ENSO Economics

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					Topic 19: ENSO Economics




          David Letson
    Marine Affairs/Economics
      University of Miami
   Value of Information
•The Economist on earthquakes:
“any warning better than none.”

•Roger Pielke Jr.: “no prediction is
better than one that is misleading,
mistaken or misused.”

•When do predictions have most
value?
          Main Points
• What is ENSO?

• Why is ENSO an economic problem?

• When do forecasts have economic value?

• Did you bring your umbrella?
         What is ENSO?
•El Niño - Southern
Oscillation
  –Warm and cold events
  –Every four to seven years
  –Sea surface temperatures,
  central & eastern Pacific

•Year-to-year climatic
variability

•Strength of events also
varies
        Why an Economic
           Problem?
• 1997-98 Niño: $33B damages.

• Ability to predict onset of an
  ENSO event
  –   agriculture
  –   natural disasters
  –   water, fisheries, forestry, energy
  –   human health
       ENSO Impacts in
         Southeast
       EL Niño                                La Niña

• Very wet winter and spring         • Dry Fall, Winter, and Spring
• Cool winter                        • Warm Winter
• Greatly reduces Atlantic           • Greatly increases Atlantic
  hurricanes                           hurricanes
• Increased wildfires in NE          • Greatly increases wildfire
  Florida in June                      activity in the spring.

 Neutral ENSO phase increases the risk of severe freezes by 3:1 odds.
Climate Forecast Uses

                   US Landfalling
               Hurricane Probabilities
     100

     80
                                El Niño
     60                         Neutral

                                La Niña
     40

     20

      0
           0    1   2   3   4      5      6   7
               Number of U.S. Hurricanes
                      (or more)
Climate Forecast Uses

   Fire Threat in a La Niña spring.
     What are Climate
       Forecasts?
•One to six months into the future.

•Uncertain; probabilistic statements.

•El Niño: Pacific surface warmer Oct-Dec

•La Niña: Pacific surface cooler Oct-Dec
      ENSO Forecasts
•U.S. Dept. Commerce/National Oceanic and
Atmospheric Administration (NOAA)

•March 1997: forecast of El Niño in October

•May improve climate sensitive decisions.

•How does equatorial Pacific SST affect
weather?
  –Several months later
  –Several thousands of miles away
Forecast Value
•Forecast users
  –repeated use over time
  –preventative actions
  –profitable opportunities

•Forecasting interpretation
  –Illinois corn yields
  –Grand Forks, ND flood
  –Yakima, WA “drought”
   Value to Agriculture?

• ENSO prediction as technical
  improvement

• Greater quantities, lower prices

• Strength of regional ENSO effect

• ENSO effect and crop season.

• Responses available to farmers
   Climate Information
       Provision
•Why not private sector?

•Socially optimal price equals marginal cost

•Cannot prevent free dissemination.

•Nonrival and nonexcludable
When is information
    valuable?
•Choice in uncertain situations
  –how uncertain
  –what is at stake

•expected gain versus cost

•"update" prior beliefs
   Agricultural Example
•Farmer worried about heavy rain can:
   (A) Harvest entire crop today for $10,000 or
   (B) Half today, half tomorrow at a cost of
   $2,500 per day.

•Harvested crop is worth $50,000.

•Payoffs are:
   $40,000 to decision A and
   p ($22,500) + (1-p) ($45,000) to decision B.

•If p = 5/22.5, then the decisions give
the same payoff.
  Table 1 -Payoff matrix
                  Heavy rain   No heavy rain
                   tomorrow     tomorrow
Decisions:
A. Harvest all     $40,000      $40,000
 today

B. Harvest over    $22,500      $45,000
 two days
Value Depends on
Probability of Rain
   X
        X=$17,500*p
$4000


$3000

                             X=$5000*(1-p)
$2000


$1000



            0.25      0.5   0.75     1   P
Value of Information
• Information has less value when
  – individual's beliefs are extreme
  – costs of a wrong decision are low
  – actions to take are few

• Information has most value when
  – decision maker indifferent
  – large costs of a wrong decision
  – many responses can be taken
             Case Studies
•Agriculture
  –U.S. (Solow et al): $300-400 M/yr;
  –Argentina (Letson, Podestá, Messina)
    ›ENSO affects crop yields and value
    ›Forecast value depends on crop prices
    ›Forecast use depends on user expectations

•Fisheries
  –Coho salmon (Costello et al.): $1 M/yr
  –harvest levels and operations of hatcheries.
         Conclusions
•Year-to-year variability

•ENSO is partly an economic problem

•Forecast interpretation not trivial

•Value of information: it all depends
 For More Information...

Climate Prediction Cntr: www.cpc.ncep.noaa.gov

Pacific Marine Envir Lab: www.pmel.noaa.gov

Climate Diagnostics Cntr: www.cdc.noaa.gov

NOAA/Global Programs: www.ogp.noaa.gov/enso

				
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posted:5/26/2012
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