trust. The low-trust economy (Gb), on the other hand, has low levels of trust and makes it harder to build trust. The transition matrix shows that there are higher chances of staying at the same level of trust or going down to a lower level of trust. This shows how hard it is to be in this kind of environment. For example, things like weak institutions, corruption, or bad experiences in the past make it more likely for someone to go from a medium level of trust to a low level of trust.

Construction of Transition Matrix

i   Define Trust States: To show the states c_i, we came up with a limited number of discrete trust levels, such as low, medium, and high. This breaking down of the complex range of trust into manageable groups makes the model easier to understand while still capturing important dynamics.

ii  Assigning Transition Probabilities: We gave each possible state transition a probability (P_ij) based on theoretical insights and empirical evidence from the literature. (G_a), for example, has strong institutions and social norms, which makes it more likely that trust will stay the same or grow. In (G_b), trust levels are more likely to drop when there are a lot of breaches of trust or problems with institutions.

iii Stochastic: To make sure it was a stochastic matrix, we made sure that the sum of the probabilities in each row of the transition matrices was one. This step is very important to keep the model’s mathematical integrity.

iv  Theoretical Foundations: To make sure the model accurately represents how society works, we used well-known theories to help us decide how to assign probabilities. We put together ideas from French34 theory of social power and the DeGroot learning model (Jackson).⁵⁵

These theories have been around for a long time and explain how people and groups can affect each other’s trust levels. The DeGroot learning model says that people change what they believe by taking the average of what other people in their network reason. In our model, this idea means that people change how much they trust others based on their interactions with them. This is similar to how trust in society changes over time through social learning. According to French’s theory of social power,³⁴ other people can change someone’s mind through social power dynamics like authority, expertise, or referent power. We used this idea by letting people’s trust levels change based on how trustworthy other people are and how they act, including the government and institutions. For example, a trustworthy government policy could make people trust it more, while a scandal could make them not trust it as much. We looked at the Markov chains of both economies in a few key steps to figure out how trust levels change and how that changes the economy. We found the steady-state distribution

π* = π* P

which shows the long-term chances that the economy will be in each trust state. To do this, the equation with the condition that

∑  π_i* = 1, for all i

Here, π_i* is the steady-state probability of state c_i. If the Markov chain is irreducible and aperiodic, this distribution shows how likely it is that the economy will be in each trust level after a long time, no matter what its state was at the start. These are the eigenvalues of the transition matrix P that show how fast the Markov chain reaches a steady state. We found the eigenvalues of P, which are

1 = λ₁>|λ₂| ≥ |λ₃|≥ … ≥|λ_n|

The steady-state distribution is shown by the largest eigenvalue, λ₁ = 1. The spectral gap

δ = 1 – | λ2|

Because the initial conditions lose their effect more quickly, a bigger spectral gap means that the system is getting closer to the steady state more quickly. We found out which economy gets to equilibrium faster by comparing δ for (G_a) and (G_b). Because there is less need for long contracts, oversight, and enforcement in economies with high trust, transaction costs are lower. Trust makes business transactions go more smoothly and lowers the barriers to working together. When people and institutions trust each other, they are more likely to work together, which makes policy implementation and governance better. Also, economies with a lot of trust get to equilibrium faster, which helps growth and integration because trust speeds up changes and adaptations to new economic conditions.

Low-trust economies, on the other hand, have higher transaction costs because they depend more on the law and enforcement. Resistance and scepticism make governance less effective because people and groups may be less willing to follow rules or work together. Delayed convergence in these economies means that there may be inefficiencies and barriers that are getting in the way of growth and making economic differences worse. We modeled how trust changed over a number of time periods to see how close each economy gets to its steady state. The following steps were part of the simulation process:

i  First State: We started with an initial probability vector m(0) that showed how trust was distributed in the economy at the start.

ii  Iteration Process: We changed the state probabilities using the equation at each time step t.

m (t +1) = m(t) P,

This equation takes the current state and the transition probabilities to get the probabilities for the next state.

iii  Convergence Assessment: We kept going through the steps until the difference between
m(t) Ù m(t + 1) was very small. This meant that the trust level distribution had become stable.

iv Analysis of Differences: The number of iterations needed for the economy to reach a steady state.

Our method is based on some assumptions and is aware of its limitations. We assumed the Markov property, which means that the level of trust in the future will depend only on the current state and not on what happened in the past. This assumption makes the model easier to understand, but it might mean that path-dependent effects in real-life trust dynamics are missed. We also thought that the transition probabilities P_ij would stay the same over time. However, this might not be the case if there are outside shocks or changes in social conditions. To make things easier to manage, trust levels were broken down into a set number of states. This was done because trust is a complex and ongoing variable. The Markov process is a good way to model how trust changes over time in an economy because it takes into account the fact that trust changes cannot be predicted because they are based on probabilities. Because Markov chains are mathematically simple, they make it easy to look at convergence and long-term behavior. This helps us understand how trust affects economic outcomes. We can use this method to compare the two economies in a structured way and learn about the role of trust in economic growth and convergence.

Transaction cost economics explain that trust lowers transaction costs, which makes economic transactions easier and more efficient. Social capital theory says that trust is a type of social capital that encourages people to work together, coordinate their efforts, and take action as a group. This leads to better economic performance and more effective institutions. According to growth and convergence theories, trust affects things that make growth possible, like ­investment, innovation, and the smart use of resources. This changes how fast economies grow and converge. We used the Markov process to create a structured and detailed framework for modeling how trust levels change over time and how that changes the economic convergence. It also lets us compare and contrast the ways that economies with and without trust work. Our results help us understand how trust is a key part of economic growth and convergence. They also show how important it is to build trust in order to improve economic performance.

Results

We found that there was a difference in trust between the two economies in this paper. One had high trust, and the other had low trust. The Markov process was used to show how trust changes over time. We find out how stable and effective each economy is by keeping track of the time it takes to reach convergence and looking at the spectral gap of the transition matrices. The study also looks at the social and economic costs of slow convergence in trust-poor economies. This is proof of how important trust is for boosting economic growth, bringing people together, and making sure institutions work well.

High-Trust Economy G_a: Structural Connectivity and Growth Outcomes

This economy is defined as G_a in which some more trustworthy individuals form strong institutions, leading to a powerful state or government. It follows a pattern similar to French³⁴ and expands upon its trust matrix for the economy, its components of economic growth (GDP), and the relationships among individuals, institutions, and states. Afterwards, a transition matrix with zeros in specific places according to the degree of connectivity among system key players is created to display the interconnection among economic powerhouses. Following this, the absence of a transition from state i to state j is indicated by the zero at (i,j) in the transition matrix. When different participants in the economic process work together and have more confidence in one another, the number of zeroes in the transition matrix decreases, which means that the economy is getting closer to a steady state where prosperity is possible. The following is one way to represent the transition matrix, G_a (Table 2).

Table 2: Transition Matrix for Economy Ga

This matrix is designated for the transition of states at various intervals of time. For remaining in their states, there is probability (0.07399) P₁₁, (0.03737) P₂₂, (0.03778) P₃₃, (0.03803) P₄₄, (0.1321) P₅₅, (0.1569) P₆₆, (0.15) P₇₇, (0.1564) P₈₈, (0.08193) P₉₉, (0.1556) P_{1010, respectively}. Furthermore, the 1st row can be interpreted as individual 1 and how much trust he puts on other constituents of the respective group, exemplified as individual 1 has a probability of trust in himself (0.07) while he puts zero levels of trust in individual 3 in making economic transactions and decisions. Transition matrix G_a can also be demonstrated graphically as (Figure 1).

To examine changes in this proportion, a Markov chain is preferred. Consequently, these variables process through several iterations or steps before achieving convergence. Furthermore, a theorem was formulated by Wielandt⁵⁸ by suggesting that “Markov chain is ergodic if and only if all elements of Pm are positive for m = (n – 1)2 + 1. Whereas P is the transition and n are several states.” Further iterations demonstrate below how proportion changes independent of the initial vector (Table 3).

Table 3: Steady state after six iterations for the economy Ga.
Steady state	0.1109	0.1559	0.0422	0.1153	0.0960	0.0463	0.1077	0.1008	0.1202	0.1047

After six steps, convergence is achieved in the form of a steady state. According to the Perron-Frobenius theorem, to achieve ergodicity, or stationary distribution, to which every initial distribution converges, we must focus on irreducibility and aperiodicity.⁵⁹ To confirm whether our chain is ergodic, we run a logical test on our Markov chain Ga. Results for the test are logical (1), which indicates ergodicity, and visually confirms this by plotting its eigenvalues on the complex plane. In terms of economic performance, trust can decrease the costs of transactions, i.e., (monitoring, enforcing, evaluation, and contracts), and also increase the speed and quality of information diffusion through a network of individuals.⁶⁰ Trust also tends to solve ­problems associated with the principle agent mechanism, due to which individuals are able to devote his or her time to other innovative activities.⁶¹ Furthermore, interpersonal trust is most influential in defining economic growth differences among various countries.^62,63 Similarly, Johnson and Mislin⁶⁴ employed a trust game, proving the positive impact of trust on monetary ­outcomes (Figure 2).

The next step is to find the reducibility, G_a. “If every state is reachable from every other state in at most n − 1 steps, where n is the number of states,” states Galler65 indicating that the Markov chain is irreducible. The resulting equation, which contains all positive elements, is Q = (I + Z) n−1. I is the identity matrix. Concerning all values of i and j, the zero-pattern matrix of the transition matrix P is Z_ij = I (P_ij > 0). In addition, the Markov chain G_a is irreducible, as shown by the result logical 0 (Figure 3).

The high level of trust among individuals, institutions, and states is causing the economy to perform better, as shown in the graph above and the results. This trust increases components of GDP such as consumption, investment, and trade. “A foundational trust is essential for specialization and the ­accompanying economic growth.”⁶⁶ Since convergence is attained in less time, it implies that the trust-based system has a positive socio-economic effect on GDP components. In high-trust economies such as the Nordic countries (Denmark, Norway, and Sweden) and Switzerland, the benefits of trust on economic performance are both profound and well-documented.⁶⁷ These countries consistently rank among the top in global measures of GDP per capita, quality of governance, and overall societal well-being. A significant factor contributing to this success is the high level of trust between citizens, institutions, and the state, which fosters an environment conducive to economic cooperation and lower transaction costs.

For instance, Delhey et al.’s⁶⁸ research shows that trust and economic outcomes are very closely linked in the Nordic countries, which are often seen as world leaders in social trust. In these types of economies, trust means that people are more likely to follow social rules and laws without the need for extensive and expensive enforcement mechanisms. This is especially clear in Denmark, where trust in the courts and other government buildings has been shown to make both public policy and the private sector more active.⁶⁹ For example, the Danish government’s social welfare programs, like healthcare and education, work very well because there isn’t much fraud and corruption.⁷⁰ People in Denmark are more likely to pay their taxes because they believe the money will be used for the good of everyone.⁷¹ This trust also speeds up economic integration and convergence in the area, which helps Denmark keep its high standard of living while encouraging new ideas and business.

When people trust one another, it makes dealing with the job market easier in both Norway and Sweden. Social partners in these nations’ labor markets—unions, employers, and the government—join forces to formulate policies that benefit everyone involved.⁷² Reduced workplace conflicts and increased output are the results of this cooperative strategy based on mutual trust. Trust in Switzerland’s decentralized political system is high because it permits strong local governance and widespread public participation in policymaking via referendums.⁷³ Because people have faith in the government, they are more likely to follow the rules when it comes to paying taxes, which reduces the likelihood of tax evasion and increases the amount of money the government gets. Similarly, Sweden has produced world-leading companies in sectors like technology and pharmaceuticals thanks to its trusted education and research system, which has encouraged a culture of innovation. Because their citizens have faith in their institutions, these nations can take calculated risks in policymaking, knowing that their citizens will back projects with a clear path to long-term prosperity.

Economy G_b: Low Trust, Social Fragmentation, and Economic Stagnation

In this economy, there is a low level of trust prevailing among individuals, which may result in weak institutions in the long run that may cause inefficiency in government policies and may hinder the economic growth process. Subsequently, less connectivity, lack of coordination, and weaker trust among key players in the economic process are shown by the more specified number of zeros in random locations. Transition matrix Gb can be represented below as (Table 4).

Table 4: Transition Matrix for Economy Gb.

Researchers have gone into detail about how our social and economic differences make us feel threatened by people who are different from us, which in turn causes us to have less trust in one another.⁷⁴ Such a group may be defined by religious, racial, or language characteristics or by income disparities that threaten to undermine the trust’s financial gains. Hence, the choices that people put their trust in themselves or other group members are represented by zeros in our matrix. We discovered that the results are consistent with the findings of Banerjee.^75,76 Looking at it from a micro perspective, it is clear that people’s experiences with discrimination or their membership in a particular group have a significant impact on their level of interpersonal trust.⁷⁷ State transitions at different time intervals are denoted by this matrix. To stay in their own states, (P₁₁, P₂₂, P₃₃, P₄₄, P₅₅, P₆₆, P₇₇, P₈₈, P₉₉, P₁₀₁₀ = 0) are all equal to zero. Another way to visually represent the transition matrix (G_b) is as (Figure 4).

There is a noticeable contrast between the previous example and the one that follows. Because there is no trust-based economy in Gb Huge gaps are visible. There are vectors in the transition matrix (Gb) that are defined by the function f(T), with y being GDP. The Markov chain is the preferred method for analyzing changes in this proportion. So, these variables go through a series of steps or iterations before they finally converge
(Table 5).

Table 5: Steady State After 38 Iterations for Economy B.
Steady state	0.1556	0.0552	0.1020	0	0.0833	0.1794	0.0320	0.1554	0.0552	0.1818

After 38 iterations, convergence is achieved in the form of a steady state. To confirm whether our chain is ergodic, we run a logical test on Gb. Results for the test are logical 1, which does not indicate ergodicity, and visually confirm this by plotting its eigenvalues on the complex plane (Figure 5).

There are several costs associated with the formulation of trust; the more there is distrust, there will be more price in terms of construction and self-assurance. If the trust of a customer fails in one person in the company, it might lead to distrust by the consumer of the whole company or its all products.⁷⁸ So, it is difficult to gain trust, but once gain net more difficult is to maintain it. Similarly, we can resemble trust as capital with people around us (Figure 6).

Figure 5 indicates that the economy Gb is not performing better because of the presence of weaker trust among individuals, states, and institutions. Therefore, this system took a longer duration of time to achieve convergence, suggesting a negative socio-economic impact of trust on GDP. Similarly, Aasvi et al.⁷⁹ confirm the relationship between epidemics and trust. They suggest that when there is a decline in social connection and decreased generalized trust during a pandemic, it has a long-term influence on the behavior of individuals by lowering their social trust for a longer period that can even tend to pass on to descendants of individuals.

In low-trust economies, such as Venezuela and Zimbabwe, the impact of weakened social cohesion and institutional distrust is starkly visible in the form of economic stagnation, institutional inefficiencies, and delayed convergence.⁸⁰ The failure of government institutions to provide basic services, such as reliable food supplies and healthcare, has further deepened mistrust, resulting in social fragmentation. The government’s inability to maintain transparency or accountability has led to rampant tax evasion, with individuals and businesses seeing little reason to contribute to a system they perceive as corrupt and ineffective.⁸¹ As the model suggests, the absence of trust in government institutions means that transaction costs, such as enforcement and monitoring, rise significantly, contributing to the delayed convergence of Venezuela’s economy toward a stable state. A lack of trust in institutions and systemic economic inefficiencies have resulted from Zimbabwe’s political and economic policies, which Muzurura⁸² analyzes as being marked by a lack of transparency and rampant corruption.

Due to a decline in trust in official financial institutions, many Zimbabweans began conducting business on the black market or informally.⁸³ The state’s fiscal crisis has worsened, and essential public services have been impacted as a result of this change because the government is less able to collect taxes. State functions are either monopolized by elites or rendered useless by corruption and inefficiency, as seen in Venezuela, where public trust in public institutions has eroded and led to a collapse in governance. Transaction costs are high, cooperation is minimal, and economic integration is severely hindered in both Venezuela and Zimbabwe due to low levels of trust in government and institutions. This study’s model implies that these high costs and inefficiencies cause low-trust economies to have delayed convergence. The result has been that neither Venezuela nor Zimbabwe are part of global trade networks, meaning they can’t benefit from international partnerships or domestic economic unity to boost their economies.

Discussion

This research uses the Markov process to model changes in trust levels and then compares and contrasts the effects of high trust (economy Ga) and low trust (economy Gb) economies on their respective economic outcomes. The results highlight various important points about the ways trust affects economic development, convergence, and society’s socioeconomic fabric as a whole.

Convergence Speed and Economic Efficiency

In terms of time to steady-state equilibrium, the high-trust economy (Ga) outperforms the low-trust economy (Gb). It takes six iterations for the first one to reach this state, but 38 iterations for the second one. As other studies have shown Alder et al.84 and Palley,85 this result backs up the idea that trust is important for lowering transaction costs, speeding up economic integration, and making institutions work better. Trust acts like an economic lubricant, making it easier and more common for people, businesses, and the government to do business with each other. The larger spectral gap is seen in the economy Ga is more proof that higher trust levels speed up mixing times, which helps economies reach equilibrium more quickly. The speeding up of convergence could be seen as a sign of a strong economy, one with lots of social capital and institutions. According to Glatz and Eder,⁸⁶ there is a link between high levels of social trust and better economic stability and growth, which is consistent with our work.

Furthermore, the research highlights the important benefits of trust in raising tax revenues and lowering the amount of money spent on rehabilitation and corrections. The Markov chain explains that in a high-trust economy (Ga), people are more likely to pay their taxes and the government is less likely to punish corrupt people. As with other studies, this result shows that trust makes people more likely to pay their taxes and makes it cheaper to enforce the law.⁸⁷ In a low-trust economy (Gb), on the other hand, crime-fighting programs, police patrols, and enforcement have higher social costs. This is because they use up resources that could be better spent on other things. Gb Convergence is slowed down by these inefficiencies. Mistrust negatively impacts developing countries and people’s well-being.⁸⁸

The results also show that when people trust each other, institutions get stronger, which helps the economy grow. In Economy (Ga), strong connections between people, groups, and the government are shown by fewer zeroes in the transition matrix. This easy flow of information supports specialization, investment, and trade, which are the three main drivers of economic growth. Economy Ga has a weaker institutional framework depicted through more zeroes in the transition matrix. This means that important players in the economic process do not work together. Institutional fragmentation caused by mistrust slows down economic growth and integration.^89,90 This backs up what other research has found, as economies with low trust have bad policies, institutions that do not efficiently work, and bad performance on international markets.⁹¹

In addition to Venezuela and Zimbabwe, other countries such as Brazil and Greece offer further examples of how low levels of trust can significantly impede economic growth, foster social fragmentation, and lead to delayed economic convergence. Both countries have struggled with institutional inefficiencies, widespread corruption, and social inequality, which have undermined trust in their governments and institutions, leading to poor economic performance. Corruption scandals, political instability, and inequality have contributed to a general lack of faith in public institutions in Brazil, which has undermined the country’s economy despite its status as one of Latin America’s biggest economies.⁹² Operation Car Wash (Lava Jato), one of several high-profile corruption scandals that rocked the nation in the last decade, revealed pervasive bribery and corruption within the country’s political elites and big state-owned companies like Petrobras.⁹³ Many Brazilians have become disillusioned with the political elite and the rule of law as a result of these scandals, which have severely damaged public faith in government institutions.

Excessive public debt, wasteful spending, and ineffective leadership were all exposed by the Greek debt crisis of 2008, which had been brewing for some time.⁹⁴ The lack of confidence between the Greek people and the government was a major cause of the country’s protracted economic crisis. A vicious cycle was set in motion: when tax evasion reduced government revenues, public spending had to be cut, leading to even lower quality services and more distrust. During the height of the debt crisis, the Greek government implemented austerity measures under pressure from international creditors, which led to widespread social unrest, strikes, and protests.

Italy is another example where low trust in public institutions, particularly in the southern regions, has contributed to economic stagnation and regional inequality.⁹⁵ Trust in the Italian government and institutions, especially in regions like Sicily, Calabria, and Campania, is among the lowest in Europe, largely due to the historical presence of organized crime, corruption, and bureaucratic inefficiency. The persistent trust gap between northern and southern Italy has hindered national economic integration and slowed down overall convergence with other advanced European economies.⁹⁶ Nigeria provides another powerful example of how low levels of trust in government and institutions can obstruct economic growth. As a result, Nigeria’s economy has struggled to diversify beyond oil, and its efforts to integrate more fully into the global economy have been hampered by these governance and trust issues.^97,98

These examples align with the theoretical predictions of the trust-based economic model, demonstrating that trust is a fundamental component of economic performance and integration. Without trust, economies struggle to reach equilibrium, as institutional inefficiencies and social fragmentation hinder growth and cooperation, delaying their convergence with more stable, high-trust economies. Building and keeping trust should be a top priority for government efforts to make institutions work better and lower transaction costs. Governments can help build trust by being more open and honest with their citizens, fighting corruption, and promoting unity in society through policies that treat everyone the same and do not depend on their income. To increase social capital and economic growth, we need good governance and fair policies. Institutional reforms should be prioritized by other economies with low trust to increase society’s trust, decrease corruption, and strengthen law enforcement. To restore public trust and boost the economy, policymakers could strive to strengthen the rule of law, increase transparency in government operations, and hold officials accountable.

Implications for Evidence-Based Policymaking

Important implications for policymaking in economic development and other areas lacking evidence-based decision-making arise from this study’s findings. That trust is more than simply a social or cultural factor that can influence economic performance. Governments should prioritize programs that encourage trust between individuals and institutions if they wish to reap the benefits of trust, which include improved governance and greater economic integration.

Legislators who value transparency and accountability in government can implement these findings. Government transparency is crucial for building trust in economies plagued by low trust, where inefficiency and corruption are prevalent. Changes that increase accountability, decrease corruption, and promote the rule of law can restore public trust in government agencies. Several steps can be taken to address the perception of institutional failure. These include strengthening law enforcement mechanisms, ensuring judicial independence, and establishing autonomous anti-corruption agencies. Through more transparent policy dialogues and participatory budgeting, citizens can feel more invested in the decision-making process and their governments and institutions. These steps, backed by model data, show that trust can be established in a systematic way, which has long-term benefits for economic growth and stability.

There must be policies that encourage inclusive economic growth and decrease inequality if societies are to build trust. Health care, education, and social services are examples of public goods; governments should consider policies that expand access to them because they are more likely to have long-term effects in reliable communities. Economic integration and convergence are both accelerated in more trusting economies, according to the model, due to lower transaction costs and stronger institutional frameworks. Investments in social infrastructure should be considered by governments as a means to foster confidence.

An additional advantage of growing international trust is, generally speaking, improved economic relations between countries. To simplify international trade and reduce reliance on complex legal systems, the study highlights the significance of trust. There is a positive correlation between a country’s level of international trust and its capacity to negotiate trade agreements, resolve disputes swiftly, and avoid protectionist policies. Governments can improve their global competitiveness through diplomatic efforts that prioritize trust-building with foreign partners and transparent trade policies. By adhering to international standards and participating in multilateral trade agreements, a country can enhance its reputation as a reliable trading partner. Mutual trust between countries is the key to more open and efficient global markets, which benefit both developed and developing economies.

Predictions regarding the relationship between trust and efficient tax collection are one of the more realistic and achievable parts of the model. Societies where trust is low tend to have lower government revenues and higher social costs due to the prevalence of tax evasion. When citizens in high-trust societies are more likely to pay their fair share in taxes, governments in these societies can spend more on public goods without increasing enforcement efforts. For proponents of this view, building trust between the government and its citizens is the key to increasing tax income and compliance. Making sure people can see their tax dollars going towards good causes is one way to make them feel good about paying them. This may manifest as overt upgrades to public facilities or social services. Government trust and efficiency would both rise as a result of these policies, which would be good for the economy in the long term. Another potential use of the model is to enhance the dynamics of the labor market. Businesses and workers alike reap the benefits of cooperative labor markets in nations with high levels of trust. Workers’ rights, corporate-labor harmony, and fair labor practices can all be advanced through legislative action by governments. As a result, confidence in the labor market would grow, industrial disputes would decrease, and productivity would rise. Due to the stability of labor relations, businesses can invest in long-term projects more frequently in high-trust environments.

Politicians should consider trust-building mechanisms when thinking about innovation and entrepreneurship. An important factor in fostering innovation and economic growth, the study found that trust lessens risk aversion and promotes entrepreneurial endeavors. Supportive regulatory environments, financial incentives for startups, and protections for intellectual property are ways in which governments can encourage innovation ecosystems. Entrepreneurs are more willing to take chances, invest in new tech, and work with others in nations with high levels of trust in institutions because they know the systems will back them up. So, to stimulate economic dynamism, policymakers should work on making it easier for innovators, investors, and institutions to trust one another. Our work has extensive and realistic implications for evidence-based policymaking. Transparency, inequality reduction, public goods investment, tax compliance, international trust, and innovation promotion are all trust-building strategies that governments can employ to boost their economic performance. Building trust is essential for efficient, cooperative, and integrated economies. Policies based on evidence can accelerate growth and foster more cohesive societies by prioritizing trust-building.

Limitations

The study helps us understand how important trust is for economic convergence, but it has some limitations that should be fixed in later research. The model starts with trust and assumes that all other factors stay the same. Nevertheless, in real life, other things such as changes in technology, the buildup of capital, and rules for international trade also have big effects on economic outcomes. In the future, these extra variables could be added to this model so that researchers can better understand how trust and other economic growth drivers work together. There is also no data used in this study; instead, theoretical modeling is used. Cross-country data should be used in future research to confirm these results through empirical analysis since the Markov process does make good predictions about how economies will act based on trust levels. Comparing emerging markets to more developed economies through research can also help us understand how important trust is in these processes of coming together and integrating.

Future Directions for Research

There are several important areas where future research can build upon this study’s findings. Evaluating the trust-based economic model with big international datasets is an encouraging step in the right direction. This study lays the theoretical groundwork for future research that could use quantitative analysis to validate the relationships between trust and economic growth and convergence. Trust levels, governance, and economic indicators can be gleaned from a wealth of data sets, including those from the European Social Survey, the World Values Survey, and international organizations like the World Bank and the International Monetary Fund. Possible areas of investigation include the effects of trust differences on trade patterns, investment flows, and GDP growth across nations. If we were to compare the Nordic nations, which have a high level of trust, with developing nations, which have a lower level of trust, we could see how trust affects economic outcomes in different contexts. Also helpful would be longitudinal studies that track people over time to see how their trust levels change and how that affects their economic performance in the long run. The theoretical model could be improved and made more applicable to various economic situations by including time-series analysis in future studies that examine the impact of changes in social trust on growth trajectories.

Future studies should also focus on how to incorporate digital trust and other technical developments into the framework. As economies continue to digitize more and more, understanding the mechanics of trust in online transactions, digital governance, and cybersecurity is crucial. Digital platforms, e-commerce, and decentralized technologies like blockchain rely on trust, which differs from traditional face-to-face interactions. To better understand how communities adapt to new technologies and how this adaptation impacts economic convergence, it may be instructive to examine the evolution of digital trust within the context of the modern economy. Consider how global trade, technological development, and monetary union might be impacted by people’s faith in online platforms, banks, and virtual currencies. Future research might look at how various policies, such as cybersecurity laws, data privacy regulations, and digital literacy initiatives, have affected local and global economies to boost public trust in digital platforms. With this data in hand, policymakers would be better equipped to foster an environment where users feel safe expressing themselves online, which could speed up the growth of digital economies and encourage more economic integration.

The role of trust in the reaction to economic shocks such as pandemics or financial crises is another possible topic for future research. The COVID-19 pandemic proved that countries with more social and institutional trust were better able to manage public health and economic resilience. How trust influences the effects of these shocks on economic recovery and stability might be the subject of future research. A better understanding of this dynamic will shed light on the importance of trust in sustaining economic resilience during crises. In addition, research could look at how trust affects the effectiveness of recovery efforts; this would provide light on how to restore faith in areas that have been devastated by societal or economic changes. In the process of refining the theoretical model, corporate and governmental leaders would obtain useful information about how to foster trust for the benefit of the economy in the long run.

Conclusion

The main reason for this study was to find out how trust affects economic growth and institutional efficiency based on the time rate of attaining convergence. We used the Markov process to model the dynamics of two economies: Economy Ga, which had high trust, and Economy Gb, which had low trust. This allowed us to explore how trust affected the rate of convergence to equilibrium and the effects on the economy. The results show that trust helps economies work together, lowers transaction costs, and makes institutions run effectively.

The study found that equilibrium was reached much faster in the high-trust economy (Economy. Ga) than in other economies. This quick convergence shows that when trust is present, everyone can work together more easily, including individuals, institutions, and the government. People are more likely to work together when they trust each other. This is good for the economy because it means fewer enforcement tools are needed. Productivity is increased as a result of these factors, which lead to reduced transaction costs and better information sharing. Better government, more effective public spending, and higher tax compliance are all outcomes of high-trust economies’ robust institutional frameworks. This leads to the government spending less on social costs like rehabilitation and crime prevention programs and more on maximizing tax revenues.

Consistent with previous studies, our results highlight the significance of trust in attaining economic efficiency. Economic growth is facilitated by trust, which permits specialization, promotes long-term investment, and backs more open trade policies. Higher GDP per capita, greater social welfare, and enhanced global trade integration have all been associated with nations with high levels of interpersonal and institutional trust, such as Norway, Denmark, and Switzerland. Trust promotes economic growth, which in turn strengthens institutional stability and public trust, creating a positive feedback loop from which these countries reap the benefits. Contrarily, it took 38 iterations for the low-trust economy to reach equilibrium, showing considerably slower convergence. We can see the inefficiencies of low-trust societies in the length of time it takes to reach economic stability. Disintegrated social interactions, ineffective institutions, and rampant corruption result from a lack of trust in these economies. Lack of trust reduces the efficacy of institutions and economic coordination, and the results demonstrated that ­people in low-trust settings are less inclined to collaborate. Consequently, more funds are directed towards crime prevention, enforcement, and monitoring because tax evasion is so common.

Delays in convergence are a reflection of the societal and economic costs of low trust. Spending more on social services, such as rehabilitation programs and enforcement mechanisms, takes money that could be put to better use elsewhere. Weak institutions and low trust make it harder for the economy and society to grow and stay together over the long term, which is called a vicious cycle of inefficiency. The results are in line with research that shows how lack of trust has made economic problems and social unrest worse in places like South Africa, Brazil, and Venezuela. Governments should foster long-term prosperity by fixing institutions, making policies that include everyone, and building trust through transparency. Because trust is multifaceted and impacts numerous critical economic variables, such as technology, governance, and globalization, more study is required in the future. With a deeper understanding of the link between trust and economic performance, scholars and policymakers can devise strategies to leverage trust for sustainable economic growth in an interconnected global economy.

Disclosure statement

We wish to confirm that there are no known conflicts of interest associated with this publication, and there has been no significant financial support for this work that could have influenced its outcome.

References

1 Williamson OE. Calculativeness, trust, and economic organization. J Law Econ. 1993;36(1, Pt 2):453-86.
https://doi.org/10.1086/467284
 
2 Conlisk J. Why bounded rationality? J Econ Literat. 1996;34(2):669-700.
 
3 Delhey J, Newton K. Predicting cross-national levels of social trust: global pattern or Nordic exceptionalism? Euro Sociol Rev. 2005;21(4):311-27.
https://doi.org/10.1093/esr/jci022
 
4 Newton K, Zmerli S. Three forms of trust and their association. Euro Politic Sci Rev. 2011;3(2):169.
https://doi.org/10.1017/S1755773910000330
 
5 Berg J, Dickhaut J, McCabe K. Trust, reciprocity, and social history. Game Econ Behav. 1995;10(1):122-42.
https://doi.org/10.1006/game.1995.1027
 
6 Rick S. Losses, gains, and brains: neuroeconomics can help to answer open questions about loss aversion. J Consum Psychol. 2011;21(4):453-63.
https://doi.org/10.1016/j.jcps.2010.04.004
 
7 Morewedge CK. Utility: Anticipated, experienced, and remembered. The Wiley Blackwell Handbook of Judgment and Decision Making. 2015;2:295-330.
https://doi.org/10.1002/9781118468333.ch10
 
8 Zak PJ, Knack S. Trust and growth. Econ J. 2001;111(470):295-321.
https://doi.org/10.1111/1468-0297.00609
 
9 Arrow KJ. Gifts and exchanges. Philos Public Aff. 1972;343-62.
 
10 Helliwell JF, Putnam RD. Economic growth and social capital in Italy. East Econ J. 1995;21(3):295-307.
 
11 Knack S, Keefer P. Does social capital have an economic payoff? A cross-country investigation. Quarter J Econ. 1997;112(4):1251-88.
https://doi.org/10.1162/003355300555475
 
12 Bjørnskov C. The happy few: cross-country evidence on social capital and life satisfaction. Kyklos. 2003;56(1):3-16.
https://doi.org/10.1111/1467-6435.00207
 
13 Bjørnskov C, Dreher A, Fischer JA. ross-country determinants of life satisfaction: exploring different determinants across groups in society. Social Choice Welfare. 2008;30(1):119-73.
https://doi.org/10.1007/s00355-007-0225-4
 
14 Cavallaro E, Villani I. Club convergence in EU countries. J Econ Integration. 2021;36(1):125-61.
https://doi.org/10.11130/jei.2021.36.1.125
 
15 Togan S. Technical barriers to trade: the case of Turkey and the European Union. J Econ Integration. 2015;121-47.
https://doi.org/10.11130/jei.2015.30.1.121
 
16 Shah SS, Shah SAH. Trust as a determinant of social welfare in the digital economy. Soc Netw Anal Mining. 2024;14(1):79.
https://doi.org/10.1007/s13278-024-01238-5
 
17 Putnam RD, Leonardi R. Making Democracy Work: Civic Traditions in Modern Italy. Princeton University Press. 1993.
https://doi.org/10.1515/9781400820740
 
18 Woolcock M. Social capital and economic development: Toward a theoretical synthesis and policy framework. Theory Soc. 1998;27(2):151-208.
https://doi.org/10.1023/A:1006884930135
 
19 Rotter JB. Interpersonal trust, trustworthiness, and gullibility. Am Psychol. 1980;35(1):1.
https://doi.org/10.1037/0003-066X.35.1.1
 
20 Coleman JS. Commentary: Social institutions and social theory. Am Sociol Rev. 1990;55(3):333-9.
https://doi.org/10.2307/2095759
 
21 Mikiewicz P. Social capital and education-An attempt to synthesize conceptualization arising from various theoretical origins. Cogent Educ. 2021;8(1):1907956.
https://doi.org/10.1080/2331186X.2021.1907956
 
22 Fukuyama F. Trust: The Social Virtues and the Creation of Prosperity (Vol. 99). Free Press. 1995.
 
23 Warren A, Gibson C. The commodity and its aftermarkets: Products as unfinished business. Econ Geography. 2021;97(4):338-65.
https://doi.org/10.1080/00130095.2021.1939007
 
24 Chandler AD. Organizational capabilities and the economic history of the industrial enterprise. J Econ Perspect. 1992;6(3):79-100.
https://doi.org/10.1257/jep.6.3.79
 
25 Easterly W, Ritzen J, Woolcock M. Social cohesion, institutions, and growth. Econ Politics. 2006;18(2):103-20.
https://doi.org/10.1111/j.1468-0343.2006.00165.x
 
26 Micallef B. Real convergence in Malta and in the EU Countries after the financial crisis. J Econ Integration. 2020;35(2):215-39.
https://doi.org/10.11130/jei.2020.35.2.215
 
27 Ingianni A, Žd’árek V. Real convergence in the new member states: myth or reality? J Econ Integration. 2009;294-320.
https://doi.org/10.11130/jei.2009.24.2.294
 
28 Hillberry R, Zurita C. Commitment behaviour in the World Trade Organization’s trade facilitation agreement. World Economy. 2022;45(1):36-75.
https://doi.org/10.1111/twec.13165
 
29 Putnam RD. Bowling Alone: The Collapse and Revival of American Community. Simon Schuster. 2000.
https://doi.org/10.1145/358916.361990
 
30 Di Cagno D, Sciubba E. Trust, trustworthiness and social networks: Playing a trust game when networks are formed in the lab. J Econ Behav Organ. 2010;75(2):156-67.
https://doi.org/10.1016/j.jebo.2010.04.003
 
31 Yamagishi T. Trust as a form of social intelligence. 2001.
 
32 Lin N, Fu YC, Hsung RM. Measurement techniques for investigations of social capital. Social Capital Theory Res. 2001;4:57-81.
https://doi.org/10.4324/9781315129457-3
 
33 Sofianos A. Self-reported & revealed trust: Experimental evidence. J Econ Psychol. 2022;88:102451.
https://doi.org/10.1016/j.joep.2021.102451
 
34 French Jr, JR. A formal theory of social power. Psychol Rev. 1956;63(3):181.
https://doi.org/10.1037/h0046123
 
35 Guiso L, Sapienza P, Zingales L. Does culture affect economic outcomes? J Econ perspectives. 2006;20(2):23-48.
https://doi.org/10.1257/jep.20.2.23
 
36 Shah SAH, Shah T, Ahmad E. Equilibrium in economic development a perspective of social capital. 2011.
 
37 Delhey J, Newton K. Social Trust: Global Pattern or Nordic Exceptionalism? (No. SP I 2004-202). WZB Discussion Paper. 2004.
 
38 Holmberg S. Social trust-the Nordic gold? 2020.
 
39 Sønderskov KM, Dinesen PT. Danish exceptionalism: Explaining the unique increase in social trust over the past 30 years. Euro Soc Rev. 2014;30(6):782-95.
https://doi.org/10.1093/esr/jcu073
 
40 Huber RA, Wicki M. What explains citizen support for transport policy? the roles of policy design, trust in government and proximity among Swiss citizens. Energ Res Soc Sci. 2021;75:101973.
https://doi.org/10.1016/j.erss.2021.101973
 
41 Kübler D, Rochat PE, Woo SY, Van der Heiden N. Strengthen governability rather than deepen democracy: why local governments introduce participatory governance. Int Rev Admin Sci. 2020;86(3):409-26.
https://doi.org/10.1177/0020852318801508
 
42 Xiao H, Scott I, Gong T. Trust and effectiveness in corruption prevention. China Rev. 2022;22(2):145-70.
 
43 Addi HM, Abubakar AB. Investment and economic growth: do institutions and economic freedom matter?. Int J Emerg Market. 2024;19(4):825-45.
https://doi.org/10.1108/IJOEM-07-2021-1086
 
44 Brinkerhoff DW, Goldsmith AA. Clientelism, patrimonialism and democratic governance: an overview and framework for assessment and programming. US Agency Int Develop Office Democ Govern. 2002;1:49.
 
45 Williamson OE. The theory of the firm as governance structure: from choice to contract. J Econ Perspect. 2002;16(3):171-95.
https://doi.org/10.1257/089533002760278776
 
46 Jenne N, Martínez R. Domestic military missions in Latin America: civil-military relations and the perpetuation of democratic deficits. Euro J Int Sec. 2022;7(1):58-83.
https://doi.org/10.1017/eis.2021.25
 
47 Ndakaripa M. Zimbabwe’s economic meltdown: are sanctions really to blame? Washington Quarter. 2021;44(2):95-120.
https://doi.org/10.1080/0163660X.2021.1934997
 
48 Nimer K, Bani-Mustafa A, AlQudah A, Alameen M, Hassanein A. Public perceptions of governance and tax evasion: insights from developed and developing economies. J Financ Report Account. 2022.
https://doi.org/10.1108/JFRA-06-2022-0234
 
49 Richardson M. Tax reforms and debt in Greece after the financial and economic crisis: Insights and challenges for tax policymaking in times of emergency. Int’l Tax Stud. 2020;2.
https://doi.org/10.59403/1ywraf1
 
50 Borsi MT, Metiu N. The evolution of economic convergence in the European Union. Emp Econ. 2015;48:657-81.
https://doi.org/10.1007/s00181-014-0801-2
 
51 Yin L, Zestos GK, Michelis L. Economic convergence in the European Union. J Econ Int. 2003:188-213.
https://doi.org/10.11130/jei.2003.18.1.188
 
52 Brezzi M, González S, Nguyen D, Prats M. An updated OECD framework on drivers of trust in public institutions to meet current and future challenges. 2021.
 
53 Keefer P, Scartascini C. Trust: The key to social cohesion and growth in Latin America and the Caribbean. Inter-American Development Bank. 2022.
https://doi.org/10.18235/0003792
 
54 Velasco A. The Many Faces of Chavismo: Beyond polarized interpretations, revisiting Chavismo’s long origins and many mutations reveals a political project marked more by adaptation and contradiction than by rigid ideological lines. NACLA Report Am. 2022;54(1):20-73.
https://doi.org/10.1080/10714839.2022.2045098
 
55 Jackson MO. Social and Economic Networks. Princeton University Press. 2010.
https://doi.org/10.2307/j.ctvcm4gh1
 
56 Lay DC. Linear Algebra and Its Applications. Pearson Education India. 2003.
 
57 Johnson CR, Horn RA. Matrix analysis. Cambridge university Press. 1985.
 
58 Wielandt H. An extremum property of sums of eigenvalues. Proc Am Math Soc. 1955;6(1):106-10.
https://doi.org/10.1090/S0002-9939-1955-0067842-9
 
59 Cohen JE. Ergodic theorems in demography. Bull Am Math Soc. 1979;1(2):275-95.
https://doi.org/10.1090/S0273-0979-1979-14594-4
 
60 Plichta J, Plichta G. Artificial intelligence as a factor in reducing transaction costs in the virtual space. In Artificial Intelligence, Management and Trust 2023 (pp. 161-85). Routledge.
https://doi.org/10.4324/9781003311409-11
 
61 Guiso L, Sapienza P, Zingales L. The role of social capital in financial development. Am Econ Rev. 2004;94(3):526-56.
https://doi.org/10.1257/0002828041464498
 
62 Zak PJ, Knack S. Trust and growth. Econ J. 2001;111(470):295-321.
https://doi.org/10.1111/1468-0297.00609
 
63 Lipovic L, Sido M, Ghoshal A. Integration interrupted: the impact of September 11, 2001. J Econ Integration. 2015;66-92.
https://doi.org/10.11130/jei.2015.30.1.66
 
64 Johnson ND, Mislin AA. Trust games: a meta-analysis. J Econ Psychol. 2011;32(5):865-89.
https://doi.org/10.1016/j.joep.2011.05.007
 
65 Gallager RG. Stochastic Processes: Theory for Applications. Cambridge University Press. 2013.
https://doi.org/10.1017/CBO9781139626514
 
66 Smith A. An Inquiry into the Nature and Causes of the Wealth of Nations (Vol. 1). Librito Mondi. 1791.
 
67 Bengtsson Å, Hansen KM, Harðarson ÓÞ, Narud HM, Oscarsson H. The Nordic voter: Myths of exceptionalism. Ecpr Press; 2024.
 
68 Delhey J, Newton K, Welzel C. How general is trust in “most people”? Solving the radius of trust problem. Am Soc Rev. 2011;76(5):786-807.
https://doi.org/10.1177/0003122411420817
 
69 Pedersen JS, Löfgren K. Public sector reforms: New public management without marketization? The Danish case. Int J Public Admin. 2012;35(7):435-47.
https://doi.org/10.1080/01900692.2012.679579
 
70 Salminen A, Ikola-Norrbacka R. Trust, good governance and unethical actions in Finnish public administration. Int J Public Sector Manage. 2010;23(7):647-68.
https://doi.org/10.1108/09513551011078905
 
71 Kleven HJ. How can scandinavians tax so much? J Econ Perspect. 2014;28(4):77-98.
https://doi.org/10.1257/jep.28.4.77
 
72 Dahl E, Lorentzen T. Norway: Social security, active labour market policies and economic progress. In Social Security, the Economy and Development 2008 (pp. 210-37). Palgrave Macmillan.
https://doi.org/10.1057/9780230582194_9
 
73 Kübler D, Rochat PE, Woo SY, Van der Heiden N. Strengthen governability rather than deepen democracy: why local governments introduce participatory governance. Int Rev Admin Sci. 2020;86(3):409-26.
https://doi.org/10.1177/0020852318801508
 
74 Hung LD. Savings wedge, productivity growth, and international capital flows. J Econ Int. 2020;35(3):503-18.
https://doi.org/10.11130/jei.2020.35.3.503
 
75 Banerjee AV. A simple model of herd behavior. Quarter J Econ. 1992;107(3):797-817.
https://doi.org/10.2307/2118364
 
76 Banerjee A, Fudenberg D. Word-of-mouth learning. Game Econ Behav. 2004;46(1):1-22.
https://doi.org/10.1016/S0899-8256(03)00048-4
 
77 Alesina A, La Ferrara E. Participation in heterogeneous communities. Quarter J Econ. 2000;115(3):847-904.
https://doi.org/10.1162/003355300554935
 
78 Cho J. The mechanism of trust and distrust formation and their relational outcomes. J Retail. 2006;82(1):25-35.
https://doi.org/10.1016/j.jretai.2005.11.002
 
79 Aassve A, Alfani G, Gandolfi F, Le Moglie M. Epidemics and trust: the case of the Spanish flu. Health Econ. 2021;30(4):840-57.
https://doi.org/10.1002/hec.4218
 
80 Peiró-Palomino J, Tortosa-Ausina E. Can trust effects on development be generalized? A response by quantile. Euro J Politic Econ. 2013;32:377-90.
https://doi.org/10.1016/j.ejpoleco.2013.09.008
 
81 Warf B, Warf B, Bakker. Global Corruption from a Geographic Perspective. Springer International Publishing. 2019.
https://doi.org/10.1007/978-3-030-03478-8
 
82 Muzurura J. Corruption and economic growth in Zimbabwe: unravelling the linkages. Int J Develop Res. 2017;7(1):11197-204.
 
83 Yon N. Hyper-Inflation and Social Security Provision in Zimbabwe, 2000-2009: An Institutional Perspective on the National Social Security Authority. Zimbos Never Die?: Negotiating Survival in a Challenged Economy, 1990s to 2015. 2023;47:151.
https://doi.org/10.1163/9789004547339_008
 
84 Alder SD, Lagakos D, Ohanian L. Labor market conflict and the decline of the rust belt. J Politic Econ. 2023;131(10):2780-824.
https://doi.org/10.1086/724852
 
85 Palley TI. The economics of globalization: Problems and policy responses. In Neoliberalism and the Road to Inequality and Stagnation 2021 (pp. 202-16). Edward Elgar Publishing.
https://doi.org/10.4337/9781802200089.00022
 
86 Glatz C, Eder A. Patterns of trust and subjective well-being across Europe: New insights from repeated cross-sectional analyses based on the European social survey 2002-2016. Soc Indic Res. 2020;148(2):417-39.
https://doi.org/10.1007/s11205-019-02212-x
 
87 Batrancea LM, Nichita A, De Agostini R, Batista Narcizo F, Forte D, de Paiva Neves Mamede S, et al. A self-employed taxpayer experimental study on trust, power, and tax compliance in eleven countries. Financ Innovat. 2022;8(1):96.
https://doi.org/10.1186/s40854-022-00404-y
 
88 Sibley CG, Greaves LM, Satherley N, Wilson MS, Overall NC, Lee CH, et al. Effects of the COVID-19 pandemic and nationwide lockdown on trust, attitudes toward government, and well-being. Am Psychol. 2020;75(5):618.
https://doi.org/10.1037/amp0000662
 
89 Shirley MM. Institutions and development. In Handbook of New Institutional Economics 2005 (pp. 611-38). Springer.
https://doi.org/10.1007/0-387-25092-1_25
 
90 Rodrik D. Where did all the growth go? External shocks, social conflict, and growth collapses. J Econ Growth. 1999;4:385-412.
https://doi.org/10.1023/A:1009863208706
 
91 Malanski LK, Póvoa ACS. Economic growth and corruption in emerging markets: does economic freedom matter? Int Econ. 2021;166:58-70.
https://doi.org/10.1016/j.inteco.2021.02.001
 
92 Flynn P. Brazil and Lula, 2005: crisis, corruption and change in political perspective. Third World Quarter. 2005;26(8):1221-67.
https://doi.org/10.1080/01436590500400025
 
93 Mészáros G. Caught in an authoritarian trap of its own making? Brazil’s ‘Lava Jato’ anti-corruption investigation and the politics of prosecutorial overreach. J Law Soc. 2020;47:S54-73.
https://doi.org/10.1111/jols.12245
 
94 Danchev S, Gatopoulos G, Kalavrezou N, Mavropoulos A, Pavlou G, Vettas N. Equally poorer: inequality and the Greek debt crisis. Fiscal Stud. 2024;45(3):359-75.
https://doi.org/10.1111/1475-5890.12384
 
95 Muro D, Vidal G. Political mistrust in southern Europe since the great recession. Mediterran Politic. 2017;22(2):197-217.
https://doi.org/10.1080/13629395.2016.1168962
 
96 Asso PF. New perspectives on old inequalities: Italy’s north-south divide. In Inequalities, Territorial Politics, Nationalism 2023 (pp. 22-40). Routledge.
https://doi.org/10.4324/9781003399773-3
 
97 Bala B, Tar UA. The giant of Africa? Explaining the Nigerian governance, security, and development paradox. In The Governance, Security and Development Nexus: Africa Rising 2021 (pp. 315-39).
https://doi.org/10.1007/978-3-030-49348-6_16
 
98 Duruigbo E. Managing oil revenues for socio-economic development in Nigeria: the case for community-based trust funds. NCJ Int’l L Com Reg. 2004;30:121.
 
99 Williamson OE. Calculativeness, trust, and economic organization. J Law Econ. 1993;36(1, Pt 2):453-86.
https://doi.org/10.1086/467284
 
100 Conlisk J. Why bounded rationality? J Econ Literat. 1996;34(2):669-700.
 
101 Delhey J, Newton K. Predicting cross-national levels of social trust: global pattern or Nordic exceptionalism? Euro Sociol Rev. 2005;21(4):311-27.
https://doi.org/10.1093/esr/jci022
 
102 Newton K, Zmerli S. Three forms of trust and their association. Euro Politic Sci Rev. 2011;3(2):169.
https://doi.org/10.1017/S1755773910000330
 
103 Berg J, Dickhaut J, McCabe K. Trust, reciprocity, and social history. Game Econ Behav. 1995;10(1):122-42.
https://doi.org/10.1006/game.1995.1027
 
104 Rick S. Losses, gains, and brains: neuroeconomics can help to answer open questions about loss aversion. J Consume Psychol. 2011;21(4):453-63.
https://doi.org/10.1016/j.jcps.2010.04.004
 
105 Morewedge CK. Utility: Anticipated, experienced, and remembered. In The Wiley Blackwell Handbook of Judgment and Decision Making 2015 (Vol. 2, pp. 295-330). Wiley.
https://doi.org/10.1002/9781118468333.ch10
 
106 Zak PJ, Knack S. Trust and growth. Econ J. 2001;111(470):295-321.
https://doi.org/10.1111/1468-0297.00609
 
107 Arrow KJ. Gifts and exchanges. Philos Public Aff. 1972;343-62.
 
108 Helliwell JF, Putnam RD. Economic growth and social capital in Italy. East Econ J. 1995;21(3);295-307.
 
109 Knack S, Keefer P. Does social capital have an economic payoff? A cross-country investigation. Quarter J Econ. 1997;112(4):1251-88.
https://doi.org/10.1162/003355300555475
 
110 Bjørnskov C. The happy few: cross-country evidence on social capital and life satisfaction. Kyklos. 2003;56(1):3-16.
https://doi.org/10.1111/1467-6435.00207
 
111 Bjørnskov C, Dreher A, Fischer JA. Cross-country determinants of life satisfaction: Exploring different determinants across groups in society. Soc Choice Welfare. 2008;30(1):119-73.
https://doi.org/10.1007/s00355-007-0225-4
 
112 Cavallaro E, Villani I. Club convergence in EU countries. J Econ Int. 2021;36(1):125-61.
https://doi.org/10.11130/jei.2021.36.1.125
 
113 Togan S. Technical barriers to trade: the case of Turkey and the European Union. J Econ Int. 2015;121-147.
https://doi.org/10.11130/jei.2015.30.1.121
 
114 Shah SS, Shah SAH. Trust as a determinant of Social Welfare in the Digital Economy. Soc Netw Anal Mining. 2024;14(1):79.
https://doi.org/10.1007/s13278-024-01238-5
 
115 Putnam RD, Leonardi R. Making Democracy Work: Civic Traditions in Modern Italy. Princeton University Press. 1993.
https://doi.org/10.1515/9781400820740
 
116 Woolcock M. Social capital and economic development: Toward a theoretical synthesis and policy framework. Theory Soc. 1998;27(2):151-208.
https://doi.org/10.1023/A:1006884930135
 
117 Rotter JB. Interpersonal trust, trustworthiness, and gullibility. Am Psychol. 1980;35(1):1.
https://doi.org/10.1037/0003-066X.35.1.1
 
118 Coleman JS. Commentary: Social institutions and social theory. Am Soc Rev. 1990;55(3):333-9.
https://doi.org/10.2307/2095759
 
119 Mikiewicz P. Social capital and education-An attempt to synthesize conceptualization arising from various theoretical origins. Cogent Educ. 2021;8(1):1907956.
https://doi.org/10.1080/2331186X.2021.1907956
 
120 Fukuyama F. Trust: The Social Virtues and the Creation of Prosperity (Vol. 99). Free press.
 
121 Warren A, Gibson C. The commodity and its aftermarkets: Products as unfinished business. Econ Geograp. 2021;97(4):338-65.
https://doi.org/10.1080/00130095.2021.1939007
 
122 Chandler AD. Organizational capabilities and the economic history of the industrial enterprise. J Econ Perspect. 1992;6(3):79-100.
https://doi.org/10.1257/jep.6.3.79
 
123 Easterly W, Ritzen J, Woolcock M. Social cohesion, institutions, and growth. Econ Politics. 18(2):103-20.
https://doi.org/10.1111/j.1468-0343.2006.00165.x
 
124 Micallef B. Real convergence in malta and in the eu countries after the financial crisis. J Econ Int. 2020;35(2):215-39.
https://doi.org/10.11130/jei.2020.35.2.215
 
125 Ingianni A, Žd’árek V. Real convergence in the new member states: myth or reality? J Econ Int. 2009;294-320.
https://doi.org/10.11130/jei.2009.24.2.294
 
126 Hillberry R, Zurita C. Commitment behaviour in the World Trade Organization’s trade facilitation agreement. World Econ. 2022;45(1):36-75.
https://doi.org/10.1111/twec.13165
 
127 Putnam RD. Bowling Alone: The Collapse and Revival of American Community. Simon Schuster. 2000.
https://doi.org/10.1145/358916.361990
 
128 Di Cagno D, Sciubba E. Trust, trustworthiness and social networks: playing a trust game when networks are formed in the lab. J Econ Behav Organ. 2010;75(2):156-67.
https://doi.org/10.1016/j.jebo.2010.04.003
 
129 Yamagishi T. Trust as a form of social intelligence. 2001.
 
130 Lin N, Fu YC, Hsung RM. Measurement techniques for investigations of social capital. Social Capital Theory Res. 2001;4:57-81.
https://doi.org/10.4324/9781315129457-3
 
131 Sofianos A. Self-reported & revealed trust: experimental evidence.
 
J Econ Psychol. 2022;88:102451.
https://doi.org/10.1016/j.joep.2021.102451
 
132 French Jr, JR. A formal theory of social power. Psychol Rev. 1956;63(3):181.
https://doi.org/10.1037/h0046123
 
133 Guiso L, Sapienza P, Zingales L. Does culture affect economic outcomes? J Econ Perspect. 2006;20(2):23-48.
https://doi.org/10.1257/jep.20.2.23
 
134 Shah SAH, Shah T, Ahmad E. Equilibrium in Economic Development A Perspective of Social Capital. 2011.
 
135 Delhey J, Newton K. Social trust: global pattern or Nordic exceptionalism? (No. SP I 2004-202). WZB Discussion Paper. 2004.
 
136 Holmberg S. Social trust-the Nordic gold? 2020.
 
137 Sønderskov KM, Dinesen PT. Danish exceptionalism: Explaining the unique increase in social trust over the past 30 years. Euro Soc Rev. 2014;30(6):782-95.
https://doi.org/10.1093/esr/jcu073
 
138 Huber RA, Wicki M. What explains citizen support for transport policy? the roles of policy design, trust in government and proximity among swiss citizens. Energy Res Soc Sci. 2021;75:101973.
https://doi.org/10.1016/j.erss.2021.101973
 
139 Kübler D, Rochat PE, Woo SY, Van der Heiden N. Strengthen governability rather than deepen democracy: why local governments introduce participatory governance. Int Rev Admin Sci. 2020;86(3):409-26.
https://doi.org/10.1177/0020852318801508
 
140 Jenne N, Martínez R. Domestic military missions in Latin America: Civil-military relations and the perpetuation of democratic deficits. Euro J Int Sec. 2022;7(1):58-83.
https://doi.org/10.1017/eis.2021.25
 
141 Ndakaripa M. Zimbabwe’s economic meltdown: Are sanctions really to blame? Washington Quarter. 2021;44(2):95-120.
https://doi.org/10.1080/0163660X.2021.1934997
 
142 Nimer K, Bani-Mustafa A, AlQudah A, Alameen M, Hassanein A. Public perceptions of governance and tax evasion: insights from developed and developing economies. J Financ Report Account. 2022.
 
143 Richardson M. Tax reforms and debt in greece after the financial and economic crisis: Insights and challenges for tax policymaking in times of emergency. Int’l Tax Stud. 2020;2.
https://doi.org/10.59403/1ywraf1
 
144 Brezzi M, González S, Nguyen D, Prats M. An updated OECD framework on drivers of trust in public institutions to meet current and future challenges. 2021.
 
145 Keefer P, Scartascini C. Trust: the key to social cohesion and growth in Latin America and the Caribbean. Inter-American Development Bank. 2022.
https://doi.org/10.18235/0003792
 
146 Jackson MO. Social and Economic Networks. Princeton University Press. 2010.
https://doi.org/10.2307/j.ctvcm4gh1
 
147 Lay DC. Linear Algebra and its Applications. Pearson Education India. 2003.
 
148 Johnson CR, Horn RA. Matrix Analysis. Cambridge University Press. 1985.
 
149 Wielandt H. An extremum property of sums of eigenvalues. Proc Am Math Soc. 1955;6(1):106-10.
https://doi.org/10.1090/S0002-9939-1955-0067842-9
 
150 Plichta J, Plichta G. Artificial intelligence as a factor in reducing transaction costs in the virtual space. In Artificial Intelligence, Management and Trust 2023 (pp. 161-85). Routledge.
https://doi.org/10.4324/9781003311409-11
 
151 Guiso L, Sapienza P, Zingales L. The role of social capital in financial development. Am Econ Rev. 2004;94(3):526-56.
https://doi.org/10.1257/0002828041464498
 
152 Zak PJ, Knack S. Trust and growth. Econ J. 2001;111(470):295-321.
https://doi.org/10.1111/1468-0297.00609
 
153 Lipovic L, Sido M, Ghoshal A. Integration interrupted: The impact of September 11, 2001. J Econ Int. 2015;66-92.
https://doi.org/10.11130/jei.2015.30.1.66
 
154 Johnson ND, Mislin AA. Trust games: A meta-analysis. J Econ Psychol. 2011;32(5):865-89.
https://doi.org/10.1016/j.joep.2011.05.007
 
155 Gallager RG. Stochastic Processes: Theory for Applications. Cambridge University Press. 2013.
https://doi.org/10.1017/CBO9781139626514
 
156 Smith A. An Inquiry into the Nature and Causes of the Wealth of Nations (Vol. 1). Librito Mondi. 1791.
 
157 Hung LD. Savings wedge, productivity growth, and international capital flows. J Econ Int. 2020;35(3):503-18.
https://doi.org/10.11130/jei.2020.35.3.503
 
158 Banerjee AV. A simple model of herd behavior. Quarter J Econ. 1992;107(3):797-817.
https://doi.org/10.2307/2118364
 
159 Banerjee A, Fudenberg D. Word-of-mouth learning. Game Econ Behav. 2004;46(1):1-22.
https://doi.org/10.1016/S0899-8256(03)00048-4
 
160 Alesina A, La Ferrara E. Participation in heterogeneous communities. Quarter J Econ. 2000;115(3):847-904.
https://doi.org/10.1162/003355300554935
 
161 Aassve A, Alfani G, Gandolfi F, Le Moglie M. Epidemics and trust: the case of the Spanish flu. Health Econ. 2021;30(4):840-57.
https://doi.org/10.1002/hec.4218
 
162 Alder SD, Lagakos D, Ohanian L. Labor market conflict and the decline of the rust belt. J Politic Econ. 2023;131(10):2780-824.
https://doi.org/10.1086/724852
 
163 Palley TI. The economics of globalization: Problems and policy responses. In Neoliberalism and the Road to Inequality and Stagnation 2021 (pp. 202-16). Edward Elgar Publishing.
https://doi.org/10.4337/9781802200089.00022
 
164 Glatz C, Eder A. Patterns of trust and subjective well-being across Europe: New insights from repeated cross-sectional analyses based on the European social survey 2002-2016. Soc Indic Res. 2020;148(2):417-39.
https://doi.org/10.1007/s11205-019-02212-x
 
165 Batrancea LM, Nichita A, De Agostini R, Batista Narcizo F, Forte D, de Paiva Neves Mamede S, et al. A self-employed taxpayer experimental study on trust, power, and tax compliance in eleven countries. Financ Innovat. 2022;8(1):96.
https://doi.org/10.1186/s40854-022-00404-y
 
166 Sibley CG, Greaves LM, Satherley N, Wilson MS, Overall NC, Lee CH, et al. Effects of the COVID-19 pandemic and nationwide lockdown on trust, attitudes toward government, and well-being. Am Psychol. 2020;75(5):618.
https://doi.org/10.1037/amp0000662
 
167 Malanski LK, Póvoa ACS. Economic growth and corruption in emerging markets: does economic freedom matter? Int Econ. 2021;166:58-70.
https://doi.org/10.1016/j.inteco.2021.02.001

Cite this article as:
Shah SS. The Economic Implications of Trust in Fostering Growth and Convergence. Premier Journal of Social Science 2024;1:100006

Export to EndNote Export to Mendeley