1. Krishnan, S., Subramanian, S., & Iyer, S. (2020). „Can waste aversion affect demand for
insurance? Evidence from experiment and survey”. Economics Letters, 216, 110594.

In their study, Krishnan et al. (2020) examine the waste aversion effect on insurance demand using
experiment and survey in India. Overall, the results of the study demonstrate the measurement of
policyholders’ waste aversion and the interconnection of their demand for a potential insurance
policy to show the impact of waste aversion on respondents’ insurance decisions. Furthermore,
experiment and survey show that waste-averse groups purchase fewer insurance policies in comparison
to non-waste-averse ones. A strength of this study is conducting an incentivized approaches
describing waste aversion theory causes and effects. The results achieved have external and
internal credibility. A weakness of the study is no waste aversion exact measurement in the survey
because there were no measures that could be taken in the insurance context. The study is valuable
because it provides consistent evidence of waste aversion theory stating policyholders do not
purchase fair insurance policies because of hypothetical losses in case an insured event does not
happen.

2. Heinrich, T., Seifert, M., & Then, F. (2020). „Near-losses in insurance markets: An experiment”.
Economics Letters, 186, 108781.

Heinrich et al. (2020) investigate an insurance market near-loss experimentally.  The results
reveal that strategic uncertainty affects audacity consequent to near-loss experience, which can be
impacted by competitiveness or other market settings. The incentivized Becker-DeGroot-Marschak
(BDM) mechanism is used to obtain valuations for insurance policies protecting potential
policyholders from hypothetic losses. The outcomes are achieved with the use of a roulette wheel,
lottery, and incentives.  A weakness of the study is that social influences are not taken into
consideration. A strength of this study is that the experiment is the first one in the near-loss
events in the insurance field, considering stronger or weaker risk-averse behaviour, depending on
the position of the roulette wheel: before or after the hypothetic loss. This paper can still be
useful because of its relevance to the near-loss effect, which influences supply and demand for
insurance in strategic uncertainty conditions but not in an individual estimation.

3.  Larrimore, J., Splinter, D. (2019). „How much does health insurance cost? Comparison of
premiums in administrative and survey data”. Economics Letters, 174, 132-135.

In their article, Larrimore and Splinter (2019) examine the cost of health insurance using premiums
comparison in administrative and survey data from Internal Revenue Service (IRS) in the USA. The
results demonstrate the health care premiums distribution sponsored by the employer. Authors
compare data from IRS and Current Population Survey (CPS), that result in many differences. CPS
downplays the premium distribution upper tail and subsequently downplays average premiums. For
workers with middle income, these downplays represent two per cent of the gross compensation. In
addition, the underestimates are accumulated among workers with higher income showing higher total
inequality in compensation. Weaknesses of the study include statistical biases and uncertainty. The
study is valuable because it provides consistent evidence about compensation inequality and shows
the contrast between two USA data sources. Moreover, the study provides evidence the increasing
health insurance value may counterbalance the potential wages of workers with middle income, which
is important for future research.