Faculty & Research

Ongoing Projects- NSE

Ongoing Projects

  1. Neuropricing (Prof. Arvind Sahay, Richa Nigam)
    Non-Price attributes are equally crucial to purchase decisions as much as the price of a commodity in enhancing the perceived value and perceived quality of the products. The current study empirically tests the effect of modulations in IRPs and purchase decisions formed as a function of changes in expected future non priced attributes.
  2. Consumer perceptions of different front-of-pack labels for Indian packaged food (Prof Arvind Sahay, Prof Ranjan Kumar Ghosh, Anushka Oza, Divya Reji)
    The objective of this study is to understand which front-of-the-pack-labels (FOPL) are most suited for Indian consumers in helping to choose healthier packaged food products. The sustainability is indicated by the comprehensibility, credibility and likeability of the FOPL and its ability to influence purchase decisions. Globally, FOPLs have evolved as an important complement to the Nutrition Facts Table as the latter are difficult for consumers to interpret (Ahmed et al., 2020; Hodgkins et al., 2012). They contain numerous forms of information on nutrients that include mandatory and voluntary measures adding to the confusion of consumers. Moreover, while consumers have the ability to interpret simple information in differentiating between product characteristics, they find the tables difficult to use for health choice decisions. On the other hand, some studies have shown that FOPL helps guide healthier product choices (Watson et al., 2014). There are numerous studies that have analyzed the effectiveness of different FOPL formats in different countries that have implemented these systems either on a voluntary or mandatory basis. However, in developing countries, FOPLs are still not much in practice. In this context, the proposed study planned to test the efficacy of different types of FOPLs.
  3. Creating online survey for risk profiling of inventors (Prof Arvind Sahay, Prof Jacob Joshy, Anushka Oza, Divya Reji)
    Lately in the field of behavioral finance there has been a rising cognizance of how biases and heuristics affect decision making. Along with these cognitive factors, investment decision making is also heavily influenced by environmental and personal factors of the investors. Emotions, habits, risk taking ability and social influences have been observed to impact people's economic decisions. People's risk propensity is seen to vary across domains, i.e., people may display higher risk taking abilities in recreational and social domain, but exhibit risk averse behavior in the financial domain. In the present project we aim to profile investors based on their behavioral biases and risk propensity.
  4. Understanding Indian Millennial Investors Stock Preferences (Prof Arvind Sahay, Anushka Oza, Divya Reji, Mayank Prakash)
    Even though the financial year 2020-21 seemed to have locked everybody in their houses due to the Covid-19 pandemic, it witnessed an unusually high influx of young Indians who decided to step in and try their hand in the Indian stock market. The Indian economy observed a shift in the investment pattern, as more people decided to opt out of traditional financial avenues to switch to alternatives like the stock market. The outcome of this switch was seen in the data from the National Securities Depository Ltd (NSDL) and the Central Depository Services Ltd (CSDL) which reported a stunning boom of 14.2 million new Demat accounts opened in FY21 (Sultana and Ramarathinam, 2021). The present study is an exploratory study aimed to assess the choices made by Millennial investors in the Indian stock market.
  5. Household Investor Survey (Prof Jeevant Rampal, Prof Jacob Joshy, Mayank Prakash, Abhishek Tripathy)
    We intend to collect granular data on how Indian households take investment decisions. The survey will try to understand what drives the Indian household investor to invest in the way they choose to invest and what are the factors that influence the asset allocation for the Indian household investors. We will try to analyse if there is persistence of the household finance puzzles in Indian context which have been extensively talked about in the literature. We also intend to understand behavioural aspects of the decision making process of the Indian household. This would be one of a kind survey for Indian household investors.
  6. Paper about the strategic interaction between the government and various agents in developing a market infrastructure institution (Prof Arvind Sahay, Mr Sudheesh Nambiath, Mayank Prakash)
    This paper tries to analyse games of strategic complementarities using the Global Games literature for situations where the fundamental is endogenous and players are heterogeneous. We intend to understand it as a single period game where a principal and continuum of heterogeneous players play the game. The fundamental evolves positively with the participation of more players. The principal has a role to persuade the players towards a socially optimal equilibrium. The decision of a player to play a particular strategy depends on the fundamentals and what other strategies of other players. Global Games literature has modelled the game in situations of bank run or regime change where the fundamental is the strength of the bank or regime given exogenously at the beginning of the game. The players get a noisy signal about the fundamental and other players' strategies and hence decide their strategy. In this paper we propose that the fundamental is endogenous. Suppose, the principal presents an idea which has a particular strength i.e initial fundamental value but it can only be successful if it is supported by enough players. So the fundamental strength of the idea is dependent on the number of players participating in support of the idea. The basic strength of the idea i.e fundamental will hence depend on the actual strength of the idea and the number of players supporting it. The players would have a situation of strategic complementarity. We intend to understand the equilibrium in such situations.
  7. Institutional Noise trading and its effect on volatility in the Stock Markets due to behavioral biases specifically Diagnostic Expectation (Prof Jacob Joshy, Mayank Prakash)
    There might be ample reason to believe that institutions might have some behavioural biases while trading especially when they are noise trading. We strive to study if in the event of a shock like the crash of March 2020, do these institutional investors relying on Diagnostic Expectations lead to excessive volatility. We would also like to understand if the results depend on whether the institutions are Domestic Institutional Investors or Foreign Institutional Investors. Further we also like to investigate if there is a difference in the results in developed and developing markets with a keen focus on India.
  8. Ethics at workplace (Prof Arvind Sahay, Richa Nigam)
    The project aims to explore modes from behavioral science that can be adopted to help a firm to assess the value of ethics among employees. These bear implications in hiring process and employee evaluation in critical times.
  9. Opponent’s foresight and optimal choices (Prof. Jeevant Rampal)
    Using two experiments, this paper demonstrates that expert players of sequential- move games best respond to their opponents’ backward-induction ability. In particular, I show that these experts take advantage of inexperienced opponents’ weakness in backward induction. I find this when the expert is explicitly told that her opponent is inexperienced, but also when she infers the opponent’s weakness from the opponent’s preceding performance. I demonstrate that other-regarding preferences have no role in these findings. I find that a novel model of limited foresight and uncertainty about the opponent’s foresight fits the data better than Level-k or Quantal Response models.
  10. Task satisfaction and charitable giving (Abhishek Mundhra, Prof. Jeevant Rampal, Divyanshu Jan, and Praneel Jain)
    Using online experiments, we study how charitable donations are causally affected by the nature of the task performed as part of one’s job. We find that donations are significantly higher for participants who were randomly allocated to a task designed to be ‘interesting’ compared to those participants who were randomly allocated to a task designed to be ‘tedious’, even though both tasks yielded equal earnings. We also measure the causal impact of making the nature-of-task salient before donation decisions. We find that this salience has a differential impact on the ‘interesting’ and ‘tedious’ tasks; salience reduces donations for the interesting task but increases donations for the tedious task.
  11. Information and behavior during COVID-19 (Prof. Ritwik Banerjee, Prof. Anujit Chakraborty, and Prof. Jeevant Rampal)
    Using a randomized-control-trial design, we study: (a) the level of support for a lockdown in rural Telangana, India, in September 2020, and (b) the causal impact of increasing COVID-salience on the support for a lockdown. As our salience intervention, we use a short audio clip containing commonly available information about COVID-19. The two control groups have a placebo audio clip which makes Dengue salient and no audio-clip respectively. We find high support (45%) for lockdowns in control groups, and, that a simple COVID-salience intervention causally increases the willingness to continue lockdown by 25 percent and the reported appropriate number of days under lockdown by 33 percent. Assuming the second wave in India increased COVID-salience, our results suggest that there may be widespread support of a lockdown despite the economic consequences.
  12. Contests within and between groups (Prof. Puja Bhattacharya and Prof. Jeevant Rampal)
    This paper examines behavior (theoretically and experimentally) in a two-stage group contest where the first stage comprises intra-group contests, followed by an inter-group contest in the second stage. Rewards accrue only to the members of the winning group in the inter-group contest, with the winners of the intra-group contest within that group receiving a greater reward. The model generates a discouragement effect, where losers from the first stage exert less effort in the second stage than winners. In contrast to previous frameworks of sequential contests, we show that a prior win may be disadvantageous, generating lower profits for first stage winners as compared to losers. This implies that incentives for participation in the first stage may not always be present. We also consider exogenous asymmetry between groups arising from a biased contest success function in the second stage. We show that although the asymmetry occurs in the second stage, the effect of the asymmetry plays out in the first stage, with the intra-group contest being more intense within the advantaged group. Experimental results find broad support for the qualitative predictions of the model. However, we find that relative overcontribution in the second stage by losers is higher than by winners of the first stage, implying that losers bear a higher burden of the group contribution than deemed strategic.
  13. Strategic incentive for giving may be counterproductive (Prof. Jeevant Rampal)
    In an experimental test of a modified dictator game, I find that incentivizing a dictator to give at least a small proportion of her endowment drives non-incentivized giving to zero. This reduces overall giving relative to the standard dictator game. Thus, introducing strategic incentives for giving can be counterproductive.
  14. Trust and Algorithmic Control (Prof. Aditya C. Moses, Prof. Shaivi Mishra)
    Algorithms may enable efficient, optimized, and data-driven decision-making, and in fact this vision is one of main drivers of increasing adoption of algorithms for managerial and organizational decisions. However, the fact that these decisions are made by algorithms, rather than by people, may influence perceptions of the decisions that are made, regardless of the qualities of the actual decision-outcomes (Sundar and Nass, 2001). Furthermore, employees who are subjected to algorithmic control may not be satisfied if they believe they have tacit knowledge which the algorithm does not possess. They may also not understand how the algorithm works. All these factors may lead to perception of reduced and agency and cause them to distrust the algorithm. Johannsen and Zak (2021) in multiple studies using neuroscience have shown that trust leads to better productivity of employees and enhances organizational performance. Therefore, we propose two research questions:
    1) What is the impact of algorithmic control on Trust? What factors impact trust?
    2) What can organizations do to enhance trust in algorithmic control?
  15. Developing CAPE indicator for the Indian market (Prof Jacob Joshy)
    It is important to assess the level of financial market valuation relative to fundamentals through suitable indicators. One of the widely employed indicators of market valuation is the cyclically adjusted PE ratio (CAPE). The research project intends to develop and maintain a frequently updated database of CAPE for the Indian market, as a barometer of market valuation. It is intended to provide guidance for financial market practitioners, including fund managers and traders to monitor the aggregate market valuation levels.
  16. A Report on the Study of Capital Requirements of Market Inter- mediaries (Prof Jacob Joshy)
    This paper aims to develop risk-based capital adequacy norms for the intermediaries that would provide reasonable comfort regarding loss-absorption capacity of the intermediaries and mitigate the risk of spillover of losses to non-defaulting clients.