A fresh perspective to economic theory: Social preferences and their impact on gender and policy
A fresh Perspective to Economic Theory: Social Preferences and their Impact on Gender and Policy
Authors: Sheral Shah
Review: Prof. Shagata Mukherjee
The Neoclassical and New Keynesian models have been traditionally used in economic theory and practice. However, in recent times the New Neoclassical synthesis (DSGE models) has been dominating the macroeconomic field. These models are being widely used even after they suffered wide criticism for failing to take into account the possibility of a crisis in the likes of the global recession. In their purest sense, what all of these schools of thought have in common is that they are constructed on the framework of representative economic agents who are self-interested and rational in their approach. They are based on the idea of homo economicus, a term believed to be first used by Vilfredo Pareto. Homo economicus concerns itself with the idea that under all circumstances an individual’s actions are driven by acts of rationality, individualism, and utility optimization and that preferences are exogenously given (Urbina and Ruiz-Villaverde, 2019). Challenging these ideas and calling into question their adequacy, the branch of behavioral economics or behavioral macroeconomics introduces an alternative approach towards decoding an individual’s behavior and predicting outcomes. According to Roos (2017), incorporating behavioral theory into macroeconomics (as it is largely accepted in microeconomics) will aid in doing away with the redundant idea of homo economicus as behavioral economics assumes bounded rationality and studies economic agents as they really are i.e. with their non-selfish or other regarding preferences. While, behavioral macroeconomics is an emerging branch which borrows from the assumptions of behavioral theory to predict outcomes more realistically, it has certain limitations which are attached to the very foundation of DSGE models. Such models either continue to maintain some degree of rationality or use the representative agent assumption (Roos, 2017).
It is extremely crucial to do away with perfect rationality on the part of economic agents and to also recognize heterogeneity in behavior. Agent-based models and complexity economics provide answers to these problems (Mullainathan and Thaler, 2000; Dawid et al, 2012; Caiani et al, 2016). Not going into further details of the synthesis between behavioral economics and macroeconomics, it is clear that behavioral theory helps in realistically and better predicting behavior and outcomes by recognizing that individuals are not always self-interested and are guided by non-selfish motives. The idea here is to provide details about the non-selfish preferences which is the essence of behavioral theory. Also known as social preferences, they are said to be exhibited by a person if he/she concerns himself/herself by the payoffs of others too. Or, according to Fehr and Fischbacher (2002, p. 2), “a person exhibits social preferences if the person does not only care about the material resources allocated to her but also cares about the material resources allocated to relevant references agents”. Numerous economists, using several experimental techniques have modelled social preferences in the forms of trust and trustworthiness (reciprocity), inequality aversion, unconditional altruism, and spiteful preferences. These experimental techniques usually take the form of ultimatum games, dictator games, trust games, public goods games, etc. Evidence from the results of these games suggests the influence of societal structure and norms on social preferences (Croson and Gneezy, 2009). That is, there is observed heterogeneity in the social preferences of groups of people and even across gender due to societal structures. There is another array of literature which posits the influence of genetic make-up on social preferences. However, no matter how social preferences develop, there is consensus about their positive association (especially trust and trustworthiness) with economic growth and development (Knack and Keefer, 1997; Zak and Knack, 2001; Guiso et al, 2004; Karlan, 2005).
Types of social preferences
As mentioned previously, over the years various forms of social preferences have been studied by experimental and behavioral scientists.
Unconditional Altruism: An unconditional altruistic behavior is when an agent does not want to reduce the material payoffs of other agents or when altruistic or cooperative behavior is not just a reaction given to the altruistic behavior shown by others (Anderoni, 1989).
Trust and Trustworthiness (Reciprocity): According to Cox (2001), trust can be defined as the beliefs that one agent has about the behavior of other agents. On the other hand, trustworthiness or reciprocity or conditional altruism is when people are induced to respond to “kindness with kindness and unkindness with unkindness even when it is not in their material interest to do so” (Greig and Bohnet, 2008, p. 77). These can be regarded as the strongest and most important preferences from the perspective of experimental research.
Inequality Aversion: Fehr and Schmidt (1999) suggest that inequality aversion is present when people want an equitable distribution of resources such that they show altruistic behavior when they feel that other people’s “material payoffs” are below a certain “equitable benchmark”, and envious behavior when they want to decrease others “material payoffs” as they may be perceived as exceeding the “equitable benchmark”. At times, a lot of similarity can be found between the behaviors of reciprocity and inequality aversion (Fehr and Fischbacher, 2002).
Spiteful Preferences: These preferences are exhibited by an agent when he/she views the material payoffs of others negatively and is willing to decrease those payoffs even when such intentions come with a personal cost. These preferences are independent of fairness or unfairness shown by the other agents. However, these preferences are not very extensively documented or studied and are less important than say reciprocal behavior in the experimental field (Fehr and Fischbacher, 2002).
Experimetal designs to study social preferences
The above explained social preferences have been studied by using various experimental designs. Different designs are used to test different kinds of preferences. These designs work on the game theoretical idea of sub-game perfect Nash equilibrium which is achieved when the behavior of the participants is driven by self-interest. A behavior deviating from this equilibrium is explained as being driven by non-selfish preferences. The basic structure of major experimental designs is explained below. All of these experiments have been used with some or the other form of variation to study various kinds of social preferences.
Dictator Game: One problem which is said to be associated with the ultimatum game is that a deviating motive can also be interpreted as that of risk aversion. Therefore, similar in design, a dictator game also consists of two players (player 1- proposer, player 2- respondent) between whom a sum of money is to be divided. However, here the respondent is not given the choice of rejecting any offer extended by the proposer. Behaviors here can be interpreted as that of inequality aversion or altruism but not risk aversion since, player 1’s offer is binding onto player 2 (Cooper and Kagel, 2013).
Ultimatum Game: A form of a bargaining game, this is a two-player game wherein a sum of money is to be divided between Player 1 (proposer) and Player 2 (responder). The proposer is given the task of deciding on an offer regarding how money to divide between the two which is then accepted or rejected by the responder. In case of acceptance, both the players end up having the offered sum of money and in case of rejection, none of the players end up with any sum of money. To give an example, giving an offer and it being accepted is the sub-game perfect Nash equilibrium. Deviations from this equilibrium have been interpreted as social preferences of inequality aversion, reciprocity (negative), and altruism (Croson and Gneezy, 2009).
Trust (Investment) Game: To measure trust and trustworthiness, in this sequential two player game player 1 is endowed with a sum of money, some or all of which can be transferred to player 2. This sum of money is first multiplied n>=1 times by the experimenter and then passed on to player 2. Player 2 then, can keep this entire multiplied sum of money or pass any amount back to Player 1. Player 1’s and Player 2’s behavior, if it deviates from the sub game perfect Nash equilibrium, is interpreted as being driven by trust and trustworthiness respectively.
Public Goods Game: Voluntary Contributions Mechanism (VCM) is a form of a public goods game, to provide for evidence for altruistic behavior. Here, participants are given with some endowment along with the option of allocating it towards their own private consumption or towards the consumption of the group. Presenting a social dilemma, the endowment is of more value if consumed privately but generates social efficiency in case of group consumption. The sub game perfect Nash equilibrium is to contribute nothing for social consumption, a deviation from which is interpreted as an altruistic motive (Croson and Gneezy, 2009).
Determinants of social preferences: Nature vs. Nurture
The existing knowledge about how social preferences develop is attributable to two streams of thought i.e. nature and nurture. Not only do they explain social preferences at the individual level but also gender differences in these preferences. That is, say the degree of trust and reciprocity may vary from person to person or group to group, it may also vary according to gender. According to Eagly and Wood (2013, p. 1), “nature refers to biological structures and nurture refers to sociocultural influences”. While, a part of the literature argues in favor of nature in influencing social preferences as well as the gender difference in social preferences, this essay lays more focus on the literature on nurture.
Socio cultural factors such as social distance between economic agents, equal/unequal distribution of resources, social norms, religion, ethnicity, social history, etc. have been positively associated with social preferences. Fehr (2009), suggests that social preferences are driven by ethnic and cultural differences. On similar lines Guiso et al (2004), put forward religion as being one of the determinants of trust. Zak and Knack (2001), find that trust is higher in more egalitarian societies, and in societies in which the social distance between agents is smaller. Berg et al (1995), find that more information regarding social history increase the likelihood of agents showing reciprocity. Socio cultural factors and related determinants lead to the internalization of certain behaviors which translate into different types and degrees of social preferences in individuals.
Social norms and societal structures also define gender specific roles which basically form a gender gap in social preferences. Croson and Gneezy (2009), conducted a review of the literature on social preferences to identify gender differences. They found that sometimes women are more altruistic, inequality averse, trusting and trustworthy than men and sometimes it is the other way around. Though, gender differences in social preferences exist, there is heterogeneity in this gap which can be attributed to the differing social norms and cultures. Other than nurture, research has attempted to link the genetic-make up of individuals with social preferences (Cesarini et al, 2009). However, the influence of genotype/genes on social preferences has been found to be comparatively weak (Garboua et al, 2006; Dickhaus, 2013). And, the view that it is ultimately the socio-cultural determinants or their interplay with genetic makeup that affect social preferences has been quite strongly dominating experimental practice.
Importance of social preferences
As opposed to the conventional over-simplified assumption of self-interested individuals, strong evidence points towards the presence of heterogeneous other-regarding preferences in agents. Incorporating social preferences – specifically, trust and reciprocity - and recognizing the non-constancy of these preferences across individuals can help models better represent the reality. As Fehr and Fischbacher (2002) suggest, “there is strong evidence indicating that the deviations from self-interest have a fundamental impact on core issues in economics”.
The benefit of adopting the social preference framework is not only limited to economic modelling. Research suggests a strong linkage between the behaviors of trust and reciprocity and economic growth, reduction in the cases of default in cash transfer programs and group lending and saving programs and increasing financial inclusion, and in increasing the effectiveness of governments and central banks (Knack and Keefer, 1997; Karlan, 2005; Bachas et al, 2017). They are also known to lead to increasing returns on human and physical capital by increasing educational attainment, public health outcomes and total factor productivity (Knack and Keefer, 1997; Gilson, 2003; Rocco et al, 2013). Trust and reciprocity have been positively related with international trade and investment, and innovation (Narayan and Pritchett, 1999; Zak and Knack, 2001; Guiso et al, 2004).
The functioning of these preferences is such that, if all transactions and markets are forms of contracts then with them come the issues of enforceability, imperfect knowledge and market failure. The preferences in questions are known to decrease the likelihood of market failures and also reduce transaction costs. According to Zak and Knack (2001), “trust reduces the cost of transactions, high trust societies produce more output than low trust societies”. It can be said that recognising social preferences through modelling and also framing policies accordingly can pave the new road towards development. If trust and reciprocity are to be focused on, then societies can take measures to increase the degree of these preferences by increasing the flow of information, transparency and accountability. Societies can also formulate policies which exploit these preferences such as, introducing and expanding micro-finance programs. These programs are specifically very beneficial for the less developed economies. According to Besley and Coate (1993), micro-financial setups, along with reducing the asymmetric information gap impose a sense of interdependence upon its beneficiaries. Ripple effects include greater financial coverage and inclusion, increased access to credit, increased investment in education and health care, and important welfare effects such as reduced consumption of alcohol and tobacco (Karlan, 2005; Bachas et al, 2017).
As mentioned previously, social preferences also vary across gender. However, this variance is a function of the societal structures and norms (according to some it is because of the gender difference in genetic make up). The very fact that a gender difference exists is enough to change the direction of policy formulation. Ranehill and Weber (2017), show that a gender difference in preferences translate into a gender difference in policy preferences. That is, women tend to prefer a different set of policies than men. Therefore, societies can take advantage of the gender gap in social and policy preferences and increase the decision-making power of women through quotas and reservations to change the flow of resources towards areas which women prefer. On the other hand, “when men and women do not have equal chances to be socially and politically active and to influence laws, politics, and policy making, institutions and policies are more likely to systematically favour the interests of those with more influence” (World Bank, 2012, p. 6). This can help bring about-the much required and sought after-gender equity. This could directly lead to women empowerment which is helpful for economic development. In fact, women empowerment and economic development share a bi-directional causal relationship (World Bank, 2012; Duflo, 2012).
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