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Household Financial Forecasting and Planning: Biases and Support Tools (Advert Reference: SF19/BL/MOS/GONUL)


Project Description

Arguments about money are a major cause of conflict in many households. Financial mismanagement (including problematic debt) is reported to have a dramatic negative effect on the well-being ( i.e., psychological and physical health) of a household leading to higher perceived stress and depression, increased financial vulnerability, and reduced resilience to unexpected shocks (Sweet, Nandi, Adam & McDade, 2013). Accordingly, effective forecasting and planning of household savings, expenses and debt are of paramount importance not only for family well-being but also to a large variety of external bodies such as policymakers, institutions and public interest groups.

The forecasting and planning process is shaped by many behavioural effects and biases (Goodwin, Gonul & Onkal, 2013, 2019; Goodwin, Onkal, Gonul, Thomson & Oz, 2017; Onkal, Goodwin, Thomson, Gonul & Pollock, 2009; Onkal, Sayim & Gonul, 2013). Examples of such behavioural tendencies include overconfidence, tunnel vision, hindsight bias and pain of paying. A particular effect of interest that may aggravate financial problems is the present bias, which refers to people being more oriented towards the present than the future, thus inconsistently overweighing current savings and expenses relative to future ones (De Baets, Onkal & Ahmed, 2019; Frederick, Loewenstein & O’Donoghue, 2002; Goda, Levy, Manchester, Sojourner & Tasoff, 2019; Tam & Dholakia, 2011).

Along these lines, this PhD project for one PhD applicant will investigate the role of such behavioural biases on household financial forecasting and planning in order to develop and test effective support mechanisms and advice tools. By adopting a multidisciplinary approach, this project will combine qualitative/interpretivist and quantitative/empirical methodology, making use of interviews, survey studies and behavioural experiments. Findings from this project are expected to contribute towards an enhanced household financial well-being, thus leading to a significant social impact.

This project is supervised by Dr. M. Sinan Gonul, Prof. Dilek Onkal and Prof Mary Thomson.

Eligibility and How to Apply:

Please note eligibility requirement:
• Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
• Appropriate IELTS score, if required.

For further details of how to apply, entry requirements and the application form, see: https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/

Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. SF19/…) will not be considered.

Northumbria University takes pride in, and values, the quality and diversity of our staff. We welcome applications from all members of the community. The University holds an Athena SWAN Bronze award in recognition of our commitment to improving employment practices for the advancement of gender equality.

Funding Notes

Please note this is a self-funded project and does not include tuition fees or stipend.

References

De Baets, S., D. Önkal, W. Ahmed (2019) “Nudging for improved forecasts of savings and expenses”, International Symposium on Forecasting, Athens, June 2019.

Goodwin, P., M.S. Gönül, D. Önkal (2019). When providing optimistic and pessimistic scenarios can be detrimental to judgmental demand forecasts and production decisions. European Journal of Operational Research, 273, 992-1004.

Goodwin P., D. Önkal, M.S. Gönül, M.Thomson and E. Öz, (2017) “Evaluating expert advice in forecasting: Users’ reactions to presumed vs experienced credibility”, International Journal of Forecasting, 33, 280-297, DOI:10.1016/j.ijforecast.2015.12.009

Önkal, D., K. Z. Sayım, and M.S. Gönül (2013). Scenarios as channels of forecast advice, Technological Forecasting & Social Change, 80, 772-788.

Goodwin, P., M.S. Gönül, and D. Önkal (2013). Antecedents and effects of trust in forecasting advice. International Journal of Forecasting, 29, 354-366.

Önkal, D., P. Goodwin, M.E. Thomson, M.S. Gönül, A.C. Pollock (2009) “The Relative
Influence of Advice from Human Experts and Statistical Methods on Forecast
Adjustments”, Journal of Behavioral Decision Making, 22(4), 390-409.

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