The Impact of Economic Crisis on Happiness

There is a common belief that economic crisis will lead to a decrease in subjective wellbeing. Previous studies indicate that income is correlated with happiness and unemployment with unhappiness. The relationship between increased income and happiness is well documented while the impact of decreased income has been less explored. The aim of this paper is to study how the economic downfall in Iceland, followed by reduced income and increased unemployment, affects happiness as well as to explore which groups are most vulnerable to changes in happiness and which are most resilient. The study is a longitudinal, nationally representative postal survey which assessed 5,918 individual’s aged 18–79. A total of 4,092 (77.3%) answered again in 2009. The relationship between economic factors and happiness was explored using multiple linear regression to find out how much they explain of the happiness variance and the changes in happiness, together with demographic factors, health and social relationships. Results indicate that income and unemployment did not predict happiness but financial difficulties did. A decrease in happiness was detected after the collapse. The change in happiness from 2007 to 2009 was normally distributed, 40% had the same score in both years and an equal number increased as decreased. The explored factors did not explain the changes in happiness. The economic crisis had a limited affect on happiness. Those with financial difficulties were hardest hit. Changes in happiness need to be studied further since they are not well explained by the factors which influence cross-sectional levels of happiness.     

MINIMUM LEVELS AND FRAMING IN PUBLIC GOOD PROVISION

Using a laboratory experiment in the field, we examine how the framing of a social dilemma, give to or take from a public good, interacts with a policy intervention that enforces a minimum contribution level to the public good. We find significantly higher cooperation in the give frame than in the take frame in our standard public goods experiment. When a minimum contribution level is introduced, contributions are crowded out in the give frame but crowded in in the take frame. Our results show the importance of choosing the frame when making policy recommendations. (JEL C91, H41)     

The Value of a Statistical Life in Transport: Findings from a New Contingent Valuation Study in Sweden

This article presents the results of a contingent valuation study from Sweden aimed at estimating the value of a statistical life (VOSL) in road traffic safety. Data on respondents' own subjective risk was collected by use of visual aids presented in a mail questionnaire. The relationship between willingness-to-pay (WTP) and absolute risk reduction was estimated by using a non-linear, least absolute deviation estimation method. This study generated an income-adjusted VOSL of SEK22.3 million (US$2.6 million). Analysis of WTP's sensitivity to probability variation indicates that in future studies, valuing risk reductions in road traffic, the magnitude of absolute risk and relative risk reductions to consider should be in perceptible range. On addition it should also be possible for respondents to compare the magnitudes of different risk reductions.     

The Influence of Quality Inspections on the Optimal Safety Stock Level

Due to yields of less than 50% during the production of curved glass for the displays on their new cell phone series, Samsung has to deal with higher than expected production costs of several million dollars. Where there is random yield, production costs as well as holding costs can be reduced by introducing quality inspections, in which defective items are discarded before further production. To achieve the greatest cost savings, it is important to determine the optimal number and positions of these inspections across the production process which, due to several influencing parameters, is not simple. We show how the positions of inspection within a production process influence the safety stock level that is required to buffer against uncertainties due to demand and yield randomness. Our approach is the first one, combining decisions about the number and positions of inspections with inventory control strategies in a warehouse. We achieve a maximum safety stock reduction of more than 30% in our examples, which can be even larger depending on the parameter setting. For a company like Intel, reporting inventories for finished goods of nearly 1.5 billion dollars in the 2014 annual report, this allows for significant savings.