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Understanding Risk Aversion in Older...

Harrati, Amal Cherifa.

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Understanding Risk Aversion in Older Americans: New Approaches Using Genetic Data.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Understanding Risk Aversion in Older Americans: New Approaches Using Genetic Data./
作者:	Harrati, Amal Cherifa.
面頁冊數:	105 p.
附註:	Source: Dissertation Abstracts International, Volume: 76-08(E), Section: A.
Contained By:	Dissertation Abstracts International76-08A(E).
標題:	Demography. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3686315
ISBN:	9781321630640

Understanding Risk Aversion in Older Americans: New Approaches Using Genetic Data.
Harrati, Amal Cherifa.

Understanding Risk Aversion in Older Americans: New Approaches Using Genetic Data. - 105 p.

Source: Dissertation Abstracts International, Volume: 76-08(E), Section: A.

Thesis (Ph.D.)--University of California, Berkeley, 2014.

In this dissertation, I explore the nature and role of risk aversion among older Americans from a variety of perspectives. Risk preferences are important to demographers for several reasons. First, risk preferences are fundamental to most individual-level demographic events, including to financial decision-making, health behaviors, labor market decisions, migration, and marriage and family-formation. Second, there is substantial evidence that risk aversion increases with age. With age also comes increased responsibility in terms of making specific financial and health decisions. In the age of decreasing pensions, older persons must make significant decisions about their financial portfolios and finances in light of pending retirement decisions. In fact, the decision to retire is itself one in which risk plays a role. Third, health behaviors, which are a function of one's riskiness, often display their effects at older ages.

ISBN: 9781321630640Subjects--Topical Terms:

614991
Demography.

Understanding Risk Aversion in Older Americans: New Approaches Using Genetic Data.
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245 1 0 $a Understanding Risk Aversion in Older Americans: New Approaches Using Genetic Data.
300 $a 105 p.
500 $a Source: Dissertation Abstracts International, Volume: 76-08(E), Section: A.
500 $a Adviser: Kenneth Wachter.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2014.
520 $a In this dissertation, I explore the nature and role of risk aversion among older Americans from a variety of perspectives. Risk preferences are important to demographers for several reasons. First, risk preferences are fundamental to most individual-level demographic events, including to financial decision-making, health behaviors, labor market decisions, migration, and marriage and family-formation. Second, there is substantial evidence that risk aversion increases with age. With age also comes increased responsibility in terms of making specific financial and health decisions. In the age of decreasing pensions, older persons must make significant decisions about their financial portfolios and finances in light of pending retirement decisions. In fact, the decision to retire is itself one in which risk plays a role. Third, health behaviors, which are a function of one's riskiness, often display their effects at older ages.
520 $a I explore the genetic nature of risk aversion through a number of approaches. Taking advantage of a newly-released database with over two million pieces of genetic variants, I examine the specific genetic nature of risk aversion through two genomic techniques: a Genome-Wide Association study (GWAS) and a Genome-Wide Complex Trait Analysis (GCTA). I provide evidence that risk aversion is a highly complex trait that is a function of a large number of possibly interactive genetic variants. Through the GWAS, I show that the number of genetic variants influencing individual-level differences in risk aversion is numerous and that these variants are likely to be scattered across the genome. The GCTA, while using a separate methodological approach, confirms this finding. I argue that the intricate nature of the genetic underpinnings to risk aversion should be better understood in order to more precisely model economic decisions involving risk preferences.
520 $a I also characterize risk aversion from a non-genetic perspective. Using panel data of risk aversion collected over nearly two decades, I use longitudinal methods to explore the extent to which the relationship between hypothetical risk and measurable risky behaviors remain consistent across both time and among individuals. As a follow-up, I examine the specific time period following the 2008 recession to examine any change in the relationship in portfolio allocations relative to stated risk tolerance for individuals after the global financial crisis. I conclude that the relationship between measured risk and risky behaviors remains relatively constant across the 15 years prior to the global financial crisis. The analysis also shows that the relationship between risk and financial assets does in fact change slightly after the global financial crisis, though the statistical evidence is not very strong.
520 $a This dissertation provides a contribution to the understanding of the complex nature of risk aversion and is on of the first to characterise it's genetic influences. This research helps to answer questions on the economic, social and biological drivers and consequences of risk aversion among older Americans.
590 $a School code: 0028.
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650 4 $a Genetics. $3 530508
650 4 $a Economics. $3 517137
650 4 $a Aging. $3 543123
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710 2 $a University of California, Berkeley. $b Demography. $3 3171382
773 0 $t Dissertation Abstracts International $g 76-08A(E).
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