Author Statement Na Young Park: Responsible for all stages of this article, as a sole author of this paper.
Trust and Trusting Behavior in Financial Institutions: Evidence from South Korea
Na Young Park1
This paper considers trust and trusting behavior towards financial institutions in South Korea. The survey data shows that people on average have higher trust towards financial institutions than towards other individual counterparties, although trust towards financial institutions in South Korea can still be improved further. My results imply that financial institutions should put more efforts in earning trust especially from those at the low end of wealth spectrum and those in young age, so that they can fully benefit from institutional services and be protected from potential frauds more likely to happen outside of regulatory boundary. This paper addresses a relative notion of trust and trusting behavior, i.e. trusting financial institutions relative to trusting other individual counterparties.
Keywords: Trust, Trusting Behavior, Use of Financial Institutions, Psychology and Financial Decisions
1
Incheon National University, Songdo-dong,119 Academy-ro, Yeonsu-gu, Incheon, South Korea, phone: 032-835-8507, e-mail: [email protected]. This work is supported by Incheon National University Research Grant 2016.
Trust and Trusting Behavior in Financial Institutions: Evidence from South Korea
This paper considers trust and trusting behavior towards financial institutions in South Korea. The survey data shows that people on average have higher trust towards financial institutions than towards other individual counterparties, although trust towards financial institutions in South Korea can still be improved further. My results imply that financial institutions should put more efforts in earning trust especially from those at the low end of wealth spectrum and those in young age, so that they can fully benefit from institutional services and be protected from potential frauds more likely to happen outside of regulatory boundary. This paper addresses a relative notion of trust and trusting behavior, i.e. trusting financial institutions relative to trusting other individual counterparties.
1
1. Introduction Many prior studies on economic development show that trust in other members of society as one of the important factors in economic development. (i.e. Arrow, 1972; Fukuyama, 1995; Knack and Keefer, 1997; La Porta et al., 1997; Zak and Knack, 2001; Bowles and Gintis, 2002; Sobel, 2002). In this light, trust can be considered as “social capital”.1 In particular, there is a large body of literature that provides significant insights and evidence on the important roles of trust in financial transactions. For example, Mayer (2008) and Guiso, Sapienza, and Zingales (2004, 2008) find that financial transactions are trust-intensive and that trust plays an important role in financial development. Also, Cao et al. (2016) show that trust is negatively associated with stock crash risks. In particular, financial institutions offer special roles. They offer the roles of intermediaries economizing the costs of monitoring activities, as argued in Diamond (1984). Financial institutions centralize financial transactions, and can enhance the easiness and efficiency of transactions. In this line of reasoning, the topic of trust in financial institutions is of importance for exploration. Although the role of trust in economic and financial development has been studied extensively in the existing literature, trusting behavior in financial institutions, i.e. the level of it, its potential associations with demographic traits, etc., has been relatively slimly addressed. Thus, this paper attempts to survey trusting behaviors towards financial institutions in association with consumers’ individual differences. The topic deserves attention in efforts to bring financial transactions into regulatory boundaries. Financial transactions outside of regulatory boundaries can often potentially cause problems. A choice of conducting financial transactions outside of regulatory boundaries mainly depends on one’s credit grade or access, i.e. often affected by wealth, earnings, or other demographic factors. At the same time, such a choice can also be influenced by one’s trust towards financial institutions versus other alternative counterparties available, i.e. other individuals, in the particular society in which the person lives in. That is, trust and trusting behaviors towards financial institutions ‘relative to’ towards other individuals matter. Trust is “firm belief in the reliability, truth, or ability of someone or something; acceptance of the truth of a statement without evidence or investigation; believing in the reliability, truth, or ability of; allowing someone to have, use, or look after (someone or something of importance or value) with confidence; and committing someone or something to the safekeeping of; placing reliance on (luck, fate, or chance)”.2 It implies that trust can 1
i.e. as noted in James (1904) and Loury (1977). More generally, social capital can be considered as resources that are valuable in social contexts, with exemplified elements including trust, justice, altruism. For example, refer to Sabatino (2019) for social capital and economic resilience, and Habib and Hasan (2017) for the role of social capital in corporate financing. 2
According to the Oxford English Dictionary 2
affect expectation regarding potential outcomes.3 By its definition, it is possible to conjecture that willingness to conduct transactions with financial institutions should be positively associated with trust towards financial institutions. In addition, it would be meaningful to examine whether people indeed have higher trust towards financial institutions compared to towards other individuals, and how such a difference varies by individual factors, i.e. demographics. Conducting this study in South Korea serves the following purposes. Despite the seemingly rapid financial development in South Korea over the recent decades, financial institutions and markets have not earned enough trust from financial consumers. This is supported in various related indexes. For example, South Korea ranked high in financial development. It ranked 6th out of 183 countries around the world, according to the new Financial Development Index of the IMF (Svirydzenka, 2016) encompassing depth, access, and efficiency of financial markets. On the other hand, South Korea ranked low in financial competitiveness. It ranked 87th out of 140 countries, according to the Global Competitiveness Index offered by the World Economic Forum (Schwab, Sala-i-Martín, 2015). This measure is based on the answers from financial consumers, reflecting users’ satisfactions towards financial institutions.4 In addition, there have been several instances of dishonest, fraudulent, and self-serving conducts by financial institutions in selling financial products undermining trust towards them in South Korea. For example, there had been a huge scandal in which corporate commercial papers of an insolvent large conglomerate have been sold to many individual investors without appropriately advising the investors of the potential risks. Similar numerous cases have occurred and have been reported as well.5 Similar to financial institutions, corporate sectors in South Korea also have not earned sufficient level of trust from potential investors in South Korea yet as well. Bae, Kang, and Kim (2002) find that conglomerates in South Korea, often known as chaebols, tend to exhibit diversionary practices that suit their own interests at the expense of minority shareholders. Similarly, Bae, Kang, and Lim (2002) compares institutional variables across country, and mentions that South Korea is characterized with relatively weaker corporate governance, diversionary practices of chaebols for own interests, and banks being controlled by entities with substantially non-financial interests. On the other hand, a deposit insurance can be thought to influence trusting behavior towards financial institutions. There exists a deposit insurance system in South Korea. It is provided by Korea Deposit Insurance Corporation founded in 1996, following the legislation of the Depositor Protection Act in 1995. Currently, it offers a coverage limit of KRW 50 million including the principals and the interests, per person for all deposits at the same institution. Deposits at banks, merchant banks, mutual savings banks, securities companies, 3
This implication of the definition of trust is also noted in Bhattacharya et al (1998). ‘Financially, does South Korea rank sixth or 87th?’, The Hankyoreh, March 18, http://english.hani.co.kr/arti/english_edition/e_business/735693.html 5 `There are 4 more like Tongyang', Korea Times, October 18, http://www.koreatimes.co.kr/www/tech/2017/10/693_144563.html 3 4
2016, 2013,
insurance companies, are all eligible for protection by the deposit insurance. Such a deposit protection system can positively influence trust and trusting behavior towards financial institutions. The existence of a deposit insurance can partially account for the relatively higher trusting behavior towards financial institutions compared to towards other individuals. Also, banks can be considered to serve a particular importance in the economy of South Korea. Banks have served important roles in financing corporations over the past decades. Banks have kept close ties with corporations as well as the government in supporting the growth of the corporate sector in South Korea over the past decades.6 In the light of the aforementioned points, consumers’ trust and trusting behavior towards financial institutions in South Korea warrants examination at this point of time. My survey is conducted in South Korea in winter 2016 through DataSpring Korea, Inc., one of the most widely used online panel survey firm in South Korea. The survey participants were 827 randomly recruited employees of various demographic characteristics. I believe the sample of this paper should be a good representation of the population of financial consumers. The survey included questions on trust towards financial institutions, willingness to entrust money at financial institutions, trust towards other individuals, willingness to lend to other individuals, risk preference, wealth, earning, as well as various other demographic factors. This paper then presents the pair-wise correlations as well as the regression results in various specifications. My results are consistent with my predictions. The survey data shows the followings. 1) People on average have higher level of trust towards financial institutions than towards other individuals. Similarly, people on average have higher willingness to conduct financial transactions with financial institutions than with other individuals. But at the same time, the level of trust and trusting behavior towards financial institutions in South Korea still have much room for further improvement. For example, the average willingness to conduct financial transactions with financial institutions is quite low in South Korea, at only 2.8 out of 5 (the score ranges 0 to 5, where 0 indicates absolute no willingness and 5 indicates absolute willingness). 2) Trust and willingness to do financial transactions are significantly positively correlated. Relative preference (or willingness) to entrust money with financial institutions rather than with other individuals is positively correlated with relative trust in financial institutions over other individuals. 3) Relative preference to entrust money with financial institutions over other individuals increases in wealth and age. 4) Relative preference to entrust money with other individuals over financial institutions increases in tendency of impulsive thinking.7 All these effects are robust when tested in a regression framework, controlling various potentially confounding factors. My results imply that financial institutions should put more efforts in earning trust
6
There are studies making significant contributions to understanding the South Korean financial market as well as other Asian financial markets, i.e. refer to Kang, Bae, Lim (2002), Kang, Baek, Park (2004), Rhee, Fraser, Shin (2012). 7 Cognitive reflection tendency refers to tendency of thinking through before rushing into conclusion. It is different from IQ, mathematical ability, or knowledge. More detailed explanation on this variable is offered in the next section. 4
especially from the people at the low end of spectrum of wealth and in younger age, so that they can fully benefit from institutional services and also be protected from potential frauds more likely to happen outside of regulatory boundary. Also, people with impulsive cognitive tendency may easily accept doing transactions with other individual counterparties. I believe such findings are likely to be generalizable and applicable to other countries to some extents. The results of this paper can be related to the literature on economic and financial development as well as financial inclusion. For some of major findings in these topics, refer to Levine (1997), Errunza (2001), Mayer and Carlin (2003), Choi (2007, 2008), Allen et al (2014, 2016), just to name a few. Moreover, this paper can be related to the literature studying important roles of non-traditional factors in financial decisions. For example, there are important studies providing insights on effects of noisy information effects, networks, implicit barriers, informal communication, prior experiences, and moral hazards.8 Also, this paper can be related to the prior studies examining determinants of trust in financial institutions. Although there are many studies examining whether trust is an important factor in the financial development, there is a slim literature on determinants of trust in financial institutions or markets. One recent study by Jansen et al (2015) finds that media reports with negative contents on banks, falls in stock prices, and ambiguity in financial product information are associated with distrust in banks, using a Dutch survey data. Also, they find that trust in banks increase in age above 55 and slightly increase in wealth. Using a survey on trust in financial service institutions in United Kingdom, Ennew and Sekhon (2007) find that trust in banks is slightly higher for women than men, and significantly increases in age. Similarly, using a survey data from retail bank customers on trust towards retails banks in China, Ennew (2008) find that trust in retail banks is slightly higher for women than men, slightly increases in income, significantly increases in age. While this paper ties in with the aforementioned studies, it attempts to contribute to the literature in another important aspect. This paper intends to focus on the difference between trust towards financial institutions versus trust towards other individual counterparties. The gap between the two must be important in deriving financial transactions with institutions. To date, there is no study examining the potential associations between cognitive tendency and trust in financial institutions, while there is some truism implied indirectly in the literature. Several studies, i.e. Hooghe, Marien, De Vroome (2012), Schoon et al (2010) find the positive correlations between cognitive ability and some measures of trust, i.e. generalized trust or political trust, using a survey data in Netherlands and a survey data in United Kingdom, respectively. Cognitive ability is positively correlated with stock market participation, according to a survey of households in Europe (Christelis, Jappelli, and Padula, 2006). IQ is positively correlated with stock market participation (Grinblatt et al., 2011).9 8
Refer to Banerji and Errunza (2005), Banerji, Almazan, Motta (2008), Chen, Guo and Tay (2010), Chen, Diltz, Huang, Lung (2011), Martinez (2011), Errunza, Carrieri, Chaieb (2013), Errunza, Ta (2015), Kim, Khanna, and Lu (2015), Martinez, Jenkinson, Jones (2016), Kim, Kang, Lu (2018) for important contributions. 9 Relatedly, trust is positively correlated with stock market participation, according to Guiso, Sapienza, Zingales (2008). 5
While this paper ties in with the aforementioned studies, it can be distinguished in an important aspect. By using a cognitive reflection tendency variable, this paper intends to measure cognitive tendency of rushing into conclusion before thorough thinking, rather than IQ, mathematical ability, or knowledge. By doing so, this article finds that an open-todevelopment cognitive tendency of thinking through can help in financial transactions. The paper is organized as follow. Section 2 offers predictions, section 3 explains the survey design and data, section 4 provides the results of the analyses, section 5 concludes. 2. Predictions This paper does not formally develop a theoretical model, but rather provides simple inferences as follow. Many previous studies support important roles of trust in financial settings in particular. For example, Mayer (2008) and Guiso, Sapienza, and Zingales (2004, 2008) show that financial transactions are very trust-intensive and that trust in financial markets is an important factor for financial development. Trust is defined as “Firm belief in the reliability, truth, or ability of someone or something; Acceptance of the truth of a statement without evidence or investigation; Believing in the reliability, truth, or ability of; Allowing someone to have, use, or look after (someone or something of importance or value) with confidence; and Committing someone or something to the safekeeping of; Placing reliance on (luck, fate, or chance)”10. One implication would be that trust can be considered as a form of or a factor influencing one’s expectation about potential outcomes.11 Building on the related prior studies and the definition of trust, predictions can be made follow. 1. Generally it is commonsensical to conjecture that, trust in financial institutions would be higher than trust in other individuals, because of the benefits institutions provide, except in extraordinary cases. 2. Trust and willingness to do financial transactions should be positively correlated with each other. This is because, by the definition of trust, trust can be considered as a factor influencing one’s expectation about potential outcomes. Thus, for example, relative preference (or willingness) to entrust money with financial institutions rather than with other individuals would be positively correlated with relative trust in financial institutions over other individuals. 3. Preference to do financial transactions with financial institutions rather than with other individuals may increase in wealth and age. It may partially be so because of prior experiences of people in financial difficulty or young age not having been sufficiently serviced or even having been rejected by institutions. Or it may be because of mere lack of experiences with financial institutions at young age. 4. Preference to do financial transactions with financial institutions rather than with other individuals can increase in cognitive reflection tendency to think through12. This may be because higher 10
According to the Oxford English Dictionary This implication of the definition of trust is also noted in Bhattacharya et al (1998). 12 I use the term cognitive reflection tendency to highlight that it is likely to be an open-to-development rather than a permanently fixed variable. With efforts and practices, individuals can enhance their cognitive tendency. 6 11
cognitive reflection tendency may help in increasing reflective thoughts in better understanding potential benefits institutions provide. 3. Survey and Data The survey was conducted in winter 2016 through DataSpring, Inc.13, an online panel survey firm in South Korea. The survey methodology is widely used in the literature of household finance decisions, i.e. the Survey of Consumer Finance in the United States, Campbell (2006), just to name a few. My survey participants are 827 randomly recruited employees in South Korea. The sample turn out to be of various demographic characteristics, i.e. assets, age, gender, fields of occupation, etc., thus I believe the sample should be a good representation of the population of financial consumers. 3.1. Measures of Trust: Towards Financial Institutions Versus Other Individual Counterparties The trust questions used in the survey of this paper follow the ones used in in the World Values Survey. The question in the World Values Survey asks “Generally speaking, would you say that most people can be trusted…?” The question is used in the the National Opinion Research Center’s General Social Survey (GSS survey) in the United States. The GSS survey has been a primary source of evidence on social capital and trust in the United States. The GSS survey has been conducted 30 times until 2014 since its inception in 1972. Although the questions change from survey to survey, the question on trust has been included in the most years’ surveys. The question is also used in the studies on trust such as Knack and Keefer (1997), Glaeser et al (2000), and Guiso, Sapienza, and Zingales (2008). Building on this trust question, I made some variations to separately ask trust levels towards financial institutions versus other individuals in general. Thus, the trust questions included in the survey of this paper are as follow. TRUST.Q1. [Trust in Other Individuals] Generally speaking, I would say that other individuals can be trusted in general. (Choose from the scale of 0 to 5, where 0 indicates absolute no and 5 indicates absolute yes.) TRUST.Q2. [Trust in Financial Institutions]: Generally speaking, I would say that financial institutions can be trusted in general. (Choose from the scale of 0 to 5, where 0 indicates 13
DataSpring Korea, Inc. is the Korean corporation of the international survey firm called DataSpring, Inc., which has its headquarter in Japan and has presence in eleven countries. DataSpring Korea, Inc. has featured in various important surveys nation-wide including a national opinion poll for presidential election or for potential policies by governments, etc. Its panel survey service is similar to that of Amazon Mechanical Turk (Mturk), one of the commonly used survey platforms in the United States. For participating in the survey, participants are paid with certain amounts of money. Other parts of my survey conducted in winter 2016 which are beyond the scope of this paper but deserve attention are reported in separate articles. 7
absolute no and 5 indicates absolute yes.) TRUSTOP, trust in other individuals, is the answer to the aforementioned trust question on other individuals, and coded in the range of 0 to 5, where 0 implies absolute no trust and 5 implies absolute trust. TRUSTFI, trust in financial institutions, is the answer to the aforementioned trust question on financial institutions, and coded in the range of 0 to 5, where 0 implies absolute no trust and 5 implies absolute trust. 3.2. Measure of Willingness to Lend to Others: Lending to Financial Institutions Versus Lending to Other Individual Counterparties Thus, survey questions on willingness to lend to other individuals and willingness to entrust money at financial institutions are also included. These questions are constructed in the ways similar to the styles of the widely known and quoted surveys on use of finance or trust, i.e. the Survey of Consumer Finance in the United States, the household finance survey in Campbell (2006), the World Values Survey. In particular, the questions are simply and plainly worded in order to avoid any misunderstanding or complication. In order to specifically measure trusting financial behavior towards financial institutions, a question on willingness to entrust money at financial institutions is included. Also, the question on willingness to entrust money at financial institutions does not specify any particular financial products involved so that it can be understood as a general question of willingness to entrust money, i.e. deposit or invest in financial products, with financial institutions. In particular, these questions in the survey of this paper focus on ‘lending’ or putting money with the respective counterparties rather than ‘borrowing’ from them because lending transaction imposes risks on the side of the prospective lenders, that is, survey participants, so that determining factors of lending decision from the perspectives of potential lenders apart from aspects of borrowers can be tested. In sum, the relevant questions are as follow. WTL.Q1. [Willingness to Lend to Other Individuals] Are you willing to lend to other individuals? Assume that a legally binding record is made on the financial transaction. (Choose from the scale of 0 to 5, where 0 indicates absolute no and 5 indicates absolute yes.) WTL.Q2. [Willingness to Entrust Money at Financial Institutions] Are you willing to entrust money at financial institutions? Assume that a legally binding record is made on the financial transaction. (Choose from the scale of 0 to 5, where 0 indicates absolute no and 5 indicates absolute yes.) LENDINGTOP is willingness to lend to other individuals, and is the score in the answer to the aforementioned relevant question. It is coded from 0 to 5, where 0 means absolute no willingness to lend to other individuals and 5 means absolute willingness to lend to other 8
individuals. LENDINGTOFI is willingness to entrust money at financial institutions, and is the score in the answer to the aforementioned relevant question. It is coded from 0 to 5, where 0 means absolute no willingness to entrust money at financial institutions and 5 means absolute willingness to entrust money at financial institutions. 3.3. Cognitive Reflection: Tendency to Think Through Cognitive reflection is different from IQ, mathematical ability, or knowledge per se, but is the tendency or ability to think through when making a decision. Formally, it is defined as the tendency of resisting reporting the initial response that comes to mind (Frederick, 2005). In particular, according to Frederick (2005), the people who get low scores in the cognitive reflection test tend to make mistakes due to their impulsive thinking. In other words, the key factor lying behind cognitive reflection is the tendency to resist impulsive thinking. This measure is one of the commonly used measures in cognitive decision-making literature featuring in many studies, i.e. Oechssler and Schmitz (2009), Weber and Johnson (2009), just to name a few. A participant’s cognitive reflection score is the number of the questions that the person gets correct, thus should range from 0 to 3. This variable is called CRT. The higher the CRT is, the higher the cognitive reflection of the participant is. Consistent with the survey results of Frederick (2005), many of the participants in the survey of this paper that fail to give correct answers are likely to give impulsive responses. Refer to Frederick (2005) for more details about the cognitive reflection test. The cognitive reflection test used in this paper follows the one provided in Frederick (2005). The three questions of the Cognitive Reflection Test are shown below. The questions are as stated in Frederick (2005) COGNITIVE REFLECTION.Q1. “A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost?” (correct response is 5 cents, and impulsive response is 10 cents) Q2. “If it takes 5 machines 5 minutes to make 5 widgets, how long would it take 100 machines to make 100 widgets?” (correct response is 5 minutes, and impulsive response is 100 minutes) Q3. “In a lake, there is a patch of lily pads. Every day, the patch doubles in size. If it takes 48 days for the patch to cover the entire lake, how long would it take for the patch to cover half of the lake?” (correct response is 47 days, and impulsive response: 24 days) 3.4. Constructions of Other Variables Constructions of other variables are as follow. AGE refers to age in years. MALE is a binary variable, coded 1 if male, and 0 if female. LN(ASSET) is natural log of ASSET. 9
ASSET is assets (assets of any type, i.e. including cash, real estates, financial assets, but net of debts) in million KRW. Monthly Earning, referred to as EARNING, is a categorical variable, which is code from 1 to 6 to and 1, 2, 3, 4, 5, and 6 mean monthly earnings below 1 mln, between 1 mln and 1.99 mln, between 2 mln and 3.99 mln, between 4 mln and 5.99 mln, between 6 mln and 7.99 mln, equal to or above 8 mln, all measured in Korean won, respectively. FIELDOCC refers to fields of occupation, and is a categorical variable and it indicates fields of occupations. It is coded as follow: 1 if finance related, 2 if humanities related, 3 if arts related, 4 if science or math related, 5 if others. EDUCATION refers to highest degree achieved. It is coded 1 if the highest degree is below a high school diploma, 2 if it is a high school diploma, 3 if it is an undergraduate degree, 4 if it is a graduate degree, i.e. master’s or PhD. TRUSTFIOVEROP is a measure of relative trust in financial institutions over other individuals in general, and is defined as TRUSTFI minus TRUSTOP. 14 LENDINGTOFIOVEROP is a measure of relative willingness to entrust money at financial institutions over other people in general, and is defined as LENDINGTOFI minus LENDINGTOP.15 Risk preference is measured using the following question, following the literature. RISKATT_CE is a measure of risk preference. Specifically, it is certainty equivalence elicited from the answers to the aforementioned risk preference questions. Specifically, I refer the answers to the series of risk preference questions comparing a certain receipt versus a risky larger receipt. As the stakes of a risky receipt increases, the participant will change his/her preference from a certain smaller receipt to a risky larger receipt. By looking the point at which the participant’s choice changes from a certain receipt to a risky larger receipt, equivalently by looking at the point at which the participant seems to be indifferent between a certain receipt versus a risky receipt, it is possible to find the certainty equivalent. RISK PREFERENCE.Q. Choose between (1) or (2) that you prefer: (1) One hundred balls are placed in the box, and among them 50 balls are red and 50 balls are white. In case you pick a red ball, you will get KRW 1,000,000 (which is approximately USD 867)16. In case you pick a white ball, you get nothing. (2) You get KRW X for sure, where x is of various amounts, some below KRW 1,000,000 and some above KRW 1,000,000.17
14
TRUSTFI, trust in financial institutions, is the answer to the aforementioned trust question on financial institutions, and coded in the range of 0 to 5, where 0 implies absolute no trust and 5 implies absolute trust. TRUSTOP, trust in other individuals, is the answer to the aforementioned trust question on other individuals, and coded in the range of 0 to 5, where 0 implies absolute no trust and 5 implies absolute trust. 15 LENDINGTOFI is willingness to entrust money at financial institutions, and is the score in the answer to the aforementioned relevant question. It is coded from 0 to 5, where 0 means absolute no willingness to entrust money at financial institutions and 5 means absolute willingness to entrust money at financial institutions. LENDINGTOP is willingness to lend to other individuals, and is the score in the answer to the aforementioned relevant question. It is coded from 0 to 5, where 0 means absolute no willingness to lend to other individuals and 5 means absolute willingness to lend to other individuals. 16 Based on the exchange rate on Feb. 13, 2017. 17 X used is KRW 30,000, 50,000, 80,000, 100,000, 130,000, 150,000, 180,000, and 200,000. 10
The key variables, their constructions, and related questions are summarized in the Appendix 1 and 2. Table I shows the summary statistics of the full sample. The mean age of the survey participants is 35.6, and their ages range between 24 and 54. 51.5% of the survey participants are male and the rest are female. The mean value of the assets of the survey participants is 205.6 million Korean won, which is approximately 174,966 U.S. dollars. 18 The mean monthly earning is 2.45 million Korean won. The mean highest educational degree achieved is approximately undergraduate degrees. The average certainty equivalence in the question choosing between 50-50 gamble verses certain outcome is KRW 23.73 in ten thousand Korean won. The mean cognitive reflection test score, CRT, is 0.99 out of the total score of 3. Since CRT refers to the number of the questions that a participant got correct among the three questions in the test, 0.99 means that participants on average got only one question correct out of the three questions. Notice that the mean of CRT in my sample is close to 1.10, the average cognitive reflection test score in the survey by Frederick (2005).
This table shows summary statistics for key variables. Details of variable definitions are in Section 3. Variable AGE MALE ASSET (in million KRW) LNASSET EARNING monthly earnings below 1 mln between 1 mln and 1.99 mln between 2 mln and 3.99 mln between 4 mln and 5.99 mln between 6 mln and 7.99 mln equal to or above 8 mln FIELDOCC Jobs in finance Jobs in humanities Jobs in arts Jobs in math or science EDUCATION highest degree achieved is a high school diploma is an undergraduate degree is a graduate degree, i.e. master’s or PhD RISKATT_CE (in ten thousand KRW) TRUSTFI TRUSTOP TRUSTFIOVEROP LENDINGTOFI LENDINGTOP LENDINGTOFIOVEROP CRT
Also, it is salient that participants show higher level of trust towards financial institutions 18
Converted at the exchange rate as of Jan.27, 2017. 11
compared to other people in general. The mean score of trust in other people is 1.92 (out of the total score of 5), whereas the mean score of trust in financial institutions is 2.98 (out of the total score of 5). (Refer to the Section 3.2. for the questions on general levels of trust.) 70.6% reported an answer of 3 or above to the question on level of trust towards financial institutions. Approximately 32.2% of the participants reported an answer of 3 or above to the question on level of trust towards other people in general. Such answers from the sample of this paper are not too far from but a bit lower than other similar previous surveys on level of trust using the GSS question: the U.S. sample data is from the GSS survey (1972-2014) shows that 37.8% reported yes than no to the question of “…people can be trusted in general”, and the data of Harvard undergraduates from Glaeser et al (2000) shows that 44.4% reported yes than no to the same question. The mean score of trust in financial institutions is higher than the mean score of trust in other people in general. Similarly, the mean score of willingness to entrust money at financial institutions is 2.76, which is higher than 1.69, the mean score of willingness to lend to other individuals. This is quite reasonable commonsensically as well. In sum, consistent with my earlier predictions, people on average have higher level of general trust in financial institutions rather than in other individuals. However, the level of trust in financial institutions still has some rooms to improve as it is only 3 out of 5. Similarly, people on average have higher willingness conduct financial transactions with financial institutions rather than with other individuals. However, still the average willingness to conduct financial transactions with financial institutions can be considered quite low, as it is only 2.8 out of 5. 4. Results In this section 4, the pair-wise correlations as well as the regression results in various specifications. Specifically, section 4.1. provides the pair-wise correlations between key variables, and then the graphical mean comparisons of LENDINGTOFIOVEROP by key demographic factors. The participants are divided into two groups (high versus low) by age, assets, earning, CRT. Then, section 4.2. provides the regression results. 4.1. Pair-wise Correlations This section presents pair-wise correlations between key variables. The results are shown in Table II. Particularly, this is to test whether trusting behavior variables are correlated with trust variables, demographic or cognitive tendency variables. Consistent with my earlier predictions, the survey data of South Korea shows that general trust level and willingness to do financial transactions are indeed significantly positively correlated. Moreover, in terms of pair-wise correlations, willingness to entrust money with financial institutions over other individuals in a relative term increases in wealth and age, consistent with my earlier prediction. That means people in the poverty and young age tend to show lower trusting 12
behavior towards financial institutions. The potential reasons behind might be that people in poverty already had negative experiences with formal financial institutions, i.e. being rejected in loan applications, and young people might lack experiences with formal institutions yet. Although relative willingness to entrust money with financial institutions over other individuals seems to have positive relation with earning as well, the effect becomes not robust when tested in a regressions framework in a later section of this paper. Trusting behavior towards financial institutions over other individuals increases in cognitive reflection tendency. This may be because higher cognitive reflection may help in increasing reflective thoughts in understanding and reflecting potential benefits institutions within regulatory boundaries provide. On another additional note, as shown in Table II, notice that risk preference does not affect the ‘relative’ choice of putting money with financial institutions over other individuals, contrary to the common misunderstanding. In other words, choice to conduct transactions with formal financial institutions rather than other individuals is more of a matter of trust, wealth, age, cognitive reflection, etc., rather than a matter of a risk preference.
Pair-wise correlations among key variables. Variable definitions are in Section 3. *, **, *** indicate significance at 10%, 5%, and 1%, respectively.
Trust and Trusting Behavior Variables
Demographic Variables
LENDINGTOFIOV EROP TRUSTFIOVEROP TRUSTOP TRUSTFI LENDINGTOP LENDINGTOFI EARNING LNASSET EDUCATION FIELDOCC AGE MALE RISKATT_CE (in ten thousand KRW) CRT
Trusting Behavior towards FIs over other Individuals
Similar observations are shown in Figure 1. The figure presents differences in LENDINGTOFIOVEROP by group where groups are categorized using selected key demographic variables. Y-axis is LENDINGTOFIOVEROP. X-axis refers to CRT, Earning, the binary variable created for assets over 500 million KRW (coded 1 if assets are higher than 500 million KRW or 0 otherwise), the binary variable created for age over 40 (coded 1 if age is higher than 40 and 0 otherwise), respectively. Similar directional observations as shown in 13
Table II and III can be observed in Figure I. Note that the effect of earnings is not significant once various controls are controlled in a regression framework, shown in Section 4.2.
The figure presents differences in LENDINGTOFIOVEROP by group where groups are categorized using selected key demographic variables. Y-axis is LENDINGTOFIOVEROP. Groups are categorized by CRT, Earning, the binary variable created for assets over 500 million KRW coded 1 if assets are higher than 500 million KRW or 0 otherwise, the binary variable created for age over 40 coded 1 if age is higher than 40 and 0 otherwise, respectively, going clockwise.
(Figure 1.1. Groups by CRT)
(Figure 1.2. Groups by EARNING)
(Figure 1.3. Groups: Asset > 500 mln KRW = 1; Asset ≤ 500 mln KRW = 0)
(Figure 1.4. Groups: AGE > 40 = 1; AGE ≤ 40 =0)
4.2. Effect of Selected Key Variables on Trusting Behavior towards Financial Institutions Relative to Other Individual Counterparties Next, OLS regressions are run in order to check the effect of key controls on relative trusting behaviors towards financial institutions over other individual counterparties. Specifically, the regressions are run with LENDINGTOFIOVEROP, relative willingness to lend to other individuals over financial institutions, as the dependent variable. Recall that LENDINGTOFIOVEROP is defined as LENDINGTOFI minus LENDINGTOP. Refer to the Section 3 and Appendix 1 and 2 for the detailed construction of the variables. The regression model is as follow. 14
LENDINGTOFIOVEROPi = β1 + β2TRUSTFIi + β3TRUSTOPi + β4RISKATT_CEi + β5EARNINGi + β6LNASSETi + β7EDUCATIONi + β8FIELDOCCi + β9AGEi + β10MALEi + β11CRTi + εit (Model 1) LENDINGTOFIOVEROPi = β1 + β2TRUSTFIOVEROPi + β3RISKATT_CEi + β4EARNINGi + β5LNASSETi + β6EDUCATIONi + β7FIELDOCCi + β8AGEi + β9MALEi + β10CRTi + εit (Model 2) , where TRUSTFIOVEROP is a measure of relative trust in other individuals over financial institutions, and is defined as TRUSTOP minus TRUSTFI. And in order to see effects of trust in other individuals and trust in financial institutions separately on relative willingness to lend to financial institutions over other individuals, another regression model has been constructed as in Model 1. The definitions of the variables are provided in Section 3. The results of these regressions for the model (1) are reported in Table III. Column (1) is the baseline regression. Among the control variables, LNASSET, AGE, and CRT are individually significant in explaining LENDINGTOFIOVEROP, with the following directional effects: LNASSET (+), AGE (+), and CRT (+). That means, the lower the assets the person has and the younger the person is, s/he is more likely to have higher willingness to lend to other individuals over financial institutions. Such effects can be explained as follow. Experiences with financial institutions accumulate with age, thus ambiguities associated with financial institutions one feels may be reduced as one ages. On the other hand, ambiguities associated with other individuals are unlikely to be reduced due to unlimitedly heterogeneous and various traits of other individuals. Wealth effect is not easy to be explained. But one potential conjecture would be that one is less likely to have previous experiences of being rejected by financial institutions. Due to higher and easy access, they are likely to have experiences with financial institutions. And the effects of both age and wealth remain robust in other regression specifications. Column (2) and (3) show the effects of trust variables on LENDINGTOFIOVEROP. Both of TRUSTOP and TRUSTFI are significant in explaining LENDINGTOFIOVEROP. Consistent with my earlier predictions, willingness to lend to financial institutions compared to other individuals increases in trust in financial institutions and decrease in trust in other individuals. Both of their effects are economically and statistically significant, and they remain robust to the inclusion of other controls, as shown in column (6). The coefficient estimate of TRUSTOP ranges from -0.35 to -0.41. The coefficient estimate of TRUSTFI ranges from 0.28 to 0.31. Recall that TRUSTFI and TRUSTOP are coded from 0 to 5 with 0 being absolute no trust and 5 being absolute trust. And LENDINGTOP and LENDINGTOFI are recorded from 0 to 5 with 0 being absolutely not willing to lend and 5 being absolutely willing to lend. Thus, the coefficient estimates mean the followings. As TRUSTOP increases by one scale, LENDINGTOFIOVEROP decreases by somewhere between 0.35 to 0.41. As 15
TRUSTFI increases by one scale, LENDINGTOFIOVEROP changes by somewhere between 0.28 to 0.31. And positive and negative changes in willingness to lend by 0.3 scale can be considered economically significant. Converted to a percentage, the result means that one scale increase in TRUSTOP leads to approximately 7% higher willingness to lend to other individuals over financial institutions. And one scale increase in TRUSTFI leads to approximately 6% lower willingness to lend to other individuals over financial institutions.
19 This table presents the results of the OLS regressions with LENDINGTOFIOVEROP as the dependent variable. Variable definitions are as in Section 3. T-statistics based on robust standard errors are reported parenthesis. +,*, ** *** , indicate significance at 15%, 10%, 5%, and 1%, respectively. (1) TRUSTOP
(2) -0.3464 (-8.32)***
TRUSTFI RISKATT_CE EARNING LNASSET EDUCATION FIELDOCC AGE MALE
The results are similar when regressions are conducted for the model (2). The results are reported in Table IV. Column (1) is the baseline regression. Among the control variables, LNASSET, AGE, and CRT are individually significant in explaining LENDINGTOFIOVEROP, with the following directional effects: LNASSET (+), AGE (+), and CRT (+), similar to the results in Table IV. On the other hand, as shown in column (2), TRUSTFIOVEROP is very significant in explaining LENDINGTOFIOVEROP. The effect is both economically and statistically significant, and it remains robust to the inclusion of other controls, as shown in column (5). Its coefficient estimate ranges from 0.36 to 0.40. Recall that TRUST variables are coded from 0 to 5 with 0 being absolute no trust and 5 being absolute trust. Thus, its coefficient estimate means that as TRUSTFIOVEROP increases by one scale, 19
A method suggested by Davidson and MacKinnon (1993) for improving the results when the model might be heteroskedastic has been applied. This method uses vce(hc3) function in STATA analysis and should produce confidence intervals and t-statistics that are much more conservative. 16
LENDINGTOFIOVEROP increases by 0.36-0.40. Recall that willingness to lend variables are recorded from 0 to 5 with 0 being absolutely not willing to lend and 5 being absolutely willing to lend. Thus, approximately 0.4 scale increase in willingness to lend can be considered economically significant. Converted to a percentage, the result means that one scale increase in TRUSTFIOVEROP leads to approximately 8% higher willingness to lend to financial institutions than other individuals. Simply put, the results imply that when an individual has to make a decision between lending to other individuals over putting money at financial institutions, the person is more likely to lend to other individuals if the person has relatively higher trust in other individuals over financial institutions, has lower assets, is younger, and is of lower cognitive reflection. And among them, relative trust in other individuals over financial institutions has the highest explanatory power in explaining one’s decision to lend to other individuals over financial institutions, as shown by its high R-squared.
20 This table presents the results of the OLS regressions with LENDINGTOFIOVEROP as the dependent variable. Variable definitions are as in Section 3. T-statistics based on robust standard errors are reported parenthesis. +, *, ** *** , indicate significance at 15%, 10%, 5%, and 1%, respectively. (1) TRUSTFIOVEROP RISKATT_CE EARNING LNASSET EDUCATION FIELDOCC AGE MALE
5. Conclusion Despite a large body of literature on the role of trust in financial development, a detailed 20
A method suggested by Davidson and MacKinnon (1993) for improving the results when the model might be heteroskedastic has been applied. This method uses vce(hc3) function in STATA analysis and should produce confidence intervals and t-statistics that are much more conservative. 17
view on financial institutions in South Korea warrants examination. This paper attempts to study trust and trusting behavior towards financial institutions in South Korea. Consistent with my predictions, my results show the followings. People on average have higher level of trust towards financial institutions compared to towards other individuals. Similarly, people on average have higher willingness to conduct financial transactions with financial institutions compared to other individuals. As an additional note, the level of trust and trusting behavior towards financial institutions in South Korea still have potentials for further improvement. Relative trust towards financial institutions over other individuals has significant explanatory power in explaining relative willingness to entrust money with financial institutions rather than with other individuals. Moreover, relative preference or willingness to entrust money with financial institutions over other individuals increases in wealth, age, and cognitive tendency to think through. Promoting trust and trusting behavior in financial institutions is important not only from the financial development perspective but also to enable people to benefit from institutional services as well as to protect them from potential negative consequences, i.e. financial frauds, more likely to be present outside of regulatory boundaries. Going forward, South Korean financial institutions face much work to be done. Earning trust from financial consumers is not an easy task, but a necessary task. This article offers where the most efforts can be made, i.e. broadening access to people in low ends of wealth spectrum as well as people at young age. Also, offering financial education in directions of improving tendency of thinking through in decision-making may also help.
Acknowledgements Comments received throughout writing of this paper are thankfully acknowledged. Special thanks go to Editor Chen and anonymous referees. Any remaining error is the responsibility of the author.
Funding This work was supported by Incheon National University Research Grant 2016.
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Appendix 1.
Definitions of key variables LENDINGTOP
Willingness to lend to other individuals, and is the score in the answer to the relevant question. It is coded from 0 to 5, where 0 means absolute no willingness to lend to other individuals and 5 means absolute willingness to lend to other individuals. Q. [Willingness to Lend to Other Individuals] Are you willing to lend to other individuals? Assume that a legally binding record is made on the financial transaction. (Choose from the scale of 0 to 5, where 0 indicates absolute no and 5 indicates absolute yes.)
LENDINGTOFI
Willingness to entrust money at financial institutions, and is the score in the answer to the relevant question. It is coded from 0 to 5, where 0 means absolute no willingness to entrust money at financial institutions and 5 means absolute willingness to entrust money at financial institutions. Q. [Willingness to Entrust Money at Financial Institutions] Are you willing to entrust money at financial institutions? Assume that a legally binding record is made on the financial transaction. (Choose from the scale of 0 to 5, where 0 indicates absolute no and 5 indicates absolute yes.)
LENDINGTOFIOVEROP
A measure of relative willingness to entrust money at financial institutions over other people in general, and is defined as LENDINGTOFI minus LENDINGTOP.
TRUSTOP
Trust in other individuals, is the answer to the trust question on other individuals, and coded in the range of 0 to 5, where 0 implies absolute no trust and 5 implies absolute trust. Q. [Trust in Other Individuals] Generally speaking, I would say that other individuals can be trusted in general. (Choose from the scale of 0 to 5, where 0 indicates absolute no and 5 indicates absolute yes.)
TRUSTFI
Trust in financial institutions, is the answer to the trust question on financial institutions, and coded in the range of 0 to 5, where 0 implies absolute no trust and 5 implies absolute trust. Q. [Trust in Financial Institutions]: Generally speaking, I would say that financial institutions can be trusted in general. (Choose from the scale of 0 to 5, where 0 indicates absolute no and 5 indicates absolute yes.)
TRUSTFIOVEROP
A measure of relative trust in financial institutions over other individuals in general, and is defined as TRUSTFI minus TRUSTOP.
RISKATT_CE
A measure of risk preference. Specifically, it is certainty equivalence elicited from the answers to the risk preference questions.
EARNING
Monthly Earning, referred to as EARNING, is a categorical variable, which is code from 1 to 6 to and 1, 2, 3, 4, 5, and 6 mean monthly earnings below 1 mln , between 1 mln and 1.99 mln, between 2 mln and 3.99 mln, between 4 mln and 23
5.99 mln, between 6 mln and 7.99 mln, equal to or above 8 mln, all measured in Korean won, respectively. LNASSET
Natural log of ASSET. ASSET is assets (assets of any type, i.e. including cash, real estates, financial assets, but net of debts) in million KRW.
EDUCATION
EDUCATION refers to highest degree achieved. It is coded 1 if the highest degree is below a high school diploma, 2 if it is a high school diploma, 3 if it is an undergraduate degree, 4 if it is a graduate degree, i.e. master’s or PhD.
FIELDOCC
FIELDOCC refers to fields of occupation, and is a categorical variable and it indicates fields of occupations. It is coded as follow: 1 if finance related, 2 if humanities related, 3 if arts related, 4 if science or math related, 5 if others.
AGE
Age in years
MALE
A binary variable, coded 1 if male, and 0 if female.
CRT
Cognitive reflection test (CRT) score is the score in the three-item cognitive reflection test suggested by Frederick (2005). It is the number of the questions that the person gets correct, thus should range from 0 to 3. The higher the CRT is, the higher the cognitive reflection of the participant is. Q1. “A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost?” (correct response is 5 cents, and impulsive response is 10 cents) Q2. “If it takes 5 machines 5 minutes to make 5 widgets, how long would it take 100 machines to make 100 widgets?” (correct response is 5 minutes, and impulsive response is 100 minutes) Q3. “In a lake, there is a patch of lily pads. Every day, the patch doubles in size. If it takes 48 days for the patch to cover the entire lake, how long would it take for the patch to cover half of the lake?” (correct response is 47 days, and impulsive response: 24 days)
24
Appendix 2. (Questionnaire) Trust and Trusting Behavior Questions TRUST.Q1. [Trust in Other Individuals] Generally speaking, I would say that other individuals can be trusted in general. (Choose from the scale of 0 to 5, where 0 indicates absolute no and 5 indicates absolute yes.) TRUST.Q2. [Trust in Financial Institutions]: Generally speaking, I would say that financial institutions can be trusted in general. (Choose from the scale of 0 to 5, where 0 indicates absolute no and 5 indicates absolute yes.) WTL.Q1. [Willingness to Lend to Other Individuals] Are you willing to lend to other individuals? Assume that a legally binding record is made on the financial transaction. (Choose from the scale of 0 to 5, where 0 indicates absolute no and 5 indicates absolute yes.) WTL.Q2. [Willingness to Entrust Money at Financial Institutions] Are you willing to entrust money at financial institutions? Assume that a legally binding record is made on the financial transaction. (Choose from the scale of 0 to 5, where 0 indicates absolute no and 5 indicates absolute yes.)
Risk Preference Questions (Summarized) Q. Choose between the two options, (A) and (B), that you prefer. (A) There are one hundred balls in the box with 5 red ones and 95 white ones. If you pick a red one, you receive KRW 1,000,000 (which is approximately USD 867)21. Otherwise, you receive nothing. (B) You receive KRW X with certainty, where x is KRW 10,000, 30,000, 50,000, 80,000, 100,000, 130,000, 150,000, 180,000, and 200,000. Q. Choose between the two options, (A) and (B), that you prefer. (A) There are one hundred balls in the box with 50 red ones and 50 white ones. If you pick a red one, you receive KRW 1,000,000 (which is approximately USD 867)22. Otherwise, you receive nothing. (B) You receive KRW X with certainty, where x is KRW 100,000, 200,000, 250,000, 300,000, 350,000, 400,000, 500,000, 600,000, and 700,000. Q. Choose between the two options, (A) and (B), that you prefer. (A) There are one hundred balls in the box with 95 red ones and 5 white ones. If you pick a red one, you receive KRW 1,000,000 (which is approximately USD 867)23. Otherwise, you receive nothing. (B) You receive KRW X with certainty, where x is KRW 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, and 950,000.
Cognitive Reflection Questions (as in Frederick (2005)) 1. “A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost?” 21 22 23
Based on the exchange rate on Feb. 13, 2017. Based on the exchange rate on Feb. 13, 2017. Based on the exchange rate on Feb. 13, 2017. 25
2. “If it takes 5 machines 5 minutes to make 5 widgets, how long would it take 100 machines to make 100 widgets?” 3. “In a lake, there is a patch of lily pads. Every day, the patch doubles in size. If it takes 48 days for the patch to cover the entire lake, how long would it take for the patch to cover half of the lake?”
Other Questions AGE: ___________ GENDER: ___________ ASSET: _____________millions Monthly earnings (Checkmark): ______ equal to or above 8 mln KRW ______ between 6 mln KRW and 7.99 mln KRW ______ between 4 mln KRW and 5.99 KRW ______ between 2 mln KRW and 3.99 mln KRW ______ between 1 mln KRW and 1.99 mln KRW ______ below 1 mln KRW Checkmark the field of your occupation: ______ finance ______ humanities ______ arts ______ science/math ______ others Checkmark the highest degree achieved: ______ below a high school diploma ______ a high school diploma ______an undergraduate degree ______a masters’ or PhD degree