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Related Concept Videos

Standard Deviation01:10

Standard Deviation

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The most commonly used measure of variation is the standard deviation. It is a numerical value measuring how far data values are from their mean. The standard deviation value is small when the data are concentrated close to the mean, exhibiting slight variation or spread. The standard deviation value is never negative, it is either positive or zero. The standard deviation is larger when the data values are more spread out from the mean, which means the data values are exhibiting more...
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Variability: Analysis01:11

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Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
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The deviations show how spread out the data are about the mean. A positive deviation occurs when the data value exceeds the mean, whereas a negative deviation occurs when the data value is less than the mean. If the deviations are added, the sum is always zero. So one cannot simply add the deviations to get the data spread. By squaring the deviations, the numbers are made positive; thus, their sum will also be positive.The standard deviation measures the spread in the same units as the data.
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The range rule of thumb in statistics helps us calculate a dataset's minimum and maximum values with known standard deviation. This rule is based on the concept that 95% of all values in a dataset lie within two standard deviations from the mean.
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Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
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R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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How Much Does Risk Tolerance Change?

Claudia R Sahm1

  • 1Claudia R. Sahm is an Economist at the Federal Reserve Board, Washington, DC 20551.

The Quarterly Journal of Finance
|December 30, 2014
PubMed
Summary
This summary is machine-generated.

Individual risk tolerance is largely stable over time, despite some changes with age and economic conditions. Persistent differences among people explain most of the variation in financial decision-making.

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Area of Science:

  • Behavioral Economics
  • Health Economics
  • Econometrics

Background:

  • Economic models often assume stable preferences for analyzing behavior.
  • Understanding risk tolerance is crucial for economic decision-making and policy.
  • The Health and Retirement Study (HRS) provides valuable longitudinal data on individuals' financial choices.

Purpose of the Study:

  • To quantify changes in risk tolerance over time.
  • To identify individual differences in risk tolerance.
  • To examine the influence of age and macroeconomic conditions on risk tolerance.

Main Methods:

  • Utilized panel data from 12,000 respondents in the Health and Retirement Study (HRS) spanning 1992-2002.
  • Employed maximum-likelihood estimation of a correlated random effects model.
  • Analyzed hypothetical gambles over lifetime income to assess risk preferences.

Main Results:

  • Results support the hypothesis of constant relative risk aversion.
  • Findings indicate that individuals make career selections based on their inherent preferences.
  • Persistent individual differences account for over 70% of the systematic variation in risk tolerance.

Conclusions:

  • Individual risk tolerance is predominantly stable, with persistent differences being the primary driver of variation.
  • Risk tolerance is influenced by aging and macroeconomic factors, but these effects are secondary to individual heterogeneity.
  • The study provides robust evidence for stable individual preferences in economic behavior.