Mining for Mood Effect in the Field
(2020) In Working Papers- Abstract
- We conduct what we believe to be the most methodologically rigorous study of mood effect in the field so far to measure its economic impact and address shortcomings in the existing literature. Using a large dataset containing over 46 million car inspections in Sweden and England in 2016 and 2017, we study whether inspectors are more lenient on days when their mood is predicted to be good, and if car owners exploit the mood effect by selecting these days to inspect low quality cars. Different sources of good mood are studied: Fridays, sunny days, and days following unexpected wins by the local soccer team, with varying degrees of the car owner’s ability to plan for inspection, and hence the likelihood of selection bias. We find limited... (More)
- We conduct what we believe to be the most methodologically rigorous study of mood effect in the field so far to measure its economic impact and address shortcomings in the existing literature. Using a large dataset containing over 46 million car inspections in Sweden and England in 2016 and 2017, we study whether inspectors are more lenient on days when their mood is predicted to be good, and if car owners exploit the mood effect by selecting these days to inspect low quality cars. Different sources of good mood are studied: Fridays, sunny days, and days following unexpected wins by the local soccer team, with varying degrees of the car owner’s ability to plan for inspection, and hence the likelihood of selection bias. We find limited evidence to support the existence of mood effects in this domain, despite survey results showing belief to the contrary. There is some indication of selection effect on the part of car owners. Our findings cast doubt on previous mood effects found in the field. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4ed05f11-5414-40eb-9867-bd7593b71c66
- author
- Samahita, Margaret and Holm, Håkan J. LU
- organization
- publishing date
- 2020-03-07
- type
- Working paper/Preprint
- publication status
- published
- subject
- keywords
- mood effect, selection bias, car inspection, D12, D22, D84, D91
- in
- Working Papers
- issue
- 2020:2
- pages
- 82 pages
- language
- English
- LU publication?
- yes
- id
- 4ed05f11-5414-40eb-9867-bd7593b71c66
- alternative location
- https://swopec.hhs.se/lunewp/abs/lunewp2020_002.htm
- date added to LUP
- 2020-04-07 11:27:43
- date last changed
- 2020-04-07 11:39:28
@misc{4ed05f11-5414-40eb-9867-bd7593b71c66,
abstract = {{We conduct what we believe to be the most methodologically rigorous study of mood effect in the field so far to measure its economic impact and address shortcomings in the existing literature. Using a large dataset containing over 46 million car inspections in Sweden and England in 2016 and 2017, we study whether inspectors are more lenient on days when their mood is predicted to be good, and if car owners exploit the mood effect by selecting these days to inspect low quality cars. Different sources of good mood are studied: Fridays, sunny days, and days following unexpected wins by the local soccer team, with varying degrees of the car owner’s ability to plan for inspection, and hence the likelihood of selection bias. We find limited evidence to support the existence of mood effects in this domain, despite survey results showing belief to the contrary. There is some indication of selection effect on the part of car owners. Our findings cast doubt on previous mood effects found in the field.}},
author = {{Samahita, Margaret and Holm, Håkan J.}},
keywords = {{mood effect; selection bias; car inspection; D12; D22; D84; D91}},
language = {{eng}},
month = {{03}},
note = {{Working Paper}},
number = {{2020:2}},
series = {{Working Papers}},
title = {{Mining for Mood Effect in the Field}},
url = {{https://swopec.hhs.se/lunewp/abs/lunewp2020_002.htm}},
year = {{2020}},
}