Risk uncertainty and sensitivity analysis
Download
1 / 15

Risk, Uncertainty, and Sensitivity Analysis - PowerPoint PPT Presentation


  • 150 Views
  • Updated On :

Risk, Uncertainty, and Sensitivity Analysis. How economics can help understand, analyze, and cope with limited information. What is “risk”?. Can be loosely defined as the “possibility of loss or injury”. Should be accounted for in social projects (and regulations) and private decisions.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Risk, Uncertainty, and Sensitivity Analysis' - aliza


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Risk uncertainty and sensitivity analysis l.jpg

Risk, Uncertainty, and Sensitivity Analysis

How economics can help understand, analyze, and cope with limited information


What is risk l.jpg
What is “risk”?

  • Can be loosely defined as the “possibility of loss or injury”.

  • Should be accounted for in social projects (and regulations) and private decisions.

  • We want to develop a way to describe risk quantitatively by evaluating the probability of all possible outcomes.


Attitude toward risk l.jpg
Attitude toward risk

  • Problem: Costello likes to ride his bike to school. If it is raining when he gets up, he can take the bus. If it isn’t, he can ride, but runs the risk of it raining on the way home.

  • Value of riding bike = $2, value of taking bus = -$1.

  • Value of riding in rain = -$6.


Costello s options the states of nature l.jpg
Costello’s options & the “states of nature”

  • Costello can either ride his bike or take the bus.

  • Bus: He loses $0 (breaks even).

  • Bike: Depends on the “state of nature”

    • Rain: $2 - $6 = -$4.

    • No rain: $2 + $2 = $4.


Probabilities risk attitude l.jpg
Probabilities & risk attitude

  • Pr(rain)=0.5.

  • Costello’s expected payoffs are equal:

    • Bus: $0.

    • Bike: .5*(-4) + .5*(4) = $0.

  • If he:

    • Always bikes: he’s a risk lover

    • Always buses: he’s risk averse

    • Flips a coin: he’s risk neutral

  • His behavior reveals his risk preference.


Risk attitudes in general l.jpg
Risk attitudes in general

  • Generally speaking, most people risk averse.

  • Diversification can reduce risk.

  • Since gov’t can pool risk across all taxpayers, there is an argument that society is essentially risk neutral.

  • Most economic analyses assume risk neutrality.

  • Note: may get unequal distribution of costs and benefits.


Expected payoff more generally l.jpg
Expected payoff more generally

  • Suppose n “states of nature”.

  • Vi = payoff under state of nature i.

  • Pi = probability of state of nature i.

  • Expected payoff is: V1p1+V2p2+…

  • Or S ViPi


Example air quality regulations l.jpg
Example: Air quality regulations

  • New air quality regulations in Santa Barbara County will reduce ground level ozone.

  • Reduce probability of lung cancer by .001%, affected population: 100,000.

  • How many fewer cases of lung cancer can we expect?…about 1

    • .00001*100,000 = 1.


Example climate change policy l.jpg
Example: Climate change policy

  • 2 states of nature

    • High damage (probability = 1%)

      • Cost = $1013/year forever, starting in 100 yrs.

    • Low damage (probability = 99%)

      • Cost = $0

  • Cost of control = $1011

  • Should we engage in control now?


Control vs no control r 2 l.jpg
Control vs. no control (r=2%)

  • Control now: high cost, no future loss

    • Cost = $1011

  • Don’t control now: no cost, maybe high future loss:

    • If high damage = 1013[1/(1.02100) + 1/(1.02101) + 1.(1.02102) + … ]

    • = (1013/(.02))/(1.02100) = $7 x 1013

    • If no damage = $0.


Overall evaluation l.jpg
Overall evaluation

  • Expected cost if control = $1011

  • Expected cost if no control =

    • (.01)(7 x 1013) + (.99)(0) = $7 x 1011

  • By this analysis, should control even though high loss is low probability event.


Value of information l.jpg
Value of Information

  • The real question is not: Should we engage in control or not?

  • The question is: Should we act now or postpone the decision until later?

  • So there is a value to knowing whether the high damage state of nature will occur.

  • We can calculate that value…this is “Value of information”


Sensitivity analysis l.jpg
Sensitivity Analysis

  • A method for determining how “sensitive” your model results are to parameter values.

    • Sensitivity of NPV, sensitivity of policy choice.

  • Simplest version: change a parameter, re-do analysis (“Partial Sensitivity Analysis”)



More sophisticated sensitivity l.jpg
More sophisticated sensitivity

  • The more nonlinear your model, the more interesting your sensitivity analysis.

  • Should examine different combinations.

  • Monte Carlo Sensitivity Analysis:

    • Choose distributions for parameters.

    • Let computer “draw” values from distn’s

    • Plot results


ad