Disclaimer: This assignment was written by a student and is not an example of our proffesional work. You can view professional samples here.

Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not reflect the views of BusinessTeacher.org. Information in this assignment should not be used to form the basis for any kind of financial or investment advice, as the content may contain inaccuracies or be out of date..

Testing Rational Choice in Economics

1834 words (7 pages) Business Assignment

24th Nov 2020 Business Assignment Reference this

Tags:

India is one of the world’s largest growing economies, yet over 90% of leftover waste is being dumped into landfills (Narayanan, 2008). Littering and waste on the streets is a large problem that detrimentally impacts public health (Kumar et al., 2016). Litter is as any piece of solid waste that has been disposed off inappropriately (Geller, 1980). This could be due to incorrect bin disposal or disposed nonchalantly onto the street. The majority of litter are cigarette butts, paper, food wrappers, and plastic (Schultz et al. 2013). The presence of litter warrants environmental, social, and health concerns. It harms the environment (Jayasiri et al., 2013), while possibly affecting the monetary value of the surroundings (Skogan, 1990) and causing health concerns due to hygiene. As of 2019, there is insufficient data available on the amount of waste that is produced on the street in the form of littering in India.

Whilst collective awareness is necessary, societal behavioural change is difficult to attain at with a population this large and diverse. Everyone may not be calculative of how littering affects their future, in spite of exposure to social norms and political campaigns (“Swatch Bharat”/“Clean India” campaign, 2016). Behavioural economics states individuals serve to maximise their own self-interest. So, what prevents individuals from behaving rationally and enhancing quality of life? The theory of bounded rationality states that irrational behaviour may occur due to lack of information, i.e. unawareness of the impact littering has on our lives and environment, but understanding may not be enough to warrant change.

Individuals who litter may be engaging in present bias or hyperbolic discounting where they inconsistently discount the future benefits of their current actions. With India’s streets being extensively littered, the reluctance to stop littering behaviour may be connected to familiarity bias; familiarity to an unclean environment results in being more accepting of it. This could also be related to anchoring bias, which establishes probability estimates relative to a set prior (Tversky & Kahneman, 1974), wherein the unclean environment becomes the status quo. Behavioural insights have successfully nudged pro-environmental behaviours (Valatin, Moseley & Dandy; 2016) by addressing the systematic errors caused by heuristics. This violates the core tenet of rational choice wherein individuals work towards maximising their utility and satisfaction, and that individuals have consistent choices independent of irrelevant reference points.

Previous studies have shown that cleaning up litter has reduced the behaviour of littering, and individuals are less likely to litter when the environment is clean with appropriate bins (Keizer et al., 2008; Cialdini, Kallgren, and Reno, 1991). Schultz et al. (2013) exhibited the presence of litter and bins predicted littering. This experiment aims to change environmental conditions in order to reduce the frequency of littering in streets, using behavioural insights as the theoretical underpinning. It addresses the anchoring and familiarity bias by changing the norm of an unclean street being the status quo for consequently littering habits, while using signs to address present bias. 

Null Hypothesis: People will litter the same amount in a clean environment, with bins and informative signs, as they would in an unclean environment.

Alternate Hypothesis: People will litter lesser if their surrounding environment is clean, with bins and informative signs.

Method:

A street in Bangalore, India, of approximately one kilometre, will be identified for the clean up. i) The amount of garbage present on the street will be counted and categorized (KAB, 2007). ii) The study will also count the number of bins. After the area is thoroughly cleaned, we will place new bins. These bins will have ashtrays, as 14% of Indians smoke (WHO Report, 2019), and will be separate for general waste, plastic, and paper. The bins will have simple instructions and informative signs stating the amount of good achieved by recycling, in an effort to increase the norm to recycle. This is in opposition to stating the harmful effects of littering as it could normalize unwanted behaviour (Schultz et al., 2007). iii) Data on the amount of litter on the street will be collected the following day, and follow-up measurements taken a week, and month later. The saliency of the bins (which can be achieved through bright colours), and its placement will be vital to the intervention, as this predicts littering behaviour. (Schultz et al., 2013; National Cooperative Highway Research program, 2009).

Expected results & Limitations

The results are expected to show a lesser amount of recorded litter the following day, than prior to the intervention. It is anticipated this may be attributed to three biases being addressed: present, familiarity, and anchoring. The informative signs hope to address the present bias, displaying how one’s immediate action significantly affects the future. The study aims to resolve the familiarity and anchoring bias, by changing the status quo to a clean street. The study does foresee the litter increasing as the clean-up efforts deteriorate over time. With India’s diverse socio-economic population, the informative signs may not appeal to illiterate individuals, which account for 26% of the population (Indian Census, 2011). The study would need to be repeated to validate its effect, which requires a team to maintain the environment. We could involve existing voluntary clean-up groups and the residents, which could further decrease littering (Roales-Nieto, 1988).

Scope & Suggestions

The country could benefit by introducing financial/ tax incentives and penalties for anti-environmental behaviour. This has been proven to increase pro-environmental behaviours (Faruqui & Sergici 2010; Hassett and Metcalf, 1995). These costs require government funding and political backing to ensure its success. Another suggestion to incentivise environmental behaviours would be installing reverse vending machines that offer coins for recyclables. These are currently being employed in Greece, America, China, etc. This could motivate the general public to recycle more, but may not impact the informal sector (“waste pickers”) that make a livelihood off collecting recyclable scraps and account for 20% of waste collected (Annepu, 2012). Organisations such as “The Ugly Indian” have cleaned up spaces to find them deteriorating weeks after the project. Part of this was because they were unaware some places served as a space to segregate waste by the collectors. It is important to collaborate with the local municipal authorities to sustain environmental projects. Additionally, it would be valuable to adopt signs that appeal to illiterate citizens. It would also be beneficial to collect data that assesses the intervention’s effect on different socioeconomic backgrounds. Further research is suggested to look at alternative reasons people litter. Schultz et al., (2013) exhibited that 85% of littering were accounted for by individual variables. This could be extended to similar methods of observation in smaller spaces prevalent across India (bakeries, tea stalls).

References:

  • Annepu RK. (2012) Report on sustainable solid waste management in India. Waste-to-Energy Research and Technology Council (WTERT) 1-189.
  • Census Provisional Population Totals. (2011) The Registrar General & Census Commissioner, India.
  • Cialdini, R. B., Kallgren, C. A., & Reno, R. R. (1991). A focus theory of normative conduct: A theoretical refinement and reevaluation of the role of norms in human behavior. Advances in Experimental Social Psychology, 21, 201-234.
  • Faruqui A and Sergici S (2010) Household response to dynamic pricing of electricity a survey of 15 experiments, Journal of Regulatory Economics, vol. 38, pp. 193-225.
  • Geller, E. S., Brasted, W., & Mann, M. (1980). Waste receptacle designs and interven- tions for litter control. Journal of Environmental Systems, 9, 145-160.
  • H.B. Jayasiri, C.S. Purushothaman, A. Vennila (2013), Plastic litter accumulation on high-water strandline of urban beaches in Mumbai, India Environ. Monit. Assess., 185 (9), pp. 7709-7719
  • K.A. Hassett, G.E. Metcalf (1995), Energy tax credits and residential conservation investment: evidence form panel data, Journal of Public Economics, 57, pp. 201-217
  • Keep America Beautiful. (2007). KAB’s seven primary sources of litter. Retrieved from http://www.kab.org/site/PageServer?pagename=litter_sevensources

  • Keizer, K., Lindenberg, S., & Steg, L. (2008). The spreading of disorder. Science, 322, 1681-1685.

  • Kumar S, Smith SR, Fowler G, Velis C, Kumar SJ, Arya S, R, Kumar R, Cheeseman C. (2017) Challenges and opportunities associated with waste management in India. R. Soc. open sci. 4: 160764. http://dx.doi.org/10.1098/rsos.160764
  • National Cooperative Highway Research Program. (2009). Reducing litter on roadsides. Washington, DC: Transportation Research Board of the National Academies.
  • Narayan T. (2008) Municipal solid waste management in India: from waste disposal to recovery of resources? Waste Management 29, 1163–1166. (doi:10.1016/j.wasman.2008. 06.038) 

  • Roales-Nieto, J. G. (1988). A behavioral community programme for litter control. Journal of Community Psychology, 16, 107-118.
  • Schultz PW, Nolan J, Cialdini RB, Goldstein NJ, Griskevicius V. (2007) The constructive, destructive, and reconstructive power of social norms. Psychological Science, 18:429- 34
  • Schultz PW, Bator RJ, Large LB, Bruni CM, Tabanico JJ (2013) Littering in Context: Personal and Environmental Predictors of Littering Behavior. Environment and Behavior 45: 35-59. doi:https://doi.org/10.1177/0013916511412179.
  • Skogan, W. (1990). Decline and disorder: Crime and the spiral of decay in American neighborhoods. New York, NY: Free Press.
  • Tversky, A. Kahneman, D. (1974), Judgement under uncertainty: heuristics and biases. Science, 185, 1124-1131.
  • Valatin G, Moseley D, Dandy N (2016) Insights from behavioural economics for forest economics and environmental policy: potential nudges to encourage woodland creation for climate change mitigation and adaptation? For Policy Econ 72:27–36
  • WHO Report on the Global Tobacco Epidemic,(2019). www.who.int/tobacco/surveillance/policy/country_profile/ind.pdf?ua=1.

Cite This Work

To export a reference to this article please select a referencing stye below:

Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.

Related Services

View all

DMCA / Removal Request

If you are the original writer of this assignment and no longer wish to have your work published on the UKDiss.com website then please: