Variation in risk seeking behaviour following large losses: A natural experiment

Page, Lionel; Savage, David A.; Torgler, Benno

doi:10.1016/j.euroecorev.2014.04.009

Cited by 159 publications

(108 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The research on natural disasters (including earthquakes, famines, floods, hurricanes, and tsunamis) suggests that such shocks increase risk aversion (Cameron and Shah, 2015; Cassar et al, 2011; Chantarat et al, 2015; Samphantharak and Chantarat, 2015; van den Berg et al, 2009), decrease risk aversion (Bchir and Willinger, 2013; Eckel et al, 2009; Hanaoka et al, 2014; Ingwersen, 2014; Page et al, 2014; Willinger et al, 2013), have no effect at all on risk preferences (Becchetti et al, 2012), or have no consistent effect on risk preferences (Said et al, 2015); increase impatience (Bchir and Willinger, 2013; Cassar et al, 2011; Sawada and Kuroishi, 2015), decrease impatience (Callen, 2011; Chantarat et al, 2015), or have no consistent effect on time preferences (Willinger et al, 2013); increase trust (Cassar et al, 2011), decrease trust (Chantarat et al, 2015), or have no effect on the level of trust (Andrabi and Das, 2010); decrease trustworthiness (Fleming et al, 2014); and increase altruism (Becchetti et al, 2012; Chantarat et al, 2015), decrease altruism (Samphantharak and Chantarat, 2015), or have no consistent effect on altruism (Afzal et al, 2015). 10 …”

Section: Previous Literaturementioning

confidence: 99%

Stability of experimental and survey measures of risk, time, and social preferences: A review and some new results

Chuang

Schechter

2015

Journal of Development Economics

289

186

View full text Add to dashboard Cite

Underlying preferences are often considered to be persistent, and are important inputs into economic models. We first conduct an extensive review of the disparate literature studying the stability of preferences measured in experiments. Then, we test the stability of individuals’ choices in panel data from rural Paraguay over almost a decade. Answers to social preference survey questions are quite stable. Experimental measures of risk, time, and social preferences do not exhibit much stability. Correlations between experimental measures of risk aversion are a more precisely estimated zero, whereas correlations for time and social preferences are larger and noisier. We also find no systematic evidence that real world shocks influence play in games. We suggest that in a developing country context researchers should explore designing simpler experiments and including survey questions in addition to experiments to measure preferences.

show abstract

Section: Previous Literaturementioning

confidence: 99%

Stability of experimental and survey measures of risk, time, and social preferences: A review and some new results

Chuang

Schechter

2015

Journal of Development Economics

289

186

View full text Add to dashboard Cite

show abstract

“…Similarly, Cassar et al (2017) find that individuals affected by the 2004 Asian tsunami are substantially more risk-averse four and half years after the disaster. In contrast, Eckel et al (2009) analyze the risk attitudes of individuals who were displaced by Hurricane Katrina and Page et al (2014) analyze risk attitudes of home owners who suffered large losses in the Australian floods in 2011. Both studies find that respondents demonstrate high levels of risk-loving immediately after the disaster.…”

mentioning

confidence: 99%

Natural disasters, social protection, and risk perceptions

et al. 2018

View full text Add to dashboard Cite

Natural disasters give rise to loss and damage and may affect subjective expectations about the prevalence and severity of future disasters. These expectations might then in turn shape individuals’ investment behaviors, potentially affecting their incomes in subsequent years. As part of an emerging literature on endogenous preferences, economists have begun studying the consequences that exposure to natural disasters have on risk attitudes, perceptions, and behavior. We add to this field by studying the impact of being struck by the December 2012 Cyclone Evan on Fijian households’ risk attitudes and subjective expectations about the likelihood and severity of natural disasters over the next 20 years. The randomness of the cyclone’s path allows us to estimate the causal effects of exposure on both risk attitudes and risk perceptions. Our results show that being struck by an extreme event substantially changes individuals’ risk perceptions as well as their beliefs about the frequency and magnitude of future shocks. However, we find sharply distinct results for the two ethnicities in our sample, indigenous Fijians and Indo-Fijians; the impact of the natural disaster aligns with previous results in the literature on risk attitudes and risk perceptions for Indo-Fijians, whereas they have little to no impact on those same measures for indigenous Fijians. To provide welfare implications for our results, we compare households’ risk perceptions to climate and hydrological models of future disaster risk, and find that both ethnic groups over-infer the risk of future disasters relative to the model predictions. If such distorted beliefs encourage over-investment in preventative measures at the cost of other productive investments, these biases could have negative welfare impacts. Understanding belief biases and how they vary across social contexts may thus help decision makers design policy instruments to reduce such inefficiencies, particularly in the face of climate change.

show abstract

“…Scholars have stressed the challenging nature of achieving smooth relationships between different levels of government and ensuring that local officials focused on recovery share similar goals as those working at the national level (Rosenthal and Kouzmin ). The Great East Japan Earthquake provides a tragic ‘natural experiment’ (Page et al ) for testing such arguments about recovery with new, quantitative data.…”

Section: Introductionmentioning

confidence: 99%

It's Who You Know: Factors Driving Recovery From Japan's 11 March 2011 Disaster

Aldrich¹

2015

Public Administration

View full text Add to dashboard Cite

The 11 March 2011 Great East Japan Earthquake affected dozens of coastal communities along the shore of Japan's Tohoku region. Following the earthquake, tsunami and nuclear meltdowns, utilities, businesses and schools in some towns have bounced back to pre-disaster capacity while other municipalities have lagged behind. The question of which factors accelerate the recovery of business, infrastructure and population after the disaster remains unanswered. This article uses a new dataset of roughly 40 disaster-affected cities, towns and villages in the area to identify the factors connected with recovery. More than tsunami damage, spending on disaster mitigation, population density, economic conditions or financial capability, the most powerful predictor of recovery for a given area is the number of powerful politicians representing the area in the national government. These findings bring with them important policy implications for residents, NGOs and government decision-makers.

show abstract

Variation in risk seeking behaviour following large losses: A natural experiment

Cited by 159 publications

References 37 publications

Stability of experimental and survey measures of risk, time, and social preferences: A review and some new results

Stability of experimental and survey measures of risk, time, and social preferences: A review and some new results

Natural disasters, social protection, and risk perceptions

It's Who You Know: Factors Driving Recovery From Japan's 11 March 2011 Disaster

Contact Info

Product

Resources

About