Present bias and its influence on financial behaviours amongst Indians

Abstract

Purpose

Present bias (PB) is a cognitive bias that stimulates the individual decision-maker to favour the present reward even over the higher reward in the future to avoid the uncertainty attached to the reward in an uncertain future. The article attempts to examine the prevalence of PB amongst Indians and the effect of such bias on savings and borrowings.

Design/methodology/approach

Secondary data on 47,132 respondents from the Financial Inclusion Insights, 2017 database was used in the study. The theory of self-control, which is captured by the widely accepted hyperbolic discounting model, was used to explore the presence of PB. Suitable statistical techniques and the binary probit regression model were employed to attain the objectives of the study.

Findings

The prevalence of PB was found amongst 8.2% of the sample respondents. The outcome of the study endorses the view of previous researchers that present-biased people tend to save less and borrow more.

Originality/value

Although the exploration of the role of various cognitive biases on financial behaviour is gaining momentum in recent times, there is a dearth of studies exploring the prevalence of PB and its implication towards financial behaviour, especially in the context of the emerging economy of India. The study makes an original contribution in this regard by using a very rich dataset of 47,132 individuals in the Indian context for the first time.

Citation

Maji, S.K. and Prasad, S. (2024), "Present bias and its influence on financial behaviours amongst Indians", IIM Ranchi Journal of Management Studies, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IRJMS-02-2024-0009

Introduction

Intertemporal decisions (such as savings for retirement, debt repayment, investment in education, fitness, home ownership, technology adoption, energy consumption, parenting, etc.) are of paramount significance, as these decisions have significant bearing on financial stability, well-being and quality of life as a whole. Even some of the individual intertemporal decisions (energy saving, energy-efficient technology adoption and environmental conservation) exacerbate broader socio-economic implications. Often it has been observed that these intertemporal decisions get affected by different behavioural biases and heuristics (Kuramoto et al., 2024). For example, an individual may encounter a conflict in the issues of saving for retirement vs expensive luxury vacation, home ownership vs rental, unhealthy lifestyles vs fitness, holding vs selling an underperforming stock and sticking to the current state vs adopting change. Therefore, the exploration of the role of various behavioural biases on financial decision-making and behaviour has emerged as a topic of great interest amongst scholars across the globe in recent times (Gathergood, 2012). Amongst all, the lack of self-control can be viewed as one of the major cognitive biases amongst individuals. Self-control is believed to be at the core of self-discipline, and thus, the lack of self-control results in sub-optimal intertemporal decision-making in almost every sphere of human life (Cheung, Tymula, & Wang, 2022). Such self-control problems can be captured by the widely accepted hyperbolic discounting model (Cheung, Tymula, & Wang, 2021). This model points out the cognitive bias in individual decision-makers that induces an inclination to prefer immediate rewards to future rewards even when the value of a present reward is smaller. For example, choosing a reward of ₹1,000 immediately rather than choosing a reward of ₹ 1050 after a week is an instance of hyperbolic discounting. Hyperbolic discounting normally occurs because people are normally risk-averse and want to avoid the uncertainty attached to the reward to be received in the future. The non-linear perception of time is the principal contributing factor to the hyperbolic discounting. However, this human behaviour does not remain consistent over time. A decision-maker can be observed to have the unwillingness to wait longer for distant future rewards and become impatient for rewards to be received in the near future. Laibson (1997) explains that it happens due to the perception of high and low discount rates for longer and shorter time horizons, respectively. Investigation of the trade-off between current and future consumption has been of great significance amongst behavioural economists for a considerable period (Balakrishnan, Haushofer, & Jakiela, 2020). The theory of hyperbolic discounting (where individuals discount immediate future rewards at a lower discount rate than the future rewards) can be used to explain the present bias (PB). It is defined as the propensity to overvalue immediate rewards at the expense of future ones. Alternatively, it is the temptation of an individual to give preference to smaller present rewards compared to the larger future rewards. However, such preferences will alter if both rewards are delayed by the same timeframe (Chakraborty, 2021). PB is considered to be one of the prominent cognitive biases in behavioural economics, reflecting time-preference anomalies that make present consumption look more lucrative than future consumption. PB has its roots in the theory of self-control (Thaler & Shefrin, 1981), initially resulting from animal research in the 1960s–1970s (O'Donoghue & Rabin, 2015). Later, economists used this theory in economic study, mainly when Laibson (1994) used it in some of their consecutive works (Laibson, 1994, 1997). The theory of self-control suggests that self-control is vital, as immediate gratification is more tempting than waiting for future rewards (Shefrin & Richard, 1988). The key to dealing with PB is to nurture good habits and use of appropriate nudges.

The notion of self-control, as well as other cognitive biases (framing and mental accounting), have been added to Modigliani and Brumberg’s (1954) classic life cycle theory to produce the behavioural life-cycle hypothesis (Shefrin & Richard, 1988). To incorporate self-control, Shefrin and Richard (1988) have utilised a dual preference structure, which suggests that an individual has two sets of mutually inconsistent personalities: the planner and the doer. According to the behavioural life-cycle model, the doer is a present-biased myopic self who cannot ignore the temptation of current consumption without being concerned about the future. On the contrary, the planner always uses willpower (defined as the psychic cost of resisting temptation) to contract current consumption and optimise the lifetime utility function of the individual (Shefrin & Richard, 1988).

Due to the growing importance of PB affecting several intertemporal decision areas, several research works have been carried out across the globe in the last two decades or so on this issue (Kuramoto et al., 2024). Understanding of PB helps to explain why individuals often fail to stick to a particular plan (such as exercising regularly, avoiding eating junk food, quitting smoking, implementing financial discipline, etc.) in reality (Chakraborty, 2021). On the other side, the culture of a country, region and people affect their decision-making process. The research on the effect of PB on financial behaviour is also important in the context of South Asian countries because of the cultural diversity in these economies. In countries like India, Bangladesh, Nepal and Sri Lanka, there is a traditional culture of spending heavily on various festivals without thinking too much about the future, which reflects the existence of PB. Although the habit of savings is promoted in different cultures, sometimes, social esteem, social recognition and social approval become extremely important, which drives overspending and ignoring long-term financial needs. The traditional Sri Lankan culture of depending on family support in old age affects their investment habit in the present. Not only PB, many other biases can also be linked with culture affecting intertemporal decisions. For example, cultural tradition of investing in gold in India reflects herd behaviour, which affects the market price in the wedding and festival seasons. Since the different biases can significantly affect the human behaviour, it is important to explore the existence of biases and how these biases affect different human behaviour. In this context and considering the significance of PB in affecting multiple intertemporal decision areas of an individual decision-maker, the article seeks to explore the effect of PB on two basic financial behaviours (savings and borrowings) in the Indian context.

Brief review of literature

Individuals exhibit distinctive time inconsistencies because PB arises from weaker self-control and the desire for immediate gratification. Some people, in particular, are not aware of their flaws and tend to seek immediate gratification for things they enjoy, while procrastinating on duties and decisions that they find unpleasant. An individual who knows how they will behave in the future must show a pattern of seeking to avoid indulgences to improve self-control (O'Donoghue & Rabin, 2000).

Several theories such as the hyperbolic discounting model, theory of self-control and behavioural life-cycle model are associated with PB. The conflict between present and future reward preferences is the genesis of PB. One needs to strike a balance between the two to eliminate the effect of PB on their behaviour. The theory of self-control speaks about the importance of exercising self-regulation to reduce the effect of PB on such behaviour (Thaler & Shefrin, 1981). According to this model, individuals have a limited capacity for self-control and that directly affects their decision-making process, especially when the question of immediate gratification over the future reward arises. The hyperbolic discounting model and theory of self-control operate in the time-inconsistent model framework, which stipulates that the preferences of individuals are inconsistent over time. What an individual prefers today will never remain the same in the future, and therefore, the decisions made by individuals may not be in line with the long-term objectives of individuals. This time-inconsistent model can be used to explain behavioural issues such as lack of self-control, addiction, overconsumption, inadequate savings, health-related issues, etc. amongst individuals. This time-inconsistent behaviour is triggered by the tendency of people to discount the present reward heavily in contrast to the future reward. Behavioural life-cycle theory challenges the rational behaviour of individuals as assumed in traditional life-cycle theory (Shefrin & Richard, 1988). Proponents of this theory argue that people do not act rationally all the time rather various behavioural biases and heuristics influence their decision-making process, leading individuals to make inconsistent behaviour (Shefrin & Richard, 1988).

During the last two decades, the new developments in the extant literature revealed that PB operates in utility and is about now. Any noticeable short-term discounting is evidence of PB (O'Donoghue & Rabin, 2015). Previous empirical studies looked into the potential implications of PB on consumer and financial behaviour. PB, in particular, has the potential to affect spending habits. For example, individuals with no PB are more lenient toward energy-efficient products (Fuerst & Singh, 2018). Hunter et al. (2018) noted that PB is inversely associated with the motivation for physical exercise.

Chronic debtors (whose spending is more earning) tend to be more present-biased (Webley & Nyhus, 2001). Individuals with PB are unlikely to save adequately for retirement (Brown & Previtero, 2014). Past studies reveal that those who are present-biased are more concerned with immediate pleasure and are less interested in executing day-to-day money management tasks. As far as the determinants of savings of individuals are concerned, income level, education (Lusardi & Mitchell, 2017), marital status (Damman, Henkens, & Kalmijn, 2015), gender (Fisher, 2010), family structure (Chatterjee & Zahirovic-Herbert, 2010), future time perspective (Tomar, Baker, Kumar, & Hoffmann, 2021), credit availability (Almås, Freddi, & Thøgersen, 2020), risk attitude (Zakaria, Nor, & Ismail, 2017), subjective norms (Tomar et al., 2021) and culture (Fuchs-Schündeln, Masella, & Paule-Paludkiewicz, 2020) affect the savings behaviour.

On the contrary, borrowing behaviour has been investigated at macroeconomic, household and individual levels. Extant literature also reveals that various socio-economic and demographic factors affect the borrowings of individuals. At the individual level, financial condition, age, location, gender, marital status, educational attainment, financial literacy (FL), religion, household size, house ownership, racial and ethnic characteristics, area population density, subjective norm and credit counselling can significantly explain the borrowing of individual and households (Elliehausen, Christopher Lundquist, & Staten, 2007; Fan & Chatterjee, 2017; Guo, Liu, Liu, Chen, & He, 2023). Present-biased individuals are more likely to choose complex mortgage products with back-loaded payments, high-cost credit products (store cards and payday loans, revolving credit) and overuse of credit cards and delayed credit card payments (Gathergood & Weber, 2017; Gathergood, 2012; Wang, Lu, & Malhotra, 2011; Meier & Sprenger, 2010; Kuramoto et al., 2024). Such a tendency of preferring credit card borrowing is also supported by the neuro-economic explanation provided by Banker, Dunfield, Huang, and Prelec (2021).

Empirical studies on the relationship between PB and financial behaviour are scanty, especially in the Indian context. For instance, Fuerst and Singh (2018) conducted a study on the effect of PB on energy-efficient appliance adoption and found the adverse effect of PB in India. The effect of PB on inheritance tax in India was examined by Bishnu, Kumru, and Nakornthab (2023). A search in Web of Science database produces only one result on this topic in the Indian context, i.e. Bishnu et al. (2023), which points out a gap in the extant literature in this direction. Thus, with the existing literature gap in studying the association between PB and financial behaviour in the Indian context, future research is needed. Keeping the research gap in context, this study seeks to explore the prevalence of PB amongst individuals in India. The study also makes a modest attempt to unearth the effects of the PB on financial behaviour (savings and borrowing) amongst the Indians.

Data sources and methodology

The study uses secondary data on a total number of 47,132 Indian respondents from the Financial Inclusion Insights (FII) survey, 2017. This database is one of the most comprehensive databases that monitor the acceptance and use of financial services across some of the developing countries in South Asia and Africa.

Measuring PB

As already pointed out, people with PB prefer immediate gratification rather than waiting for the future. Thus, a question capable of capturing such a tendency is to be taken into account to identify whether an individual is present-biased or not. PB in individuals can be captured by using experimental questions such as asking the respondents to choose a reward of $ 1,000 immediately or choosing a reward of $1,050 after a week. Alternatively, Xiao and Porto (2019) and Asgari and Pouralimardan (2024) in their study have identified PB amongst individuals based on the following statement: “I intend to live in the present more and do not consider the future”. Owsley, Hajimoladarvish, and Laumas (2023) asked the respondents to opt to either receive “INR 2000 today or Receive INR 2500 in one month”. The use of this question is assumed to be the easiest approach, as this question directly tries to evaluate the PB amongst the individuals. The liberty to use any question in any survey depends upon the data source of the study. In the case of primary data, exact or original questions can be incorporated in the questionnaire. However, if any study is based on secondary data, identical questions may not be available. Under such circumstances, a similar question can be considered the best proxy for the original question. However, when the research is dependent upon secondary data, identical questions to measure PB may not be readily available. Under such a situation, any similar kind of question that can be the closest proxy of PB can be used, which can also be contextual. Wang and Sloan (2018) mention that in recent times, hypothetical questions are presented before the respondents and the PB is estimated based on that. One of the major benefits of this approach is that the questions can be modified to deal with different trade-offs (Wang & Sloan, 2018). A different statement (“I am prepared to spend now and let the future take care of itself.”) was used by Gathergood and Weber (2017) to estimate PB. In the FII survey, there is a similar kind of question that requires the respondents to respond to the following question.

“Overall, how worried are you about the future? Would you say that you are: very worried, somewhat worried, neither worried nor unworried, somewhat unworried or very unworried?” Taking cues from past studies, this question was used as the proxy to measure PB. If the response to this question is either “somewhat unworried” or “very unworried,” it is presumed that the respondent is present-biased and vice-versa.

Financial behaviours

The effect of PB was explored on two important financial behaviours such as savings and borrowing. The FII survey contains questions on whether a particular individual saves in any of the various alternative sources (such as banks, microfinance institutions, post offices, etc.). If a particular individual saves in any one or more of the various formal or informal sources, it is assumed that the person exhibits savings behaviour. Similarly, to know the borrowing habits of the respondents, the questions inquiring whether the respondents were currently borrowing from any available source (such as a bank, microfinance institutions, post office, mobile money, savings/lending groups and any other financial institutions and/or service provider) was taken into account. If the respondent was borrowing from any of these sources, they were assigned a score of one (indicating borrowing); otherwise, the score was zero.

Effect of PB on financial behaviour

Once the PB amongst the respondents is determined based on the individual responses to the PB-related question, the effect of such PB on financial behaviours was explored using a binary probit model. The reason for using the probit model was the nature of the dependent variables. Since both the dependent variables (savings and borrowing) were binary carrying values of either zero and one, the binary probit model was applied to capture the effect of PB in the presence of other control variables. Although PB has a significant role in determining the savings and borrowing behaviour of an individual, the significance of FL can never be undermined. Many research scholars (Goyal & Kumar, 2021) have examined the role of FL on various financial behaviours (such as savings, borrowing, stock market participation, insurance adoption, retirement planning, etc.). In our assessment of the effect of PB on savings and borrowings, the effect of FL will be controlled by including FL as one of the predictors. The study uses the Standard and Poor (S&P) Global FL questions to measure the level of FL amongst the respondents. These questions are widely used parameters by researchers across the globe (Das & Maji, 2023; Klapper & Lusardi, 2020) to test the level of FL. The S&P FL survey involves multiple-choice type questions on numeracy, risk-diversification, inflation and the time value of money. For every right answer, one mark was awarded, and finally adding the scores obtained by the respondents for the five questions, the percentage of the FL score of the individual level was ascertained. The different variables that are used in the study are summarised in Table 1. PB is the variable of concern in this study, and the rest of the independent variables are control variables.

The following two empirical specifications were used in the study:

Savingsi=δ0+δ1P_Bi+δ2Fin_Liti+δ3Geni+δ4Mari+δ5Widi+δ6 Div i+δ7Livi+δ8 Poori+δ9Age i+δ10 Edu_Prii+δ11Edu_Seci+δ12 Edu_HSi+δ13Edu_Othi+ε

Borrowingsi=β0++β1P_Bi+β2Fin_Liti+β3Geni+β4Mari+β5Widi+β6 Div i+δ7Livi+δ8 Poori+δ9Age i+δ10 Edu_Prii+δ11Edu_Seci+δ12 Edu_HSi+δ13Edu_Othi+µ

Results and discussion

Table 2 exhibits the demographic attributes of the respondents of the study. Out of the total number (47,132) of respondents, a very small percentage (8.23%) was found to be present biased. It emphasises that the majority of the respondents do not prefer instant gratification at the cost of future returns and are free from such behavioural bias in the Indian context. Of the total respondents, 52.9% were female, whereas out of the total present biased respondents (3,878), 51.7% were female and 48.3% were male. Analysis of the marital status of the respondents unveils that most (73%) of the respondents with PB (70.4%) were married, which points out that married people are more inclined towards the present as compared to their counterparts. As far as the economic condition of the respondents was concerned, 60.8% belonged to “below poverty line” economic status. Similarly, amongst the total number of present-biased respondents, 58.2% were from “below poverty line” economic conditions, and the rest (41.8%) were from “above poverty line” backgrounds, which implies that poor people tend to be more present-biased. It is evident that people of poor economic status are more concerned with the present situation due to low levels of income, and therefore, they have a greater likelihood of being present-biased. Approximately 67% of the total, as well as present-biased respondents, were from 15–24, 25–34 and 35–44 age groups. The presence of present-biased respondents across all age groups reflects that no particular age cohort is more prone to such behavioural bias. Out of the total number of respondents, 31.8, 31, 27.9 and 9% had no formal education, primary education, secondary education and higher education, respectively. On the other hand, 28.8% of the present-biased respondents did not have any formal education, 27.7% had primary education and 30.9% possessed secondary education. 477 (12.2%) respondents with higher education were found to be present-biased. The frequency distribution of present-biased respondents across different education levels shows a weak linkage between the levels of education with such behavioural biases.

In Table 3, an attempt was made to explore the effect of PB on and borrowing habits. The adverse effect of this cognitive bias on both financial behaviours such as saving and borrowing was very much evident. The sign associated with the variable PB was found to be negative and statistically significant concerning the savings habits of the sample respondents. In line with the theoretical proposition, a present-biased individual prefers present consumption instead of thinking about the future, and thereby, such bias tends to augment present consumption and ultimately limit the ability of those individuals to save. Aronsson and Sjögren (2014) also argue that due to the bounded rationality problem and PB, an individual fails to save adequately. The finding of the study is in line with the outcome of the study carried out by Goda, Levy, Manchester, Sojourner, and Tasoff (2019), in which they advocated that PB as well as exponential growth bias [1] adversely affected the retirement savings of the individuals. Individuals with PB fail to exercise adequate control over their spending, resulting in inadequate savings (Meier & Sprenger, 2010). Empirical evidence also suggests that lack of self-control adversely affects wealth accumulation as a result of inadequate savings due to excessive present consumption (Ameriks, Caplin, Leahy, & Tyler, 2007; Gathergood, 2012). Brown and Previtero (2014) also argue that present-biased individuals fail to save adequately for their retirement.

Similarly, the outcome of the study also reveals that borrowing is expected to be augmented by a lack of self-control vis-à-vis the presence of PB. PB is regarded as one of the prominent explanations behind the human tendency to borrow by behavioural economists (Kuchler & Pagel, 2021). Heidhues and Kőszegi (2010). Meier and Sprenger (2010) showed that self-control problems can be cited as the possible explanations for high levels of credit card borrowing. Such a high level of borrowing ultimately leads to consumer over-indebtedness. Kuchler and Pagel (2021) argue that it seems convenient for present-biased individuals to carry forward the debt to the next period, which supports their urge to go for greater consumption in the current period. A naive individual suffers more from this problem than informed and conscious individuals (Donoghue & Rabin, 1999). The naive individuals do so because of their ignorance about their future impatience. Such ignorance leads them to postpone their debt paydown in the subsequent period, which he/she incorrectly predicts himself/herself to be more patient. In reality, they keep on delaying the debt paydown in each period, which ultimately culminates in indebtedness. On the contrary, sophisticated individuals who are aware of their future impatience do not delay the debt pay-down and tend to seriously follow a debt paydown schedule. Gathergood (2012) observed that overindebtedness was found to be prominent amongst the present-biased individuals. Often, such people with a lack of self-control use quick-access credit products to buy goods impulsively (Gathergood, 2012). Further, Gathergood and Weber (2017) highlighted the inclination of the present-biased individuals in choosing complex mortgage products with back-loaded payments such as alternative mortgage products rather than a standard repayment mortgage. Because of a short-run myopic attitude toward the present, neglecting future preferences, individuals often tend to borrow excessively (even at a high rate of interest) and ultimately fail to repay.

As far as the control variables are concerned, the effect of FL on savings and borrowing behaviour was found to be positive and negative, respectively. The effect of FL on the two financial behaviours was observed to be in line with the existing theoretical propositions. The catalytic role that FL plays in nurturing saving habits amongst individuals is well documented in the extant literature (Beckmann, 2013; Lusardi & Mitchell, 2014). A financially literate person has adequate knowledge of various fundamental financial issues, which helps them to exploit the advantages associated with savings. Further, FL induces financial discipline, which leads to underspending and, ultimately, savings. The outcome of the positive effect of FL on savings behaviour is consistent with the findings of the study carried out by Murendo and Mutsonziwa (2017). Empirical evidence also suggests that FL prompts excessive borrowing (Lusardi & Tufano, 2015). The negative effect of financial illiteracy on borrowing behaviour is well-accepted in the extant literature. For example, Sevim, Temizel, and Sayılır (2012) noted that Turkish people with a low level of FL borrowed excessively and recommended the promotion of FL to curb over-borrowing tendencies. Mitchell and Lusardi (2015) also argue that financially literate people are less likely to borrow and manage credit effectively to avoid indebtedness. Firstly, low FL adversely affects savings, and due to such low savings, people opt to borrow. On the other hand, Stango and Zinman (2009) opine that people lacking FL, more specifically debt literacy (Lusardi & Tufano, 2015), cannot properly compute interest and are expected to borrow excessively.

Out of the demographic variables, gender was found to be the important predictor of both financial behaviours. It implies that male respondents are more likely to save as well as borrow as compared to their female counterparts. Such a significant gender divide in savings and borrowing was also observed by Murendo and Mutsonziwa (2017) and Sevim et al. (2012), respectively. The outcome of the study also pointed out that marital status appears to be one of the major determining factors of savings and borrowing, which is similar to the findings of the study carried out by Sevim et al. (2012). Perhaps the most common and yet most sensitive determinant of savings and borrowing habits of the individual is the income and economic status. It is very much obvious that people belonging to the low-income strata, due to resource constraints (along with a higher marginal propensity to consume), fail to save adequately and are inclined to borrow to make ends meet. The outcome of the study also shows that the coefficient associated with the variable “poor” was found to be negative with respect to savings and positive with respect to borrowing, respectively. In line with the accepted belief, the result of the study also signifies the inability of poor people to save more and thereby borrow more (Grohmann, 2018; Lusardi & Scheresberg, 2013). The age of the individual was noticed to be a major predictor of the financial behaviours of the sample respondents. Lastly, the outcome of the study showed that respondents with primary, secondary and higher secondary education are expected to save more compared to the respondents with no formal education, which is in line with the study carried out (Beckmann, 2013; Grohmann, 2018). Respondents with primary and other forms of education were noticed to exhibit greater borrowing inclination compared to the respondents with no formal education. The goodness of fit of both the estimation can be confirmed from the values of pseudo R² were and the statistically insignificant Hosmer–Lemeshow test statistic. Moreover, the prediction accuracy for both the models was observed to be more than 80% (with very few Type-I error) along with the values of area under receiver operating characteristic (ROC) curve over 75% in both models, ensuring the good predict ability of the estimations.

Conclusions and policy recommendations

Cognitive biases play an important role in shaping the financial behaviour of individuals. Behavioural economists across the globe are making every effort to dig deep into these cognitive biases and explore the presence of any new form of cognitive bias and how such biases affect financial behaviour. Such biases prompt individuals to undertake sub-optimal financial decisions. Knowledge in this direction will help the researchers, financial advisors, analysts, financial institutions and policymakers to adopt appropriate strategies and induce the required nudges to reduce the effect of these cognitive biases. PB is one of the cognitive biases that create an inclination amongst individuals to prefer immediate gratification at the cost of higher future rewards. PB can be explained hyperbolic discounting model, the theory of self-control and behavioural life-cycle models. In this context, using the FII 5th wave (2017) data, the article makes a modest effort to investigate the presence of PB amongst individuals in the Indian context. The study also tries to test the adverse effect of this bias on individual financial behaviours, namely savings and borrowings. The outcome of the study showed that PB was found to be prevalent amongst 8.2% of the sample respondents. As far as the effect of the PB on the savings and borrowing decision is concerned, the major result of the study, in line with the existing theoretical conviction, revealed that present-biased individuals fail to save adequately, whereas they are more inclined towards borrowing.

Insufficient savings of present-biased individuals can be detrimental to the overall financial health of the individual as well as the household. The over-indebtedness problem on account of excessive borrowing by the present-biased individuals makes them financially vulnerable. Such financial fragility of present-biased individuals also makes them susceptible to any kind of contingent financial shocks. Reducing the PB is therefore extremely important to shield present-biased individuals from such financial fragility. The role of FL through financial education in contracting the adverse effect of this bias cannot be undermined in this process of de-biasing (Xiao & Porto, 2019). PB amongst individuals can be reduced by self-imposed commitment (discipline) to overcome this problem. Saving is not only important for financial well-being at the individual level but is also equally significant for economic growth and the prospects of an economy (Aronsson & Sjögren, 2014). Government subsidies in the form of some matching contribution or tax concessions have been advocated for by previous researchers to encourage present-biased individuals to save (Aronsson & Sjögren, 2014; Laibson, 1996). Automatic enrolment in savings with an opting-out option, automatic periodic increase, mandatory lock-in period, solution-oriented investment, savings incentives, matching contributions, visual progress tracking and peer comparison in terms of peer comparison can be effectively utilised to curtail the effect of PB on the savings behaviour of the individuals. Similarly, financial counselling, availability of transparent information, pre-committed repayment plans, compulsory borrowing decision rethinking (cooling-off) period, highlighting cost consequences and debt tracker can be utilised to minimise the effect of the PB on the borrowing behaviour. In addition, FL of the individuals is also to be promoted to improve their financial behaviours. Upon identification of a present-biased client, financial planners have an important role in making the client aware of such bias and applying appropriate nudges so that de-biasing can effectively be executed systematically.

Table 1

Description of the variables

Variables (abbreviation)	Description
Savings	Respondent saves=1,else=0
Borrowing	Respondent has borrowing = 1, else=0
Present bias (P_B)	Present biased=1,else=0
Financial literacy (Fin_Lit)	Financial literacy score ranging between 0 to 1
Gender (Gen)	Male=1,else=0
Married (Mar)	Married=1,else=0
Widow (Wid)	Widow=1,else=0
Divorced (Div)	Divorced=1,else=0
Living-in (Liv)	Living in=1,else=0
Poor (Poor)	Poor=1,else=0
Age (Age)	Actual age of the respondent
Education up to class 4 (Edu_Pri)	Respondent’s education up to class 4=1,else=0
Education up to class 10 (Edu_Sec)	Respondent’s education up to class 10=1,else=0
Education up to class 12 (Edu_HS)	Respondent’s education up to class 12=1,else=0
Other Education (Edu_Oth)	Respondent’s having other education=1,else=0

Source(s): Author’s own compilation

Table 2

Demographic profile of the respondents

Attributes		Overall		Present biased
		Frequency	%	Frequency	%
Present_Biased	Yes	3,878	8.2	–
	No	43,254	91.8
	Total	47,132	100.0	3,878	100
Gender	Male	22,179	47.1	1,872	48.3
	Female	24,953	52.9	2,006	51.7
	Total	47,132	100	3,878	100
Marital status	Single	8,695	18.4	790	20.4
	Married	34,385	73.0	2,730	70.4
	Divorced	280	0.6	27	0.7
	Widowed	2,746	5.8	232	6.0
	Living together	1,026	2.2	99	2.6
	Total	47,132	100.0	3,878	20.4
Economic condition	Above Poverty Line	18,473	39.2	1,620	41.8
	Below Poverty Line	28,659	60.8	2,258	58.2
	Total	47,132	100.0	3,878	100
Age group	15–24	9,959	21.1	836	21.6
	25–34	12,081	25.6	1,002	25.8
	35–44	10,004	21.2	810	20.9
	45–54	6,909	14.7	529	13.6
	55 and Above	8,179	17.4	701	18.1
	Total	47,132	100.0	3,878	100.0
Education	No formal education	15,004	31.8	1,115	28.8
	Primary education	14,631	31.0	1,073	27.7
	Secondary education	13,137	27.9	1,200	30.9
	Higher education	4,262	9.0	474	12.2
	Other education	98	0.2	16	0.4
	Total	47,132	100.0	3,878	100.0

Source(s): Author’s own compilation

Table 3

Effect of present bias on savings and borrowing behaviour

Note

1. Inclination to ignore compounding.