Natural hazards, poverty traps and adaptive livelihoods in Nicaragua

Berg, M.M. van den; Burger, C.P.J.

doi:10.4324/9781351278768-6

Cited by 5 publications

(4 citation statements)

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“…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

292

186

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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.

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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

292

186

View full text Add to dashboard Cite

show abstract

“…suggest that the experience of such violent events could explain psychological changes. These studies cover large economic shocks (Arrondel and Masson 2014;Brunnermeier and Nagel 2008;Krupka and Stephens 2013;Malmendier and Nagel 2011), and also include natural disasters (Akesaka 2019;Bernile, Bhagwat, and Rau 2017;Callen 2015;Cameron and Shah 2015;Cassar, Healy, and Von Kessler 2017;de Blasio et al 2021;Eckel, El-Gamal, and Wilson 2009;Hanaoka, Shigeoka, and Watanabe 2018;Van den Berg, Fort, and Burger 2009;Willinger, Bchir, and Heitz 2013) and violence (Brown et al 2019;Callen et al 2014;Jakiela and Ozier 2019;Kim and Lee 2014;Moya 2018;Voors et al 2012). Moreover, Hanaoka, Shigeoka and Watanabe (2018) and Akesaka (2019) find that changes in preferences persist even five years after an earthquake, and Bernile, Bhagwat and Rau (2017) obtain similar results for chief executive officers who experienced extreme fatal disasters in early life.…”

Section: Introductionmentioning

confidence: 90%

Does Affective Forecasting Error Induce Changes in Preferences? Lessons from Danish Soldiers Anticipating Combat in Afghanistan

Chanel

Lyk-Jensen

Vergnaud

2022

Defence and Peace Economics

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This paper investigates how affective forecasting errors (A.F.E.s), the difference between anticipated emotion and the emotion actually experienced, may induce changes in preferences on time, risk and occupation after combat. Building on psychological theories incorporating the role of emotion in decision-making, we designed a before-and-after-mission survey for Danish soldiers deployed to Afghanistan in 2011. Our hypothesis of an effect from A.F.E.s is tested by controlling for other mechanisms that may also change preferences: immediate emotion, trauma effect -proxied by post-traumatic stress disorder (P.T.S.D.)and changes in wealth and risk perception. At the aggregate level, results show stable preferences before and after mission. We find positive A.F.E.s for all three emotions studied (fear, anxiety and excitement), with anticipated emotions stronger than those actually experienced. We provide evidence that positive A.F.E.s regarding fear significantly increase risk tolerance and impatience, while positive A.F.E.s regarding excitement strengthen the will to stay in the military. Trauma has no impact on these preferences.

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“…The research on natural disasters (including earthquakes, famines, floods, hurricanes, and tsunamis) suggests that such shocks increase risk aversion [21][22][23][24][25], decrease risk aversion [26][27][28][29][30], have no effect at all on risk preferences [31], or have no consistent effect on risk preferences [32].…”

Section: Literature Reviewmentioning

confidence: 99%

Evidence From Data Science on the Relationship Between Individual Beliefs/Behaviors Survey During COVID-19 Pandemic and Risk Preference

Adekunle,

Riedl,

Dumontier

2023

AAIML

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The factors that affect individual risk preference have been of central interest to behavioral economics and psychology. However, how to measure it and its stability remain a challenge. Dutch law requires financial institutions, including pension providers, to consider customers' risk preferences when offering their services. In this study, we apply data science to investigate whether individual perceptions of risk and social effects associated with COVID-19 are related to general risk preferences of individuals, while observing whether the relevant features that influence risk preferences remain consistent. A supervised machine learning task over two different target measures of risk preferences (a self reported risk preference measure from the survey and a lottery based experimental measure) using three datasets: a main study dataset with (𝑁 = 4, 282) adult survey participants in the Netherlands and two pretest survey dataset with (𝑁 = 314) and (𝑁 = 306) respectively. The experimental measure employs a multiple price list to estimate an average number of safe choices of participants which is an integer, as such, a regression task using lasso regression over all of the datasets has been carried out to detect the relationship between behavior during the pandemic and the experimental risk preference measure. The self reported risk measure employs a likert scale to determine the risk likelihood of participants, as such, a classification task using a random forest model over the different risk tolerance classes on all of the datasets has also been studied. This assesses the stability of correlating such behavioral features to the revealed preference approach of eliciting risk preference as compared to self-reported risk preference from surveys. The hypothesis is that the individual choices selected regarding 1800

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Natural hazards, poverty traps and adaptive livelihoods in Nicaragua

Cited by 5 publications

References 0 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

Does Affective Forecasting Error Induce Changes in Preferences? Lessons from Danish Soldiers Anticipating Combat in Afghanistan

Evidence From Data Science on the Relationship Between Individual Beliefs/Behaviors Survey During COVID-19 Pandemic and Risk Preference

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