Literature DB >> 25544881

How Much Does Risk Tolerance Change?

Claudia R Sahm1.   

Abstract

Stability of preferences is central to how economists study behavior. This paper uses panel data on hypothetical gambles over lifetime income in the Health and Retirement Study to quantify changes in risk tolerance over time and differences across individuals. Maximum-likelihood estimation of a correlated random effects model utilizes information from 12,000 respondents in the 1992-2002 HRS. The results are consistent with constant relative risk aversion and career selection based on preferences. While risk tolerance changes with age and macroeconomic conditions, persistent differences across individuals account for over 70% of the systematic variation.

Entities:  

Year:  2012        PMID: 25544881      PMCID: PMC4276321          DOI: 10.1142/S2010139212500206

Source DB:  PubMed          Journal:  Q J Finance        ISSN: 2010-1406


  2 in total

1.  Risk Preferences in the PSID: Individual Imputations and Family Covariation.

Authors:  Miles S Kimball; Claudia R Sahm; Matthew D Shapiro
Journal:  Am Econ Rev       Date:  2009-05

2.  Imputing Risk Tolerance From Survey Responses.

Authors:  Miles S Kimball; Claudia R Sahm; Matthew D Shapiro
Journal:  J Am Stat Assoc       Date:  2008-09-01       Impact factor: 5.033

  2 in total
  10 in total

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7.  The link between health and economic preferences: Evidence from 22 OECD countries.

Authors:  Xi Cen; David W Johnston; Claryn S J Kung; Michael A Shields; Eric C Sun
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8.  Defining and achieving permanency among older youth in foster care.

Authors:  Amy M Salazar; Kevin R Jones; Jamie Amemiya; Adrian Cherry; Eric C Brown; Richard F Catalano; Kathryn C Monahan
Journal:  Child Youth Serv Rev       Date:  2018-04

9.  Risk, uncertainty and ambiguity amid Covid-19: A multi-national analysis of international travel intentions.

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10.  Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences.

Authors:  Richard Karlsson Linnér; Pietro Biroli; Edward Kong; S Fleur W Meddens; Robbee Wedow; Mark Alan Fontana; Maël Lebreton; Stephen P Tino; Abdel Abdellaoui; Anke R Hammerschlag; Michel G Nivard; Aysu Okbay; Cornelius A Rietveld; Pascal N Timshel; Maciej Trzaskowski; Ronald de Vlaming; Christian L Zünd; Yanchun Bao; Laura Buzdugan; Ann H Caplin; Chia-Yen Chen; Peter Eibich; Pierre Fontanillas; Juan R Gonzalez; Peter K Joshi; Ville Karhunen; Aaron Kleinman; Remy Z Levin; Christina M Lill; Gerardus A Meddens; Gerard Muntané; Sandra Sanchez-Roige; Frank J van Rooij; Erdogan Taskesen; Yang Wu; Futao Zhang; Adam Auton; Jason D Boardman; David W Clark; Andrew Conlin; Conor C Dolan; Urs Fischbacher; Patrick J F Groenen; Kathleen Mullan Harris; Gregor Hasler; Albert Hofman; Mohammad A Ikram; Sonia Jain; Robert Karlsson; Ronald C Kessler; Maarten Kooyman; James MacKillop; Minna Männikkö; Carlos Morcillo-Suarez; Matthew B McQueen; Klaus M Schmidt; Melissa C Smart; Matthias Sutter; A Roy Thurik; André G Uitterlinden; Jon White; Harriet de Wit; Jian Yang; Lars Bertram; Dorret I Boomsma; Tõnu Esko; Ernst Fehr; David A Hinds; Magnus Johannesson; Meena Kumari; David Laibson; Patrik K E Magnusson; Michelle N Meyer; Arcadi Navarro; Abraham A Palmer; Tune H Pers; Danielle Posthuma; Daniel Schunk; Murray B Stein; Rauli Svento; Henning Tiemeier; Paul R H J Timmers; Patrick Turley; Robert J Ursano; Gert G Wagner; James F Wilson; Jacob Gratten; James J Lee; David Cesarini; Daniel J Benjamin; Philipp D Koellinger; Jonathan P Beauchamp
Journal:  Nat Genet       Date:  2019-01-14       Impact factor: 38.330

  10 in total

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